Handbook of the Cerebellum and Cerebellar Disorders [2 ed.] 3030238113, 9783030238117

Table of contents :
Preface to the Second Edition
Preface to the First Edition
Contents
About the Editors
Contributors
Part I: Cerebellar Development
1 Specification of the Cerebellar Territory
Introduction
Delineating the Cerebellar Primordium
Fate Maps of the Cerebellum
Rotation of the Cerebellar Primordium
Specification of the Cerebellar Primordium
The Midbrain-Hindbrain (MHB) Domain
Organizing Properties of the Isthmic Neuroepithelium - Fgf8
The MHB Organizer: A Molecular Network Set up at the Otx2-Gbx2 Boundary
The Otx2-Gbx2 Boundary: A Stable or Drifting Limit?
Genes Regulating the Competence of the Neuroepithelium to Develop a MHB Identity
Genes Regulating Distinct Neuroepithelium Competences on Either Sides of the MHB Boundary
Subdivisions of the Cerebellar Plate
Anteroposterior Subdivisions of the Cerebellar Plate
Dorsoventral Subdivisions of the Cerebellar Plate
Conclusions and Future Directions
References
2 Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip
Introduction
Proneural Genes in Drosophila melanogaster Development
The Roles of Proneural Genes in Vertebrate Neurogenesis
Atoh1: The Master Gene in Granule Cell Development
Atoh1 Plays a Key Role in Granule Cell Clonal Expansion
Other Glutamatergic Neurons Derive from Atoh1+ Progenitors
Late Atoh1+ Progenitors in the URL Give Rise to Unipolar Brush Cells
NeuroD: A ``Nearly Proneural´´ Gene with Key Roles in Cerebellar Development
Ascl1 in Ventricular Zone Neurogenesis
Ptf1a Is a Master Gene of Cerebellar GABAergic Neurogenesis
Ascl1 Labels the Cerebellar GABAergic Lineage
Neurogenins in Cerebellar GABAergic Development
Neurog1 and Neurog2 Are Expressed in the Ptf1a+ Ventricular Neuroepithelium
Neurog1 Is Expressed in Cerebellar GABAergic Interneuron Progenitors
Neurog2 Labels the PC Lineage and Regulates PC-Progenitor Cell-Cycle Progression and Dendritogenesis
Conclusion
References
3 Zones and Stripes: Development of Cerebellar Topography
The Architecture of the Adult Cerebellar Cortex
From Allocation to Rhombomere 1 to Two Germinal Epithelia
Purkinje Cell Birth Date, Phenotype, and Location
From Ventricular Zone to Clusters
Purkinje Cell Subtype Specification
From Embryonic Clusters to Adult Stripes
Afferent Topography
Climbing Fibers
Mossy Fibers
Interneurons
Cerebellar Topography and Circuit Function
From Zones-And-Stripes to Complex Motor Behaviors
Conclusions
References
4 Roof Plate in Cerebellar Neurogenesis
Introduction
Cellular and Molecular Mechanisms Regulating Development of the 4th Ventricle Roof Plate and Choroid Plexus Epithelium
The Role of the Roof Plate and Choroid Plexus in the Development of the Cerebellar Rhombic Lip
Roof Plate-Derived Bmp Signaling as Regulator of Rhombic Lip Development
Other Roof Plate-Derived Secreted Molecules as Regulators of Rhombic Lip Development
The Role of Roof Plate and Choroid Plexus Signaling in Development of the Cerebellar Ventricular Zone and Its Progeny
Roof Plate-Dependent Bmp and Wnt Signals as Regulators of Proliferation of the Cerebellar Ventricular Zone
Shh Signals from the Hindbrain Choroid Plexus Regulate Proliferation of Progenitors in the Late Embryonic Ventricular Zone
Contribution of Bmp Signaling to Migration of Purkinje Cells
Conclusions and Future Directions
Cross-References
References
5 Specification of Cerebellar and Precerebellar Neurons
Specification of Cerebellar Neurons
Specification of Precerebellar Neurons
Conclusions and Future Directions
Cross-References
References
6 Specification of Granule Cells and Purkinje Cells
Introduction
Territorial Allocation
Dorsoventral ``Compartments´´ and the Origin of Cell Types
Temporal Patterning and Lineage in the Rhombic Lip
Secondary Proliferation and Neurogenesis
Diversity of Granule and Purkinje Cells
An Evolutionary Perspective on Neurogenesis
Conclusions
References
7 Gliogenesis
Introduction
Origin and Differentiation of Cerebellar Astrocytes
The Phenotypic Heterogeneity of Cerebellar Astrocytes
Origin of Cerebellar Astrocytes
Lineage Relationship Between Cerebellar Astrocytes and Neurons
Postnatal Amplification of Intermediate Astrocyte Precursors
Differentiation of Cerebellar Astrocytes
Maturation of Morphological Features
Maturation of Molecular Profiles
Origin and Differentiation of Cerebellar Oligodendrocytes
Origin of Cerebellar Oligodendrocytes
Differentiation of Cerebellar Oligodendrocytes
Conclusions and Future Directions
References
8 Granule Cell Migration and Differentiation
Introduction
Granule Cells Exhibit Different Mode, Speed, and Direction of Migration at Different Cortical Layers
Mechanisms Involved in Granule Cell Migration
Control of Granule Cell Migration by Intrinsic Programs
Phase I (PI, a Period of 0-20 h In Vitro)
Phase II (PII, a Period of 20-40 h In Vitro)
Phase III (PIII, a Period of 40-60 h In Vitro)
Time-Dependent Changes in Granule Cell Migration and Morphology by Intrinsic Programs
Possible Roles of Intrinsic Programs on the Regulation of Granule Cell Migration In Vivo
Glutamate Accelerates Granule Cell Migration Through the Activation of NMDA Receptors
Reciprocal Regulation of Granule Cell Migration in the EGL and the IGL by Somatostatin
Halt of Granule Cell Migration in the PCL by PACAP
Ca2+ Spikes Control Granule Cell Migration and Its Termination
EGL
ML
PCL
IGL
Cyclic Nucleotide Signaling Plays a Role in the Control of Granule Cell Migration
Exposure to Alcohol, Methyl Mercury, and Light Alters Granule Cell Migration
Alcohol Adversely Affects Granule Cell Migration
Impairment of Granule Cell Migration by Methylmercury
Light Stimulus Controls Granule Cell Migration via Altering Insulin-Like Growth Factor 1 Signaling
Control of Granule Cell Differentiation
Conclusions and Future Directions
Cross-References
References
9 Purkinje Cell Migration and Differentiation
Introduction
The Generation of Purkinje Cells in the Ventricular Neuroepithelium
Migration of Purkinje Cells
Migration Toward the Cerebellar Cortex and Formation of the Purkinje Cell Plate
Formation of the Purkinje Cell Monolayer
Development of the Purkinje Axon
Development of the Corticofugal Purkinje Axon
Development of the Intracortical Plexus of the Purkinje Axon
Intrinsic Mechanisms and Environmental Control of Purkinje Axon Development
Development of the Purkinje Dendritic Tree
Sequential Phases of Dendritic Differentiation
Intrinsic Determinants Regulate the First Phase of Purkinje Cell Dendritogenesis
Role of ROR-Alpha in the Formation of Purkinje Cell Dendrites
Extrinsic and Intrinsic Factors That Control the Late Phase of Purkinje Dendritic Growth
Role of Parallel Fibers in the Monoplanar Disposition and Branching Pattern of Purkinje Cell Dendrites: Comparison of Control ...
Purkinje Cells as the Organizers of the Architecture and Projectional Arrangement of the Cerebellum
Failure in the Differentiation of Purkinje Cells Leads to the Apparent Disappearance of the Cerebellum
Purkinje Cells Stimulate Granule Cell Neurogenesis
Modular Organization of the Input/Output Projections in the Cerebellum: The Olivocerebellar System
Adult Cerebellum: Purkinje Cell Biochemical Heterogeneity, Parasagittal Stripes of Protein Expression
One Congruent Map or Several Independent Maps?
Organization of the Cerebellar Cortical Layering; Transient Biochemical Heterogeneity of Purkinje Cells and Inferior Olivary N...
Organization of the Three-Dimensional Architecture of the Projectional Maps; Validation of the ``Matching Hypothesis´´ with th...
Conclusions
References
10 Development of Cerebellar Nuclei
Introduction
Overview of Cerebellar Development
Patterning and Morphogenesis
Cerebellar Neuron Subtypes Are Produced Sequentially
Development of the Cerebellar Nuclei in Mammals
Cerebellar Morphogenesis Leading to the Formation of CN
Formation of Deep Cerebellar Neurons: Differentiation, Cellular Migration, and Transcription Factor Expression
Differentiation and Migration of CN GABAergic Neurons
Differentiation and Migration of CN Glutamatergic Neurons
Anatomical and Molecular Classifications of CN Neurons
Efferent Projections: Molecular Determinants for Axonal Guidance
Development of Human Cerebellar Nuclei
Cerebellar Nuclei Abnormalities
Cerebellar Nuclei Defects: Mouse Mutant Phenotypes
Cerebellar Nuclei Defects: Insights from Human Malformations
Joubert Syndrome
Rhombencephalosynapsis
Thanatophoric Dysplasia
Pontocerebellar Hypoplasia
Autism
Conclusions and Future Directions
References
11 Specification and Development of GABAergic Interneurons
Introduction
Cerebellar Inhibitory Interneurons: A Surprisingly Diverse Ensemble
Origins of Cerebellar GABAergic Interneurons
Ptf1a And the Delineation of Cerebellar GABAergic Interneurons
The Deep Cerebellar Mass/Nascent White Matter of the Cerebellar Anlage: An Instructive Environment?
Terminal Differentiation and Synaptic Integration of Postmigratory Precursors of GABAergic Interneurons
Maturation of GABAergic Interneurons Resident in the Molecular Layer
Inhibitory Interneurons of the Granule Cell Layer
Differentiation of Subsets of Golgi Cells and of Non-Golgi GABAergic Interneurons of the Granule Cell Layer
Concluding Remarks
Cross-References
References
12 Development of Glutamatergic and GABAergic Synapses
Introduction
The Mossy Fibers and the Glomeruli
Parallel Fibers
Climbing Fibers
Molecular Specificity of PF and CF Synapses and Heterosynaptic Competition
GABAergic Interneurons of the Molecular Layer: Stellate and Basket Cells
Golgi Cells
Other Inhibitory Interneurons
The Axon Collaterals of Purkinje Cells
Deep Cerebellar Nuclei
Conclusions
Cross-References
References
13 Synaptic Remodeling and Neosynaptogenesis
Introduction
Climbing Fiber-Purkinje Cell Synaptogenesis
Initial Interactions Between Climbing Fibers and Purkinje Cells
Somatodendritic Translocation of Climbing Fiber Terminals
Selective Synapse Elimination Is Based on Homosynaptic Competition
Selective Synapse Elimination Requires Heterosynaptic Competition
Purkinje Cell Function Within the Synaptic Network Regulates Climbing Fiber Refinement
Remaining Questions
Differential Effects of Climbing Fiber and Purkinje Cell Maturation on Selective Axon-Target Interactions
Reinnervation of Purkinje Cells After Mechanical Lesion in the Early Postnatal Period
Climbing Fiber Reinnervation of Mature Purkinje Cells
Post-lesion Reinnervation of Maturing Purkinje Cells: Similarities and Differences from Neonatal Reinnervation
Purkinje Cell Reinnervation After Partial Olivary Lesion by 3-Aminopyridine (3-AP)
Differential Maturation of Synaptic Partners Alter Climbing Fiber - Purkinje Cell Interactions
Mature Climbing Fibers Multi-innervate Immature Purkinje Cells
Prior Purkinje Cell Synaptogenesis Determines the Capacity for Neosynaptogenesis
A Critical Period for Synapse Elimination?
Conclusions
References
14 Synaptogenesis and Synapse Elimination
Introduction
Climbing Fiber Synaptogenesis on Immature Purkinje Cells
Functional Differentiation and Selective Strengthening of Single Climbing Fiber Inputs
Dendritic Translocation of Single Climbing Fibers
Early Phase of Climbing Fiber Synapse Elimination
Late Phase of Climbing Fiber Synapse Elimination
Heterosynaptic and Homosynaptic Competition in Purkinje Cell Synaptic Wiring
Conclusions and Future Directions
References
15 Genes and Cell Type Specification in Cerebellar Development
Introduction
Cerebellar Structure and Early Development
Cerebellar Germinal Zones and Lineage Specification
Ventricular Zone and Cell Type Specification Within GABAergic Lineages
Rhombic Lip and Cell Type Specification Within Glutamatergic Lineages
Cerebellar Glial Cells
Bioinformatic Strategies to Identify Novel Genes in the Specification of Cells During Cerebellar Development
Cerebellar Gene Regulation in Time and Space (CbGRiTS)
The FANTOM5 Consortium
Conclusion and Looking Forward
References
16 Hormones and Cerebellar Development
Introduction
Thyroid Hormone and Cerebellar Development
Molecular Mechanisms of Thyroid Hormone Action
The Effect of Thyroid Hormone on the Developing Cerebellum
Animal Models to Study Thyroid Hormone Action in the Developing Cerebellum
Steroid Hormones and Cerebellar Development
General Overview
Adrenal Steroid Hormones and Cerebellar Development
Gonadal Hormones and Cerebellar Development
Conclusions and Future Directions
Cross-References
References
17 Development of Physiological Activity in the Cerebellum
Introduction
Neuronal Development
Cerebellar Physiology
Early Influences of Adult Firing Patterns
What Influences Physiological State of Developing Purkinje Cells?
Ion Channels
Sodium Channels
Potassium Channels
Calcium Channels
Ion Channels Summary
Other Regulators of Physiological Activity During Development
Calcium Buffers
Synapses
Other Influences of Normal Developmental Physiology
Development Gone Awry: Disease States
Autism Spectrum Disorders
Ataxia
Early-Onset Ataxias
Altered Cerebellar Development in Late-Onset Ataxias?
Conclusions and Future Directions
Cross-References
References
18 Epigenetic Regulation of the Cerebellum
A Brief Introduction to Epigenetic Mechanisms
Genome-Wide Changes in the Epigenetic Landscape in the Developing Cerebellum
Families of Epigenetic Regulators in Mouse Cerebellar Development
ATP-Dependent Chromatin Remodeling Enzymes
Histone Tail Modifiers
DNA Methylation
Perspectives on Epigenetic Regulators in the Mouse Cerebellum
Epigenetic Control of Cerebellar-Dependent Behavior
Epigenetics in Human Disease
Conclusions and Future Directions
References
19 Analysis of Gene Networks in Cerebellar Development
Introduction
Transcription Factor Targetomes
En2 (Engrailed-2)
Atoh1 (Math1)
Rora (RORα)
Physiological and Metabolic Control of Development
Cell Type Specific Genes and Gene Networks
Conclusions and Future Directions
References
Part II: Anatomy, Connections, and Neuroimaging of the Cerebellum
20 Vascular Supply and Territories of the Cerebellum
Overview
Posterior Inferior Cerebellar Arteries (PICAs)
Anterior Inferior Cerebellar Arteries (AICAs)
Superior Cerebellar Arteries (SCAs)
References
21 Vestibulocerebellar Functional Connections
Introduction
Vestibular Primary Afferent Fibers Project to Vestibular Nuclei and Vermal Lobules IX-Lobule X
Vestibular Secondary Mossy Fiber Afferents Terminate Bilaterally in the Cerebellum
Vestibular Climbing Fibers Project to Vermal Lobules IX-X
Purkinje Neurons Generate Two Different Action Potentials
Vestibular Stimulation Modulates the Discharge of CSs and SSs Antiphasically
CSs and SSs Are Aligned in Sagittal Zones in Vermal Lobules IX-X
Granule Cells and Unipolar Brush Cells (UBCs) Discharge in Phase with Mossy and Climbing Fibers
Stellate and Golgi Cells Are Oppositely Modulated by Vestibular Stimulation
A Unilateral Microlesion of β-Nucleus Reduces Vestibular Modulation of Contralateral CSs and SSs
Microlesions of ß-Nucleus Reduce the Modulated Discharge of Contralateral Stellate and Golgi Cells
A Unilateral Labyrinthectomy (UL) Blocks Vestibular Primary Afferent Input to Ipsilateral Vermal Lobules IX-X, but Leaves Inta...
Vestibularly Modulated Discharge of Stellate and Golgi Cells Is Reduced by a Contralateral UL
Functions of Climbing and Mossy Fiber Circuitry
Three Distinct Climbing Fiber-Evoked Pauses in the Discharge of SSs
Cerebellar Functions
Abnormal Cerebellar Function
Conclusions and Future Directions
References
22 Cerebellar Nuclei and the Inferior Olivary Nuclei: Organization and Connections
Introduction
The Cerebellar Nuclei
Subdivision of the Inferior Olive
Afferent Connections of the Inferior Olive
Projections from Spinal Cord, Trigeminal Nuclei, and Dorsal Column Nuclei
Ventral Spino-Olivary Pathways
Projections from the Sensory Nuclei of the Trigeminal Nerve
Projections from the Dorsal Column Nuclei
Optokinetic and Vestibular Projections to the Inferior Olive
Afferents from Tectum and Pretectum
Nuclei at the Mesodiencephalic Border: The Central and Medial Tegmental Tracts
The Corticonuclear and Olivocerebellar Projections
The Corticonuclear Projection
The Olivocerebellar Projection
The Nucleo-Olivary Pathway
Olivocerebellar and Corticonuclear Projections in Primates
The Cerebellar Nuclei: Efferent Connections and Recurrent Climbing Fiber Paths
The Fastigial Nucleus
Anterior Interposed Nucleus
Posterior Interposed Nucleus and Interstitial Cell Groups
Dentate Nucleus
Cross-References
References
23 Axonal Trajectories of Single Climbing and Mossy Fiber Neurons in the Cerebellar Cortex and Nucleus
Introduction
Axonal Trajectories of Single Olivocerebellar Axons
Distribution of CFs
Thin Collaterals of OC Axons
Relationship Between the Longitudinal Distribution of CFs of Single OC Axons and Aldolase C Bands in the Cx
Compartmentation of the CN and Its Relationship to the Cortical Compartments
Morphology of Single Mossy Fibers
Lateral Reticular Nucleus Neurons
General Features of Axonal Trajectories of Single LRN Neurons
Distribution of Terminals of Single LRN Axons in the Cx
Morphology of Collaterals Terminating in the Cerebellar and Vestibular Nuclei
Dorsal Column Nucleus Neurons
Pontine Nucleus Neurons
Spinal Cord Neurons
General Features of Axonal Projection Patterns of Single CF and MF Neurons
Functional considerations: Conclusions
Cross-References
References
24 Visual Circuits from Cerebral Cortex to Cerebellum; The Link Through Pons
Which Cells in the Cerebral Cortex Have an Axon that Projects to the Pons?
Which Areas of Cortex Project to the Pons?
What Is the Pathway of the Cortical Projection to the Pons?
Where Do Corticopontine and Collicular Fibers Terminate in the Pons?
Demagnification
Fibers from the Cerebral Cortex and Colliculus Give off Collaterals
What Are the Receptive Field Properties of Pontine Visual Cells?
Where and how Do the Axons of Pontine Cells Terminate on the Cerebellum?
Some Further Speculations on the Role of the Cortico-Ponto-Cerebellar System
Behavioral Evidence of the Function of the Corticopontine Link
Collateral Fibers and the Corollary Discharge
Receptive Fields and Visual Guidance; the Appearance of the Ground to a Walking Cat
Cerebellum and Kinesie Paradoxale
Cerebellar Localization and Current Problems
References
25 Cerebellar Connections with Limbic Circuits: Anatomy and Functional Implications
Introduction
Defining the Limbic System
Cerebellar Connections with the Limbic System
Cerebellar-Hypothalamic Circuits
Cerebellar Connections with Paralimbic and Neocortical Association Areas
Observations from Neuroimaging Studies
Functional Topography in the Cerebellum
Cerebellum and Pain Modulation
Autonomic Influences
Indirect Limbic Inputs
The Cerebellum Is Implicated in Autism Spectrum Disorders (ASD)
Implications of a Cerebellar Role in Emotional Processing
Therapeutic Implications
Conclusions and Future Directions
References
26 Cerebellar Influences on Descending Spinal Motor Systems
Introduction
The Cerebellar Nuclei
Medial and Lateral Descending Motor Systems from the Brainstem
Reticulospinal Tracts
Medial Cerebellar Nucleus
The Posterior Interposed Nucleus and the Interstitial Cell Groups
The Anterior Interposed Nucleus and the Dorsolateral Hump
The Lateral Cerebellar Nucleus
Vestibulospinal Tracts
Cerebellar Corticovestibular Projections
Cerebellar Nucleo-Vestibular Connections
Rubrospinal Tract
Cerebellar Projections to the Red Nucleus
Tectospinal Tract
Cerebellar Nucleo-Tectal Connections
Interstitiospinal Tract
Cerebellar Projections to the Interstitial Nucleus of Cajal
Cerebellar Projections to Other Areas
Divergence of Cerebellar Projections
Convergence of Cerebellar Projections
Functional Implications
Clinical Implications
Hypotonia
Ataxia
Intention Tremor
Conclusions and Future Directions
Cross-References
References
27 Cerebellar Thalamic and Thalamocortical Projections
Introduction
Cyto- and Chemoarchitecture of the Motor Thalamus
Afferents of the Motor Thalamus
Motor Thalamic Projections to Cortex
Projections to MI
Projections to SMA and Pre-SMA
Projections to the Premotor Cortex
Projections to Other Cortical Areas
General Topography of Projections
Conclusions and Future Directions
References
28 Cerebellar Outputs in Non-human Primates: An Anatomical Perspective Using Transsynaptic Tracers
Introduction
Cerebellar Output Channels
Macro-Architecture of Cerebro-Cerebellar Loops
The Cerebellum Is Interconnected with the Basal Ganglia
Summary and Conclusions
References
29 Delineation of Cerebrocerebellar Networks with MRI Measures of Functional and Structural Connectivity
Introduction
Functional Connectivity
ROI-Based fcMRI of the Dentate Nucleus
ROI-Based fcMRI of the Cerebellar Cortex
ROI-Based fcMRI of the Cerebral Cortex
ICA fcMRI
Tractography
Conclusions and Future Directions
References
30 Radiographic Features of Cerebellar Disease: Imaging Approach to Differential Diagnosis
Introduction
Congenital
Cerebellar Agenesis, Hypoplasia, and Atrophy
Cerebellar Dysplasia and Malformations of Cortical Development
Congenital Posterior Fossa Cysts and Related Disorders (Poretti et al. 2016a)
Acquired
Cerebrovascular
Ischemic Changes
Hemorrhage
Vascular Pathologies
Traumatic
Infectious
Genetic
Autoimmune
Neurodegenerative
Neoplastic
Toxic and Miscelaneous Disorders
Conclusions
References
31 Imaging Vascular Anatomy and Pathology of the Posterior Fossa
Introduction
Vascular Anatomical Overview
Ischemic Diseases of the Posterior Fossa
Brainstem Ischemic Syndromes
Medullary Ischemic Syndromes
Pontine Ischemic Syndromes
Midbrain Ischemic Syndromes
Basilar Artery Occlusion
Cerebellar Ischemic Syndromes
Posterior Inferior Cerebellar Artery Infarction
Anterior Inferior Cerebellar Artery Infarction
Superior Cerebellar Artery Infarction
Hemorrhagic Diseases of the Posterior Fossa
Aneurysmal Disease
Saccular Aneurysms
Fusiform Aneurysms
Distal Cerebellar Aneurysms
High-Flow Vascular Malformations
Pial Arteriovenous Malformations
Dural Arteriovenous Fistulas
Imaging Approach for Posterior Fossa Neurovascular Disease
Conclusion and Future Directions
References
32 MR Spectroscopy in Health and Disease
Introduction
Neurochemicals Detectable by 1H MRS
Technical Challenges of MR Spectroscopy in the Cerebellum
Neurochemical Profile of the Cerebellum
MRS of the Cerebellum in Neurodegenerative Diseases
MRS of the Cerebellum in Cancer
MRS of the Cerebellum in Metabolic Disorders
Other Applications of MRS of the Cerebellum
Conclusions and Future Directions
References
33 Functional Topography of the Human Cerebellum Revealed by Functional Neuroimaging Studies
Introduction
Functional Connectivity Data Reveal Different Functional ``Zones´´ in the Cerebellum
Activation During Sensorimotor Tasks
Fractured Somatotopy: Cerebellar Activation During Simple Sensorimotor Tasks
Eye Movements
Complex Sensorimotor Tasks: Motor Learning, Tool Use
Cerebellar Activation During Cognitive Tasks
Language and Reading
Spatial Processing
Executive Function Tasks, Including Working Memory
Social/Emotional/Affective Processing
Cross-domain Relative Topography
Meta-analyses of Neuroimaging Literature
Multidomain Imaging Studies
Within-Task Topography
Multiple Representations of Motor, Cognitive, and Affective Function in the Cerebellar Cortex
Conclusions and Future Directions
References
Part III: Neurotransmission, Neuromodulation, and Physiology
34 Cerebellar Granule Cell
Introduction
Granule Cell Ontogenesis and Connectivity
Granule Cell Neurobiology: Receptors and Transduction Pathways
Intrinsic Electroresponsiveness
Fast Synaptic Transmission at Glomerular Synapses
Long-Term Synaptic Plasticity
Granule Cell Activity In Vivo
Granule Cell Models
New Views on the Granule Cell Function: Transformations of Signals in Time, Frequency, and Space
Pathologies of the Granule Cells
Conclusions and Future Directions
References
35 Purkinje Neurons: Synaptic Plasticy
Introduction
PF-LTD
Involvement of Intracellular Ca2+ Increase
Decrease of Functional Postsynaptic AMPA Receptor Number at PF-PC Synapses
Kinase and Phosphatase Signaling Pathways
Role of Presynaptic Receptors at PF-PC Synapses
Transcription Factors, Protein Synthesis
PF-LTP
Additional Forms of PC Synaptic Plasticity
Conclusions and Future Directions
References
36 Stellate Cells: Synaptic Processing and Plasticity
Introduction
Physiological Properties of Molecular Layer Interneurons
Function of Molecular Layer Interneurons
Synaptic Plasticity of Molecular Layer Interneurons
Conclusions and Future Directions
Cross-References
References
37 Golgi Neurons
Introduction
Neurochemical and Morphological Diversity of Golgi Cells: Toward a Functional Classification
Golgi Cells and Lugaro Cells Represent Two Different Types of Neurons
Organization of the Golgi Cells´ Inhibitory Input onto Granule Cells
Golgi Cells Are a Neurochemically Heterogenous Group of Cells
Synaptic Inputs onto Golgi Cells
Excitatory Synaptic Inputs to Golgi Cells
Mossy Fiber Inputs
Granule Cell Inputs
Climbing Fibers Preferentially Target Lugaro Cells
Inhibitory Synaptic Inputs to Golgi Cells
Lugaro Cells Are Master Inhibitory Interneurons of the Cerebellar Cortex
Purkinje Cells Contact Lugaro, but Not Golgi Cells
In Vivo Studies
Golgi Cell Spontaneous Activity in Anesthetized Animals Is Characterized by Slow Irregular Firing
Golgi Cells Display a Complex Triphasic Response to Peripheral Stimulations
Golgi Cells Display Large Receptive Fields and Modulated Discharge Patterns during Motor Behavior
Golgi Cell Excitability and Granular Layer Dynamics: Gain Control and Oscillations
Role of the Cerebellum in Oscillatory Motor Control
Gap-Junctional Coupling of Firing Golgi Cells Generates Beta-Band Resonant Population Oscillations
Feedback Inhibition and Oscillations in Models of the Granule Cell Layer
Conclusions and Future Directions
References
38 Glutamate Receptor Auxiliary Subunits and Interacting Protein Partners in the Cerebellum
Introduction
Glutamate Receptors in Cerebellar Neurons and Glia
AMPARs and Plasticity in the Cerebellum
Glutamate Receptor Auxiliary and Interacting Protein Partners in the Cerebellum
Transmembrane AMPAR Regulatory Proteins: TARPs
Cornichon Homologues Interact with AMPARs
PICK1, GRIP, and ABP: Intracellular Protein Partners of AMPARs
N-Ethylmaleimide Sensitive Fusion Protein Interacts with GluA2
AMPAR Interaction with Synapse-Associated Scaffolding Proteins (SAPs)
The Cadherin-Catenin Cell-Adhesion Complex
Kainate Receptor Interacting Proteins in the Cerebellum
NETO2
KRIP6
Conclusions
References
39 GABA and Synaptic Transmission in the Cerebellum
Introduction
Purkinje Cells
Basket and Stellate Cells
Golgi Cells
Other Types of Neurons in the Cerebellar Cortex
GABAergic Neurons in the Cerebellar Nuclei
GABA Receptors in the Cerebellum
Regulation of Glutamatergic Synaptic Inputs to GABAergic Neurons
Regulation of GABAergic Synapses
Behavioral Abnormality Caused by Alteration of GABAergic Synaptic Transmission
GABA in Cerebellar Ataxia
Conclusion and Future Directions
Cross-References
References
40 Norepinephrine and Synaptic Transmission in the Cerebellum
Introduction
Anatomical Considerations
Physiology of NE in Cerebellum
Noradrenergic Receptors in Cerebellum
Cerebellar Dysfunction in Aging
Conclusions and Future Directions
References
41 Serotonin and Synaptic Transmission in the Cerebellum
Introduction
Serotonergic Fiber Innervation of the Cerebellum
Serotonergic Modulation in the Cerebellar Cortex
Serotonergic Modulation in the Deep Cerebellar Nuclei
Conclusions and Future Directions
References
42 Cannabinoids and Synaptic Transmission in the Cerebellum
Introduction
The Endocannabinoid System
Endocannabinoid Biosynthesis and Degradation
Targets of Endocannabinoids
CB1 Cannabinoid Receptors
Retrograde Endocannabinoid Signaling
Autocrine Signaling and Regulation of Neuronal Excitability
Endocannabinoid Release in Purkinje Cells
DSE and DSI: Global Endocannabinoid Signaling
Synaptically Evoked Suppression of Excitation (SSE): Local Endocannabinoid Signaling
Long-Term Depression (LTD)
Long-Term Potentiation (LTP)
Endocannabinoid Signaling in Cerebellar Circuitry
Parallel Fiber to Stellate Cell and Basket Cell Synapses
Parallel Fiber to Golgi Cell Synapses
The Spread of Endocannabinoids in the Cerebellar Cortex
Endocannabinoid Signaling and Information Flow Through the Cerebellar Cortex
The Endocannabinoid System and Cerebellar Function
Human Studies
Animal Models
Endocannabinoid Signaling in Other Cerebellar Circuits
Conclusion
References
43 Nitric Oxide and Synaptic Transmission in the Cerebellum
Introduction
The Sources of NO and cGMP
Nitric Oxide Synthases
Soluble Guanylyl Cyclases
Downstream cGMP Effectors
Ion Channels
Phosphodiesterases
cGMP-Dependent Protein Kinases
NO and Synaptic Transmission in the Cerebellum
Granule Cells as a Central Player in Cerebellar NO Signaling
Mossy Fiber-Granule Cell Synapses
Parallel Fiber (PF)-Purkinje Cell Synapses
Vesicle Recycling as a Target of NO/cGMP/cGK Signaling to Regulate Synaptic Transmission
Conclusions and Future Directions
Cross-References
References
44 Purinergic Signaling in the Cerebellum
Introduction
ATP (P2) Receptors
P2 Receptor Expression in the Cerebellum
Functional Effects of P2 Receptor Activation in the Cerebellum
Synaptic Actions of ATP
Role of ATP in Glial Signalling
Extracellular Metabolism of ATP
Adenosine Signalling in the Cerebellum
Adenosine (P1) Receptors in the Cerebellum
Adenosine Release
Does the Extracellular Adenosine Tone Arise from Extracellular ATP Metabolism?
Release of Adenosine in Cerebellar Cultures
Release of Adenosine in Cerebellar Slices
Molecular Layer Stimulation: Is Adenosine a Neurotransmitter?
Do Climbing Fibers Release ATP or Adenosine?
Breakdown and Uptake of Adenosine
Hypoxia and Ischemia
The Role of Purinergic Signalling in the Cerebellum and in Motor Control
Conclusions and Future Directions
Cross-References
References
45 Modulatory Role of Neuropeptides in the Cerebellum
Introduction
Corticotropin-Releasing Factor Family of Peptides
Distribution
CRF Receptors in the Cerebellum
Functional Roles of CRF in the Cerebellum
Ligand-Receptor Mismatch
Functional Role of UCN in the Cerebellum
Conclusions
References
46 Taurine in the Cerebellum
Introduction
Cellular Actions of Taurine
Effects of Taurine Neuronal Circuits
Taurine Induced Biochemical Alterations in the Brain
Taurine Enhances the Neuroendocrine Interaction Between the Brain and the Pancreas
Conclusion
References
47 Biological Actions of Neurosteroids in the Growth and Survival of Purkinje Cells During Cerebellar Development
Introduction
Discovery of the Purkinje Cell as a Major Site for Neurosteroidogenesis
Biosynthesis of Neurosteroids in the Purkinje Cell
Biological Actions of Progesterone, Allopregnanolone, and Estradiol Produced in the Purkinje Cell on the Growth and Survival o...
Mode of Action of Progesterone and Estradiol Produced on Purkinje Cell Growth During Cerebellar Development
Discovery of the Pineal Gland as a Major Site for Neurosteroidogenesis
Identification of Major Neurosteroids Produced in the Pineal Gland
Biological Action of Allopregnanolone Produced in the Pineal Gland in the Survival of Purkinje Cells During Cerebellar Develop...
Mode of Action of Pineal Allopregnanolone on Purkinje Cell Survival During Cerebellar Development
Conclusions
Cross-References
References
48 Inferior Olive: All Ins and Outs
Development of the Inferior Olive and Climbing Fibers
The Origin of Inferior Olivary Neurons
Migration of Inferior Olivary Neurons
Inferior Olivary Subdivisions and Cell Types
Climbing Fiber Outgrowth and Elimination
Ultrastructure of the Inferior Olivary Neuropil
Glomeruli and Gap Junctions
Inputs and Origin
Neurotransmitters and Receptors
Cell Physiology of Inferior Olivary Neurons
Subthreshold Oscillations and Spike Timing
Electrical Synapses in the Inferior Olive
Synaptic Modification of Oscillations and Coupling
Action Potential Waveforms
Models of the Olivary Neurons
Single-Cell Models
Network Models
Climbing Fiber Patterns and Behavioral Consequences
Spatiotemporal Patterns
Behavioral Consequences
Functional Models of the Olivocerebellar System
Marr-Albus-Ito Learning Models
Motor Timing Models
Pathology of Inferior Olive
Conclusions
References
49 Dynamics of the Inferior Olive Oscillator and Cerebellar Function
Introduction
Basic Features of the Inferior Olive
Excitable Properties of IO Neurons
Subthreshold Oscillations
Gap Junctions and Synchrony
Oscillations and Olivary Output
Extrinsic Control of Oscillations
Rhythmicity and Synchrony in the Climbing Fiber System
Conclusion
References
50 Feedback Control in the Olivocerebellar Loop
Introduction
Anatomical Features of the NO Pathway
Neurophysiological Properties of the NO Pathway
Functions of the NO Pathway
Regulation of Spontaneous Purkinje Cell Activity
Regulation of Cerebellar Learning
Regulation of Electrotonic Coupling in the Inferior Olive
Indirect Cerebellar Control of Olivary Excitability
Conclusion
Acknowledgments
References
51 Neurons of the Deep Cerebellar Nuclei
Introduction
Projection Neurons
Large Glutamatergic Projection Neurons
Small, GABAergic Projection Neurons
Glycinergic Projection Neurons: Nucleocortical and Nucleovestibular
Interneurons
GABAergic/Glycinergic Interneurons
Non-GABAergic (Putatively Glutamatergic) Interneurons
Summary
References
52 Cerebellar Nuclei and Cerebellar Learning
Introduction
Functional Considerations
Cellular Properties and Synaptic Integration in the CN
Modulation of Spike Rate
Activation of Rebound Firing
The Eyeblink Conditioning Paradigm as a Blueprint for Learning Mechanisms in the CN
Adaptation of the Vestibulo-Ocular Reflex (VOR) Gain Shares Many Features with Eyeblink Conditioning
Learning Limb Movements Does Not Take Place in the CN but Submovement Coordination May
Cellular Plasticity in the CN
Plasticity in the Mossy Fiber Inputs to CN Neurons
Plasticity in the Purkinje Cell CN Pathway
Other Forms of Plasticity in the CN
Conclusion and Future Directions
Cross-References
References
53 Cerebro-cerebellar Connections
Introduction
Descending Projections to the Cerebellum
Cerebro-Pontocerebellar Pathways
Cerebro-Olivocerebellar Pathways
Conclusions and Future Directions
Cross-References
References
54 Cerebellar Control of Eye Movements
Introduction
Floccular Complex
Neuronal Responses
Nodulus and Uvula
Neuronal Responses
Oculomotor Vermis and Fastigial Oculomotor Region
Motor Learning in Eye Movements by the Cerebellar Cortex
Models of Eye Movement Control of the Cerebellum
Conclusions and Future Directions
References
55 Cerebellum and Eyeblink Conditioning
Introduction
Critical Neural Circuitry
Eyeblink Conditioning and Cerebellar Dysfunction
Conclusions and Future Directions
References
56 Purkinje Neurons During Eye Blink Conditioning and New Mechanisms of Cerebellar Learning and Timing
Introduction
Pause Responses in Purkinje Cells During Conditioning
Correspondences Between Overt CRs and Purkinje Cell CRs
Acquisition and Extinction
Temporal Properties of Purkinje Cell CRs
Minimum CS-US Interval
Cellular Mechanisms of Simple Spike Suppression and Timing
Conclusions and Future Directions
Cross-References
References
57 Cerebellar Control of Speech and Song
Introduction
Anatomical Substrates
Internal Models
Laterality
Cerebellum and Working Memory
Verbal Fluency
Grammar Processing
Linguistic Deficits in Cerebellar Patients
Conclusions and Perspectives
References
58 Cerebellum and Timing
History/Background
Cerebellar Function in Sensorimotor Timing: Neuropsychological Studies
Cerebellar Function in Sensorimotor Timing: Neuroimaging and TMS Studies
Cerebellar Contributions to Perceptual Timing: Neuropsychological Studies
Cerebellar Contributions to Perceptual Timing: Neuroimaging Studies
Cerebellar Timing Function in Sensorimotor Learning
The Range of Cerebellar Timing
The Cerebellum as an Event Timer
Conclusions
References
59 Cerebellar Control of Posture
Introduction
Anatomical Aspects
Historical Aspects
Postural Disturbances After Cerebellar Lesions
Animal Data
Postural Deficits in Cerebellar Patients
Genetic Aspects
Plasticity in Cerebellum
Role of Cerebellum in Learning
Cerebellum and Learning Postural Tasks
Conclusion
References
60 Channelopathies and Cerebellar Disease
Introduction
Channels and Channelopathy
SCA6 (CACNA1A)
SCA13 (KCNC3)
SCA15/29 (ITPR1)
SCA19 (KCND3)
SCA41 (TRPC3)
SCA42 (CACNA1G)
SCA44 and SCAR13 (GRM1)
SCAR18 (GRID2)
EA1 (KCNA1)
EA5 (CACNB4)
EA6 (SLC1A3)
Clinical Overview
Treatment of Channelopathy
Conclusions and Future Directions
References
61 Disruption of the Microbiota-Gut-Brain (MGB) Axis and Mental Health of Astronauts During Long-Term Space Travel
Introduction
The Microbiota-Gut-Brain (MGB) Axis in a Nutshell
The Role of the Cerebellum in the Gut-Brain Axis: A Gut-Cerebellar Brunch
Examples of Clinical and Animal Data Supporting the Concept of Disrupted MGVHB Axis in Space
Altered Gut Microbiota and Gut Structure in Space Environment
Vagus Nerve Signaling and Heart Abnormalities in Astronauts
Changes in Brain Structure and Behavior
Impact of Space Environmental Factors on the MGVHB Axis
Diet
Gravity
Radiation
Stress
Sexually Dimorphic Nature of the MGVHB Axis, as a Factor in Selection of Women Versus Men for Long-Term Space Travel
Possible Means of Minimizing the Effects of the Environment of Space Travel on Astronauts´ MGVHB Axis and Mental Health
Concluding Remarks
Cross-References
References
62 Cerebellum-Like Structures
Introduction
Cerebellum-Like Structures in Different Vertebrate Groups
Circuitry of Cerebellum-Like Structures
Comparison of the Local Circuitries of Cerebellum-Like Structures and the Cerebellum
Patterns of Gene Expression in Cerebellum-Like Structures and the Cerebellum
Evolution of Cerebellum-Like Structures and the Cerebellum
Sensory Predictions in Cerebellum-Like Structures
Plasticity at Parallel Fiber Synapses in Cerebellum-Like Structures and the Cerebellum
Adaptive Function in Cerebellum-Like Structures Versus the Cerebellum
Predictions in the Cerebellum
Conclusions and Future Directions
References
Part IV: Computational Models of Cerebellar Function
63 Cerebellum and Internal Models
Introduction
Internal Models and the Central Nervous System
Internal Models for Motor Control and the Cerebellum
Motor Deficits in Patients with Cerebellar Disease
Functional Imaging Studies
Noninvasive Cerebellar Stimulation
Electrophysiological Investigations
Cerebellar Internal Models for Tool Use
Cerebellar Internal Models Beyond Motor Function
Conclusion and Future Directions
Cross-References
References
64 State Estimation and the Cerebellum
Introduction
Internal Models
Behavioral Evidence of State Estimation
State Estimation and the Cerebellum
Prediction Error and Adaptative Learning
Conclusions and Future Directions
References
65 Adaptive Filter Models
Introduction
Model Alterations
Molecular Layer Interneurons
Spike-Timing-Dependent Plasticity
Initial Plausibility of Altered Model
Problems with LTD
Possible Solutions
Importance of LTP
Problems in Characterizing LTD
In Vivo LTD
Conclusions
References
66 Cerebellum and Human Evolution: A Comparative and Information Theory Perspective
Introduction
Comparative Changes in the Cerebellum and Information Processing
Estimated Comparative Changes in the Volume Fraction of the Neocerebellum
Comparative Changes in the Number of Granule-Cell-Purkinje-Cell (gcPc) Synapses in Mammals
Summary
The Role of the Cerebellum in Complex and Adaptive Behavior
Adaptive Behavior and the Cerebellum: Action Perception and Learning and Memory
Complex Behavior and the Cerebellum: Information Coding and Processing Capacity
Comparative Changes of the Cerebellum and Behavior
Cerebellum and Human Evolution
Conclusions and Future Directions
References
67 Computational Structure of the Cerebellar Molecular Layer
Introduction
Motor Control as the Computational Context for Cerebellar Theory
Linking Function to Structure
What Do Parallel Fibers Do to Purkinje Cells?
Uncovering Function from Structure
Functional and Algorithmic Implications for the Cerebellar Molecular Layer
Implications for Previous Models of Cerebellar Function
A New Cortical Computational Algorithm
Conclusions and Future Directions
References
68 Recursive Genome Function of the Cerebellum: Geometric Unification of Neuroscience and Genomics
Introduction
Agenda: The Cerebellum as the Platform for the Unification of Neuroscience and Genomics by the Geometric School of Biophysics
Recursion in the Cerebellum
Review: Philosophies, Theories, and Computational Models as Foundations of the School of Cerebellar Recursion
The Concept of Coordinates and Their Recursion as Basics of Tensor Network Theory of Cerebellar Neural Nets
Generalization of Recursion from Cerebellar Neuroscience to Genomics; Covariant and Contravariant RNA Functors and Their Eigen...
Recursive Algorithms Rule Both Vector-Matrix and Fractal Representations
Tensor Network Theory: Vector-Matrix Recursion as Basis of the Cerebellum Acting as a Sensorimotor Metric Tensor
Fractals Are Pervasive in Nature; Both the Cerebellar Brain Cells and the DNA are Fractal Objects
The Zipf-School Suspected that the DNA Contained a Fractal Language
The Genome is Fractal: Grosberg-School Suspected that the DNA Showed Fractal Folding
The Perez-School Shows that the DNA is Fractal at DNA, Codon- and Full Chromosome Set and Whole Genome Levels
Fractals to DNA Numerical Decoding: Toward the Golden Ratio
The ``Fractal Chaos´´ Artificial Neural Network
``DNA SUPRACODE´´ Overview
In Single-Stranded DNA Human Genome, Codons Population are Fine-Tuned in Golden Ratio Proportions
A Strange Meta-Architecture Organizes Our 24 Human Chromosomes
Unifying All Biological Components of Life: DNA, RNA, Proteins
Neural Net Elements are Fractal: Purkinje Neuron Fractal Model
The Genome is Fractal! Proof of Concept and the Basis of Generalization: Whole Genome Analysis Reveals Repetitive Motifs Confo...
Conclusions
Neuronal and Genomic Systems are Governed by Recursive Algorithms of Massively Parallel Networks, Not Only Including, but Surp...
Application of Fractal Genomics is Already Here
Friedreich Spinocerebellar Ataxia
Application of Fractal Genomics for Cancer
Future Directions
Theory of Recursive Algorithms
Neural Net Algorithms Comprise Massively Parallel and Coordinated Genome Function
Integration of Neural Net and Fractal Algorithms
Develop and Integrate Quantum Theory of Neuroscience and Genomics
Public Domain Agenda in Industrialization of Genomics: Local and Global Fractal Dimension as a Standard Definition for Optimal...
Proprietary Agenda in Industrialization of Genomics
Hybrid Computation on Private Clouds
Consumer Genomics in Continuous Customer Care
References
Part V: Animal Models to Study Cerebellar Function
69 Animal Models: An Overview
Introduction
Non-mammallian Animal Models
Non-vertebrate Animal Models
Fish Models
Amphibian and Reptile Models
Avian Models
Rodent Models
Mouse Models for Inherited Ataxia
Non-mouse Rodent Models
Non-rodent Mammal Models
Primate Models
Cat Models
Conclusions and Future Directions
Cross-References
References
70 Cerebellar Development and Neurogenesis in Zebrafish
Introduction
The Cerebellar Anatomy and Architecture
Cerebellar Cell Layers, Cell Types, and Circuitry
Cerebellar Afferents and Efferents
Cerebellar Development
Positioning of the Midbrain-Hindbrain Boundary and Role of the Isthmic Organizer in Establishing the Cerebellar Territories
Cerebellar Germinal Zones and Progenitor Domains
Cerebellar Neurogenesis
Adult Neurogenesis and Regenerative Potential of the Zebrafish Cerebellum
Conclusions and Future Directions
References
71 Teleost Fish
Introduction
Gross Morphology of the Teleost Cerebellum
Cellular Organization and Neural Circuit
Cerebellar Efferent Neurons in Teleost
Afferent and Efferent Fiber Connections with Other Brain Regions
Functions of Teleost Cerebellum
Conclusions and Future Directions
References
72 Robotic Mouse
Introduction
Phenotype, Neuropathology, and Behavior
Genetic and Molecular Basis
AF4, the Mutated Disease Protein, Abnormally Accumulates in Robotic PCs
AF4: A Cofactor of Transcriptional Elongation and Chromatin Remodeling
Downregulation of the IGF-1 Signaling Pathway Causes PC Degeneration in the Robotic Cerebellum
Conclusions and Future Directions
Cross-References
References
73 Lurcher Mouse
Introduction
Morphological and Cellular Changes in the Lurcher Mutant Central Nervous System
Pathogenesis of the Neurodegeneration in Lurcher Mice
Lurcher Mutation
Etiology of the Degeneration and Role of GluRδ2
Cell Death Mechanisms
Neurochemical Abnormalities and Changes of Brain Metabolism
Abnormalities of Neurotransmitters and Receptors Systems
Abnormalities in the Endocrine and Immune Systems of Lurcher Mice
Behavioral Characteristics of Lurcher Mice
Motor Functions
Cognitive Functions
Other Behavioral Characteristics
Experimental Influencing of Lurcher Mice
Effects of Cerebellectomy
Lurcher Mice in Neurotransplantation Research
Enforced Physical Activity and Enriched Environment
Pharmacological Influencing
Breeding and Colony Maintenance
Conclusions and Future Directions
Cross-References
References
74 Tottering Mouse
Introduction
Tottering Mouse as a Model of a Human Calcium Channelopathy
Behavioral Phenotype
Morphological and Histochemical Alterations
P/Q-Type Channel Dysfunction in Tottering
Altered Synaptic Transmission in Tottering
Purkinje Cell Dysfunction in Tottering
Upregulation of L-Type Ca2+ Channels in Tottering
Role of Cerebellum in Episodic Dystonia
Cerebellar Contribution to Absence Seizures
Low-Frequency Oscillations in Tottering
Triggers of Episodic Dystonia
Conclusions and Future Directions
References
75 Rolling Nagoya Mouse
Introduction
Phenotypic Description of the Rolling Nagoya Mouse
CaV2.1 Channels and the Rolling Nagoya Mutation in Cacna1a
Histological Analyses of Rolling Nagoya Brain Areas
Effect of the Rolling Nagoya Mutation on CaV2.1 Channel Electrophysiology
Effects of the Rolling Nagoya Mutation on Cellular Neurophysiological Behavior
Aberrant Action Potential Firing Pattern in Cerebellar Purkinje Cells
Dysfunction of Cerebellar Synapses and the Neuromuscular Junction
The Rolling Nagoya Mouse as a Model for Human CaV2.1 Channelopathies?
Ataxia
Migraine
Lambert-Eaton Myasthenic Syndrome
Conclusions and Future Directions
Cross-References
References
76 Ataxic Syrian Hamster
Introduction
Origin of Discovery and Hereditary Mode
Breeding and General Properties
Histology
Genetics
Possible Applications
pcd Mutation in Mice
Comparison to pcd Mutant Mice
Conclusions and Future Directions
Cross-References
References
77 Moonwalker Mouse
Introduction
The mGluR1-TRPC3 Pathway in Cerebellar Ataxia
The Moonwalker Mutation
Pathophysiology
Behavioral Phenotype
Morphological Changes
Loss of Cells
Impaired Dendritic and Synaptic Development
Conclusions and Future Directions
References
78 Hemicerebellectomy
Introduction
The Hemicerebellectomy Model
HCb and Experimentally Induced Neuroplasticity
HCb as a Model for Studying Axotomy-Induced Neurodegeneration
HCb and Endocannabinoids
HCb and Neuron-Glia Crosstalk in Neurodegeneration
HCb at Various Developmental Stages and Motor Recovery
HCB and Maze Learning
HCB and Changes in Motor Cortical Physiology
Conclusions and Future Directions
References
Part VI: Symptoms of Cerebellar Disorders in Human
79 Role of Cerebellum in Gaze-Holding Disorders
Introduction
Physiology of Gaze Holding: The Neural Integrator
Gaze-Evoked Nystagmus: Abnormal Function of Ocular Motor Neural Integrator
Vestibular Neural Integrator and the Velocity Storage
Gravity-Dependent Nystagmus
Periodic Alternating Nystagmus (PAN)
Vertical Nystagmus
Oculopalatal Tremor
References
80 Cerebellar Motor Disorders
Introduction
Contributions of Luciani, Babinski, and Holmes
Symptoms
Oculomotor Disturbances
Dysarthria and Other Speech Deficits
Dysphagia
Ataxia of Limbs
Ataxia of Stance and Gait
Topography of Clinical Deficits
References
81 Lesion-Symptom Mapping of the Human Cerebellum
Introduction
Human Cerebellar Lesion Conditions
Cerebellar Stroke
Cerebellar Tumors
Cerebellar (Cortical) Degeneration
Lesion-Symptom Mapping
Focal Cerebellar Disorders
Structural MRI Sequences and Delineation of Focal Lesions
Chronic Cerebellar Lesions
Acute Cerebellar Lesions
Cerebellar Nuclei
Normalization of the Cerebellar Cortex and Nuclei
Statistical Analysis in Focal Cerebellar Lesions
Superimposition of Lesions in Patients Showing the Same Disorder
Comparing Lesion Site in Two Groups of Patients
Voxel-Wise (Inferential) Statistical Mapping
Cerebellar (Cortical) Degeneration
Volumetric Analysis of the Cerebellum
Voxel-Based Morphometry (VBM)
Structural Connectivity of Cerebellar Pathways
Atlases of the Cerebellar Cortex and Nuclei
Atlas of the Cerebellar White Matter Tracts
Conclusions and Future Directions
Cross-References
References
82 Deficits of Grasping in Cerebellar Disorders
Introduction
Deficits of Reaching and Grasping
Predictive and Reactive Control of Grasping Forces
Internal Forward Models
Living Without a Cerebellum
Case Description
Deficits of Grasping Force Control
Deficits of Higher-Order Motor Control Related to Grasping?
References
83 Ataxic Hemiparesis
Introduction
A Brief History of AH
Core Symptoms of AH
Variations of AH
Painful AH
Sensory AH
Other Variations
The Severity of AH
Nonischemic AH
Hemorrhagic Stroke Causing AH
Other Causes of AH
Frequency of AH
Mechanisms and Topography of AH Lesions Following IS
Cerebral Cortex
Subcortical Lesions
Thalamus and Internal Capsule
Basal Ganglia
Brainstem and Cerebellum
The Role of Afferent and Efferent Pathways
Etiology of Stroke Associated with AH
Diagnostic Testing for AH
Treatment for AH
Prognosis of AH
Conclusions and Future Directions
References
84 Cerebellum and Cognition
Introduction
Evolution
Congenital Malformations of the Posterior Fossa
Abnormalities of Cerebellar Volumes and Structure
Pre- and Perinatally Acquired Cerebellar Problems
Acquired Problems During Childhood
Late-Onset Cerebellar Problems
Functional Neuroimaging
Conclusion
References
85 Cerebellar Sequencing for Cognitive Processing
Introduction
Somatosensory Processing
Cognition
Scripts
Acquisition of Procedures
Visuospatial Processing
Language
Sequencing for Language Processing
Sequencing for Writing
Conclusion and Future Directions
Cross-References
References
86 The Cerebellar Cognitive Affective Syndrome and the Neuropsychiatry of the Cerebellum
Introduction
Anatomical Connections: Overview
Topographic Arrangement of Anatomical Connections
Imaging Observations in Humans
The Cerebellar Motor Syndrome: Clinical Features and Structure-Function Correlations in Stroke
The Cerebellar Cognitive Affective Syndrome: The Initial Description
The Cerebellar Cognitive Affective Syndrome: Subsequent Reports
Selected Case Series
Selected Case Reports
The Cerebellar Cognitive Affective Syndrome in Children
Postoperative Pediatric Cerebellar Mutism and CCAS
Neuropsychiatry of the Cerebellum: The Affective Component of the CCAS
The Cerebellum in Psychiatric Disease: Focus on the Vermis
Cognition in Ataxic Disorders
Cerebellar Lesions Impair Cognition in the Developing Brain: Developmental CCAS
Mechanisms of the Cerebellar Contribution to Cognition and Emotion
An Approach to Testing Cerebellar Cognition at the Bedside
Implications for Diagnosis and Management of Patients with Cerebellar Disease
References
87 Cerebellar Mutism Syndrome in Children and Adults
Introduction
Semiological Characteristics of Cerebellar Mutism Syndrome
Cerebellar Mutism Syndrome in Children
Cerebellar Mutism Syndrome in Adults
Preoperative Neurocognitive Assessments
Risk Factors for POPCMS
Pathophysiological Explanations and Hypotheses
Functional Lateralization of the Cerebellum: Evidence from CMS
Treatment and Rehabilitation
Concluding Remarks
Cross-References
References
88 Human Cerebellum in Motivation and Emotion
Introduction
Argument 1
Argument 2
Argument 3
Argument 4
Argument 5
Argument 6
Discussion
Conclusions and Future Directions
References
Part VII: Cerebellar Disorders
89 Clinical Scales of Cerebellar Ataxias
Introduction
International Cooperative Ataxia Rating Scale (ICARS)
Validation
Clinical Application
Friedreich Ataxia Rating Scale (FARS)
Validation
Clinical Application
Scale for the Assessment and Rating of Ataxia (SARA)
Validation
Clinical Application
Brief Ataxia Rating Scale (BARS)
Validation
Clinical Application
Scales for the Clinical Evaluation of Cerebellar Disorders: From Pediatric Perspective
ICARS, SARA, and BARS in Pediatric Patients
Clinical Implications
In Conclusion
References
90 Approach to the Differential Diagnosis of Cerebellar Ataxias
Introduction
The Natural History and Pathophysiological Approaches of Ataxia
Autosomal Recessive Cerebellar Ataxias (ARCAs)
Autosomal Dominant Cerebellar Ataxias (ADCAs)
Episodic Ataxias
X-Linked Cerebellar Ataxias
Mitochondrial Cerebellar Ataxias
Idiopathic Late-Onset Cerebellar Ataxias
Spastic Ataxias
Molecular Genetics of Ataxias
Genetic Testing
Conclusions and Future Directions
Cross-References
References
91 Cerebellar Malformations
Introduction
Cerebellar Malformations
Rhombencephalosynapsis
Congenital Muscular Dystrophies
Molar Tooth Malformations
Cystic Posterior Fossa Malformations
Dandy Walker Malformation
Mega Cisterna Magna
Blake Pouch Cyst
Isolated Inferior Vermian Hypoplasia
Posterior Fossa Arachnoid Cysts
Cerebellar Hypoplasia
Cerebellar Agenesis
Global Cerebellar Hypoplasia
Unilateral Cerebellar Hypoplasia
Pontocerebellar Hypoplasia
Cerebellar Cortical Dysplasias
Lhermitte-Duclos Disease
Conclusions and Future Directions
References
92 Consequences for Cerebellar Development of Very Premature Birth
Introduction
Preterm Birth: Background
Classification of Prematurity
Brain Injury in the Perinatal Period
Injury to the Developing Cerebellum
Cerebellar Hemorrhage
IVH
Neonatal Adversity
Iatrogenic Steroids
Effect of Damage Elsewhere in the Brain
Cerebellar Development in the Neonatal Period
The Long-Term Consequences of VPT Birth
The Ongoing Contribution of the Cerebellum
Risk and Resilience
Conclusion and Future Directions
References
93 Cerebellar Agenesis
Introduction
Cerebellar Development, Pathological Mechanisms of Cerebellar Anomalies, and Classifications
Cerebellar Development
Pathological Mechanisms of Cerebellar Anomalies
Classification Systems
Cases Report
Literature Review
Recent Neuroradiological Studies
Personal Case
Clonclusion and Future Directions
References
94 Chiari Malformations
Introduction
Historical Aspects
Classification and Description of Chiari Malformations
Chiari Type I
Chiari Type II
Chiari Type III
Chiari Type IV
Roles of Imaging Techniques
Pathogenesis of Chiari Malformations
Management
Surgery
Tracheostomy
Medications
Rehabilitation
Incidental Discovery
Prognosis
References
95 Dandy-Walker Malformations
Introduction
Etiology
Diagnosis
Symptomatology
Central Nervous System Abnormalities
Non-CNS Abnormalities
Management
Prognosis
Conclusions and Future Directions
References
96 Autism Spectrum Disorders and Ataxia
Introduction
The Cerebellum Has a Role in Multiple Domains Impaired in Autism
Structural Pathology of the Cerebellum in Autism
Deficits in Specific Proteins in Autistic Cerebellum
Ataxia
Conclusions and Future Directions
Cross-References
References
97 Cerebellum and Schizophrenia: The Cerebellum Volume Reduction Theory of Schizophrenia
Introduction
Schizophrenia Overview
Classifications
Studies of Risk Factors
Prevalence and Mortality
Pharmacological Treatment
Typical Antipsychotics
Atypical Antipsychotics
Pharmacological Mechanism of Neuroleptic Therapy
Nonpharmacological Therapy
Psychotherapies
Electroconvulsive Therapy (ECT)
Cognitive Behavioral Therapy (CBT)
Social Skill Training (SST)
Studies of Cerebellum Volume and Schizophrenia
Neuroimaging Studies
Structural Magnetic Resonance Imaging (MRI) Studies
Cerebellum Volume Reduction and Schizophrenia
Evidence for Progressive Volume Reduction in Schizophrenia
Diffusion Tensor Imaging (DTI) Studies
Susceptibility Genes and Neuronal Disconnectivity in Schizophrenia
Conclusion and Future Directions
Volume Reduction Theory of Schizophrenia
References
98 Progressive Myoclonic Epilepsies
Introduction
Unverricht-Lundborg Disease (ULD; Baltic Myoclonus)
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
EEG Characteristics
Diagnosis
Myoclonic Epilepsy and Ragged Red Fibers (MERRF)
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
EEG Characteristics
Diagnosis
Neuronal Ceroid Lipofuscinosis
Introduction
Epidemiology
Genetics
Clinical-Pathological Manifestations-EEG Findings
Diagnosis
Dentatorubropallidoluysian Atrophy (DRPLA)
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
Diagnosis
EEG Characteristics
Gaucher Disease
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
Diagnosis
EEG Characteristics
Lafora Disease (LD)
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
Diagnosis
EEG Characteristics
Cherry-Red Spot Myoclonus Syndrome (Type 1 Sialidosis)
Introduction
Epidemiology
Genetics
Pathology
Clinical Manifestations
Diagnosis
EEG Characteristics
Other Rare Forms of PME
Treatment of PME
Cross-References
References
99 Cerebellar Stroke
Introduction
General Clinical Features
Headache
Dizziness
Ataxia
Dysarthria
Ocular Motor Dysfunction
Cognitive Functions
Cerebellar Infarction
PICA Infarction
AICA Infarction
SCA Infarction
Nonterritorial Small Infarcts
Bilateral Cerebellar Infarction
Complications
Cerebellar Hemorrhage
Cerebellar Venous Infarction or Hemorrhage
Diagnosis
Treatment
Conclusion and Future Directions
Cross-References
References
100 Immune Diseases
Introduction
Gluten Ataxia
Anti-GAD Ataxia
Primary Autoimmune Cerebellar Ataxia (PACA)
Opsoclonus Myoclonus Ataxia Syndrome (OMAS)
Post-infectious Cerebellitis
Less Common Immune-Mediated Ataxias
Miller Fisher Syndrome
Anti-DPPX Ataxia
Anti-MAG Ataxia
CLIPPERS
HIV-Associated Cerebellar Ataxia
Conclusions and Future Directions
References
101 Endocrine Disorders
Thyroid Disorders
Hypothyroidism
Hyperthyroidism
Hashimoto Ataxia
Drug-Induced Dysfunction
Parathyroid Disorders
Hypoparathyroidism
Pseudohypoparathyroidism and Pseudopseudohypoparathyroidism
Hyperparathyroidism
Cerebellar Ataxia and Diabetes
Friedreich Ataxia
Mitochondrial Diseases
Anti-GAD Antibodies
APS Syndromes (Autoimmune Polyglandular Syndromes)
Aceruloplasminemia
Von Hippel-Lindau Disease
Langerhans Histiocytosis
Wolfram Disease (DIDMOAD Syndrome)
Cerebellar and Pancreatic Agenesis
Cerebellar Ataxia and Hypogonadism
Most Common Causes: Holmes Ataxia and Boucher-Neuhäuser Syndrome
Marinesco-Sjögren Syndrome
Septo-Optic Dysplasia
Kallman Syndrome
Congenital Disorders of Glycosylation
4H Syndrome
Conclusion and Future Directions
References
102 Infectious Diseases of the Posterior Fossa
Introduction
Bacterial Infections
Epidemiology
Clinical Presentation
Investigations
Pathogenesis
Treatment
Cerebellitis
Epidemiology
Clinical Presentation
Investigations
Pathogenesis
Treatment
Human Prion Diseases
Epidemiology
Clinical Presentation
Investigations
Pathogenesis
Treatment
Conclusion and Future Directions
Cross-References
References
103 Diagnosis of Neoplastic and Paraneoplastic Cerebellar Ataxia
Introduction
Cerebellar Tumors
Clinical Presentation
Neuroimaging
Biological Evaluation
Different Cerebellar Tumor
Medulloblastoma
Pilocytic Astrocytomas
Cerebellar Metastasis
Hemangioblastoma
Other Cerebellar Tumors
Paraneoplastic Cerebellar Ataxia (PCA)
Clinical and Biological Features of Patients with PCA
Clinical Specificities According to the Type of Onconeuronal Antibody
PCA with Anti-Yo
Anti-Hu Patients with Cerebellar Ataxia
PCA with Anti-Tr Antibodies
Anti-CV2/CRMP5 and Cerebellar Ataxia
PCA Associated with Anti-Channel Blockers
PCA Associated with Anti-Ri
Treatment
Conclusion
References
104 Posterior Fossa Trauma
Introduction
Epidemiology
Types of Posterior Fossa Trauma
Intra-Axial Lesions
Concussion
Contusion
Diffuse Axonal Injury
Secondary Traumatic Lesions
Extra-Axial Lesions
Epidural Hematoma
Subdural Hematoma
Subarachnoid Hemorrhage
Traumatic Vascular Lesions
Clinical Presentation
General Presentation
Traumatic Brainstem Lesions
Traumatic Cerebellar Lesions
Hematoma Within the Posterior Fossa
Vertebral Artery Dissection
Imaging
Computed Tomography (CT) and Magnetic Resonance (MR) Imaging
Intra-axial Lesion
Cerebellar Injuries: CT Findings
Cerebellar Injuries: MRI Findings
Brainstem Injuries
Diffuse Axonal Injury
Extra-Axial Lesions
Epidural Hematoma (EDH)
Subdural Hematoma
Subarachnoid Hemorrhage
Traumatic Vascular Lesions
Other Techniques: Diffusion Tensor Imaging (DTI), MR Spectroscopy, Voxel-Based Morphometry (VBM), Positron Emission Tomography...
Pathophysiology
Management
Control of Vital Functions
Control of Intracranial Pressure
Relief of Space-Occupying Lesions
Vertebral Artery Dissection
Long-Term Complications
``Delayed-Onset Cerebellar Syndrome,´´ ``Delayed-Onset Intention Tremor´´ and ``Rubral Tremor``
Crossed Cerebellar Atrophy
Olivary Hypertrophy
Superficial Siderosis
Conclusion and Future Directions
References
105 Cerebellotoxic Agents
Cerebellar Toxicity of Alcohol
Clinical Findings
Cerebellar Atrophy
Posture and Gait Studies
Blood Studies
Neuropathological Findings
Pathogenesis
Risk Factors
Treatment
Prognosis
Drugs
Anticonvulsants
Phenytoin
Carbamazepine
Other Anticonvulsants
Antineoplastics
5-FU and Capecitabine
Ara-C (Cytarabine)
Methotrexate
Cisplatin, Oxaliplatin, Taxol
Epothilone D
Other Drugs
Lithium Salts
Amiodarone
Procainamide
Cyclosporin and Other Calcineurin Inhibitors (Tacrolimus, Sirolimus)
Bismuth
Mefloquine
Isoniazid
Lindane
Statins
Metronidazole
Nicotine
Diphenoxylate-Atropine
Drug Abuse and Addiction
Cocaine
Heroin
Phencyclidine
Herbs
Methadone
Environment
Metals
Mercury
Lead
Manganese
Copper
Gadolinium
Aluminum
Thallium
Germanium
Uranium
Vanadium
Toluene/Benzene Derivatives
Hyperthermia
Carbon Monoxide
Chemical Weapons
Insecticides/Herbicides/Pesticides
Others
Dimethylamine Borane
Eucalytpus Oil
Saxitoxin (Shellfish Poisoning)
Edible Morels
Seasonal Ataxia
Cyanide
Baptisia Poisoning
Animal-Related Cerebellar Toxicity
Scorpions
Conclusions and Future Directions
References
106 Multiple System Atrophy (MSA)
Introduction
Epidemiology
Clinical Features and Diagnostic Criteria
Diagnostic Criteria
Investigations
Disease Progression
Neuropathology
Pathogenesis
Therapies
Disease-Modifying Strategies
Symptomatic Treatment
Motor Symptoms
Parkinsonism
Dopaminergic Agents
NMDA Receptor Antagonists
Selective Serotonin Receptor Inhibitors
Anticholinergic Agents
Cerebellar Ataxia
Dystonia
Sialorrhea
Autonomic Symptoms
Urinary Dysfunction
Orthostatic Hypotension
Constipation
Erectile Dysfunction
Non-medical Therapy and Palliative Care
Conclusions
References
107 Idiopathic Late Onset Cerebellar Ataxia (ILOCA), and Cerebellar Plus Syndrome
Introduction
Idiopathic Late-Onset Cerebellar Ataxia (ILOCA)
ILCOA with Cerebellar-Plus Syndrome
Multiple System Atrophy (MSA)
Epidemiology of SCAs in Japan
References
108 Essential Tremor
Introduction
Epidemiology
Clinical Features
Tremors
Accessory Motor Features
Cognitive Features
Psychiatric Features
Electrophysiological Studies
Neuroimaging Studies
Pathological Features and Pathophysiology
ET as a Cerebellar Disorder: Conclusions and Future Directions
References
109 Autosomal Recessive Cerebellar Ataxias
Introduction
Friedreich´s Ataxia
Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS)
Autosomal Recessive Cerebellar Ataxia Type 1 (ARCA-1)
Autosomal Recessive Cerebellar Ataxia Type 2 (ARCA-2)
Ataxia with Oculomotor Apraxia Type 1 (AOA-1)
Ataxia with Oculomotor Apraxia Type 2 (AOA-2)
Ataxia with Vitamin E Deficiency (AVED)
Conclusion and Future Directions
References
110 Autosomal Dominant Spinocerebellar Ataxias and Episodic Ataxias
History, Nomenclature, and Classification
Epidemiology and Frequency
Spinocerebellar Ataxias (SCAs and DRPLA)
Genetic Bases
Anticipation
Neuropathology
Pathogenesis
Polyglutamine SCAs
Other SCAs
General Clinical Presentation
Neuroimaging
Clinical Description of Subforms
SCA1
SCA2
SCA3 (Machado-Joseph Disease)
SCA4
SCA5
SCA6
SCA7
SCA8
SCA10
SCA11
SCA12
SCA13
SCA14
SCA15/SCA16
SCA17
SCA18
SCA19 and SCA22
SCA20
SCA21
SCA23
SCA25
SCA26
SCA27
SCA28
SCA29
SCA30
SCA31
SCA32
SCA35
SCA36
DRPLA
Episodic Ataxias
EA1
EA2
EA3
EA4
EA5
EA6
EA7
Conclusions
Diagnosis
Treatment
Future Perspectives
References
111 Mitochondrial Disorders
Introduction to Mitochondrial Functions
Transport Systems
Degradative Metabolic Pathways
Mitochondrial Dynamics
Oxidative Phosphorylation and the Respiratory Chain
RC Function
Cerebellar Disorders Due to Defects of Nuclearly Encoded Mitochondrial Proteins
Friedreich Ataxia (FRDA)
POLG-Related Ataxias
Myoclonic Epilepsy Myopathy Sensory Ataxia (MEMSA)
Ataxia Neuropathy Spectrum (ANS)
Infantile-Onset Spinocerebellar Ataxia (IOSCA)
Ataxia with Coenzyme Q10 Deficiency
X-Linked Sideroblastic Anemia with Ataxia (XLSA/A)
Autosomal Dominant Spinocerebellar Ataxia Type 28 (SCA28)
Cerebellar Disorders Due to Defects of MtDNA
Heteroplasmic Point Mutations
Myoclonic Epilepsy with Ragged-Red Fibers (MERRF)
Mitochondrial Encephalomyopathy with Lactic Acidosis and Stroke-Like Episodes (MELAS)
MELAS/MEERF Overlapping Syndrome
Neuropathy, Ataxia, and Retinitis Pigmentosa (NARP)
Maternally Inherited Leigh Syndrome (MILS)
Hearing Loss-Ataxia-Myoclonus (HAM)
Other Mitochondrial Disorders with Ataxia
Large-Scale Rearrangements of Mitochondrial DNA
Kearns-Sayre Syndrome (KSS)
References
112 X-Linked Ataxias
Introduction
Fragile X-Associated Tremor Ataxia Syndrome (FXTAS)
X-Linked Sideroblastic Anemia with Ataxia (XLSA)
X-Linked Ataxia Due to GJB1 Mutations
Spinocerebellar Ataxia Due to PMCA3 Mutations
X-Linked Adrenoleukodystrophy
X-Linked Pyruvate-Dehydrogenase (PDH) Deficiency
X-Linked Ataxias with Ataxia as a Nondominant Feature
Management
Conclusion
References
113 Neuropathology of Ataxias
Introduction
Spinocerebellar Degeneration
Sporadic Disorders
Multiple System Atrophy
Late Cortical Cerebellar Atrophy
Hereditary Disorders
Spinocerebellar Ataxia Type 1
Spinocerebellar Ataxia Type 2
Machado-Joseph Disease/Spinocerebellar Ataxia Type 3
Spinocerebellar Ataxia Type 6
Spinocerebellar Ataxia Type 7
Spinocerebellar Ataxia Type 8
Spinocerebellar Ataxia Type 31
Dentatorubral-Pallidoluysian Atrophy
Friedreich´s Ataxia
Early-Onset Ataxia with Ocular Motor Apraxia and Hypoalbuminemia/Ataxia-Oculomotor Apraxia Type 1
Marinesco-Sjögren Syndrome
Conclusions and Future Directions
References
114 General Management of Cerebellar Disorders: An Overview
Introduction
General Predictions of Functional Recovery
Medical Intervention
Idebenone in Friedreich´s Ataxia
Riluzole
Acetylleucine
Aminopyridines
Cognitive Rehabilitation
Motor Rehabilitation
Impairments in Motor Performance and the Adaptation of Movements
Animal Cerebellar Lesion Models Indicate Long-Term Adaptation and Effects of Motor Training
Motor Rehabilitation in Human Cerebellar Disease
Discussion
Current Praxis of Motor Rehabilitation
Open Questions in Cerebellar Motor Rehabilitation
Motor Rehabilitation for Upper Extremities
Further Clinical Studies in Different Disease Stages
Long-Term Studies and Quality of Life
Prediction of Intervention Benefits
Future Studies on Mechanisms of Motor Adaptation and Motor Rehabilitation
Modern Brain Imaging Techniques
The Relationship Between Short-Term Motor Adaptation Alternative Learning Methods and Motor Rehabilitation
Noninvasive Brain Stimulation Techniques
Conclusions and Future Directions
References
115 Novel Therapeutic Challenges in Cerebellar Diseases
Introduction
Treatments for Autosomal Recessive Spinocerebellar Ataxias
Friedreich´s Ataxia (FRDA)
Ataxias with Vitamin E and Coenzyme Q10 Deficiencies
Abetalipoproteinemia
Cerebrotendinous Xanthomatosis (CTX)
Refsum´s Disease
Ataxia-Telangiectasia (AT)
Treatments for Autosomal Dominant Spinocerebellar Ataxias
Treatments for Episodic Ataxias
Emerging Therapeutic Strategies
Physical Therapy in Cerebellar Diseases
Physical Therapy Examination
Physical Therapy Interventions
Concluding Remarks and Future Directions
Cross-References
References
Index

Citation preview

Mario U. Manto Donna L. Gruol Jeremy D. Schmahmann Noriyuki Koibuchi Roy V. Sillitoe Editors

Handbook of the Cerebellum and Cerebellar Disorders Second Edition

Handbook of the Cerebellum and Cerebellar Disorders

Mario U. Manto • Donna L. Gruol • Jeremy D. Schmahmann • Noriyuki Koibuchi • Roy V. Sillitoe Editors

Handbook of the Cerebellum and Cerebellar Disorders Second Edition

With 512 Figures and 64 Tables

Editors Mario U. Manto CHU-Charleroi University of Mons Charleroi, Belgium Jeremy D. Schmahmann Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology Department of Neurology Massachusetts General Hospital and Harvard Medical School Boston, MA, USA

Donna L. Gruol Department of Neuroscience The Scripps Research Institute La Jolla, CA, USA Noriyuki Koibuchi Department of Integrative Physiology Gunma University Graduate School of Medicine Maebashi, Gunma, Japan

Roy V. Sillitoe Department of Pathology and Immunology Baylor College of Medicine Houston, TX, USA Department of Neuroscience Baylor College of Medicine Houston, TX, USA Program in Developmental Biology Baylor College of Medicine Houston, TX, USA Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital Houston, TX, USA

ISBN 978-3-030-23809-4 ISBN 978-3-030-23810-0 (eBook) ISBN 978-3-030-23811-7 (print and electronic bundle) https://doi.org/10.1007/978-3-030-23810-0 1st edition: © Springer Science+Business Media Dordrecht 2013 2nd edition: © Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To the memory of Professors Masao Ito, Ferdinando Rossi, and Peter Marien, who all contributed to the understanding of cerebellar functions.

Preface to the Second Edition

The field of cerebellar research is expanding exponentially. The number of basic and clinical scientists involved in research on the cerebellum keeps growing and ataxia clinics are now emerging worldwide, with the expectation that effective therapies will be developed in the coming decade. This growth of the field is due to a combination of factors. First, the cerebellum contains the largest number of neurons in the brain and has a unique anatomical organization. Second, the cerebellum communicates with many brain regions, and the fascinating cooperation with the extra-cerebellar structures attracts scientists from numerous disciplines. Third, the number of clinical disorders recognized to affect the cerebellum keeps growing, and cerebellar ataxias are being increasingly identified in daily practice, in particular due to the advances in genetics and neuroimaging as well as the establishment of novel biomarkers. It is now widely accepted that the cerebellum is a central structure in the broader areas of both fundamental and clinical neuroscience. The first edition of the handbook was very successful, with a very high number of downloads. The edition gathered chapters from fundamental neurobiology to clinical applications, providing the first authoritative resource for the international community of scientists, clinicians, and other professionals interested in the science of the cerebellum. We have been extremely lucky to have on board an international panel of outstanding investigators in the field. This second edition includes the most recent advances in cerebellar research. Starting from the first edition, our goal was to produce novel editions of the handbook. Suggestions and critiques provided by experts in the field have strengthened this compilation. In this edition, the chapters have been updated accordingly, so that readers can have faster access to the most recent advances that will pave the way for novel research avenues in the coming years. We are particularly grateful to the staff at Springer who provided excellent support throughout this project. We particularly wish to acknowledge Rukmani

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Parameswaran, Neha Thapa, William Lamsback, and Mallaigh Nolan for their high degree of professionalism. Charleroi, Belgium La Jolla, USA Boston, USA Gunma, Japan Houston, USA November 2021

Mario U. Manto Donna L. Gruol Jeremy D. Schmahmann Noriyuki Koibuchi Roy V. Sillitoe

Preface to the First Edition

The cerebellum has long attracted a core group of scientists intrigued by the sophistication of its circuitry, its unique geometric arrangement and developmental biology, and its characteristic clinical manifestations. With the advances in genetic studies, the rising awareness of the roles of the cerebellum in the nonmotor domain, and the profusion of brain imaging techniques that have generated a vast amount of new knowledge revealing novel aspects of cerebellar function, the field of cerebellar neurobiology has expanded rapidly. Large communities of scholars now setting out on their own paths of scientific enquiry are keenly interested in the cerebellum and its multiple roles in nervous system function. The evolution, and in some instances revolution, in knowledge of the cerebellum has sparked new fields of enquiry and attracted new schools of thought and legions of new investigators. The motivating goal of this comprehensive text therefore was to assemble an international panel of experts who could summarize the state of the art of the many facets of cerebellar clinical and basic neuroscience, and incorporate the most recent developments in the field. There are several excellent books on the neurobiology and clinical neurology of the cerebellum, but until the present volume there has been no single comprehensive work that can serve as an in-depth authoritative resource for the international community of scientists, clinicians, and other professionals interested in the science of the cerebellum. The Handbook of the Cerebellum and Cerebellar Disorders has been in preparation for over 2 years. This detailed work required the contributions of an international panel of renowned scientists and clinicians with experience in a diverse array of fields of neuroscience who were invited to write chapters that provide synthesis, analysis, and interpretation of both the historical and contemporary literature. This handbook could not have been completed without their considerable efforts, and we gratefully acknowledge their commitment to the project. We would like to recognize the staff at Springer who provided excellent service throughout this project. We particularly wish to acknowledge Ann Avouris, Martijn Roelandse, Somodatta Roy, Namita Mathur, Mansi Seth, and Vasuki Ravichandran for their input, assistance, constant support, and high degree of professionalism. They have been invaluable in helping to bring this work to completion. In addition to the printed version, we have arranged with Springer that the handbook be made

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available electronically on the Springer website. The reader may find that the ebook format is more accessible and that it facilitates searches more readily. The editors have attempted to cover what we regard as essential material, while striving to avoid redundancy. In the belief that this volume may be useful to the scientific and clinical communities, we plan to produce future editions of this work, and we therefore invite suggestions and critique in order to further strengthen this compilation, and perhaps include other authors and material that could serve to enhance the handbook and draw attention to the increasingly vibrant field of the basic science and clinical neurology of the cerebellum. Brussels, Belgium La Jolla, USA Boston, USA Gunma, Japan Turin, Italy

Mario Manto Donna L. Gruol Jeremy D. Schmahmann Noriyuki Koibuchi Ferdinando Rossi

Contents

Volume 1 Part I

Cerebellar Development

.............................

1

...................

3

1

Specification of the Cerebellar Territory Marion Wassef

2

Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip . . . . . . . . . . . . . . . . . . . . . . . . . . . Gian Giacomo Consalez, Marta Florio, Luca Massimino, Filippo Casoni, and Laura Croci

23

3

Zones and Stripes: Development of Cerebellar Topography . . . . Lauren N. Miterko, Roy V. Sillitoe, and Richard Hawkes

45

4

Roof Plate in Cerebellar Neurogenesis . . . . . . . . . . . . . . . . . . . . . Victor V. Chizhikov

67

5

Specification of Cerebellar and Precerebellar Neurons Mikio Hoshino, Satoshi Miyashita, Yusuke Seto, and Mayumi Yamada

........

83

6

Specification of Granule Cells and Purkinje Cells . . . . . . . . . . . . Thomas Butts, Victoria Rook, Tristan Varela, Leigh Wilson, and Richard J. T. Wingate

99

7

Gliogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Valentina Cerrato and Annalisa Buffo

121

8

Granule Cell Migration and Differentiation . . . . . . . . . . . . . . . . . Yutaro Komuro, Tatsuro Kumada, Nobuhiko Ohno, Jennifer K. Fahrion, Kathryn D. Foote, Kathleen B. Fenner, David Vaudry, Ludovic Galas, and Hitoshi Komuro

139

9

Purkinje Cell Migration and Differentiation Constantino Sotelo and Ferdinando Rossi

................

173 xi

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10

Development of Cerebellar Nuclei . . . . . . . . . . . . . . . . . . . . . . . . Gina E. Elsen, Gordana Juric-Sekhar, Ray A. M. Daza, and Robert F. Hevner

207

11

Specification and Development of GABAergic Interneurons . . . . Karl Schilling

235

12

Development of Glutamatergic and GABAergic Synapses . . . . . . Marco Sassoè-Pognetto and Annarita Patrizi

265

13

Synaptic Remodeling and Neosynaptogenesis . . . . . . . . . . . . . . . . Ann M. Lohof, Mathieu Letellier, Jean Mariani, and Rachel M. Sherrard

285

14

Synaptogenesis and Synapse Elimination . . . . . . . . . . . . . . . . . . . Masanobu Kano and Masahiko Watanabe

309

15

Genes and Cell Type Specification in Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joanna Yeung, Matt Larouche, Miguel Ramirez, Rémi Robert, and Dan Goldowitz

333

16

Hormones and Cerebellar Development . . . . . . . . . . . . . . . . . . . . Noriyuki Koibuchi and Yayoi Ikeda

353

17

Development of Physiological Activity in the Cerebellum Sriram Jayabal and Alanna J. Watt

......

379

18

Epigenetic Regulation of the Cerebellum . . . . . . . . . . . . . . . . . . . Yue Yang, Tomoko Yamada, and Azad Bonni

409

19

Analysis of Gene Networks in Cerebellar Development . . . . . . . . John Oberdick

429

Part II Anatomy, Connections, and Neuroimaging of the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

449

20

Vascular Supply and Territories of the Cerebellum . . . . . . . . . . . Louis Caplan

451

21

Vestibulocerebellar Functional Connections . . . . . . . . . . . . . . . . . Neal H. Barmack and Vadim Yakhnitsa

467

22

Cerebellar Nuclei and the Inferior Olivary Nuclei: Organization and Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . Jan Voogd, Yoshikazu Shinoda, Tom J. H. Ruigrok, and Izumi Sugihara

23

Axonal Trajectories of Single Climbing and Mossy Fiber Neurons in the Cerebellar Cortex and Nucleus . . . . . . . . . . . . . . Yoshikazu Shinoda and Izumi Sugihara

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25

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Visual Circuits from Cerebral Cortex to Cerebellum; The Link Through Pons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mitchell Glickstein

595

Cerebellar Connections with Limbic Circuits: Anatomy and Functional Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jeremy D. Schmahmann, Adrian L. Oblak, and Gene J. Blatt

605

26

Cerebellar Influences on Descending Spinal Motor Systems . . . . Tom J. H. Ruigrok

625

27

Cerebellar Thalamic and Thalamocortical Projections . . . . . . . . Sharleen T. Sakai

661

28

Cerebellar Outputs in Non-human Primates: An Anatomical Perspective Using Transsynaptic Tracers . . . . . . . . . . . . . . . . . . . Andreea C. Bostan and Peter L. Strick

681

Delineation of Cerebrocerebellar Networks with MRI Measures of Functional and Structural Connectivity . . . . . . . . . . Christophe Habas, William R. Shirer, and Michael D. Greicius

703

Radiographic Features of Cerebellar Disease: Imaging Approach to Differential Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . Otto Rapalino

721

29

30

31

Imaging Vascular Anatomy and Pathology of the Posterior Fossa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zeshan A. Chaudhry, Ronil V. Chandra, R. Gilberto González, and Albert J. Yoo ...................

32

MR Spectroscopy in Health and Disease Gülin Öz

33

Functional Topography of the Human Cerebellum Revealed by Functional Neuroimaging Studies . . . . . . . . . . . . . . . . . . . . . . Catherine J. Stoodley, John E. Desmond, Xavier Guell, and Jeremy D. Schmahmann

739

775

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Volume 2 Part III Neurotransmission, Neuromodulation, and Physiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

835

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837

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863

34

Cerebellar Granule Cell Egidio D’Angelo

35

Purkinje Neurons: Synaptic Plasticy Hervé Daniel and F. Crepel

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Contents

36

Stellate Cells: Synaptic Processing and Plasticity . . . . . . . . . . . . . Siqiong June Liu and Christophe J. Dubois

881

37

Golgi Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Katarzyna Pietrajtis and Stéphane Dieudonné

903

38

Glutamate Receptor Auxiliary Subunits and Interacting Protein Partners in the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . Ian D. Coombs and Stuart G. Cull-Candy

39

GABA and Synaptic Transmission in the Cerebellum . . . . . . . . . Tomoo Hirano

40

Norepinephrine and Synaptic Transmission in the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Daniel J. Chandler, Shevon E. Nicholson, Gerard Zitnik, and Barry D. Waterhouse

929 957

971

41

Serotonin and Synaptic Transmission in the Cerebellum . . . . . . . Moritoshi Hirono, Fumihito Saitow, and Hidenori Suzuki

991

42

Cannabinoids and Synaptic Transmission in the Cerebellum Michael H. Myoga and Wade G. Regehr

43

Nitric Oxide and Synaptic Transmission in the Cerebellum . . . . . 1025 Andrea Collado-Alsina, Alberto Rampérez, José Sánchez-Prieto, and Magdalena Torres

44

Purinergic Signaling in the Cerebellum . . . . . . . . . . . . . . . . . . . . 1047 Mark J. Wall

45

Modulatory Role of Neuropeptides in the Cerebellum . . . . . . . . . 1073 Georgia A. Bishop and James S. King

46

Taurine in the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1095 Abdeslem El Idrissi, Francoise Sidime, Salvatore Rotondo, and Zaghloul Ahmed

47

Biological Actions of Neurosteroids in the Growth and Survival of Purkinje Cells During Cerebellar Development . . . . . . . . . . . . 1115 Kazuyoshi Tsutsui

48

Inferior Olive: All Ins and Outs . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 S. Loyola, L. W. J. Bosman, J. R. De Gruijl, M. T. G. De Jeu, M. Negrello, T. M. Hoogland, and C. I. De Zeeuw

49

Dynamics of the Inferior Olive Oscillator and Cerebellar Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1193 Dimitar Kostadinov, Alexandre Mathy, and Beverley A. Clark

50

Feedback Control in the Olivocerebellar Loop . . . . . . . . . . . . . . . 1215 Fredrik Bengtsson, Anders Rasmussen, and Germund Hesslow

. . . 1005

Contents

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51

Neurons of the Deep Cerebellar Nuclei . . . . . . . . . . . . . . . . . . . . . 1239 Marylka Yoe Uusisaari and Thomas Knöpfel

52

Cerebellar Nuclei and Cerebellar Learning . . . . . . . . . . . . . . . . . 1251 Dieter Jaeger

53

Cerebro-cerebellar Connections . . . . . . . . . . . . . . . . . . . . . . . . . . 1275 Thomas C. Watson and Richard Apps

54

Cerebellar Control of Eye Movements . . . . . . . . . . . . . . . . . . . . . 1301 Pablo M. Blazquez and Angel M. Pastor

55

Cerebellum and Eyeblink Conditioning . . . . . . . . . . . . . . . . . . . . 1319 Derick H. Lindquist, Joseph E. Steinmetz, and Richard F. Thompson

56

Purkinje Neurons During Eye Blink Conditioning and New Mechanisms of Cerebellar Learning and Timing . . . . . . . . . . . . . 1335 Germund Hesslow, Dan-Anders Jirenhed, and Fredrik Johansson

57

Cerebellar Control of Speech and Song . . . . . . . . . . . . . . . . . . . . 1345 Daniel E. Callan and Mario U. Manto

58

Cerebellum and Timing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1359 Rebecca M. C. Spencer and Richard B. Ivry

59

Cerebellar Control of Posture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1379 M. E. Ioffe

60

Channelopathies and Cerebellar Disease . . . . . . . . . . . . . . . . . . . 1399 Hiroyuki Morino, Yukiko Matsuda, and Hideshi Kawakami

61

Disruption of the Microbiota-Gut-Brain (MGB) Axis and Mental Health of Astronauts During Long-Term Space Travel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415 Elżbieta M. Sajdel-Sulkowska

62

Cerebellum-Like Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1437 Nathaniel B. Sawtell and Curtis C. Bell

Volume 3 Part IV

Computational Models of Cerebellar Function . . . . . . . . .

1459

63

Cerebellum and Internal Models . . . . . . . . . . . . . . . . . . . . . . . . . 1461 Laurentiu S. Popa and Timothy J. Ebner

64

State Estimation and the Cerebellum . . . . . . . . . . . . . . . . . . . . . . 1487 Robert M. Hardwick, Maria Dagioglou, and R. Chris Miall

65

Adaptive Filter Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1503 Paul Dean, Henrik Jörntell, and John Porrill

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Contents

66

Cerebellum and Human Evolution: A Comparative and Information Theory Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . 1515 C. Huang and Robert E. Ricklefs

67

Computational Structure of the Cerebellar Molecular Layer James M. Bower

68

Recursive Genome Function of the Cerebellum: Geometric Unification of Neuroscience and Genomics . . . . . . . . . . . . . . . . . . 1559 Andras J. Pellionisz, Roy Graham, Peter A. Pellionisz, and Jean-Claude Perez

Part V

. . . 1537

Animal Models to Study Cerebellar Function . . . . . . . . . . .

1603

69

Animal Models: An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1605 Noriyuki Koibuchi

70

Cerebellar Development and Neurogenesis in Zebrafish . . . . . . . 1623 Jan Kaslin and Michael Brand

71

Teleost Fish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1647 Takanori Ikenaga

72

Robotic Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1667 Emmanuelle Bitoun, Peter L. Oliver, and Kay E. Davies

73

Lurcher Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1685 Jan Cendelin and Frantisek Vozeh

74

Tottering Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1709 Timothy J. Ebner, Russell E. Carter, and Gang Chen

75

Rolling Nagoya Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1733 Else A. Tolner, Arn M. J. M. van den Maagdenberg, and Jaap J. Plomp

76

Ataxic Syrian Hamster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1757 Kenji Akita

77

Moonwalker Mouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1773 Esther B. E. Becker

78

Hemicerebellectomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1789 M. T. Viscomi, M. G. Leggio, and M. Molinari

Part VI

Symptoms of Cerebellar Disorders in Human . . . . . . . . . .

1807

79

Role of Cerebellum in Gaze-Holding Disorders . . . . . . . . . . . . . . 1809 Neel Fotedar, Fajun Wang, and Aasef G. Shaikh

80

Cerebellar Motor Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1827 Giuliana Grimaldi

Contents

xvii

81

Lesion-Symptom Mapping of the Human Cerebellum . . . . . . . . . 1857 Dagmar Timmann, Michael Küper, Elke R. Gizewski, Beate Schoch, and Opher Donchin

82

Deficits of Grasping in Cerebellar Disorders . . . . . . . . . . . . . . . . 1891 Dennis A. Nowak, Dagmar Timmann, and Joachim Hermsdörfer

83

Ataxic Hemiparesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1903 Akiyuki Hiraga

84

Cerebellum and Cognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1923 Maja Steinlinand and Kevin Wingeier

85

Cerebellar Sequencing for Cognitive Processing Marco Molinari and Maria Leggio

86

The Cerebellar Cognitive Affective Syndrome and the Neuropsychiatry of the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . 1955 Jeremy D. Schmahmann

87

Cerebellar Mutism Syndrome in Children and Adults . . . . . . . . . 1995 Peter Mariën, Stefanie Keulen, Kim van Dun, Hyo Jung De Smet, Peter P. De Deyn, Jo Verhoeven, and Philippe Paquier

88

Human Cerebellum in Motivation and Emotion Dennis J. L. G. Schutter

. . . . . . . . . . . . . 1937

. . . . . . . . . . . . . 2019

Volume 4 Part VII

Cerebellar Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2031

. . . . . . . . . . . . . . . . . . . . . . 2033

89

Clinical Scales of Cerebellar Ataxias Katrin Bürk and Deborah A. Sival

90

Approach to the Differential Diagnosis of Cerebellar Ataxias . . . 2053 Francesc Palau and Carmen Espinós

91

Cerebellar Malformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2077 Ozlem Alkan, Osman Kizilkilic, and Tulin Yildirim

92

Consequences for Cerebellar Development of Very Premature Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2095 Matthew Allin

93

Cerebellar Agenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2113 Romina Romaniello and Renato Borgatti

94

Chiari Malformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2135 Mario U. Manto and Christian Herweh

95

Dandy-Walker Malformations . . . . . . . . . . . . . . . . . . . . . . . . . . . 2151 George A. Alexiou and Neofytos Prodromou

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Contents

96

Autism Spectrum Disorders and Ataxia . . . . . . . . . . . . . . . . . . . . 2159 Timothy D. Folsom and S. Hossein Fatemi

97

Cerebellum and Schizophrenia: The Cerebellum Volume Reduction Theory of Schizophrenia . . . . . . . . . . . . . . . . . . . . . . . 2177 Gaku Okugawa

98

Progressive Myoclonic Epilepsies . . . . . . . . . . . . . . . . . . . . . . . . . 2193 Benjamin Legros and Mary L. Zupanc

99

Cerebellar Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2229 Keun-Hwa Jung and Jae-Kyu Roh

100

Immune Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2257 Marios Hadjivassiliou, Hiroshi Mitoma, and Mario U. Manto

101

Endocrine Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2283 Mario U. Manto

102

Infectious Diseases of the Posterior Fossa . . . . . . . . . . . . . . . . . . . 2301 Mario U. Manto and Patrice Jissendi

103

Diagnosis of Neoplastic and Paraneoplastic Cerebellar Ataxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2319 Geneviève Demarquay and Jérôme Honnorat

104

Posterior Fossa Trauma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2337 Matthias Maschke, Maria Mörsdorf, Dagmar Timmann, and Uwe Dietrich

105

Cerebellotoxic Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2363 Mario U. Manto

106

Multiple System Atrophy (MSA) . . . . . . . . . . . . . . . . . . . . . . . . . 2409 Gregor K. Wenning, Florian Krismer, and Sid Gilman

107

Idiopathic Late Onset Cerebellar Ataxia (ILOCA), and Cerebellar Plus Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2433 Shoji Tsuji

108

Essential Tremor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2441 Elan D. Louis

109

Autosomal Recessive Cerebellar Ataxias . . . . . . . . . . . . . . . . . . . 2465 Ikhlass Haj Salem, Anne Noreau, Jean-Pierre Bouchard, Patrick A. Dion, Guy A. Rouleau, and Nicolas Dupré

110

Autosomal Dominant Spinocerebellar Ataxias and Episodic Ataxias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2483 Franco Taroni, Luisa Chiapparini, and Caterina Mariotti

Contents

xix

111

Mitochondrial Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2561 Stefano Di Donato, Daniele Marmolino, and Franco Taroni

112

X-Linked Ataxias Josef Finsterer

113

Neuropathology of Ataxias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2615 Mitsunori Yamada

114

General Management of Cerebellar Disorders: An Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2639 Winfried Ilg and Dagmar Timmann

115

Novel Therapeutic Challenges in Cerebellar Diseases . . . . . . . . . 2667 Antoni Matilla-Dueñas, Jon Infante, Carmen Serrano-Munuera, Yerko Ivánovic-Barbeito, Ramiro Alvarez, and Ivelisse Sánchez

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2603

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2701

About the Editors

Prof. Mario U. Manto is a professor of neuroanatomy at the University of Mons, Belgium. He is the head of the Department of Neurology at the CHU-Charleroi. He is the founding editor of The Cerebellum (Springer Nature). He has published more than 10 books. He is co-founder of the Society for Research on the Cerebellum and Ataxias. He has received research grants from national and international agencies (NIH, European Commission).

Dr. Donna L. Gruol PhD, is an associate professor in the Department Neuroscience at the Scripps Research Institute, La Jolla, California, and an adjunct associate professor in the Neuroscience Department at the University of California San Diego. She obtained a PhD in biology from the Illinois Institute of Technology and did post degree training in neuroscience at the University of Maryland Medical School, The National Institutes of Health, and The Salk Institute. Donna has been a member of several NIH grant review panels and has served on journal editorial boards and advisory committees. Her current research focuses on neuroimmune regulation of brain physiology and synaptic transmission and the role of the neuroimmune system in the actions of ethanol on the brain in preclinical models of alcohol use disorders.

xxi

xxii

About the Editors

Dr. Jeremy D. Schmahmann is a professor of neurology at Harvard Medical School and a senior clinical neurologist at the Massachusetts General Hospital where he is founding director of the Ataxia Center, director of the Laboratory for Neuroanatomy and Cerebellar Neurobiology, and a founding member of the Cognitive Behavioral Neurology Unit. Dr. Schmahmann received his medical degree with distinction from the University of Cape Town, completed residency in the Neurological Unit of the Boston City Hospital, and did his postdoctoral fellowship with Professor Deepak Pandya in the Department of Anatomy and Neurobiology at Boston University School of Medicine. He is a fellow of the American Academy of Neurology, American Neurological Association, and American Neuropsychiatric Association; a member of the Medical and Scientific Research Advisory Board of the National Ataxia Foundation and the Clinical Research Consortium for the Study of Cerebellar Ataxias; the executive committee member of the Society for Research on the Cerebellum and Ataxias; and past president of the American Neuropsychiatric Association. Dr. Schmahmann’s clinical and research efforts focus on the anatomical substrates of intellect and emotion, and the anatomy, clinical neurology and basic science of the ataxias, and other cerebellar disorders. He was awarded the Norman Geschwind Prize in 2000 by the American Academy of Neurology and the Behavioral Neurology Society for his description of the cerebellar cognitive affective syndrome and its neurobiological and theoretical underpinnings. Dr. Noriyuki Koibuchi is a professor and director of integrative physiology at the Gunma University Graduate School of Medicine, Maebashi, Japan. Dr. Koibuchi obtained MD degree from Gunma University School of Medicine, followed by a PhD degree from the Institute of Endocrinology, Gunma University. He completed a postdoctoral research fellowship in neurobiology and behavior at the Rockefeller University. Following a tenure as an assistant/associate professor at the Dokkyo University School of Medicine, and as a visiting assistant professor at the Brigham and Women’s Hospital and Harvard Medical School, he took up his current position

About the Editors

xxiii

in 2001. He has been serving as a council member in several societies, such as the Physiological Society in Japan, the Japan Endocrine Society, and the Japan Thyroid Association. He is also serving as an associate editor in several journals such as The Cerebellum and Frontiers in Endocrinology. Dr. Roy V. Sillitoe completed a PhD in neuroscience at the University of Calgary. He then received postdoctoral training at the University of Oxford, New York University, and Memorial Sloan-Kettering Cancer Center. He is currently an investigator at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital in Houston, Texas. Dr. Sillitoe is also the co-director of the Development, Disease Models & Therapeutics Graduate Program at Baylor College of Medicine. The focus of his research is to understand how the cerebellum contributes to different diseases. To accomplish these goals, his group uses mouse genetics, neuroanatomy, behavioral paradigms, and in vivo electrophysiology approaches. In addition, they are testing how deep brain stimulation (DBS) and exercise correct altered neural signals and rescue behavior in mouse models of ataxia, dystonia, tremor, and seizure disorders.

Contributors

Zaghloul Ahmed The Center for Developmental Neuroscience, College of Staten Island, Staten Island, NY, USA The Graduate Center, Program in Biology – Neurosciences, The City University of New York, New York, NY, USA Department of Physical Therapy/School of Health Sciences, College of Staten Island, Staten Island, NY, USA Kenji Akita R&D Division, Hayashibara Co., Ltd., Naka-ku, Japan George A. Alexiou Department of Neurosurgery, University Hospital of Ioannina, Ioannina, Greece Ozlem Alkan Department of Radiology, Baskent University Medical School, Adana, Turkey Matthew Allin Department of Psychosis Studies, Biomedical Research Centre for Mental Health, Institute of Psychiatry, King’s College, London, UK Ramiro Alvarez Neurodegeneration Unit, Neurology Service, Department of Neuroscience, University Hospital Germans Trias i Pujol (HUGTiP), Badalona, Barcelona, Spain Richard Apps School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK Neal H. Barmack Department of Physiology and Pharmacology, Oregon Health and Science University, Portland, OR, USA Esther B. E. Becker Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK Curtis C. Bell Neurological Sciences Institute, Oregon Health and Science University, Beaverton, OR, USA Fredrik Bengtsson Department of Experimental Medical Science, Division for Neuroscience, University of Lund, Lund, Sweden xxv

xxvi

Contributors

Georgia A. Bishop Department of Neuroscience, The Ohio State University, Columbus, OH, USA Emmanuelle Bitoun Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK Gene J. Blatt Program in Neuroscience, Hussman Institute for Autism, Baltimore, MD, USA Pablo M. Blazquez Department of Otolaryngology, School of Medicine, Washington University, St. Louis, MO, USA Azad Bonni Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA Renato Borgatti Child Neurology and Psychiatry Unit, IRCCS Mondino Foundation, Pavia, Italy Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy L. W. J. Bosman Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands Andreea C. Bostan Department of Neurobiology, Center for the Neural Basis of Cognition, Systems Neuroscience Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA Jean-Pierre Bouchard Université Laval, Québec, QC, Canada Département des sciences neurologiques, CHU de Québec, Hôpital de l’EnfantJésus, Québec, QC, Canada James M. Bower Barshop Institute to Longevity and Aging Studies, Department of Radiology, University of Texas Health Science Center, San Antonio, TX, USA Department of Biology, Neuroscience Institute, University of Texas, San Antonio, TX, USA Michael Brand CRTD - Center for Regenerative Therapies TU Dresden, TU Dresden, Dresden, Germany Annalisa Buffo Department of Neuroscience Rita Levi-Montalcini, University of Turin, Neuroscience Institute Cavalieri Ottolenghi, Turin, Italy Katrin Bürk Department of Neurology, University of Marburg, Marburg, Germany Kliniken Schmieder, Stuttgart-Gerlingen, Germany Thomas Butts School of Life Sciences, University of Liverpool, Liverpool, UK Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK

Contributors

xxvii

Daniel E. Callan Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka University, Osaka, Japan Louis Caplan Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA Russell E. Carter Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA Filippo Casoni Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy Jan Cendelin Department of Pathophysiology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic Laboratory of Neurodegenerative Disorders, Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic Valentina Cerrato Department of Neuroscience Rita Levi-Montalcini, University of Turin, Neuroscience Institute Cavalieri Ottolenghi, Turin, Italy Daniel J. Chandler Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA Ronil V. Chandra Department of Interventional Neuroradiology and Endovascular Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Zeshan A. Chaudhry Department of Diagnostic Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Gang Chen Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA Luisa Chiapparini Unit of Neuroradiology, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milan, Italy Victor V. Chizhikov Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA Beverley A. Clark Wolfson Institute for Biomedical Research, University College London, London, UK Andrea Collado-Alsina Departamento de Bioquímica, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain Gian Giacomo Consalez Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy

xxviii

Contributors

Ian D. Coombs Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK F. Crepel Laboratoire de Pharmacologie et Biochimie de la synapse, CNRS UMR 8619, Institut de Biochimie et de Biophysique Moléculaire et Cellulaire, Université Paris-Sud 12, Orsay Cedex, France Laura Croci Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy Stuart G. Cull-Candy Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK Egidio D’Angelo Università di pavia, Pavia, Italy Maria Dagioglou Behavioural Brain Sciences, School of Psychology, University of Birmingham, Birmingham, UK Hervé Daniel Laboratoire de Pharmacologie et Biochimie de la synapse, CNRS UMR 8619, Institut de Biochimie et de Biophysique Moléculaire et Cellulaire, Université Paris-Sud 12, Orsay Cedex, France Kay E. Davies Department of Physiology, Anatomy and Genetics, University of Oxford, MDUK Oxford Neuromuscular Centre, Oxford, UK Ray A. M. Daza Department of Neurological Surgery, Seattle Children’s Research Institute, Center for Integrative Brain Research, Seattle, WA, USA Paul Dean Department of Psychology, University of Sheffield, Sheffield, UK Geneviève Demarquay Centre de Référence, de Diagnostic et de Traitement des Syndromes Neurologiques Paranéoplasiques, Hospices Civils de Lyon, Lyon, France John E. Desmond Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA Peter P. De Deyn Department of Neurology, University Medical Center Groningen, Universiteit Groningen, Groningen, The Netherlands J. R. De Gruijl Netherlands Institute for Neuroscience, The Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands M. T. G. De Jeu Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands Hyo Jung De Smet Research Group on Clinical and Experimental Neurolinguistics, Vrije Universiteit Brussel, Brussels, Belgium C. I. De Zeeuw Netherlands Institute for Neuroscience, The Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands

Contributors

xxix

Uwe Dietrich Department of Neuroradiology, Evangelisches Krankenhaus Bielefeld, Bielefeld, Germany Stéphane Dieudonné Laboratoire de Neurobiologie, Inhibitory Transmission Team, IBENS, Ecole Normale Supérieure (CNRS UMR 8197; INSERM U 1024), Paris, France Stefano Di Donato Fondazione IRCCS Istituto Neurologico C., Milan, Italy Patrick A. Dion Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada Department of Pathology and Cellular Biology, Université de Montréal, Montreal, QC, Canada Opher Donchin Department of Biomedical Engineering and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Be’er Sheva, Israel Christophe J. Dubois Department of Cell Biology and Anatomy, LSU Health Sciences Center, Medical Education Building, New Orleans, LA, USA Nicolas Dupré Centre Hospitalier Universitaire de Québec, Department of Medicine, CHU de Québec – Université Laval, Québec, QC, Canada Timothy J. Ebner Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA Abdeslem El Idrissi Department of Biology, College of Staten Island, Staten Island, NY, USA The Center for Developmental Neuroscience, College of Staten Island, Staten Island, NY, USA The Graduate Center, Program in Biology – Neurosciences, The City University of New York, New York, NY, USA Gina E. Elsen Department of Neurological Surgery, Seattle Children’s Research Institute, Center for Integrative Brain Research, Seattle, WA, USA Carmen Espinós Centro de Investigación Príncipe Felipe, Valencia, Spain Jennifer K. Fahrion Research Support Core, Clinical Research Center, University Hospitals, Cleveland, OH, USA S. Hossein Fatemi Department of Psychiatry and Behavioral Sciences, Division of Neuroscience Research, University of Minnesota, Minneapolis, MN, USA Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA Kathleen B. Fenner Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA Josef Finsterer Klinik Landstrasse, Messerli Institute, Vienna, Austria

xxx

Contributors

Marta Florio Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy Department of Genetics, Harvard Medical School, Boston, MA, USA Timothy D. Folsom Department of Psychiatry and Behavioral Sciences, Division of Neuroscience Research, University of Minnesota, Minneapolis, MN, USA Kathryn D. Foote Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA Neel Fotedar Department of Neurology, Case Western Reserve University, Cleveland, OH, USA Ludovic Galas Normandie University, UNIROUEN, Inserm, PRIMACEN, Rouen, France Sid Gilman Department of Neurology, University of Michigan, Ann Arbor, MI, USA Elke R. Gizewski Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria Mitchell Glickstein Cell and Developmental Biology, University College London, London, UK Dan Goldowitz Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada R. Gilberto González Department of Diagnostic Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Roy Graham DRC Computer, Sunnyvale, CA, USA Michael D. Greicius Department of Neurology and Neurological Sciences, Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Stanford University School of Medicine, Stanford, CA, USA Giuliana Grimaldi Unité d’Etude du Mouvement (UEM), Neurologie – ULB Erasme, Bruxelles, Belgium Xavier Guell Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Christophe Habas Service de NeuroImagerie, CHNO des XV–XX, Université Pierre et Marie Curie, Paris, France Marios Hadjivassiliou Academic Hallamshire Hospital, Sheffield, UK

Department

of

Neurosciences,

Royal

Contributors

xxxi

Ikhlass Haj Salem Faculté de médecine, Université Laval, Québec, QC, Canada Robert M. Hardwick Behavioural Brain Sciences, School of Psychology, University of Birmingham, Birmingham, UK Richard Hawkes Department of Cell Biology and Anatomy Genes and Development Research Group, Hotchkiss Brain Institute, The University of Calgary, Calgary, AB, Canada Joachim Hermsdörfer Lehrstuhl für Bewegungswissenschaft, Fakultät für Sportund Gesundheitswissenschaft, Technische Universität München, Munich, Germany Christian Herweh Department of Neuroradiology, University of Heidelberg, Medical Center, Heidelberg, Germany Germund Hesslow Department of Experimental Medical Science, Division for Neuroscience, University of Lund, Lund, Sweden Robert F. Hevner Department of Pathology, University of California, San Diego, CA, USA Akiyuki Hiraga Department of Neurology, Chiba Rosai Hospital, Ichihara-shi, Chiba, Japan Tomoo Hirano Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto, Sakyo-ku, Japan Moritoshi Hirono Graduate School of Brain Science, Doshisha University, Kyoto, Japan Jérôme Honnorat Centre de Référence, de Diagnostic et de Traitement des Syndromes Neurologiques Paranéoplasiques, Hospices Civils de Lyon, Lyon, France Université Claude Bernard Lyon 1, Lyon, France Neuro–Oncologie, Hôpital Neurologique, Bron, France T. M. Hoogland Netherlands Institute for Neuroscience, The Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands Mikio Hoshino Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan C. Huang School of Biological Sciences, University of Missouri-Kansas City, Kansas City, MO, USA Yayoi Ikeda Department of Anatomy, School of Dentistry, Aichi Gakuin University, Nagoya, Japan Takanori Ikenaga Department of Chemistry and Bioscience, Kagoshima University, Kagoshima, Japan

xxxii

Contributors

Winfried Ilg Section Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany Jon Infante Neurology Service, University Hospital Marqués de ValdecillaIDIVAL, University of Cantabria, Santander, Spain M. E. Ioffe Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, Moscow, Russia Yerko Ivánovic-Barbeito Servicio de Neurología, Unidad de ELA y enfermedades neuromusculares, Complejo Hospitalario Universitario de Canarias, La Laguna, Tenerife, Spain Neurology Department, Hospital Puerta del Sur HM, Móstoles, Madrid, Spain Richard B. Ivry Department of Psychology, University of California, Berkeley, CA, USA Dieter Jaeger Department of Biology, Emory University, Atlanta, GA, USA Sriram Jayabal Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA Dan-Anders Jirenhed Department of Experimental Medical Science, Lund University, Lund, Sweden Patrice Jissendi Radiology Department, Centre Hospitalier de Wallonie picarde, Tournai, Belgium Fredrik Johansson Department of Experimental Medical Science, Lund University, Lund, Sweden Henrik Jörntell Neural Basis for Sensorimotor Control, Department of Experimental Medical Sciences, Lund University, Lund, Sweden Keun-Hwa Jung Department of Neurology, Seoul National University Hospital, Seoul, South Korea Gordana Juric-Sekhar Department of Pathology, Harborview Medical Center, Seattle, WA, USA Masanobu Kano Department of Neurophysiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan Jan Kaslin ARMI- Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia Hideshi Kawakami Department of Epidemiology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan

Contributors

xxxiii

Stefanie Keulen Research Group on Clinical and Experimental Neurolinguistics, Vrije Universiteit Brussel, Brussels, Belgium Center for Language and Cognition, Universiteit Groningen, Groningen, The Netherlands Research Foundation Flanders (F.W.O.), Brussels, Belgium James S. King Department of Neuroscience, The Ohio State University, Columbus, OH, USA Osman Kizilkilic Department of Radiology, Istanbul University Cerrahpasa Medical School, Istanbul, Turkey Thomas Knöpfel Laboratory for Neuronal Circuit Dynamics, RIKEN Brain Science Institute, Saitama, Japan Noriyuki Koibuchi Department of Integrative Physiology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan Hitoshi Komuro Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA Yutaro Komuro Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA Dimitar Kostadinov Wolfson Institute for Biomedical Research, University College London, London, UK Florian Krismer Division of Clinical Neurobiology, Department of Neurology, Medical University, Innsbruck, Austria Tatsuro Kumada Faculty of Health and Medical Sciences, Tokoha University, Hamamatsu, Shizuoka, Japan Michael Küper Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany Matt Larouche Neurology, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, BC, Canada M. G. Leggio I.R.C.C.S. Santa Lucia Foundation, Rome, Italy Department of Psychology, Sapienza University of Rome, Rome, Italy Maria Leggio Department of Psychology, Sapienza University of Rome, Rome, Italy Ataxia Lab, IRCCS Santa Lucia Foundation, Rome, Italy Benjamin Legros Department of Neurology; Reference Center for the Treatment of Refractory Epilepsy, Université Libre de Bruxelles- Hôpital Erasme, Brussels, Belgium

xxxiv

Contributors

Mathieu Letellier Centre National de la Recherche Scientifique and Université de Bordeaux, Bordeaux, France Derick H. Lindquist Department of Psychology, The Ohio State University, Columbus, OH, USA Siqiong June Liu Department of Cell Biology and Anatomy, LSU Health Sciences Center, Medical Education Building, New Orleans, LA, USA Ann M. Lohof Sorbonne Université and Centre National de la Recherche Scientifique, Paris, France Elan D. Louis Department of Neurology, University of Texas Southwestern, Dallas, TX, USA S. Loyola Netherlands Institute for Neuroscience, The Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands Mario U. Manto CHU-Charleroi, University of Mons, Charleroi, Belgium Peter Mariën Research Group on Clinical and Experimental Neurolinguistics, Vrije Universiteit Brussel, Brussels, Belgium Department of Neurology and Memory Clinic, ZNA Middelheim General Hospital, Antwerp, Belgium Jean Mariani Sorbonne Université and Centre National de la Recherche Scientifique, Paris, France Caterina Mariotti Department of Diagnostics and Applied Technology, Unit of Genetics of Neurodegenerative and Metabolic Disease, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milan, Italy Daniele Marmolino Laboratoire de Neurologie expérimentale, Université Libre de Bruxeles (ULB), Bruxelles, Belgium Matthias Maschke Department of Neurology, Krankenhaus der Barmherzigen Brüder, Trier, Germany Department of Neurology, University of Duisburg-Essen, Essen, Germany Luca Massimino Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy Alexandre Mathy Wolfson Institute for Biomedical Research, University College London, London, UK Peter Mariën: deceased

Contributors

xxxv

Antoni Matilla-Dueñas Functional and Translational Neurogenetics Unit, Department of Neuroscience, Health Sciences Research Institute Germans Trias i Pujol (IGTP), Badalona, Barcelona, Spain Yukiko Matsuda Department of Epidemiology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan R. Chris Miall Behavioural Brain Sciences, School of Psychology, University of Birmingham, Birmingham, UK Lauren N. Miterko Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, Houston, TX, USA Hiroshi Mitoma Tokyo Medical University, Medical Education Promotion Centre, Shinjuku-ku, Tokyo, Japan Satoshi Miyashita Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan M. Molinari I.R.C.C.S. Santa Lucia Foundation, Rome, Italy Marco Molinari Neurorehabilitation 1 and Spinal Center, Robotic Neurorehabilitation Lab, IRCCS Santa Lucia Foundation, Rome, Italy Hiroyuki Morino Department of Epidemiology, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan Maria Mörsdorf Department of Neuroradiology, Bruederkrankenhaus Trier, Trier, Germany Michael H. Myoga Department of Neurobiology, Harvard Medical School, Boston, MA, USA M. Negrello Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands Shevon E. Nicholson Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA Anne Noreau Montreal Neurological Institute, McGill University, Montreal, QC, Canada Dennis A. Nowak Klinik Kipfenberg, Neurologische Fachklinik, Kipfenberg, Germany Neurologische Universitätsklinik, der Philipps–Universität, Marburg, Germany

xxxvi

Contributors

John Oberdick Department of Neuroscience and Center for Molecular Neurobiology, The Ohio State University, Columbus, OH, USA Adrian L. Oblak Department of Radiology and Imaging Sciences, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA Nobuhiko Ohno Department of Anatomy, Division of Histology and Cell Biology, School of Medicine, Jichi Medical University, Shimotsuke-shi, Tochigi, Japan Division of Ultrastructural Research, National Institute for Physiological Sciences, Okazaki, Aichi, Japan Gaku Okugawa Department of Psychiatry, Kansai Kinen Hospital, Hirakata, Osaka, Japan Peter L. Oliver MRC Harwell Institute, Harwell Campus, Oxfordshire, UK Gülin Öz Center for Magnetic Resonance Research, Department of Radiology, Medical School, University of Minnesota, Minneapolis, MN, USA Francesc Palau Department of Genetic and Molecular Medicine and Pediatric Institute of Rare Diseases (IPER), Sant Joan de Déu Children’s Hospital, Barcelona, Spain CIBER on Rare Diseases (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain Division of Pediatrics, University of Barcelona School of Medicine and Health Sciences, and Clínic Institute of Medicine and Dermatology, Hospital Clínic, Barcelona, Spain Philippe Paquier Research Group on Clinical and Experimental Neurolinguistics, Vrije Universiteit Brussel, Brussels, Belgium Unit of Translational Neurosciences, School of Medicine and Health Sciences, Universiteit Antwerpen, Antwerp, Belgium Services de Neurologie et de Neuropsychologie, ULB-Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium Angel M. Pastor Departamento de Fisiología, Facultad de Biología, Universidad de Sevilla, Sevilla, Spain Annarita Patrizi Chica und Heinz Schaller-Stiftung Research Group, German Cancer Research Center (DKFZ), Heidelberg, Germany Andras J. Pellionisz HolGenTech, Sunnyvale, CA, USA Peter A. Pellionisz UCLA, Westwood, CA, USA Jean-Claude Perez IBM Emeritus, Martignas, France

Contributors

xxxvii

Katarzyna Pietrajtis Laboratoire de Neurobiologie, Inhibitory Transmission Team, IBENS, Ecole Normale Supérieure (CNRS UMR 8197; INSERM U 1024), Paris, France Jaap J. Plomp Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands Laurentiu S. Popa Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA John Porrill Department of Psychology, University of Sheffield, Sheffield, UK Neofytos Prodromou Department of Neurosurgery, University Hospital of Ioannina, Ioannina, Greece Miguel Ramirez Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada Genome Sciences and Technology, University of British Columbia, Vancouver, BC, Canada Alberto Rampérez Departamento de Bioquímica, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain Otto Rapalino Neuroradiology Division, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA Anders Rasmussen Department of Experimental Medical Science, Division for Neuroscience, University of Lund, Lund, Sweden Wade G. Regehr Department of Neurobiology, Harvard Medical School, Boston, MA, USA Robert E. Ricklefs University of Missouri-St. Louis, St. Louis, MO, USA Rémi Robert Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada Jae-Kyu Roh Department of Neurology, Seoul National University Hospital, Seoul, South Korea Department of Neurology, The Armed Forces Capital Hospital, Sungnam, South Korea Romina Romaniello Department of Child Neuropsychiatry and Neurorehabilitation, “E. Medea” Scientific Institute, Bosisio Parini (LC), Italy Victoria Rook School of Biological and Chemical Sciences, Queen Mary, University of London, London, UK

xxxviii

Contributors

Ferdinando Rossi Neuroscience Institute of Turin (NIT), Department of Neuroscience, University of Turin, Turin, Italy Neuroscience Institute of the Cavalieri-Ottolenghi Foundation (NICO), University of Turin, Turin, Italy Salvatore Rotondo Department of Biology, College of Staten Island, Staten Island, NY, USA Guy A. Rouleau Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada Tom J. H. Ruigrok Department of Neuroscience, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands Fumihito Saitow Department of Pharmacology, Nippon Medical School, Tokyo, Japan Elżbieta M. Sajdel-Sulkowska Department of Experimental and Clinical Physiology, Center for Preclinical Research, Medical University of Warsaw, Warsaw, Poland Department of Psychiatry Harvard Medical School, Boston, MA, USA Sharleen T. Sakai Department of Psychology and Neuroscience Program, Michigan State University, East Lansing, MI, USA Ivelisse Sánchez Functional Biology and Experimental Therapeutics Laboratory, Functional and Translational Neurogenetics Unit, Department of Neuroscience, Health Sciences Research Institute Germans Trias i Pujol (IGTP), Badalona, Barcelona, Spain José Sánchez-Prieto Departamento de Bioquímica, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain Marco Sassoè-Pognetto Department of Neuroscience “Rita Levi Montalcini”, National Institute of Neuroscience-Italy, Turin, Italy Nathaniel B. Sawtell Department of Neuroscience and Kavli Institute for Brain Science, Hammer Health Sciences Center, New York, NY, USA Karl Schilling Anatomisches Institut – Anatomie und Zellbiologie, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany Jeremy D. Schmahmann Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Beate Schoch Stiftungsklinikum Mittelrhein GmbH, Koblenz, Germany Dennis J. L. G. Schutter Department of Experimental Psychology, Faculty of Social Sciences, Utrecht University, CS, Utrecht, The Netherlands

Contributors

xxxix

Carmen Serrano-Munuera Neurology Section, Hospital Sant Joan de Déu de Martorell, Barcelona, Spain Yusuke Seto Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan Laboratory of Developmental Systems, Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan Aasef G. Shaikh Department of Neurology, Case Western Reserve University, Cleveland, OH, USA Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA Neurological Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, USA Neurology Service, Louis Stokes Cleveland VA Medical Center, Cleveland, OH, USA Rachel M. Sherrard Sorbonne Université and Centre National de la Recherche Scientifique, Paris, France Yoshikazu Shinoda Department of Systems Neurophysiology, Graduate School of Medicine, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan William R. Shirer Department of Neurology and Neurological Sciences, Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Stanford University School of Medicine, Stanford, CA, USA Francoise Sidime Department of Biology, College of Staten Island, Staten Island, NY, USA The Center for Developmental Neuroscience, College of Staten Island, Staten Island, NY, USA Roy V. Sillitoe Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, Houston, TX, USA Deborah A. Sival Beatrix Kinderziekenhuis, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Constantino Sotelo Neurociences Institute, Miguel Hernandez University and CSIC, Campus de San Juan, Alicante, Sant Joand’Alacant, Spain INSERM, U968, Paris, France UPMC Univ Paris 06, UMR_S 968, Institut de la Vision, Paris, France CNRS, UMR_7210, Paris, France

xl

Contributors

Rebecca M. C. Spencer Department of Psychology, University of Massachusetts, Amherst, MA, USA Maja Steinlinand Neuropaediatrics, University Children’s Hospital Inselspital, Bern, Switzerland Joseph E. Steinmetz Department of Psychology, University of Southern California, Los Angeles, CA, USA Catherine J. Stoodley Department of Neuroscience, American University, Washington, DC, USA Peter L. Strick Pittsburgh Veterans Affairs Medical Center, Pittsburgh, PA, USA Izumi Sugihara Department of Systems Neurophysiology, Graduate School of Medicine, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan Hidenori Suzuki Department of Pharmacology, Nippon Medical School, Tokyo, Japan Franco Taroni Fondazione IRCCS Istituto Neurologico C., Milan, Italy Department of Diagnostics and Applied Technology, Unit of Genetics of Neurodegenerative and Metabolic Diseases Istituto Neurologico “Carlo Besta”, Milan, Italy Richard F. Thompson Department of Psychology, The Ohio State University, Columbus, OH, USA Dagmar Timmann Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany Else A. Tolner Departments of Neurology and Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands Magdalena Torres Departamento de Bioquímica, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain Shoji Tsuji Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan Kazuyoshi Tsutsui Laboratory of Integrative Brain Sciences, Department of Biology, Waseda University, and Center for Medical Life Science of Waseda University, Shinjuku-ku, Tokyo, Japan Marylka Yoe Uusisaari Laboratory for Neuronal Circuit Dynamics, RIKEN Brain Science Institute, Saitama, Japan Theoretical and Experimental Neurobiology Unit, Okinawa Institute of Science and Technology (OIST), Okinawa, Japan

Contributors

xli

Arn M. J. M. van den Maagdenberg Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands Kim van Dun Rehabilitation Sciences Group, Universiteit Hasselt, Hasselt, Belgium Tristan Varela MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK David Vaudry Laboratory of Neuronal and Neuroendocrine Communication and Differentiation, Neuropeptides, Neuronal Death and Cell Plasticity Team, Normandie University, UNIROUEN, Inserm, Rouen, France Normandie University, UNIROUEN, Inserm, PRIMACEN, Rouen, France Jo Verhoeven Department of Language and Communication Science, City University London, London, UK Computational Linguistics and Psycholinguistics Research Center, Universiteit Antwerpen, Antwerp, Belgium M. T. Viscomi Istituto di Istologia ed Embriologia, Università Cattolica del S. Cuore and I.R.C.C.S. Santa Lucia Foundation, Rome, Italy Jan Voogd Department of Neuroscience, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands Frantisek Vozeh Department of Pathophysiology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic Laboratory of Neurodegenerative Disorders, Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic Mark J. Wall School of Life Sciences, University of Warwick, Coventry, UK Fajun Wang Department of Neurology, Case Western Reserve University, Cleveland, OH, USA Marion Wassef Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Paris, France CNRS UMR 8197, Paris, France INSERM U1024, Paris, France Masahiko Watanabe Department of Anatomy, Faculty of Medicine, Hokkaido University, Sapporo, Japan Barry D. Waterhouse Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA Thomas C. Watson Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK Patrick Wild Centre for Autism Research, University of Edinburgh, Edinburgh, UK

xlii

Contributors

Alanna J. Watt Department of Biology, McGill University, Montreal, QC, Canada Gregor K. Wenning Division of Clinical Neurobiology, Department of Neurology, Medical University, Innsbruck, Austria Leigh Wilson MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK Richard J. T. Wingate MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK Kevin Wingeier Neuropaediatrics, University Children’s Hospital Inselspital, Bern, Switzerland Vadim Yakhnitsa Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, USA Mayumi Yamada Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan Laboratory of Brain Development and Regeneration, Graduate School of Biostudies, Kyoto University, Kyoto, Japan Mitsunori Yamada Division of Neuropathology, Department of Brain Disease Research, Shinshu University School of Medicine, Matsumoto-city, Nagano, Japan Tomoko Yamada Faculty of Medicine, University of Tsukuba, Tsukuba, Japan Yue Yang Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA Joanna Yeung Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada Tulin Yildirim Department of Radiology, Baskent University Medical School, Adana, Turkey Albert J. Yoo Department of Interventional Neuroradiology and Endovascular Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Gerard Zitnik Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, USA Mary L. Zupanc Pediatric Neurology, University of California – Irvine/Children Hospital of Orange County, Orange County, CA, USA

Part I Cerebellar Development

1

Specification of the Cerebellar Territory Marion Wassef

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Delineating the Cerebellar Primordium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fate Maps of the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rotation of the Cerebellar Primordium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Specification of the Cerebellar Primordium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Organizing Properties of the Isthmic Neuroepithelium – Fgf8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The MHB Organizer: A Molecular Network Set up at the Otx2-Gbx2 Boundary . . . . . . . . . . . . . . The Otx2-Gbx2 Boundary: A Stable or Drifting Limit? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genes Regulating the Competence of the Neuroepithelium to Develop a MHB Identity . . . . . . Genes Regulating Distinct Neuroepithelium Competences on Either Sides of the MHB Boundary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Subdivisions of the Cerebellar Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anteroposterior Subdivisions of the Cerebellar Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dorsoventral Subdivisions of the Cerebellar Plate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 5 7 8 9 9 11 11 12 13 13 15 16 19 19

Abstract

The cerebellar primordium develops dorsally at an intermediate anteroposterior (AP) level of the neural tube. Its size is modulated by the early anteriorizing and posteriorizing signals, which pattern the neural tube. Two important signaling centers, the midbrain–hindbrain organizer and the roof plate, intersect at the level of the cerebellar anlage and control its positioning, differentiation, growth, survival, and patterning. Neural tube bending in the pontine region induces a widening of the fourth ventricle, which is made possible by choroid plexus differentiation and extension. As M. Wassef (*) Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Paris, France CNRS UMR 8197, Paris, France INSERM U1024, Paris, France e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_1

3

4

M. Wassef

a consequence of these morphogenetic changes, the AP axis of the cerebellar primordium is rotated by 90 , and the cerebellar vermis and hemispheres derive from the anterior and posterior parts of the early cerebellar plate, respectively. The cerebellar plate is progressively subdivided along its dorsoventral axis into distinct domains, which generate subsets of cerebellar neurons according to their neurotransmitter phenotype. The roof plate marked by Gdf7 expression is at the origin of choroid plexus cells but does not contribute neurons or glia to the cerebellum. The rhombic lip, marked by Atoh1 expression, produces all the glutamatergic neurons of the cerebellum and a large number of non-cerebellar neurons. Finally, the ventral cerebellar neuroepithelium, marked by Ptf1a expression, generates all the GABAergic neurons and can be further subdivided into two progenitor domains, devoted to the production of Purkinje cells and GABAergic projection neurons of the deep cerebellar nuclei. The so-called cerebellar primordium is not restricted to the production of cerebellar neurons but contributes to a large number of nuclei in the isthmic region. Keywords

Neural Tube · FGF8 Signaling · Deep Cerebellar Nucleus · Cerebellar Vermis · Neural Tube Closure

Introduction The relative positions of the main brain subdivisions (Fig. 1) are established during development and have been conserved in the course of vertebrate evolution. The neural tube progressively differentiates into distinct regional identities resulting in local modifications of the growth and mechanical properties of the neuroepithelium and the formation of bulges called vesicles. In parallel, the different domains of the neuroepithelium evolve distinct competences to respond to adjacent or intrinsic signals. The forebrain, midbrain, and hindbrain vesicles, which form first, are known as the primary brain vesicles and become further subdivided later. The vesicles and intervening constrictions have often been used as stage-specific landmarks of early brain regionalization (but see below). In early studies based on retrospective anatomical observations during development, the cerebellar primordium was identified by its proximity to two landmarks: the midbrain anteriorly and the hindbrain choroid plexus posteriorly. Soon after neural tube closure, the cerebellar plate was identified as a pair of dorsal extensions of the anterior hindbrain adjacent to the midbrain vesicle and limited by the choroidal plate (Fig. 2). However, the extent of the cerebellar primordium and the localization of its boundaries could not be determined solely on the basis of anatomical or histological studies. Furthermore, specification of the cerebellar territory is likely to have begun much earlier with neural plate regionalization. Beginning from the 1990s, a series of fate mapping studies were therefore undertaken aiming at mapping early brain subdivisions or, more specifically, at delineating the cerebellar primordium. Several vertebrate species were examined at successive developmental stages in these studies, which used a large variety of lineage tracing methods. The fate maps performed at a given stage provide information about the destiny of a region of the neural tube left under the influence of

1

Specification of the Cerebellar Territory

a

c

midbrain

cerebellum

5

forebrain

hindbrain choroid plexus

b

vellum medullaris MIDBRAIN r1 HINDBRAIN

FOREBRAIN

Fig. 1 Relative positions of the main brain subdivisions in adult mice: (a) dorsal and lateral views of a dissected adult mouse brain. The main brain subdivision have been colored, forebrain in brown, midbrain in blue, cerebellum in red, and the rest of the hindbrain in yellow. (b) schematic representation of a medial sagittal section through a similar brain depicting the structures which derive from the r1 (rhombomere 1) developmental compartment. These include the pontine region and the cerebellum which are highlighted in red. (c) higher magnification of the vermal region of the cerebellum illustrating the continuity of neural structures forming the roof of the fourth ventricle. The cerebellum is connected to the midbrain through the vellum medullaris and to the posterior hindbrain through the choroid plexus

adjacent structures in its normal context. It is also interesting to determine at what stage the cerebellar primordium becomes specified (or committed) and is able to maintain its cerebellar fate in isolation when cultured in vitro or transplanted to ectopic locations. Finally, the development of sophisticated molecular genetics tools provided new insight into the molecular pathways involved in the control of the size of the cerebellar territory and the positioning of its boundaries.

Delineating the Cerebellar Primordium Obtaining a fate map at a given stage consists in labeling a region of a living embryo in order to follow its fate at later developmental stages when anatomical structures can be unambiguously identified. This requires that the label should not spread to adjacent structures or be diluted by tissue growth. Isotopic transplants are often used

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a midbrain forebrain midbrain hindbrain r1 r2 hindbrain

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Fig. 2 Localization of the cerebellar primordium in chick and mouse embryos: (a) schematic representation of the neural tube vesicles and main brain subdivisions in chick embryos at 1.5 days of incubation (E1.5, dorsal view) and E3.5 (lateral view), corresponding to developmental stages 11 and 20 of Hamburger and Hamilton (1951), respectively. The arrowheads mark the limits of the major brain subdivisions. Note the marked bending of the neural tube at 3.5 days of incubation and the appearance of a choroid plexus forming the roof of the hindbrain. The cerebellum (in red) derives from the dorsal part of r1. (b) Lateral (E8.5 and E9.5) and posterior (E11.5) views of three mouse embryos. The cerebellar primordium is colored in pink and the midbrain in green. The mouse neural tube closes between E8.5 and E9.5. Notice that at E11.5 the two cerebellar halves which were previously opposed are separated by the transparent choroid plexus posteriorly and widely diverge

to minimize the spread of the label. The donor embryo is labeled by injection, incorporation of a dye, or by genetic tagging. Homologous fragments are excised from the donor and host. The host fragment is discarded and replaced by its labeled donor counterpart. This technique of embryological manipulations is powerful but concerns only few vertebrate species which are accessible to embryological manipulations at early stages. In particular, it is not appropriate for mammalian embryos. Nevertheless, it is possible to extend to other species the fate maps obtained from experimentally amenable species by using the gene expression boundaries as landmarks for performing grafts. The gene map then serves as a common reference. Based on the observation that the pattern of gene expression is globally well

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conserved across species, it is assumed that the relation between the fate map and the gene map is conserved. The genetic technologies developed in mouse during the last decades have directly confirmed the suitability of this molecular anatomy. It has become possible to genetically label a specific cell subset at a given embryonic stage in mouse embryos and subsequently trace their lineage (Zinyk et al. 1998; Rodriguez and Dymecki 2000; Sgaier et al. 2005; Dymecki and Kim 2007).

Fate Maps of the Cerebellum The first detailed fate maps of the cerebellar primordium, soon after neural tube closure, were obtained independently by the groups of Alvarado-Mallart (Martinez and Alvarado-Mallart 1989, 1990) and Le Douarin (Hallonet et al. 1990) in ten somite-stage avian embryos (stage 10 of Hamburger and Hamilton 1951, noted HH10). The fate maps were obtained by isotopic transplantation of fragments of the neural tube between quail and chick embryos. The quail-chick chimera transplantation method designed by Le Douarin (1982) is based on the similarity between avian species at early developmental stages. It takes advantage of a specific cytological feature to identify quail cells. A clump of nucleolus-associated heterochromatin appears as a central dot within the nucleus of quail cells labeled with DNA stains. In chick cells, the chromatin appears diffusely organized. The QCPN monoclonal antibody which specifically recognizes quail cells was later developed and is now often used instead of DNA stains. The avian fate maps allowed to localize the anterior and posterior limits of the cerebellar primordium soon after neural tube closure. It is also indicated that, unexpectedly, the anterior limit of the cerebellar primordium at the 10 somite stage (HH10) is not marked by the isthmic constriction. Rather, the prospective cerebellum extends anteriorly into the adjacent mesencephalic vesicle. The anterior limit of the cerebellum was not materialized by a morphological landmark but likely corresponded to the MHB boundary as defined by Otx2 expression (Millet et al. 1996). Indeed, the Otx2 boundary lies slightly anterior to the isthmic constriction (Millet et al. 1996). Recent genetic fate maps performed in mouse embryos demonstrated that the anterior brain domain, characterized by Otx2 and Wnt1 expressing cells, are adjacent to the cerebellar primordium (Sgaier et al. 2005; Zervas et al. 2005). Interestingly, at later developmental stages, Otx2 is also expressed at the caudal edge of the cerebellar primordium and is required for its development. The hindbrain is further subdivided into seven developmental units called rhombomeres (r1-r7). The quail-chick fate maps indicated that the cerebellum originates from the most anterior rhombomere, r1. It was unclear if the primordium of the cerebellum is confined to dorsal r1. The auricular part of the cerebellum was identified by Marin and Puelles (1995) as originating from the caudalmost region of the cerebellar primordium and was postulated by these authors to derive from r2. Genetic tracing indicated, however, that dorsal r2 cells do not contribute to the cerebellum in mouse embryos (Awatramani et al. 2003; Farago et al. 2006). Anteroposterior specification along the hindbrain and spinal cord is controlled by a family

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of widely conserved transcription factors, the Hox genes. The most anteriorly expressed, Hoxa2 reaches r2 but is not expressed in r1. The fate maps thus indicate that the cerebellar primordium lies anterior to the domain of influence of the Hox genes. Accordingly, downregulation of Hoxa2 in mouse (Gavalas et al. 1997) and chick (Irving and Mason 2000) results in a posterior extension of the cerebellar primordium at the expense of r2. As concerns the dorsoventral dimension of the cerebellar primordium, the quail chick fate maps indicated that even if it is restricted to the neural tubular plate, it extends more in ventral r1 than previously suspected, encompassing two thirds of the neural tube dorsoventral axis.

Rotation of the Cerebellar Primordium At the time of neural closure, the cerebellar primordium consists of a pair of dorsal wings which flank the roof plate and extend along the anteroposterior axis of the anterior hindbrain (r1). Fate maps obtained at this stage by transplantation or by genetic cell lineage tracing indicated that the two posterior cerebellar plates will develop as the cerebellar hemispheres. They are pushed apart laterally by the flexure of the neural tube at the level of the pons (pontine flexure) and the constriction of the neural tube at the MHB boundary. Their mediolateral rotation is made possible by the rapid growth of the choroidal plate (Fig. 3). The final rotation of the prospective

Fig. 3 Differentiation of the hindbrain choroid plexus from the roof plate: Schematic representation of the development of the choroid plexus between E1.5 and E3.5 in chick embryos based on data obtained in mouse and chick. At each age the neural tube is illustrated in toto on the left and the corresponding transverse section through the anterior hindbrain on the right. The choroid plexus derives from epithelial cells which constitute the roof plate at day 1.5. These cells start to proliferate and undergo an epitheliomesenchymal transition in such a way that they form a wide thin sheet of neural cells which constitute the roof of the hindbrain, fourth ventricle. At the same time, anterior bending of the neural tube tends to widen the dorsal hindbrain (forces represented by the divergent arrows at E3.5)

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cerebellar vermis takes place slightly later in the anterior cerebellar plate and involves active cell reorganization.

Specification of the Cerebellar Primordium The Midbrain–Hindbrain (MHB) Domain At early developmental stages, under the influence of posteriorizing and anteriorizing signals, the neural plate becomes subdivided into anterior and posterior domains, which express distinct combinations of transcription factors (Wurst and Bally-Cuif 2001; Liu and Joyner 2001; Kobayashi et al. 2002; Raible and Brand 2004). The homeodomain transcription factors Otx2 and Gbx2 are expressed, respectively, in the anterior and posterior neural plate. Slightly later, at the end of gastrulation, between E7.5 and E9.5 in the mouse, a new region of the neural tube forms progressively at an intermediate anteroposterior location. Called midbrain– hindbrain (MHB) domain, it expresses a combination of transcription factors and signaling molecules, which endow it with the competence to develop as midbrain and cerebellum. Among transcription factors with conserved function in MHB development are the vertebrate homologs of the drosophila engrailed segmentation genes, En1 and En2 in mouse and chick, eng1, 2 and 3 in zebrafish, the paired homeodomain transcription factors Pax2, Pax5 and Pax8, the Lim homeodomain transcription factors Lim1a and Lim1b (depending on species). Development of the MHB domain is also dependent on the function of two secreted cell–cell signaling molecules Wnt1 (wingless-related) and Fgf8 (fibroblast growth factor 8), which are expressed in the presumptive midbrain and anterior hindbrain, respectively. The major MHB-specific genes are not interdependent at early stages. The onset of their expression in the MHB domain is triggered independently by vertical signals derived from non-neural structures underlying the neural plate (McMahon et al. 1992; Wurst et al. 1994; Ye et al. 2001; Li and Joyner 2001). Closely related genes belonging to the same family often contribute to MHB development displaying small differences in timing or expression patterns between paralogs. These variations may explain why the phenotypes, resulting from inactivating the same paralog, may markedly differ in severity between species. Some of the genes expressed in the early MHB domain will be later maintained in the cerebellum, the midbrain, or both.

Organizing Properties of the Isthmic Neuroepithelium – Fgf8 As a complement of quail-chick fate map studies, ectopic transplantations were performed with the aim of testing the commitment of the neuroepithelium of the posterior midbrain and anterior hindbrain to a cerebellar fate (Alvarado-Mallart et al. 1990; Martinez et al. 1991). The resulting chimeras were analyzed at short and long survival times posttransplantation. Unexpectedly, both anterior and posterior quail cerebellar transplants switched the fate of the adjacent host neuroepithelium. Isthmic

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transplants, grafted anterior to the MHB, affected the fate or polarity of adjacent structures. The neuroepithelium of the anterior diencephalon (p2) was transformed into optic tectum, a midbrain structure, instead of its normal thalamic fate. More anterior transplants resulted in the formation of one or two ectopic optic tectum structures, which often fused with the endogenous tectum. The optic tectum is a polarized structure marked by the graded expression of several transcripts and proteins including En2, which can be detected by immunocytochemistry. The tectal structures, induced by isthmic transplants, were always polarized with their caudal end close to the grafts. In the hindbrain, the dorsal neuroepithelium of r2, r3, and r4 was recruited to a cerebellar fate by adjacent cerebellar grafts. Thus, pieces of cerebellar primordium behaved as long-range signaling centers. When transplanted into a wide competent territory they induced the adjacent neural structures to complete an ectopic MHB domain. These properties are the hallmark of secondary organizers. The neuroepithelium of the isthmic constriction adjacent to the MHB boundary is therefore known as the MHB or isthmic organizer. Wnt1 and Fgf8, two diffusible signaling molecules expressed in the midbrain and anterior hindbrain, respectively, were candidate organizing signals. Loss of function experiments in the mouse indicated that either one is essential for the formation of the cerebellum and midbrain. Gain of function experiments, obtained by implantation of beads soaked in FGF8 in the neural tube of avian embryos, indicated that an ectopic source of FGF8 mimicks the inductive properties of fragments of the MHB organizer (Crossley et al. 1996). FGF8 has several important functions in the specification of the cerebellar territory. First, it prevents the expression of potent repressors of the cerebellar fate, Otx2 anteriorly, and Hoxa2 posteriorly. It also stabilizes the expression of Gbx2, which is required for cerebellum development. FGF8 controls growth and polarity of the MHB domain by maintaining pools of actively proliferating undifferentiated precursors on each side of the MHB boundary and by controlling the gradient of En1/2 expression. FGF8 is a potent morphogen, which serves as a major component of several organizing centers in the brain and body. FGF8 organizing activity relies on the rapid and progressive deployment of a set of target genes with nested expressions many of which act as inhibitors of the FGF8 signaling pathway. Besides, alternative splicing of Fgf8 generates several secreted isoforms differing only at their mature amino terminus (MacArthur et al. 1995). Two of the four FGF8 splice isoforms, FGF8a and FGF8b, are expressed in the mid-hindbrain region during development. Although the only difference between these isoforms is the presence of an additional 11 amino acids at the N terminus of FGF8b, these isoforms possess remarkably different abilities to pattern the midbrain and anterior hindbrain (Olsen et al. 2006). Quantitative analysis showed that Fgf8b signal is 100 times stronger than Fgf8a signal (Sato et al. 2001). The FGF8 subfamily comprises two additional members, FGF17 and FGF18, which are expressed by the MHB organizer. The FGF17b splice variant and FGF18 display intermediate receptor-binding affinities and patterning abilities compared to FGF8a and FGF8b (Olsen et al. 2006).

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The MHB Organizer: A Molecular Network Set up at the Otx2Gbx2 Boundary Otx2 and Gbx2 mutually cross-inhibit each other’s expression resulting in the formation of a sharp boundary between their expression domains. Positioning of the Otx2-Gbx2 boundary, also called MHB boundary, depends on the relative “strength” of Otx2 and Gbx2 (Simeone 2000; Wurst and Bally-Cuif 2001). Loss of Gbx2 function or ectopic expression of Otx2 posteriorly results in a posterior displacement of the MHB boundary (Wassarman et al. 1997; Broccoli et al. 1999; Millet et al. 1999). Conversely, reducing the number of Otx2 copies in an Otx1 mutant background shifts the MHB boundary anteriorly up to the p2 prosomere and dramatically increases the size of the cerebellar primordium. Otx2 plays a major role in preventing the midbrain and posterior hindbrain to turn into cerebellum. In contrast, in the absence of Gbx2, the anterior hindbrain fails to develop a coherent midbrain or cerebellum structure (Wassarman et al. 1997). Conversely, anterior ectopic expression of Gbx2 induces a milder and transient enlargement of the cerebellum (Millet et al. 1999). This indicates that other factors (FGF8, Hox. . .) cooperate with Gbx2 to prevent transformation of the anterior hindbrain into midbrain. At the stabilized Otx2-Gbx2 boundary, the Wnt1, En1, FGF8, and Pax2 genes initiate cross-regulatory interactions and soon become interdependent, as schematized in Fig. 4. Once established, the function of the MHB organizer relies on each member of this genetic network. Thus, inactivation of a single gene (Wnt1: McMahon et al. 1992, En1: Wurst et al. 1994), or of two members of the same gene family (Pax2 and 5: Urbánek et al. 1997), or conditional inactivation of Fgf8 to bypass its early requirement for embryonic development, all result in the deletion of most of the midbrain and cerebellum, preceded by a downregulation of the expression of the other genes involved in MHB organizer function.

The Otx2-Gbx2 Boundary: A Stable or Drifting Limit? Because Fgf8 is highly expressed adjacent to the Otx2-Gbx2 boundary and ectopic FGF8 induces Gbx2 and represses Otx2 expression the cell lineage restriction and stability of the MHB boundary has been a matter of debate. Distinct methods were used in chick and mouse embryos in order to follow the fate of cells adjacent to the MHB boundary. In chick embryos, the Otx2 boundary at the MHB junction was found to coincide with the posterior end of the early generated neurons of the mesencephalic nucleus of nerve V (Millet et al. 1996). In mouse embryos, a fate map of the MHB boundary was obtained by Wnt1-CreERT conditional labeling at E7.5, E8.5, and E9.5 (Sgaier et al. 2005). A cell lineage restriction was observed in the dorsal posterior midbrain beginning from E8.5 but the lineage restriction was not established ventrally before E9.5. The lineage restriction that prevented Wnt1 expressing cells from contributing to the cerebellar plate was not absolute, as a few cells were observed posteriorly in the anterior part of the cerebellar plate. At

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Gbx2

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Fig. 4 Genetic network controlling midbrain–hindbrain organizer positioning and function: At early stages, positioning of the MHB organizer depends on cross interactions between Otx2 and Gbx2, which code for homeodomain transcription factors. Otx2 is a potent repressor of cerebellar fate even at relatively late stages of development. Transcription of the En1/2, Fgf8, and Wnt1 genes is initiated independently in the MHB domain. They soon engage in cross-regulatory interactions constituting a tight genetic network which is deployed in space around the Otx2/Gbx2 boundary and is completely dependent on the function of each of its components. The potent patterning and polarizing activity of the MHB organizer probably also reflects its capacity to maintain a pool of undifferentiated midbrain and hindbrain cells. Also dysfunction of the MHB organizer results in truncation of adjacent structures

later stages, these cells did not contribute to the mature cerebellum. Taken together, the data in chick and mouse indicate that the early MHB boundary is stable in the dorsal neural tube and marks the anterior limit of the mature cerebellum. In contrast, ventral midbrain cells may relocate in the adjacent anterior hindbrain between E8.5 and E9.5, resulting in a discrete anterior shift of the Wnt1 lineage boundary between these two stages.

Genes Regulating the Competence of the Neuroepithelium to Develop a MHB Identity During zebrafish gastrulation, iro1 and iro7 are expressed in a broad neural plate domain that includes the prospective MHB. The iro1 and iro7 expression domain is expanded in headless and masterblind mutants, which are characterized by exaggerated Wnt signaling. Early expansion of iro1 and iro7 expression in these mutants

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correlates with expansion of the (MHB) domain, raising the possibility that iro1 and iro7 have a role in the determination of the MHB. Knockdown of both iro1 and iro7 genes prevents Pax2.1 expression and the establishment of the MHB organizer. Their ectopic expression is not sufficient to induce a MHB identity (Itoh et al. 2002). These observations suggest that the Iro genes are required for the early acquisition of a MHB identity. The POU domain transcription factor spg/pou2 (Reim and Brand 2002), which is specifically expressed in the MHB primordium of zebrafish is involved in conferring a MHB identity. spg/pou2 is orthologous to mammalian Oct3/Oct4, and is required for the early expression of key molecules that function in the formation of the MHB, such as pax2.1, spry4, wnt1, her5, eng2, and eng3. Pou2 mutant embryos are insensitive to FGF8, although FGF receptor expression and activity of the FGF8 signaling pathway appear intact. This indicates that spg/pou2 mediates the regional competence to respond to FGF8 signaling.

Genes Regulating Distinct Neuroepithelium Competences on Either Sides of the MHB Boundary If the MHB boundary remains stable it is because it forms at the interface between two domains, which from the onset have distinct competences. This means that they differ in their responses to the same signals. Several transcription factors expressed on either sides of the MHB boundary have been shown to affect the competence of their expression domains to respond to FGF8 signaling. Chick Irx2, a homeobox gene of the Iroquois family is expressed in the presumptive cerebellum and is a target of the FGF8/MAP kinase cascade (Matsumoto et al. 2004). Chick Irx2 modulates the response of neuroepithelial cells to FGF8 signaling. At the difference of Fgf8b, which when expressed ectopically in the midbrain shifts neuroepithelium identity to a cerebellum fate, Fgf8a stimulates midbrain growth but fails to induce a fate change. Overexpression of Irx2 with Fgf8a turns the entire dorsal midbrain into a cerebellum. Meis2, which is expressed in the chick tectal primordium, is both necessary and sufficient for tectal development. Otx2 transcriptional activity in the tectum depends on the balance between a co-repressor, the Groucho family co-repressor Tle4/Grg4, and a coactivator, the TALE-homeodomain protein Meis2. Meis2 acts by competing with the Grg4 corepressor for binding to Otx2 and thereby restores Otx2 transcriptional activator function in the tectum (Agoston and Schulte 2009).

Subdivisions of the Cerebellar Plate Like other parts of the early neural tube, the neuroepithelium of the cerebellar primordium is progressively subdivided along is anteroposterior and dorsoventral axis. This partition reflects differences in the duration (Sato and Joyner 2009) and intensity (Basson et al. 2008) of exposure to diffusible signaling molecules produced

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by adjacent signaling centers like FGF8/17/18, WNT1, BMP4/7, GDF7, SHH. . ., and to their various downstream effectors. The identity of cerebellar progenitors thus depends on their distance from the midbrain–hindbrain organizer, the roof plate/ choroid plexus, and the floor plate, which contribute to increase their diversity. The current paradigm to understand the successive developmental steps leading to the production of a large diversity of neuronal types derives from the pioneer studies of the T. Jessell group on the developing spinal cord. Neuronal diversity in the spinal cord was shown to result from the subdivision of the neuroepithelium into progenitor domains according to their dorsoventral coordinates. Each progenitor domain expresses a unique combination of transcription factors and generates a characteristic set of neuronal types in a stereotyped succession. The establishment of progenitor domains occurs in two steps. In an early phase, opposed gradients of SHH and BMP signals derived from the floor plate and roof plate, respectively, activate or repress the expression of a first set of transcription factors which provide broad dorsal or ventral identities to epithelial cells. The second step relies on successive and mutual cross-interactions between transcription factors. These interactions subdivide the early broad neural tube domains into dedicated progenitor domains with sharpened boundaries. This second step is less well documented in the cerebellar primordium than in the spinal cord even if mutual cross-repressions between transcription factors expressed in adjacent cerebellar domains have been reported. As illustrated in Fig. 5, the rotation of the cerebellar primordium tends to obscure the relationship between the early axes which determine the orientation of gradients of diffusible molecules derived from the midbrain–hindbrain organizer or the roof plate and those of the late embryonic cerebellum.

Fig. 5 Anteroposterior and dorsoventral subdivisions of the cerebellar plate. Schematic representation of anteroposteriorly (AP left) and dorsoventrally (DV right) arranged cerebellar patterns observed on whole-mount stained brains. The dotted line represents a sagittal section. Imagine the pattern changes on sagittal sections when the line is moved mediolaterally and how it is complicated to reconstitute the global pattern from sections

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Anteroposterior Subdivisions of the Cerebellar Plate Cerebellar vermis and hemisphere. Fate map studies in mouse and chick have shown that the cerebellar vermis derives from the anterior cerebellar plate, while the cerebellar hemispheres derive from its posterior part. Several genes involved in the function of the midbrain–hindbrain organizer like Fgf8, En1, and Pax2 are known to display differential expression along the anteroposterior axis of the cerebellar plate. This is also the case for several targets or inhibitors of FGF8 signaling including the Fgf8 family members Fgf17 and Fgf18, the Sprouty1/2/4 genes, which together modulate the chronology and spatial deployment of FGF8 signaling. Expression of the basic helix-loop-helix (bHLH) transcription factors Ngn1/2 is also modulated along the anteroposterior axis. Vermis size depends on the duration and intensity of FGF8 signal expressed in the anterior hindbrain (Sato and Joyner 2009). Interestingly, the cerebellar domains from which the vermis and hemispheres derive seem to be distinct and differ in their response to FGF8 signaling. The vermal region is atrophied or deleted in mutants in which the function of the MHB organizer is affected or in which the intensity or duration of FGF8 signaling is decreased. Conversely, FGF8 signaling can be increased in the midbrain–hindbrain domain through the conditional inactivation of two or three of the functionally redundant Sprouty genes which belong to a family of FGF8 inhibitors. Sprouty1/2 conditional mutation in the MHB results in a marked enlargement of the vermis but does not affect the size of the hemispheres (Yu et al. 2011). The mature cerebellar midline derives from the midbrain-hindbrain boundary. At early developmental stages, the cerebellar vermis is a paired structure. In early embryos, the two adjacent vermal halves are separated by the roof plate. Fate map studies have shown that the midline of the mature cerebellar vermis derives from a narrow group of cells at the midbrain–hindbrain boundary (Kala et al. 2008). This indicates that similar to the cerebellar hemispheres, the vermis also experiences a nearly 90 rotation of its axis from anteroposterior to mediolateral. This complex process also explains the occurrence of incomplete fusions of the vermis in pathological and experimental contexts. An isthmic compartment intervening between the cerebellum and midbrain? In late embryos and pups, the isthmus is an ill-defined region straddling the anterior hindbrain and posterior midbrain. Early embryological studies have described several populations of neurons originating in the cerebellar plate and destined to populate the isthmic nuclei. The Wnt1-CreER fate maps described above indicate that the Wnt1 expression domain contributes cells to a rostral hindbrain subdivision distinct from the cerebellum which could belong to the isthmus. At early stages of cerebellar neurogenesis in mice (E11.5, E12.5), a Ptf1a negative domain intervenes on sagittal sections (see below) between the Ptf1a positive cerebellar neuroepithelium and the ring of Wnt1 positive cells which marks the midbrain– hindbrain boundary. These cells express low level of Pax2. It is unclear if they belong to a portion of the ventral neuroepithelium of the pons repositioned dorsally as a consequence of morphogenetic movements or constitute a bona fide component of the cerebellar primordium. Some authors consider the isthmus as a separate

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compartment intervening between the midbrain and r1 but the existence of an isthmic neuroepithelium compartment is still questionable. The isthmic compartment is proposed to correspond to the Fgf8 expression domain and would not contribute to the cerebellar primordium located more posteriorly in dorsal r1. Genetic lineage tracing indicates, however, that the progeny of FGF8 expressing cells largely contributes to the mature cerebellum (Charles Watson and Tomomi Shimogori, personal communication). It is nevertheless possible that a proportion of the Ptf1a negative cells of the isthmic neuroepithelium turn on Ptf1a expression at some point as is the case for cells adjacent to the RL, which successively turn on Atoh1/Math1 expression (see below).

Dorsoventral Subdivisions of the Cerebellar Plate The rhombic lip/cerebellar neuroepithelium (Atoh1/Ptf1a) subdivision. In the early hindbrain (also called rhombencephalon) as in the rest of the neural tube the roof plate is a row of specialized cells which marks the dorsal midline. The roof plate cells express Gdf7, a member of the BMP family of signaling molecules. Fate mapping of the Gdf7 positive cells using Gdf7-Cre mice indicated that the neural part of the hindbrain choroid plexus or choroidal plate derives from the roof plate. The dorsal most subdivision of the hindbrain neuroepithelium called rhombic lip (RL) lines the roof plate. The RL in r1 is called cerebellar, rostral, anterior, or upper rhombic lip (uRL) whereas the rhombic lip of r2-r7 is called lower rhombic lip (lRL). The uRL has been classically described as the source of cerebellar granule cell precursors and thought to generate only cerebellar granule neurons precursors whereas the mossy fiber precerebellar nuclei is derived from the lRL (Altman and Bayer 1997; Rodriguez and Dymecki 2000). The bHLH transcription factor Atoh1 (for mouse Atonal homolog 1) also known as Math1 is expressed in the RL as early as E9.5. Atoh1 is required for the development of the uRL-derived cerebellar granule neurons and the lRL-derived mossy-fiber precerebellar nuclei (Ben-Arie et al. 1997; Wang and Zoghbi 2001; Wang et al. 2005). Short- and long-term tracing of the progeny of the Atoh1-positive RL progenitors identified a large population of additional derivatives (Wang et al. 2005; Machold and Fishell 2005). Strikingly, the Atoh1+ progenitors of the uRL produce all the glutamatergic neurons in the cerebellum. This includes the granule cells, the scarce population of unipolar brush cells, and all the glutamatergic projection neurons of the deep cerebellar nuclei (Wang et al. 2005; Machold and Fishell. 2005; Fink et al. 2006). The GABAergic neurons of the cerebellum originate from the non-RL cerebellar neuroepithelium, which is characterized by the expression of the Ptf1a bHLH transcription factor (Hoshino 2006). Ptf1a is required for the differentiation of all the GABAergic cell types of the cerebellum (Hoshino et al. 2005). This comprises the two types of projection neurons: Purkinje cells and the GABAergic projection neurons of the deep cerebellar nuclei, and a multitude of Pax2-positive interneuron types, that is, Golgi, basket, and molecular layer interneurons in the cerebellar cortex, and the GABAergic interneurons of the deep cerebellar nuclei (Maricich and Herrup 1999).

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It is interesting to note that the RL and the cerebellar epithelium cannot be considered as lineage restricted compartments. The fates of successive waves of Atoh1expressing cells have been traced in Atoh-CreER x R26R mice in which the Cre recombinase is tethered in the cytoplasm of Atoh1 expressing cells (Machold and Fishell 2005). Timed injection of Tamoxifen to Atoh-CreER x R26R pregnant mice allows the recombinase to enter the nucleus and recombine the LacZ reporter. The progeny of progenitors, which were expressing Atoh1 at the time of Tamoxifen injection, can be followed. It was observed that the RL progenitors, which express Atoh1 at early stages, give rise to the early generated neurons of the deep cerebellar nuclei and the non-cerebellar populations of isthmic nuclei. They do not contribute to the granule cell population. In contrast, later injections of tamoxifen trace successive waves of granule cells which first populate the anterior cerebellar cortex then progressively its more posterior aspects. These observations indicate that new Atohnegative “naïve” progenitors in the adjacent cerebellar neuroepithelium are recruited to express Atoh. This suggests that the RL acts as a device in which “naïve” progenitors are transformed into successive RL derivatives, which then migrate out allowing a new population of “naïve” progenitors to enter the RL domain. Ptf1a and Atoh1 repress each other’s expression (Pascual et al. 2007) but beginning from the onset of Purkinje cell generation at E11.5, the pattern of Ptf1a protein expression is “salt and pepper” in the cerebellar neuroepithelium, leaving room for putative “naïve” progenitors. In addition, in Atoh1 mutants, a small population of granule cells develops which is derived from Ptf1a + progenitors (Pascual et al. 2007). Taken together, these findings suggest that GABAergic and glutamatergic cerebellar neurons originate from distinct neuroepithelial regions, the cerebellar neuroepithelium and the RL. Furthermore, normal development of these neurons requires the activity of bHLH transcription factors Ptf1a or Atoh1, respectively (Hoshino et al. 2005; Ben-Arie et al. 1997). A similar subdivision of progenitors related to the neurotransmitter phenotype of their progeny is also observed in the forebrain. The glutamatergic and GABAergic neurons which form the cerebral cortex arise from distinct subdivisions of the forebrain neuroepithelium (Anderson et al. 1997; Wonders and Anderson 2006). Their differentiation is under the control of distinct bHLH transcription factors: the glutamatergic projection neurons of the cerebral cortex are produced in the dorsal pallium under the control of Ngn1/2, whereas generation of the GABAergic interneurons in the subpallial neuroepithelium is dependent on Ascl1/Mash1. Other subdivisions of the cerebellar plate. The cerebellar plate is currently considered to comprise four subdivisions and an intervening non-cerebellar isthmic domain (Fig. 6a): from dorsal to ventral: the roof plate, the RL, and two additional domains Ptf1dorsal and Ptf1ventral (Chizhikov et al. 2006; Zordan et al. 2008; Mizuhara et al. 2010). The existence of two subdivisions in the cerebellar neuroepithelium was first suggested by the presence of populations of early postmitotic neurons in the mantle zone of the cerebellar plate, which segregate along the dorsoventral axis and differ in marker expression (Fig. 6b). This includes an early ventral expression of Pax2, a marker of cerebellar GABAergic neurons, with the

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Ptf1a ventral Ptf1a dorsal RL RP

Fig. 6 Dorsoventral subdivisions of the cerebellar primordium: (a) Most studies agree that the cerebellar primordium comprises the following subdivisions from dorsal to ventral. 1, The roof plate does not contribute cells to the cerebellum. 2, The rhombic lip which expresses Atoh1/Math1 and produces all the glutamatergic neurons of the cerebellum and other neurons destined to populate a variety of isthmic nuclei. 3, A Ptf1a expressing domain which can be subdivided into a dorsal and a ventral component on the basis of differences in marker expression in the early neuroepithelium as well as in the overlying neurons. 4, Finally, a ventral domain whose cerebellar fate is uncertain. (b) Several populations of postmitotic neurons overlie different portions of the neuroepithelium of the cerebellar plate (Chizhikov et al. 2006). 1, A stream of migrating deep cerebellar neurons (in green) marked by Atoh1/Math1 and Tbr1 which accumulate ventrally, 2, Purkinje cells (in light purple) marked by Lhx1/5 or Corl2, 3, putative GABAergic neurons of the deep cerebellar nuclei (in orange) marked by Pax2 and Lmx1a. C-E Abrupt changes in the expression of markers in the cerebellar neuroepithelial cells suggest the existence of subdivisions in the cerebellar neuroepithelium. (c) E-Cadherin (Mizuhara et al. 2010), (d) Ngn1 and (e) Ngn2 (Zordan et al. 2008)

exception of Purkinje cells. Lhx1/5 and Corl2 (Minaki et al. 2008) are both considered to be Purkinje cell markers. More recently, an abrupt change in the level of expression of E-cadherin in the cerebellar neuroepithelium was shown to correspond to fate differences in the overlying neurons (Fig. 6c). Nephrocystin3 (Neph3), which encodes a membrane protein and is a target of Ptf1a is expressed in both compartments. Antibodies to the two surface molecules, Neph3 and E-cadherin, were used for fluorescence activated cell sorting (FACS). The fate of the sorted cells was identified after 2 days of culture in vitro, based on their expression of cell typespecific markers detected by immunocytochemistry. The Neph3+/E-cadherinhigh neuroepithelial cells of the dorsalmost compartment were shown to produce Corl2 + Purkinje cells whereas the Neph3+/E-cadherinlow neuroepithelial cells generated Pax2+ neurons. These neurons, based on their birthdates, were GABAergic projection neurons of the deep cerebellar nuclei (Mizuhara et al. 2010). Subdivisions of the cerebellar neuroepithelium have also been detected on the basis of the expression of the Ngn1 (Fig. 6d) and Ngn2 (Fig. 6e) neurogenic proteins (Zordan et al. 2008). In summary, like other parts of the brain, the cerebellar plate is subdivided into progenitor domains, which produce different types of neurons. The spatial segregation of progenitors fated to produce specific cell types is, however, much looser than in the rest of the hindbrain or in the spinal cord.

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Conclusions and Future Directions The existence of a neuroepithelial territory specialized in the production of cerebellar neurons could be anticipated based on some of the adult characteristics of the cerebellum. The cerebellum is a well-delineated organ with a characteristic histological organization. If the origin of cerebellar neurons can be traced back to a restricted domain of dorsal r1, the same domain also contributes to a wide range of extracerebellar nuclei: the cerebellar territory is not devoted to the production of cerebellar neurons. Positioning, patterning, and growth of the cerebellar territory depend on two orthogonal organizers, the MHB organizer and the roof plate, which provide specific properties to the adjacent neuroepithelial domains, the isthmic neuroepithelium and the rhombic lip, respectively. Recently obtained fate maps have increased our understanding of the organization of the cerebellar rombic lip and the neurogenic processes taking place in this structure. Future studies should further our understanding of the organization of the rest of the cerebellar plate cell and improve our knowledge of the lineages it produces. Modifications in cerebellar plate patterning are observed in mouse embryos when the late expression of genes involved MHB organizer is modified. It would be interesting to investigate if the diversity in cerebellar shape and organization observed during evolution results from similar molecular variations.

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Minaki Y, Nakatani T, Mizuhara E et al (2008) Identification of a novel transcriptional corepressor, Corl2, as a cerebellar Purkinje cell-selective marker. Gene Expr Patterns 8:418–423 Mizuhara E, Minaki Y, Nakatani T et al (2010) Purkinje cells originate from cerebellar ventricular zone progenitors positive for Neph3 and E-cadherin. Dev Biol 338:202–214 Olsen SK, Li JY, Bromleigh C et al (2006) Structural basis by which alternative splicing modulates the organizer activity of FGF8 in the brain. Genes Dev 20:185–198 Pascual M, Abasolo I, Mingorance-Le Meur A et al (2007) Cerebellar GABAergic progenitors adopt an external granule cell-like phenotype in the absence of Ptf1a transcription factor expression. Proc Natl Acad Sci U S A 104:5193–5198 Raible F, Brand M (2004) Divide et Impera–the midbrain-hindbrain boundary and its organizer. Trends Neurosci 27:727–734 Reim G, Brand M (2002) Spiel-ohne-grenzen/pou2 mediates regional competence to respond to Fgf8 during zebrafish early neural development. Development 129:917–933 Rodriguez CI, Dymecki SM (2000) Origin of the precerebellar system. Neuron 27:475–486 Sato T, Joyner AL (2009) The duration of Fgf8 isthmic organizer expression is key to patterning different tectal-isthmo-cerebellum structures. Development 136:3617–3626 Sato T, Araki I, Nakamura H (2001) Inductive signal and tissue responsiveness defining the tectum and the cerebellum. Development 128:2461–2469 Sgaier SK, Millet S, Villanueva MP et al (2005) Morphogenetic and cellular movements that shape the mouse cerebellum; insights from genetic fate mapping. Neuron 45:27–40 Simeone A (2000) Positioning the isthmic organizer where Otx2 and Gbx2meet. Trends Genet 16: 237–240 Urbánek P, Fetka I, Meisler MH et al (1997) Cooperation of Pax2 and Pax5 in midbrain and cerebellum development. Proc Natl Acad Sci U S A 94:5703–5708 Wang VY, Zoghbi HY (2001) Genetic regulation of cerebellar development. Nat Rev Neurosci 2: 484–491 Wang VY, Rose MF, Zoghbi HY (2005) Math1 expression redefines the rhombic lip derivatives and reveals novel lineages within the brainstem and cerebellum. Neuron 48:31–43 Wassarman KM, Lewandoski M, Campbell K et al (1997) Specification of the anterior hindbrain and establishment of a normal mid/hindbrain organizer is dependent on Gbx2 gene function. Development 124:2923–2934 Wonders CP, Anderson SA (2006) The origin and specification of cortical interneurons. Nat Rev Neurosci 7:687–696 Wurst W, Bally-Cuif L (2001) Neural plate patterning: upstream and downstream of the isthmic organizer. Nat Rev Neurosci 2:99–108 Wurst W, Auerbach AB, Joyner AL (1994) Multiple developmental defects in Engrailed-1 mutant mice: an early mid-hindbrain deletion and patterning defects in forelimbs and sternum. Development 120:2065–2075 Ye W, Bouchard M, Stone D et al (2001) Distinct regulators control the expression of the mid-hindbrain organizer signal FGF8. Nat Neurosci 4:1175–1181 Yu T, Yaguchi Y, Echevarria D et al (2011) Sprouty genes prevent excessive FGF signaling in multiple cell types throughout development of the cerebellum. Development 138:2957–2968 Zervas M, Blaess S, Joyner AL (2005) Classical embryological studies and modern genetic analysis of midbrain and cerebellum development. Curr Top Dev Biol 69:101–138 Zinyk DL, Mercer EH, Harris E et al (1998) Fate mapping of the mouse midbrain-hindbrain constriction using a site-specific recombination system. Curr Biol 8:665–668 Zordan P, Croci L, Hawkes R et al (2008) Comparative analysis of proneural gene expression in the embryonic cerebellum. Dev Dyn 237:1726–1735

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Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip Gian Giacomo Consalez, Marta Florio, Luca Massimino, Filippo Casoni, and Laura Croci

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Proneural Genes in Drosophila melanogaster Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Roles of Proneural Genes in Vertebrate Neurogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atoh1: The Master Gene in Granule Cell Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atoh1 Plays a Key Role in Granule Cell Clonal Expansion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Glutamatergic Neurons Derive from Atoh1+ Progenitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Late Atoh1+ Progenitors in the URL Give Rise to Unipolar Brush Cells . . . . . . . . . . . . . . . . . . . NeuroD: A “Nearly Proneural” Gene with Key Roles in Cerebellar Development . . . . . . . . . . . . Ascl1 in Ventricular Zone Neurogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ptf1a Is a Master Gene of Cerebellar GABAergic Neurogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ascl1 Labels the Cerebellar GABAergic Lineage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neurogenins in Cerebellar GABAergic Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neurog1 and Neurog2 Are Expressed in the Ptf1a+ Ventricular Neuroepithelium . . . . . . . . . Neurog1 Is Expressed in Cerebellar GABAergic Interneuron Progenitors . . . . . . . . . . . . . . . . . . Neurog2 Labels the PC Lineage and Regulates PC-Progenitor Cell-Cycle Progression and Dendritogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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G. G. Consalez (*) · L. Massimino · F. Casoni · L. Croci Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy e-mail: [email protected]; [email protected]; [email protected]; fi[email protected]; [email protected] M. Florio Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy Università Vita-Salute San Raffaele, Milan, Italy Department of Genetics, Harvard Medical School, Boston, MA, USA e-mail: marta_fl[email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_2

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Abstract

The cerebellar primordium arises between embryonic days 8.5 and 9.5 from dorsal rhombomere 1, adjacent to the fourth ventricle. Cerebellar patterning requires the concerted action of several morphogens secreted by the rhombic lip and roof plate and leads to the formation of two main neurogenic centers, the upper rhombic lip and the ventricular zone, from which glutamatergic and GABAergic neurons arise, respectively. These territories contain gene expression microdomains that are partially overlapping and, among others, express proneural genes. This gene family is tightly conserved in evolution and encodes basic helix-loop-helix transcription factors implicated in many neurogenetic events, ranging from cell fate specification to terminal differentiation of a variety of neuronal types across the embryonic nervous system. The present chapter deals with the established or suggested roles of proneural genes in cerebellar neurogenesis. Of the proneural genes examined in this chapter, Atoh1 plays a quintessential role in the specification and development of granule cells and other cerebellar glutamatergic neurons. Besides playing key roles at early stages in these early developmental events, Atoh1 is a key player in the clonal expansion of GC progenitors of the external granule layer. NeuroD, formerly regarded as a proneural gene, acts as a master gene in granule cell differentiation, survival, and dendrite formation. Ascl1 participates in GABA interneuron and cerebellar nuclei neuron generation and suppresses astrogliogenesis. Conversely, less is known to date about the role(s) of Neurog1 and Neurog2 in cerebellar neurogenesis, and a combination of loss- and gain-of-function studies is required to elucidate their contribution to cerebellar neurogenesis. Keywords

Achaete/scute like 1 · Amos · as-c complex · Ascl1 · Ato · Atoh1 · Atoh5 · Atonal · Atonal homolog 1 · Basic helix-loop-helix · bHLH · Biparous · BMP · Bone morphogenetic protein · Cato · Cerebelless · Drosophila · Drosophila melanogaster · FGF8 · GABAergic neurogenesis · Genetic fate mapping · Gli2 · Granule cell clonal expansion · Granule cell development · Lhx1 · Lhx5 · Lmx1a · Mash1 · Math1 · Medulloblastoma · NeuroD · Neurog1 · Neurog2 · Neurogenin 1 · Neurogenin 2 · Ngn1 · Ngn2 · Notch · Notch signaling · NTZ · Nuclear transitory zone · Olig2 · Patched · Pax2 · Proneural gene · Proneural genes · Ptf1a · sc · SHH · Smoothened · Sonic hedgehog · Sox9 · Upper rhombic lip · URL · Ventricular zone · Vertebrate neurogenesis · VZ · WNT · Xath1 · Xath5 · Xenopus laevis · XneuroD · Zic1

Introduction The mature cerebellum represents only 10% of the total brain volume but contains the majority (80–85%) of human neurons (reviewed in Herrup and Kuemerle 1997). It is the primary center of motor coordination, and it is essential for cognitive processing and sensory discrimination (Schmahmann 2004). In humans, the

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cerebellum achieves its mature configuration only many months after birth, and for this reason, it is especially vulnerable to developmental abnormalities. Like the cerebrum, the cerebellum comprises an outer cortical structure, a layer of white matter, and a set of cerebellar nuclei (CN) beneath the white matter. The CN project efferent fibers to the thalamus, brainstem, and spinal cord (Paxinos 1994) mediating the fine control of motor movements and balance. During mouse embryonic development, the cerebellum arises between embryonic days (E)8.5 and 9.5 from dorsal rhombomere 1 (r1), adjacent to the fourth ventricle, due to the mutual interactions between patterning genes, including Gbx2, Otx2, Fgf8, Wnt1, En1, En2, Pax2, Pax5, and others (reviewed in Liu and Joyner 2001). Cerebellar development requires a contribution from the posterior mesencephalon (Martinez and Alvarado-Mallart 1987) and the alar plate of rhombomere 2 (Marin and Puelles 1995). Normal patterning of the cerebellar anlage (Fig. 1a, b) depends on the formation and function of the isthmic organizer, a signaling center secreting the morphogens fibroblast growth factor 8 (FGF8) and WNT1, that defines the cerebellar territory along the anterior–posterior axis of the central nervous system (Martinez and Alvarado-Mallart 1987; Marin and Puelles 1994; Crossley et al. 1996; Wassarman et al. 1997; Martinez et al. 1999) and entails a fundamental contribution by the roof plate, secreting WNT and bone morphogenetic protein (BMP) ligands (Alder et al. 1999; Chizhikov and Millen 2004; Chizhikov et al. 2006). The patterning of the cerebellar primordium leads to the formation of two main germinal centers that will give rise to the multitude of neuronal types and subtypes observed in the mature cerebellum. These germinal regions, called ventricular zone (VZ) and upper rhombic lip (URL), contain gene expression microdomains that are partially overlapping and that will regulate the genesis of neuronal precursors fated to adopt GABAergic and glutamatergic phenotypes, respectively. Among other genes expressed in these microdomains are four proneural genes, namely, neurogenin 1 and neurogenin 2 (Neurog1/Ngn1, Neurog2/Ngn2) and achaete/scute like 1 (Ascl1/ Mash1) in the VZ, as well as Atonal homolog 1 (Atoh1/Math1) in the URL (Fig. 1c).

Proneural Genes in Drosophila melanogaster Development The defining event of neurogenesis is the switch from uncommitted, cycling progenitor cells to committed neuronal precursors. Nervous system development in Drosophila melanogaster has served as a paradigm for the discovery and dissection of neurogenetic processes and their regulation, providing a conceptual framework for the understanding of mammalian neurogenesis. In Drosophila, the entire nervous system arises from neuroectodermal cells, which delaminate from the surface epithelium and migrate into the interior of the embryo to form neural precursor cells or neuroblasts. The first step of neural fate determination in the Drosophila nervous system is the singling-out of neuroblasts from the neuroectodermal epithelium. Prior to such cell-selection process, all the ectodermal precursors share an equivalent potentiality to become either neuroblasts or epidermoblasts. The choice between these alternative fates was proven to rely on the expression of a small group of

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mesencephalon isthmic organizer

Extracellular signals

FGF8, WNTs sub-a

rachn

cereb

ellar p

oid sp

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sagittal view anterior to the left

rimor

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rl SHH? IV ventricle

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Fig. 1 Schematic of a cerebellar primordium with respect to patterning (a, b), neurogenesis (gene names in red boldface, c), and neuronal migration. See text for details. In (d) (highly simplified illustration), vertical upward arrows indicate radially migrating ventricular zone progenitors. Curved arrows indicate granule cell precursors (purple) and cerebellar neuron precursors (black). ctz cortical transitory zone, egl external granule layer, ntz nuclear transitory zone, rl upper rhombic lip (abbreviated as URL in the text); rp roof plate, vz ventricular zone

transcription factors, belonging to the basic helix-loop-helix (bHLH) family, which instruct neuroectodermal cells to take up the fate of neural precursors – from which they were termed proneural genes (reviewed in Jan and Jan 1994). Several expression studies have shown that a combination of upstream regulatory genes acts on the promoter regions of proneural genes to induce their expression within the so-called proneural clusters, i.e., regularly spaced patches of cells, all of which initially share an equivalent potential to become neural progenitors (Skeath and Doe 1996). Progressively, through a cell-cell interaction process called lateral inhibition, clustered progenitors start competing one another. As a result of this competition, the expression of proneural genes becomes restricted to one single prevailing cell, which will delaminate to form the neuroblast and will maintain and further upregulate proneural gene expression. Conversely and simultaneously, the remaining progenitor cells within the cluster receive inhibitory signals from the

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predominant neural precursor cell, and they partially or completely downregulate proneural gene expression, thereby acquiring the alternative fate of epidermoblasts (Artavanis-Tsakonas et al. 1999). Finally, singled-out neural progenitors undergo a stereotyped pattern of cell division producing a fixed number of daughter cells, which will terminally differentiate into the distinct cell types characteristic of the mature fly nervous system: neurons and associated support cells of the sensory organs (Jan and Jan 1994). The final cell type that a given neuron is fated to adopt is decided in a hierarchical, stepwise fashion. At each step, the neuroblast restricts its developmental potential along specific neuronal lineages, undergoing binary or multiple cell fate choices at determined phenotypic branch points of the cell-type specification process. As previously mentioned, a striking observation, first made in Drosophila, is the fact that the expression of individual proneural genes is restricted to different neuronal lineages. Indeed, genes belonging to the as-c complex were shown to be specifically involved in the determination of neuroblasts in external sense organs; ato provides the competence to form chordotonal organs (a type of internal sense organs) and photoreceptors; and amos is employed in the formation of multidendritic neurons and olfactory sensilla. Such observations raised the possibility that proneural genes might be involved not only in triggering a “generic” program of neural determination (epidermis versus neuroblast) but also in the subsequent specification of a given neural identity (e.g., multidendritic neurons versus chordotonal organs). Support to this hypothesis came from gain-of-function experiments: the ectopic expression of as-c induces the formation of ectopic external sense organs, while the forced expression of amos leads to ectopic multidendritic neurons and olfactory sensilla (Rodriguez 1990; Chien 1996; Parras 1996; Goulding et al. 2000). Drosophila proneural genes had been initially subdivided into two classes, based on their function: (i) determination genes, like ac, sc, or amos – dominantly expressed before any sign of neuronal differentiation and acting in the sorting out of neural progenitors from the neuroectoderm – and (ii) differentiation genes, like cato and biparous, expressed after the selection of neural precursors and involved in the process of neuronal differentiation per se. The sequential activation of these two classes of proneural genes – in a regulatory cascade in which early expressed determination genes induce downstream effectors of differentiation – was in agreement with the stepwise progression of undifferentiated progenitors toward differentiated neural cells (Campuzano and Modolell 1992). Indeed, a classical concept of experimental embryology is that the transition from an undifferentiated to a fully differentiated cell comprises two steps: cell specification/determination and cell differentiation. Nevertheless, such functional categorization of proneural genes turned out not to be completely exhaustive nor completely explanatory, as many proneural genes, like atonal, were proven to exert both functions or either, i.e., to trigger a generic program of neural development and/or to induce neuronal lineage or subtypespecific programs, depending primarily on the temporal- and regional-specific cues active throughout their expression window. Furthermore, an individual bHLH

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protein could be required for several different cell types at different times or locations during development. Factors affecting the outcome of proneural gene function include the context (cellular and genetic) and timing of their expression. More sophisticated criteria were therefore required to assess proneural function in neural development in order to explain such functional complexity. Placing proneural genes in temporal and, whenever possible, epistatic cascades has been a major goal in the past few years. Mapping these cascades onto precise stages and cellular events of the neuronal differentiation pathway remains an open challenge.

The Roles of Proneural Genes in Vertebrate Neurogenesis Cell fate decisions in the development of the vertebrate and invertebrate nervous systems are controlled by remarkably similar mechanisms. Among other ontogenetic programs, the coupling of neural determination and lineage/cell-type specification, by means of the combined action of proneural genes and positional identity determinants, is a mechanism strikingly conserved in evolution. Unsurprisingly, vertebrate genomes were proven to contain several orthologs of Drosophila proneural genes (Ledent and Vervoort 2001; Simionato et al. 2007). Based on the homology to their Drosophila counterparts, such genes have been isolated, cloned, and shown to play a pivotal role in vertebrate neurogenesis (Ghysen and Dambly-Chaudiere 1988; Lee 1997). As in Drosophila, vertebrate proneural genes commit cycling progenitor cells to a neuronal fate, which involves activation of Notch signaling and the induction of cell-cycle exit. As in Drosophila development, vertebrate proneural genes act in regulatory cascades, with early expressed genes inducing fate specification of neural progenitors and later-expressed genes regulating terminal differentiation (Cau et al. 1997; Lee 1997). In terms of sequence conservation in the bHLH domain, the mouse atonal homologs Atoh1 and Atoh5 are the genes most closely related to Drosophila atonal. Loss-of-function studies in the mouse have shown that Atoh1 is necessary for the generation of cerebellar granule neurons (see further) and for the development of the sensory epithelium of the inner ear (Ben-Arie et al. 1997; Chen et al. 2002), while Atoh5 is essential for retinal ganglion cell production (Wang 2001). Close members of the ato family were also found in Xenopus laevis – Xath1 and Xath5 – where they have been shown to induce a neural fate (Kanekar et al. 1997; Kim 1997). In Xenopus laevis, overexpression of Neurog1 leads to a massive ectopic formation of XneuroD-positive neurons (Ma et al. 1996). Incidentally, NeuroD, a gene initially labeled as a proneural gene thanks to its homology to other proneural factors and to its ability to convert presumptive dorsal epidermis into neurons in Xenopus laevis (Lee et al. 1995), is in fact involved in later stages of neuronal differentiation in vertebrates. Again, in addition to their generic neurogenetic role, numerous lines of evidence indicate that proneural genes also specify neuronal subtype identity. For instance, in the neocortex, the proneural genes Neurog1 and Neurog2 are absolutely required to specify the identities of early born, deep layer neurons, whereas they are dispensable for later stages of neuronal fate specification (Schuurmans et al. 2004).

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In the developing spinal neural tube, Atoh1 on one hand and Neurog1 and Ascl1 on the other are expressed in nonoverlapping patterns, and cross-inhibition occurs between the two sets of genes (Gowan et al. 2001). Furthermore, constitutive or ectopic expression of neurogenins, and other atonal homologs, yields specific neuronal subtypes in vivo (Blader et al. 1997; Kanekar et al. 1997; Olson et al. 1998; Perez et al. 1999; Gowan et al. 2001). Neurog1 or Neurog2 single-mutant mice lack complementary sets of cranial sensory ganglia, and Neurog1/2 double mutants lack, in addition, spinal sensory ganglia and a large fraction of ventral spinal cord neurons (Fode et al. 1998; Ma et al. 1998, 1999). Likewise, loss-of-function and gain-of-function analyses have shown that Ascl1 contributes to the specification of neuronal subtype identity (Fode et al. 2000) and is both required and sufficient to specify ventral telencephalic fates. Further evidence indicates that Ascl1 acts cooperatively in sympathetic ganglia as an instructive determinant of cell fate to induce the noradrenergic phenotype (Goridis and Brunet 1999). Ascl1 has also been implicated in the differentiation of early-born (but not late-born) neurons in the striatum, indicating that it regulates both progenitor cell behavior and neuronal fate specification in a temporally defined manner (Casarosa et al. 1999; Yun et al. 2002). The present chapter deals with the established or presumptive roles of proneural genes in the context of neuronal type specification, determination, differentiation, and clonal expansion at various stages during cerebellar neurogenesis. This chapter will provide a review of the literature about the roles played in that context by four established proneural genes and by one of their targets, NeuroD, formerly considered a proneural gene. Emphasis will be placed on the evidence accrued from the analysis of wild-type and transgenic mice.

Atoh1: The Master Gene in Granule Cell Development More than a century ago, the URL was recognized as the origin of the most numerous neuronal population in the CNS, the cerebellar granule cells (GCs), that first migrate tangentially (Fig. 1d, purple arrow) and then radially during embryonic and postnatal development, respectively (Cajal 1889; Schaper 1897). During postnatal proliferation in the external granule layer (EGL), GC precursors maintain Atoh1 expression until they radially migrate inward to form the internal granule layer (IGL) (Hatten and Heintz 1995; Helms et al. 2001). Atoh1 is the murine homolog of the Drosophila proneural gene atonal, as shown by sequence similarity and functional conservation in evolution (Ben-Arie et al. 2000). It encodes the homonymous bHLH transcription factor and is expressed starting at E9.5 in the dorsal neural tube, from rhombomere 1 to the tail (Akazawa et al. 1995). In the URL, Atoh1 is expressed in progenitors distinct from Lmx1a+ roof plate cells (Chizhikov et al. 2006). Atoh1 plays key roles in the development of all glutamatergic neurons of the cerebellum. The cerebellum of Atoh1 / mice is reduced in size and displays no foliation. In Atoh1 null embryos, unlike at earlier stages (Chizhikov et al. 2006), BrdU incorporation is strikingly reduced in the rhombic lip at E14.5, and the EGL fails to form, resulting in the complete absence of cerebellar GCs (Ben-Arie et al.

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1997; Bermingham et al. 2001). Instead, Purkinje cells (PCs), which form normally in the cerebellar VZ, migrate into the outermost part of the cerebellum and form a rudimentary PC layer, although some PCs fail to migrate toward the cortex and are retained in deep regions of the cerebellar primordium. Balanced levels of Atoh1 expression are essential for the correct timing of GC precursor differentiation. As mentioned, Atoh1-null mice have a small, poorly foliated cerebellum devoid of GCs. However, while Atoh1 overexpression leads to the upregulation of early differentiation markers (e.g., NeuroD, Dcx), it is insufficient to promote a complete differentiation of GC precursors (Helms et al. 2001). This paradox can be explained by the fact that, physiologically, Atoh1 is downregulated by its own protein product through a negative regulatory feedback loop (Gazit et al. 2004), and by other factors such as Notch intracellular domain, and the zinc-finger transcription factor Zic1 at the onset of GC precursor migration from the EGL to the IGL (Ebert et al. 2003). Likewise, in vitro experiments demonstrated that bone morphogenetic protein (BMP) signaling activation leads to the posttranslational inactivation of Atoh1, which is targeted to the proteasome for degradation (Zhao et al. 2008).

Atoh1 Plays a Key Role in Granule Cell Clonal Expansion Peak cerebellar growth occurs relatively late compared to the rest of the brain, driven primarily by proliferation of EGL cells. In the mouse, starting at the end of embryonic development (around E16.5), GC precursors resident in the EGL start undergoing an impressive wave of clonal expansion, before differentiating and undertaking their radial migration into the IGL. The highest growth rate is recorded during the first 2 weeks of postnatal life, while in humans, the corresponding proliferative peak occurs in utero during the third trimester, although EGL remnants can persist for up to a year after birth (Abraham et al. 2001). This prolonged ontogenetic period makes the cerebellum susceptible to developmental aberrations and tumor formation. Medulloblastoma (MB), the most common brain tumor of childhood, has been studied by histological means and, more recently, by molecular analysis (Eberhart et al. 2000; Thompson et al. 2006). Physiologically, the clonal expansion phase is promoted non-cell-autonomously by PCs, as first shown by John Oberdick and coworkers through transgenic expression of the diphtheria toxin in these neurons, leading to the virtual abolition of GC precursor proliferation in the EGL (Smeyne et al. 1995). This non-cell-autonomous effect is driven by the secreted morphogen and mitogen sonic hedgehog (SHH), as shown by Matthew Scott’s group and by others (Dahmane and Ruiz-i-Altaba 1999; Wallace 1999; WechslerReya and Scott 1999). In fact, in conditional knockout mice in which SHH is specifically removed from PCs, MacMahon and coworkers (Lewis et al. 2004) observed a drastic reduction of GC precursors expansion. Accordingly, heterozygous mutants for the inhibitory SHH receptor patched, in which SHH signaling (reviewed in Villavicencio et al. 2000) is upregulated in a ligand-independent fashion, are prone to the development of medulloblastoma (MB)-like tumors. Among the MB

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subtypes that have been characterized in patients, the desmoplastic variant seems to be derived from Atoh1+ GC precursors in the EGL (Pomeroy et al. 2002; Salsano et al. 2004). Collectively, this evidence prompted questions as to whether Atoh1 plays any role in GC precursor proliferation. Zoghbi and coworkers addressed this point in a paper published in 2009 (Flora et al. 2009) showing that Atoh1 is required for the peri- and postnatal expansion of GC progenitors. To investigate the molecular effects of Atoh1 deletion, they isolated GC progenitors from Atoh1flox/flox P5 mice and infected them with adenoviruses expressing either the green fluorescent protein (GFP) or the Cre recombinase gene and cultured transduced cells in the presence of SHH to evaluate their proliferative status. Their results showed that Atoh1 deletion led to a sharp decrease in cell proliferation, suggesting that, in those cells, the response to SHH is largely dependent on Atoh1. Through various approaches, they showed that Atoh1 mediates this response by transcriptionally upregulating the expression of Gli2, a critical mediator of SHH signaling (reviewed in Villavicencio et al. 2000). Next, they asked whether its expression might be required for the genesis of MBs induced by constitutive activation of the SHH pathway. To address this point, they crossed mice harboring a conditional deletion of Atoh1 with tamoxifen-inducible Cre deleters expressing a constitutively active form of the SHH co-receptor smoothened. While, in the presence of Atoh1, smoothened overexpression caused hyperplasia of the EGL, this effect was drastically quenched in mice carrying a homozygous Atoh1 deletion.

Other Glutamatergic Neurons Derive from Atoh1+ Progenitors Some Atoh1+ cells migrate from the RL to the nuclear transitory zone (NTZ) (Jensen et al. 2004) (black downturned arrow in Fig. 1d), a transitory cell cluster that will give rise to the cerebellar nuclei (CN). A paper published in 2005 by Gord Fishell’s group (Machold and Fishell 2005) clearly revealed that GCs are not the only glutamatergic lineage derived from Atoh1+ progenitors of the URL. This work was conducted taking advantage of a mouse line expressing a tamoxifen-inducible form of Cre recombinase (CreERT2) under transcriptional control of the Atoh1 promoter. This approach, dubbed genetic inducible fate mapping (Joyner and Zervas 2006), allowed the authors to tag several waves of neuronal progenitors born at successive stages of development, determining their final fate and location in the adult brainstem and cerebellum, shedding light on the spatiotemporal regulation of cerebellar glutamatergic neurogenesis. The results of this study clearly demonstrated that, prior to E12.5, Atoh1 is transiently expressed in cohorts of cerebellar rhombiclip neural precursors that populate the ventral hindbrain and deep cerebellar nuclei in the adult. Starting at E12.5, Atoh1+ progenitors start giving rise mostly to granule cells that will populate the anterior lobe; finally, Atoh1+ progenitors born at later stages until E16.5 will progressively populate the entire EGL and, after inward migration, the IGL of all cerebellar lobules. A parallel study, conducted by Zoghbi and colleagues (Wang et al. 2005), took advantage of an Atoh1LacZ/+ knock-in line to analyze the migration and fate of Atoh1

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+ progenitors and corroborated the findings of Machold and Fishell. In addition, this study, using a Atoh1LacZ/ null mutant, demonstrated that Atoh1 is essential for the establishment of the NTZ first and eventually for the formation of the glutamatergic component of CNs. Thus, Atoh1 is required to support the development of both GCs and the glutamatergic CN neurons. The role of Atoh1 in precerebellar nuclei development is discussed elsewhere (Machold and Fishell 2005; Wang et al. 2005) and is beyond the scope of the present chapter.

Late Atoh1+ Progenitors in the URL Give Rise to Unipolar Brush Cells Unipolar brush cells (UBCs) are the other glutamatergic neurons located in the adult IGL. They were first described for their morphology: they feature a single brush-like dendritic ending (Harris et al. 1993; Mugnaini and Floris 1994) and project their axons to GCs and to other UBCs (Nunzi et al. 2001). In 2006, Hevner and colleagues showed that UBCs also originate from the Atoh1+ URL that produces GCs, except that they do so later in development (Englund et al. 2006). UBC precursors are born in the URL between E15.5 and E17.5 and migrate into the prospective white matter during late embryonic and early postnatal development. Interestingly, while Atoh1 / mice show the complete loss of GC precursors, UBCs were severely reduced but not completely depleted in the same mutants. In the context of cerebellar neurogenesis, Atoh1 expression in the URL plays a quintessential role in the specification and development of GC precursors and of progenitors of other neurons, namely, glutamatergic ones populating the CN, besides several ventral hindbrain nuclei. While Atoh1 is expressed in UBC progenitors, it is not strictly required for the determination of this specific cell fate. Besides playing key roles at early stages in these early developmental events, Atoh1 is a key player in the clonal expansion of GC progenitors in the EGL at the end of their tangential migration from the URL (Fig. 1d).

NeuroD: A “Nearly Proneural” Gene with Key Roles in Cerebellar Development NeuroD is a bHLH transcription factor originally studied in Xenopus laevis for its ability to convert embryonic epithelial cells into differentiated neurons and for its role in promoting cell cycle exit and neuronal differentiation (Lee et al. 1995). A loss-of-function approach was used to study NeuroD functions during brain development (Miyata et al. 1999). NeuroD null mice died shortly after birth due to diabetes. In the study conducted by Miyata et al., the authors rescued this phenotype introducing a transgene that encodes the mouse NeuroD gene under control of the insulin promoter. The rescued null mice featured an ataxic gait, walked around incessantly, and failed to balance themselves. A histological analysis performed at P30 revealed a severe reduction of cerebellar GCs in the posterior lobules (VI–X), whereas a small population of GCs survived in the anterior cerebellum. Secondary to

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GC depletion, PCs of the posterior cerebellum failed to arrange into a proper monolayer. However, PC development appeared normal in terms of PC-specific marker expression. At birth, NeuroD is expressed in the inner layer of the EGL where post-mitotic granule cells reside and in the post-migratory GCs located in the IGL. In null mice, at birth, Miyata et al. found an increased rate of cell death in the inner half of the posterior EGL, which harbors post-mitotic precursors. GC death continued until P30, indicating a degeneration of the surviving GCs of the IGL. The authors concluded that NeuroD regulates a transcriptional cascade of genes that are essential for the differentiation and survival of post-mitotic cerebellar GCs. Another study conducted by Azad Bonni’s group at Harvard University (Gaudilliere et al. 2004) revealed a novel role for NeuroD in regulating GC neuron dendritic morphogenesis. They demonstrated that the knockdown of NeuroD expression by RNA interference in both primary cerebellar GC culture and organotypic cerebellar slices resulted in a profound alteration of dendritic morphogenesis, while it had no effect on axonal growth. Moreover, they demonstrated that neuronal activity leads to the phosphorylation of NeuroD by the protein kinase CAMKII. This event activates a downstream intracellular signaling pathway that regulates dendritogenesis in cerebellar granule neurons. Additional studies will be necessary to fully dissect the transcriptional machinery downstream of NeuroD responsible for the growth and maintenance of granule cell neuron dendrites. The above findings demonstrate that NeuroD acts as a master gene in the context of cell-intrinsic transcriptional mechanisms that guide GC differentiation, survival, and dendrite formation. It is worth mentioning that NeuroD is not only expressed in the progeny of URL progenitors. Expression of this gene is clearly detectable in the cerebellar cortical transitory zone (CTZ), a post-mitotic compartment hosting PCand other GABAergic precursors (Croci and Consalez unpublished observation; Lee et al. 2000).

Ascl1 in Ventricular Zone Neurogenesis Ptf1a Is a Master Gene of Cerebellar GABAergic Neurogenesis Although the cerebellum contains a relatively small variety of neurons, the molecular machinery governing neuronal generation and/or subtype specification is still poorly understood. In 2005, Hoshino et al. (2005) published the characterization of a novel mutant mouse, cerebelless, which lacks the entire cerebellar cortex but survives up to adult stages. The analysis of its phenotype, and the characterization of the underlying gene mutation, clarified that Ptf1a (pancreas transcription factor 1a), which encodes a bHLH transcription factor, is required for generating the cerebellar GABAergic compartment. Atoh1 and Ptf1a participate in regionalizing the cerebellar neuroepithelium and define two distinct areas, the VZ (Ptf1a) and the URL (Atoh1), which generate GABAergic and glutamatergic neurons, respectively (Hoshino et al. 2005; Pascual et al. 2007). Although Ptf1a is not a proneural gene,

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the expression of three proneural genes (Ascl1, Neurog1, and Neurog2) overlaps with that of Ptf1 in the VZ, warranting this brief foreword.

Ascl1 Labels the Cerebellar GABAergic Lineage While many studies have investigated the distribution and roles of Atoh1 in the cerebellar glutamatergic lineage, fewer studies have been devoted to analyzing GABAergic precursors born in the cerebellar VZ and to dissecting the roles of proneural genes in this context. In 2008, Zordan et al. (2008) published a systematic descriptive analysis of proneural gene expression at early stages of mouse cerebellar development. The results of this study established that at the onset of cerebellar neurogenesis, starting at about E11, the Ascl1 transcript becomes detectable by in situ hybridization in the VZ and presumptive NTZ. A similar distribution is observed at later stages, with the Ascl1 transcript occupying the entire thickness of the Ptf1a+ VZ all the way to its apical (ventricular) margin. Accordingly, the territories occupied by Ascl1 and Atoh1 are clearly complementary. The Ascl1 transcript remains confined to the VZ until E13.5. An additional study by Jane Johnson and coworkers (Kim et al. 2008), published 1 month later, reported the results of genetic fate mapping performed using two transgenic Ascl1-Cre lines, one of which expressed a tamoxifen-inducible Cre recombinase, CreER™ (Helms et al. 2005; Battiste et al. 2007), and two Cre-inducible reporter lines (Soriano 1999; Srinivas et al. 2001). The evidence produced in this elegant lineage analysis was in full agreement with the conclusions drawn by Zordan et al.: in particular, Ascl1+ progenitors are initially (E12.5) restricted to the cerebellar VZ and excluded both from the post-mitotic CTZ and from the rhombic-lip migratory stream. The locations of Ascl1+ and Atoh1+ progenitors are mutually exclusive, whereas a high degree of overlap was shown between Ptf1a+ and Ascl1+ progenitors, revealing that Ascl1 labels GABAergic neuronal progenitors. However, at later stages (E17.5), Ascl1+ progenitors were no longer confined to the VZ but were detected in a scattered pattern throughout the cerebellar primordium. Some of these cells coexpressed Ascl1 and Olig2, which at this stage decorates oligodendrocytes. In addition, the fate mapping analysis contained in this study revealed that Ascl1+ progenitors born either before E11.5 or after E13.5 give rise to the GABAergic components of the CN, whereas progenitors born between E11.5 and E13.5 are mainly fated to become PCs. Finally, when Ascl1+ progenitors are tagged by tamoxifen administration after E16, some of them acquire an oligodendroglial identity and localize in the prospective white matter. In the same study, no colocalization was ever scored between Ascl1+ progenitors and astrocyte-specific markers. Finally, a study authored by Marion Wassef and collaborators (Grimaldi et al. 2009) further refined the analysis of the role of Ascl1 in cerebellar neurogenesis, incorporating an description of the effects of Ascl1 gene disruption and overexpression. Regarding the distribution of Ascl1+ progenitors, Grimaldi et al. established that these precursors progressively delaminate out of the VZ to settle

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in prospective white matter first and cerebellar cortex next. By studying an Ascl1GFP transgenic mouse, they demonstrated that Ascl1+ progenitors give rise to interneurons positive for Pax2 and to oligodendrocyte precursors positive for Olig2. Conversely, glutamatergic neurons as well as astrocytes and Bergmann glia cells never expressed GFP. To clarify the role of Ascl1 in the generation of different cerebellar cell types, the authors analyzed Ascl1 null mice at E18.5. The loss of Ascl1 led to a dramatic reduction of Pax2+ and Olig2+ precursors, whereas astrocytic precursors, labeled by Sox9, were moderately increased in number. No major change was detected in PC development. Furthermore, to circumvent the perinatal lethality of Ascl1 null mice and study the effect of Ascl1 at later stages, the authors transplanted solid grafts obtained from E15.5 mutant- and wild-type cerebella into the cerebral cortex of newborn recipients. After 2 months, they analyzed the grafts, and, consistent with previous results, they found that they contained a reduced number of parvalbumin+ interneurons but a normal number of PCs. Finally, the authors resorted to a gain-of-function approach (in vivo electroporation of a GFP plasmid, stage E14.5) to determine whether oligodendrocytes and Pax2+ interneurons are lineally related in the cerebellum. After electroporation, cerebella were dissected and cultured for 6 days in vitro. By comparing the results of intraventricular vs. parenchymal electroporations, they concluded that most Ascl1 + oligodendrocytes do not originate from the cerebellar VZ. In addition, they electroporated an Ascl1-GFP vector into the cerebellar VZ. This led to an increased number of Pax2+ interneurons, to a reduced number of Olig2+ oligodendrocyte precursors, and to a complete absence of astroglial cells. This prompted them to conclude that Ascl1 overexpression pushes progenitors toward the Pax2 interneuron fate while suppressing the astrocytic fate. Taken together, the above evidence suggests that, in cerebellar neurogenesis, Ascl1 contributes to the GABAergic pool. It participates in GABA interneuron and CN neuron generation and in PC development. However, it is not required for PC specification, suggesting that, in this process, it may either be irrelevant or act redundantly with other VZ-specific proneural genes. When overexpressed at E14.5, Ascl1 promotes the GABA interneuron phenotype, suppressing the astrocytic fate.

Neurogenins in Cerebellar GABAergic Development Neurog1 and Neurog2 Are Expressed in the Ptf1a+ Ventricular Neuroepithelium As shown by Zordan et al. (2008), the Neurog2 transcript is first observed around E11 in CN neuron progenitors of the cerebellar primordium, whereas Neurog1 appears 1 day later, in a rostral region located between the isthmic organizer, labeled by Fgf8, and the territory marked by Ascl1. At E12.5, both Neurog1 (see also Salsano et al. 2007) and Neurog2 are present in the VZ but with a few differences

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in distribution: in the anterior cerebellum, Neurog1 is expressed at high levels in a region close to the midline, whereas Neurog2 is detected mostly in the lateral VZ. In posterior territories, the expression patterns of the two proneural genes overlap completely. Neurog1 and Neurog2 are adjacent and partially overlap with postmitotic domains labeled by Lhx1 and Lhx5, two genes that control PC differentiation (Zhao et al. 2007). This suggests that Neurog1 and Neurog2 are upregulated in progenitors that are undertaking the last cycle of cell division, to become postmitotic PC precursors. At E13.5 the differential anterior boundaries of Neurog1 and Neurog2 are maintained, although the transcript levels of both genes are downregulated. The authors conclude that Neurog1 and Neurog2 are mainly expressed in the cerebellar germinal epithelium that gives rise to GABAergic progenitors, while they are completely absent from the URL, the source of all glutamatergic cerebellar progenitors. Moreover, their expression patterns are similar but not totally overlapping, suggesting that they may contribute to the diversity of cerebellar GABA neurons and, possibly, PC subtypes.

Neurog1 Is Expressed in Cerebellar GABAergic Interneuron Progenitors In 2009, Doughty and coworkers published a lineage analysis in which, by using transgenic fate mapping, they described the mature cerebellar neurons deriving from Neurog1-positive cell fates in the developing mouse cerebellum (Lundell et al. 2009) and extended their analysis of Neurog1 expression to include late embryonic and postnatal cerebellar development. At E14–E20, Neurog1 is present in Ptf1a+ neurons, but it is excluded from the URL and EGL. Moreover, at P7, it colocalizes with Ptf1a and BrdU in the cerebellar white matter. This suggests that Neurog1 is expressed in early GABAergic interneuron precursors that, shortly after birth, migrate from the white matter to reach their destination in the cortex. To test their hypothesis, the authors used two artificial chromosome (BAC)-reporter mice imported from the NIH GENSAT consortium (Rockefeller University, New York) to study short-term and long-term Neurog1-positive cell fates. The first to be characterized was the Neurog1-EGFP transgenic mouse line, previously used to map short-term cell fates in the developing thalamus (Vue et al. 2007). Their results supported the hypothesis that Neurog1 is expressed in Pax2+ interneuron progenitors. Surprisingly, they could not reveal any fluorescence in PC neurons. A recent study by Jane Johnson and coworkers, by genetic inducible fate mapping, confirmed the notion that, in the cerebellar primordium, the Neurog1+ lineage gives rise to PCs and to GABAergic interneurons (Kim et al. 2011). This notion was further confirmed in fine detail by the Doughty group, demonstrating a close correlation between the timing of tamoxifen administration and the cell lineage labeled, including CN GABA interneurons and different GABA interneurons of the cerebellar cortex, with a clear inside-out progression. This work showed that Purkinje cells express Neurog1 around the time they become post-mitotic, while GIFM labeled both mitotic and post-mitotic interneurons (Obana et al. 2015).

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Finally, a genome-wide analysis of gene expression was conducted in the cerebellar primordium of E11.5 Neurog1 null mice to identify the Neurog1 transcriptome in the developing cerebellum. This screen identified 117 genes differentially enriched in Neurog1 / versus control sample sets with a high presence of gene sets enriched for functions in nervous system development. An in silico analysis of promoter regions identified high probability Neurog1 regulatory (E-box) binding sites in many of the differentially expressed genes, sometimes accompanied by Pax6 binding motifs in 25 of these 94 promoters, suggesting a Neurog1-Pax6 cross talk in the activation of some genes (Dalgard et al. 2011). In summary, Neurog1 is expressed in progenitors giving rise to PCs and GABAergic interneurons of the cerebellar cortex and nuclei. This gene appears to regulate a large number of downstream genes controlling development. A detailed analysis of Neurog1 null cerebella is required to define the specific role of this gene in the ontogeny of the cerebellar territory.

Neurog2 Labels the PC Lineage and Regulates PC-Progenitor Cell-Cycle Progression and Dendritogenesis Finally, a study by Florio et al. (2012) has addressed some of the roles played by neurogenin 2 in cerebellar development. As mentioned, this Atonal homolog is expressed in the cerebellar VZ: at E12.5, its expression domain roughly coincides with those of Ptf1a and Ascl1 (Zordan et al. 2008). Florio et al. replaced the only coding exon of Neurog2, namely, exon 2, with the Cre-ERT2 fusion gene (Imai et al. 2001). In this way, they generated a Neurog2-null knock-in allele expressing a tamoxifen-inducible Cre in a pattern faithfully recapitulating the Neurog2 expression domain. Thus, they could use the expression of the human estrogen receptor as a proxy for Neurog2 gene transcription. The gene is expressed at low levels in proliferating, neurogenic radial glia of the cerebellar VZ, in a pattern complementary to that of the Notch intracellular domain. By cumulative S-phase labeling with thymidine analogs, Florio et al. established for the first time that the duration of the cell cycle at E12.5, corresponding to the peak of Purkinje cell neurogenesis, is ~14 h. By calculating the duration of each cell cycle stage, they determined that, in the VZ, Neurog2 is expressed mostly, albeit not exclusively, in G1 progenitors. Embryos homozygous for the null allele progressed slowly through the cell cycle, stalling mainly in early G1, leading to an overall reduction of the mature cerebellar volume. However, ectopic overexpression of Neurog2 induced cell cycle withdrawal and precocious differentiation. Taken together, these results are compatible with a role for oscillating Neurog2 protein levels in regulating and promoting cell cycle progression and with the notion that VZ cells upregulating Neurog2 prior to the G1 restriction point exit the cell cycle and start delaminating to undertake neuronal differentiation. By GIFM these authors showed that a large majority of Neurog2 progenitors give rise to the PC lineage, with a minority of them contributing to the VZ-derived component of CN, mostly projection Smi32+ projection neurons, likely representing nucleo-olivary ones. Only in rare cases did cycling Neurog2+

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progenitors give rise to Pax2+ interneurons or S100β+ astroglia. When transplanted heterochronically into the postnatal cerebellum, Neurog2+ cerebellar progenitors overwhelmingly gave rise to well-differentiated PCs. In addition, these authors found that Neurog2 plays an important role in the early stages of dendritogenesis, that is while this process is for the most part cellautonomous, progressing independently of the influence of GCs. Neurog2-null PCs develop stunted and poorly branched dendrites since early stages of dendritogenesis. This important evidence was supported by the results of loss- and gain-of-function experiments alike. Neurog2 is expressed by cycling progenitors cell autonomously fated to become PCs, even when transplanted heterochronically. During cerebellar development, Neurog2 is expressed in G1 phase by VZ progenitors poised to exit the cell cycle. In the absence of Neurog2, both cell-cycle progression and neuronal output are significantly affected, leading to an overall reduction of the mature cerebellar volume. Although PC fate identity is correctly specified, the maturation of their dendritic arbor is severely affected in the absence of Neurog2. Thus, Neurog2 is a regulator of PC development and maturation.

Conclusion Proneural genes are expressed at crucial stages in cerebellar neurogenesis. Their ascertained roles include the regulation of neuronal fate determination, neuronal type specification, terminal differentiation, and GC clonal expansion. Under all those circumstances, they may be part of as yet unclarified combinatorial codes that integrate their function with that of many other genes, particularly those encoding other transcription factors. Further studies are required to dissect the molecular machinery in which they function, in cooperation with regulatory cascades controlling positional identity, fate specification, and differentiation. Acknowledgments Giacomo Consalez’ group has been supported by grant GGP13146 from the Italian Telethon.

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Zones and Stripes: Development of Cerebellar Topography Lauren N. Miterko, Roy V. Sillitoe, and Richard Hawkes

Contents The Architecture of the Adult Cerebellar Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From Allocation to Rhombomere 1 to Two Germinal Epithelia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Purkinje Cell Birth Date, Phenotype, and Location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From Ventricular Zone to Clusters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Purkinje Cell Subtype Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From Embryonic Clusters to Adult Stripes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Afferent Topography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climbing Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mossy Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interneurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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L. N. Miterko Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, Houston, TX, USA R. V. Sillitoe Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA Program in Developmental Biology, Baylor College of Medicine, Houston, TX, USA Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, Houston, TX, USA e-mail: [email protected] R. Hawkes (*) Department of Cell Biology and Anatomy Genes and Development Research Group, Hotchkiss Brain Institute, The University of Calgary, Calgary, AB, Canada e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_3

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Cerebellar Topography and Circuit Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From Zones-And-Stripes to Complex Motor Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Cerebellar architecture is organized around the Purkinje cell. Purkinje cells in the mouse cerebellum come in many different subtypes, organized first into four transverse zones and then further grouped into hundreds of reproducible topographical units – stripes. Stripes are identified by their functional properties, connectivity, and expression profiles. The molecular pattern of stripes is highly reproducible between individuals and is conserved through evolution. Pattern formation in the cerebellar cortex is a multistage process that begins with the generation of the Purkinje cells in the ventricular zone (VZ) of the fourth ventricle. During this stage, or shortly after, Purkinje cell subtypes are specified toward specific positions. Purkinje cells migrate from the VZ to form an array of clusters that form the framework for cerebellar topography. At around birth, these clusters begin to disperse, triggered by Reelin signaling pathway proteins, to form the adult stripe array. The chapter will begin with a brief overview of adult cerebellar topography, primarily focusing on the mouse cerebellum, and then discuss the cellular and molecular mechanisms that establish these remarkable patterns. Considering how functionally diverse the cerebellum is despite its conserved organization of patterns, this chapter will end exploring how stripes might contribute to neuronal activity and the execution of cerebellar-dependent behaviors. Keywords

Cerebellum · Purkinje cell · Patterning · Stripes · Zones · Topography

The Architecture of the Adult Cerebellar Cortex The adult mouse cerebellum is shown in Fig. 1, immunoperoxidase stained for the antigen zebrin II (Brochu et al. 1990: zebrin II. aldolase C (AldoC) – Ahn et al. 1994). There are two subsets of Purkinje cells: zebrin II-immunopositive (zebrin II+) and zebrin II-immunonegative (zebrin II-). Purkinje cells in each subset are aligned to form an alternating array of parasagittal stripes (Brochu et al. 1990; Sillitoe and Hawkes 2002). Stripes are reproducible between individuals and symmetrically distributed about the midline (Hawkes et al. 1985; Hawkes and Leclerc 1987; Brochu et al. 1990). Zebrin II+ stripes are numbered as P1+ to P7+ starting from the midline and going laterally, and the intervening zebrin II- stripes are numbered with reference to the medial zebrin II+ stripe (i.e., P1- lies immediately lateral to P1 +, etc.). In the vermis, four transverse domains in the anterior–posterior axis are identified by zebrin II expression: the striped anterior zone (AZ: ~lobules I–V), the

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Fig. 1 The mouse cerebellum is organized into an array of transverse zones and parasagittal stripes. (a) Adult mouse cerebellum immunoperoxidase stained in whole mount with anti-zebrin II/aldolase C. (b) Schematic illustrating the pattern of zebrin II in the mouse cerebellum. (c) Embryonic day (E) 15 mouse cerebellum stained in whole mount for alkaline phosphatase (hAP) to detect the expression of an L7/Pcp2-hAP transgene (see Sillitoe et al. 2009 for details). (d) Schematic illustrating the pattern of embryonic Purkinje cell clusters as revealed by hAP staining in L7/ Pcp2-hAP transgenic mice. Abbreviations: AZ anterior zone, CZ central zone, PZ posterior zone, NZ nodular zone, Sim simplex, Fl/Pfl flocculus/paraflocculus, Pmd paramedian, Cop copula pyramidis. Lobule numbers are indicated by Roman numerals, and stripes are labeled with Arabic numerals (panels C and D were adapted from Sillitoe et al. 2009)

uniformly zebrin II+ central zone (CZ: ~lobules VI–VII), the striped posterior zone (PZ: ~lobules VIII–dorsal IX), and the uniformly zebrin II+ nodular zone (NZ: ~lobules IX ventral and X: Ozol et al. 1999). A similar alternation of zones is seen in the hemispheres (Sarna et al. 2006). Numerous molecular markers are co-localized with either the zebrin II+ or zebrin II- Purkinje cells. For example, the GABA-B receptor is expressed in the zebrin II+ population (Chung et al. 2008a) and phospholipase C(PLC) ß4 in the zebrin IIpopulation (Sarna et al. 2006). However, detailed comparisons between zebrin II expression and other antigenic markers reveal that the parasagittal stripes are much more elaborate than the expression of any one antigen indicates. For example, comparisons between zebrin II and the glycoprotein epitope HNK1 reveal that although these two antigens are largely co-localized (Eisenman and Hawkes 1993),discrete Purkinje cell populations in several lobules can express these antigens separately (Marzban et al. 2004). Similarly, expression of the 25 kDa small heat shock protein (HSP) 25 reveals parasagittal Purkinje cell heterogeneity in both the CZ and NZ – areas in which zebrin II is homogeneously expressed in all Purkinje cells (Armstrong et al. 2000). As a result, the adult cerebellar cortex of the mouse can

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reliably and reproducibly be subdivided into several hundred distinct regions, each typically comprising no more than a few hundred Purkinje cells (e.g., reviewed in Hawkes 1997; Sarna and Hawkes 2003; Apps and Hawkes 2009). Stripe and zone compartments influence all aspects of cerebellar biology. They are highly reproducible between individuals, conserved through evolution (AZ – Sillitoe et al. 2005; PZ – Marzban and Hawkes 2011), and insensitive to experimental manipulation (reviewed in Larouche et al. 2006). Afferent topography is also striped. Zone and stripe boundaries restrict afferent terminal fields (e.g., climbing fibers, spinocerebellar mossy fibers, and trigeminocerebellar mossy fibers that relay somatosensory signals terminate mainly in zebrin II- stripes throughout the AZ and into rostral lobule VI, where the AZ interdigitates with the CZ, e.g., reviewed in Voogd and Ruigrok 2004) into compartments that are reflected by functional cerebellar maps (e.g., Chockkan and Hawkes 1994; Hallem et al. 1999; Ebner et al. 2012). Many cerebellar mutant phenotypes are restricted by zone and stripe boundaries. For example, swaying (Thomas et al. 1991), rostral cerebellar malformation/ Unc5h3 (Napieralski and Eisenman 1996), cerebellar deficient folia (Cook et al. 1997; Beierbach et al. 2001; Park et al. 2002), and meander tail (Ross et al. 1990) all exhibit deficits restricted primarily to the AZ; the gain of function δ2 glutamate receptor mutant lurcher (Lc/+) has a zebrin II expression domain during development that is restricted at the CZ/PZ boundary (Tano et al. 1992); and the weaver mouse exhibits a Purkinje cell ectopia that is primarily restricted to the CZ (Eisenman et al. 1998; Armstrong and Hawkes 2001). Finally, most examples of Purkinje cell death due to mutation or insult show restriction to parasagittal stripes (reviewed in Sarna and Hawkes 2003; Duffin et al. 2010; Armstrong et al. 2011; Williams et al. 2007; Ragagnin et al. 2017). How does this remarkable zone-and-stripe pattern develop?

From Allocation to Rhombomere 1 to Two Germinal Epithelia In mice, the cerebellar primordium arises between E8.5 and E9.5 entirely from within the metencephalon (Wassef and Joyner 1997; Zervas et al. 2004). The boundary between Otx2 and Gbx2 expression domains initially demarcates the border between mes- and metencephalon and the location of the isthmic organizer, a tissue patterning structure that promotes interactions between cerebellar patterning genes (reviewed in Zervas et al. 2005). Several studies have examined putative allocation events during this period, which generate the Purkinje cell population: the general conclusion is that the entire Purkinje cell population in the adult arises from ~100 to 150 precursors, likely specified at around E7–E8 (Baader et al. 1996; Mathis et al. 1997; Hawkes et al. 1998; Watson et al. 2005), although there is no evidence that these are restricted to a particular Purkinje cell subset. The early stages of cerebellar development are reviewed in detail in ▶ Chap. 6, “Specification of Granule Cells and Purkinje Cells.” This chapter will only consider mechanisms pertinent to the origin of stripe patterning (for other reviews, see Hawkes and Gravel 1991; Hawkes and Eisenman 1997; Herrup and Kuemerle 1997; Oberdick et al.

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1998; Armstrong and Hawkes 2000; Larouche and Hawkes 2006; Sillitoe and Joyner 2007; White and Sillitoe 2013). The cerebellum houses two distinct germinal matrices: the dorsally located rhombic lip and the ventrally located ventricular zone (VZ) of the fourth ventricle. Genetic fate mapping studies show that the rhombic lip gives rise to glutamatergic projection neurons of the cerebellar nuclei, cerebellar granule cells, and unipolar brush cells (Wingate 2001; Machold and Fishell 2005; Wang et al. 2005; Englund et al. 2006). The VZ gives rise to GABAergic components of the cerebellum including all GABAergic interneurons and all Purkinje cells: all cerebellar GABAergic neurons derive from progenitors expressing Ptf1a, which is required for their specification (Hoshino et al. 2005; Pascual et al. 2007). However, the VZ is not homogenous but divided by gene expression into numerous overlapping molecular domains (e.g., Chizhikov et al. 2006; Zordan et al. 2008). This issue is discussed in ▶ Chap. 15, “Genes and Cell Type Specification in Cerebellar Development.”

Purkinje Cell Birth Date, Phenotype, and Location Purkinje cells undergo terminal mitosis in the VZ between E10 and E13 in the mouse (Miale and Sidman 1961; Hashimoto and Mikoshiba 2002). Birthdating studies, using incorporation of either adenovirus (Hashimoto and Mikoshiba 2002), bromodeoxyuridine (e.g., Feirabend et al. 1985; Karam et al. 2000; Larouche and Hawkes 2006), or genetic fate mapping (Sudarov et al. 2011), reveal a direct correlation between the birthdate of a Purkinje cell and its final mediolateral location, suggesting that Purkinje cells acquire positional information at or shortly after their terminal differentiation in the VZ. It is not known whether positional information and phenotype are specified at the same time. Postmitotic Purkinje cells migrate dorsally out of the VZ, presumably along radial glia processes (Morales and Hatten 2006), and stack in the cerebellar anlage with the earliest-born Purkinje cells located most dorsally.

From Ventricular Zone to Clusters After migration from the VZ, the Purkinje cells undergo a complex and poorly understood reorganization (E14–E18), possibly involving cell-signaling molecules including cadherin (Redies et al. 2010) and Eph-ephrin (Karam et al. 2000), to yield a stereotyped array of early clusters with a range of molecular phenotypes. The Purkinje cell migration pathways are carefully described in Miyata et al. (2010) (see also ▶ Chap. 9, “Purkinje Cell Migration and Differentiation”). During this same period, Purkinje cell clusters begin to express a variety of early markers that reveal both rostrocaudal and mediolateral compartments (e.g., calbindin, Wassef et al. 1985; cyclic GMP-dependent protein kinase, Wassef and Sotelo 1984; HSP25, Armstrong et al. 2001; neurogranin, Larouche et al. 2006; cadherins, reviewed in Redies et al. 2010; homeobox genes, including En1, En2, Pax2, and Wnt17b,

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Bally-Cuif et al. 1992; Millen et al. 1995; L7/pcp2-LacZ, Smeyne et al. 1991; Oberdick et al. 1993; Ozol et al. 1999; OMP-LacZ, Nunzi et al. 1999; inositol 1,4,5-trisphosphate (IP3) receptor (IP3R)nls-LacZ, Furutama et al. 2010; etc.). Detailed comparisons of various other early markers are not comprehensive but such data as are available suggest that they all fit into a common schema.

Purkinje Cell Subtype Specification When is Purkinje cell stripe phenotype specified? In order to answer this, many attempts have been made to alter Purkinje cell phenotype, which have almost always been ineffective. First, surgical interventions in the neonate have no effect on the expression of compartmentation markers (e.g., zebrin I, Leclerc et al. 1988; L7/pcp2LacZ, Oberdick et al. 1993; HSP25, Armstrong et al. 2001). Secondly, in cerebellar explants taken as early as E13 and placed either in slice culture (Oberdick et al. 1993; Seil et al. 1995; Rivkin and Herrup 2003; Furutama et al. 2010) or transplanted (Wassef et al. 1990), Purkinje cell subtypes apparently develop normally. Finally, ectopic Purkinje cells in various mouse mutants develop their normal adult phenotypes (e.g., reeler, Edwards et al. 1994; disabled, Gallagher et al. 1998; weaver, Armstrong and Hawkes 2001). These data suggest that cell autonomous mechanisms early in cerebellar development direct the specification of Purkinje cell phenotypes toward distinct subtypes. The only experimental manipulation that is known to alter Purkinje cell subtype is deletion of Early B-cell Factor 2 (Ebf2, Croci et al. 2006; Chung et al. 2008b). In the adult cerebellum, Ebf2 expression is restricted to the zebrin II- Purkinje cell subset. When Ebf2 is deleted, a complex cerebellar phenotype results, but in particular a prominent subset of zebrin II- Purkinje cells express zebrin II+ markers in addition to the normal zebrin II- ones (Croci et al. 2006; Chung et al. 2008b). This suggests that EBF2 is a repressor of the zebrin II+ phenotype. The role of Ebf2 is discussed in detail in ▶ Chap. 2, “Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip.”

From Embryonic Clusters to Adult Stripes Starting at around E18, the embryonic clusters begin to disperse. This occurs at the same time as cerebellar lobules begin to exhibit extensive morphogenetic changes (Sudarov and Joyner 2007). The two processes are coupled – if Purkinje cell dispersal is blocked, then lobulation is prevented, and the cerebellum is lissiform – but the mechanistic relationship is unknown. In contrast to the relationship between cluster dispersal and lobules, a recent genetic study demonstrated that Purkinje cell stripe patterning and foliation can be uncoupled and En1/2 controls each process independently (Sillitoe et al. 2008b). Whether cluster dispersal is the passive concomitant of granular layer maturation and lobule formation or requires active Purkinje cell migration is not known. Whatever the case, because cluster dispersal

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occurs primarily in the rostrocaudal plane – the rostrocaudal length of the mouse vermis increases ~25-fold from E17 to P30, while the width of the vermis increases only ~1.5
during the same time period (Gallagher et al. 1998) – the clusters elongate into long parasagittal stripes. About 50 embryonic clusters are thought to produce the adult pattern of stripes (Fujita et al. 2012). The transformation of embryonic Purkinje cell clusters into mature stripes is mediated by Reelin signaling (Tissir and Goffinet 2003). The external granular layer (EGL) secretes Reelin starting around E17 (D’Arcangelo et al. 1997; Jensen et al. 2002). Reelin binds two receptors on Purkinje cells – the apolipoprotein E receptor 2 (Apoer2) and the very low-density lipoprotein receptor (VLDLR, Trommsdorff et al. 1999). Binding induces receptor clustering (Strasser et al. 2004) and activates an intracellular protein kinase cascade leading to tyrosine phosphorylation of the docking protein Disabled-1 (mdab-1, Howell et al. 1997; Goldowitz et al. 1997; Sheldon et al. 1997). Downstream of Disabled-1 are interactions with Src and Fyn cytoplasmic tyrosine kinases and with phosphatidylinositol 3-kinase (Bock and Herz 2003; Kuo et al. 2005). The cyclin-dependent kinase (cdk)5 signaling pathway has also been implicated in Reelin signaling as Purkinje cells in cdk5 pathway mutants phenocopy the reeler mouse (e.g., Ohshima and Mikoshiba 2002). The end result is thought to be a drop in Purkinje cell-cell adhesion, thereby allowing the early clusters to disperse. Accordingly, mutations in the Reelin pathway affect all Purkinje cells and result in the complete failure of cluster dispersal and global Purkinje cell ectopia. However, deletion of either of the Reelin receptors, Apoer2 and Vldlr, results in selective, specific Purkinje cell ectopias (Larouche et al. 2008): in Apoer2/ mice, ectopic Purkinje cells are largely restricted to the zebrin II- population of the anterior vermis; in contrast, Vldlr/ mice have a much larger population of ectopic Purkinje cells that includes members from both zebrin II+/ phenotypes, and HSP25 immunoreactivity reveals that a large portion of ectopic zebrin II+ cells is destined to become stripes in lobules VI–VII. Finally, a small, very specific population of ectopic zebrin II- Purkinje cells is observed in animals heterozygous for both receptors (Apoer2þ/: Vldlrþ/: no ectopia is present in mice heterozygous for either receptor alone). Despite the known importance of the Reelin pathway in regulating Purkinje cell dispersal, other genetic cues are also likely required. For example, the HSP25+/ zebrin II+ Purkinje cell subset in the CZ is selectively ectopic in weaver mutants (Armstrong and Hawkes 2001). This model suggests a direct genealogical relationship between embryonic clusters and adult stripes. This is not straightforward to establish because the parasagittal pattern of early antigens tends to disappear perinatally, either because they are downregulated (e.g., neurogranin, Larouche et al. 2006) or because they become expressed uniformly by all Purkinje cells (e.g., calbindin, Wassef et al. 1985), while most adult stripe antigens are not expressed in the mature pattern of stripes until ~P15 (e.g., zebrin II, Lannoo et al. 1991; HSP25, Armstrong et al. 2001). While the basic cerebellar architecture seems to be laid down in the embryo, the maturation of stripe phenotypes is not complete until P15 or so. For example, zebrin II is first expressed at around P6, but by P10–P12 all Purkinje cells express zebrin II. From P12 to P15 zebrin II is downregulated in the zebrin II- population to reveal the

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mature stripe array (Brochu et al. 1990; Lannoo et al. 1991; Rivkin and Herrup 2003). The molecular mechanism that mediates zebrin II downregulation is not known. However, recent studies have identified markers that bridge between clusters to stripes (e.g., Larouche et al. 2006; Marzban et al. 2007; Sillitoe et al. 2009; White and Sillitoe, 2013). The current hypothesis is that embryonic clusters are the precursors of the adult stripes. While the hypothesis implies a direct relationship, experimental evidence indicates that it is not at all simple. On the one hand, current maps suggest about 20 different clusters but 10 times as many stripes in the adult. Where does the additional complexity come from? While the apparent lack of complexity could merely be a reflection of an underdeveloped toolkit, the internal consistency of the different cluster antigens does not support this view: all known embryonic markers conform to a common schema with ~10 clusters on each side of the cerebellum. Therefore, there may be secondary patterning stages, perhaps associated with the transformation of clusters into stripes, which takes the embryonic broad-stroke pattern and elaborates it into a more complex adult form. Perhaps the 20 clusters are partitioned into 50 during postnatal development before these go on to form the adult stripes (Fujita et al. 2012). On the other hand, there is evidence that some stripes in the adult result from the coalescence of multiple clusters (e.g., the P1stripe in the AZ is the fusion of three distinct clusters in the embryo, Ji and Hawkes 1994; Marzban et al. 2007). Finally, genetic fate mapping using an L7/pcp2-CreER allele supports the hypothesis that at least some embryonic clusters contribute Purkinje cells to multiple stripes in the adult cerebellum (Sillitoe et al. 2009).

Afferent Topography It is generally believed that the Purkinje cell map serves as a scaffold around which other cerebellar structures are organized – both afferent projections (climbing fibers and mossy fibers, reviewed in Sotelo 2004) and interneurons including granule cells, Golgi cells, and unipolar brush cells (e.g., Chung et al. 2009; reviewed in Apps and Hawkes 2009).

Climbing Fibers In the adult, climbing fibers project from neurons in the contralateral inferior olivary complex and terminate on Purkinje cell dendrites, with each Purkinje cell receiving input from a single climbing fiber. Each subnucleus in the inferior olive projects to a limited number of Purkinje cell stripes (e.g., Voogd and Ruigrok 2004; Sugihara and Quy 2007; Apps and Hawkes 2009). The cerebellar projection neurons of the inferior olive are born in the caudal rhombic lip and migrate ventrally in the submarginal stream (Sotelo and Chédotal 2005). Similar to their target Purkinje cells, the fate, survival, differentiation, and migration of inferior olivary neurons are dependent on the function of Ptf1a (Yamada et al. 2007). Climbing fibers enter the cerebellar anlage at ~E15 and immediately terminate within specific Purkinje cell clusters (e.g., Chédotal and Sotelo

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1992; Paradies et al. 1996). During Purkinje cell cluster dispersal into stripes, the climbing fibers are presumably carried along with them, thereby creating parasagittal terminal fields that align with the Purkinje cell stripes (Gravel et al. 1987; Apps and Hawkes 2009). In the neonatal cerebellum, each Purkinje cell receives input from several climbing fibers. This is converted to the adult mono-innervation pattern by the elimination of all but one (reviewed in Cesa and Strata 2009; Carrillo et al. 2013). However, it appears that the sculpting of climbing fiber innervation does not contribute significantly to the refinement of cerebellar stripe topography (Crépel 1982; Sotelo et al. 1984). Sotelo and colleagues have argued that matching gene expression domains between the cerebellum and inferior olive contain cues that guide the formation of a precise topographical projection map (Wassef et al. 1992; Chédotal et al. 1997; Sotelo and Chédotal 2005). In support of this model, Nishida et al. (2002) demonstrated that overexpression of Ephrin-A2 by using retroviral vectors disrupts the general topography of the olivocerebellar projection. Moreover, inferior olivary axons expressing high Eph receptor activity are prevented from entering into domains with ectopic Ephrin-A2 ligand expression (Nishida et al. 2002). Although the parasagittal band topography of climbing fibers was never examined, these experiments identify the Eph/Ephrin signaling pathway as likely to provide positional information during afferent/target matching.

Mossy Fibers The other major afferents of the cerebellum are mossy fibers, which arise from multiple sources and terminate in synaptic glomeruli on the dendrites of granule cells. Mossy fibers are also restricted by transverse zone and parasagittal stripe boundaries (e.g., Gravel and Hawkes 1990; Ji and Hawkes 1994; Armstrong et al. 2009; Sillitoe et al. 2010; Ruigrok 2011; Gebre et al. 2012). In some cases, mossy fiber terminal fields align with specific subsets of stripes (e.g., Armstrong et al. 2009), and in others they split Purkinje cell stripes into smaller units (e.g., cuneocerebellar/spinocerebellar terminal fields in the P1- stripes of the AZ, Ji and Hawkes 1994). The major features of the development of mossy fiber topography are similar to that for climbing fibers. The earliest mossy fibers enter the cerebellar anlage by around E12 (rat, Ashwell and Zhang 1992, 1998). Mossy fiber topography is established before most granule cells are formed (Arsenio-Nunes and Sotelo 1985) and is accompanied by direct contacts between mossy fiber growth cones and Purkinje cells in embryonic and early postnatal clusters (Mason and Gregory 1984; Takeda and Maekawa 1989; Grishkat and Eisenman 1995; Kalinovsky et al. 2011; Sillitoe 2016). This model is consistent with observations from mutant animals with agranular cerebella, in which the spinocerebellar mossy fiber topography is organized into bands despite the absence of a normal mossy fiber-granule cellPurkinje cell pathway (e.g., Arsenio-Nunes and Sotelo 1985; Arsenio-Nunes et al. 1988; Eisenman and Arlinghaus 1991), and with the data from neonatal lesion studies demonstrating that there does not seem to be a significant role for

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competition between mossy fiber sources in sculpting terminal fields (Ji and Hawkes 1995). The molecular basis of mossy fiber terminal field restriction is not well understood, but deletion of either the retinoic acid receptor-related orphan receptor alpha (RORalpha: Arsenio-Nunes et al. 1988) or En1/2 (Sillitoe et al. 2010) or overexpression of En2 in Purkinje cells (Baader et al. 1999) results in mossy fiber targeting defects. As for climbing fibers, mossy fiber terminals are presumed to disperse along with the Purkinje cells as embryonic clusters transform into stripes. Then postnatally, as granule cells are born in the external granular layer and descend past the Purkinje cells to the granular layer, the mossy fiber terminals displace from the Purkinje cells and synapse with differentiated granule cells. As a result, the mossy fiber terminal fields become aligned with the overlying Purkinje cell stripes. Although there is evidence that the process of establishing afferent compartmentation is genetically controlled (Sillitoe et al. 2010), the refinement of the map may be in part dependent on neuronal activity (Tolbert et al. 1994; White et al. 2014).

Interneurons Several cerebellar inhibitory interneurons show evidence of restriction by the Purkinje cell scaffold. First, Golgi cell dendrites are restricted by Purkinje cell stripe boundaries (Sillitoe et al. 2008a). Second, subsets of unipolar brush cells are associated with particular adult stripes (Chung et al. 2009; Lee et al. 2015). Models have been proposed by which both patterns of restriction involve mechanisms similar to those that organize mossy fiber afferent growth cones. Both Golgi cells and unipolar brush cells are thought to intermingle with Purkinje cells at the embryonic cluster stage. Hence, as the Purkinje cell clusters disperse, the interneurons become restricted to a particular stripe. Next, and as the granule cells form, the Golgi cells displace from the Purkinje cells to the neighboring granule cell axons, and the unipolar brush cells displace to the underlying granular layer, where mossy fibers contact them and they in turn synapse with granule cells and other unipolar brush cells (Mugnaini et al. 2010). Granule cells are born in the external granular layer (EGL), a germinal epithelium that forms from the rhombic lip and spreads to cover the cerebellar surface. Postmitotic granule cells migrate into the cerebellar anlage, following Bergmann glial guides, for 20–30 days, to create the adult granular layer (reviewed in Sillitoe and Joyner 2007). The EGL of the developing cerebellum and the granular layer of the adult cerebellum are subdivided by transverse boundaries revealed by lineage tracing, gene expression patterns, or through the consequences of genetic mutations. Several patterns of granular layer and/or EGL gene expression reveal transverse expression boundaries (e.g., reviewed in Hawkes et al. 1999), one aligned with the AZ/CZ boundary (~lobule V–VI) and another at the PZ/NZ boundary (in lobule IX: reviewed in Ozol and Hawkes 1997). In addition, mRNA analysis reveals a complex map of Fgf receptor and ligand expression in the EGL and granular layer (Yaguchi

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et al. 2009). These zonal relationships may reflect either epigenetic interactions with Purkinje cells or distinct cell autonomous effects. It is likely that both occur. From the spatial distribution of genotypes in embryonic stem cell chimeras, it was concluded that the cerebellar granular layer derives from two distinct precursor pools on either side of a lineage boundary within the rhombic lip (Hawkes et al. 1999). This is consistent with previous chimera studies, which also suggested that granule cells across the AZ/CZ and PZ/NZ boundaries have separate developmental origins (e.g., Goldowitz 1989). Additional evidence for a multiple origin of the EGL comes from studies of scrambler (Goldowitz et al. 1997) and disabled (Gallagher et al. 1998) mutants in which there is an incomplete fusion of the anterior and posterior granular layers in lobule VI leaving distinct, overlapping anterior and posterior leaflets. Finally, by using a Math1CreER allele, Machold and Fishell (2005) demonstrated by genetic fate mapping that granule cell progenitors are destined to populate specific anterior–posterior zones. For example, lineages marked at E12.5 selectively populate the AZ, whereas those marked at E15.5 populate all but the NZ. Together, these data suggest that the allocation of cells to specific EGL compartments may be dependent on spatial and temporal regulation of cellular movements and gene expression. It is difficult to imagine that the striped expression patterns in the granular layer are generated by the differential migration of EGL lineages. For example, neuronal nitric oxide synthase (nNOS – or its surrogate nicotinamide adenine dinucleotide phosphate (NADPH)-diaphorase) is expressed in the adult granular layer in stripes that align with Purkinje cell stripes (Hawkes and Turner 1994). NADPHd/nNOS activity is first detected at P3. During the first postnatal week of development, the granular layer expresses nNOS uniformly (Schilling et al. 1994). Subsequently, clusters of granule cells begin to suppress their expression of nNOS, and from this, a new heterogeneous pattern of nNOS expression emerges that persists into adulthood (Yan et al. 1993; Schilling et al. 1994; Hawkes and Turner 1994). In such cases, it seems more plausible that differential gene expression is induced by the local Purkinje cell environment or by the input from mossy fiber stripes (Schilling et al. 1994). However, the migration of differentiated granule cells within parasagittal “raphes” could provide a physical mechanism that supports the segregation of granule cells into different topographic domains as they proceed toward the internal granular layer (Lin and Cepko 1998; Karam et al. 2001).

Cerebellar Topography and Circuit Function It is evident that Purkinje cells are central to cerebellar topography. Purkinje cells contact or communicate with climbing fibers, mossy fibers, and granule cells throughout development to organize the cerebellar cortex into distinct domains. Given the structural role Purkinje cells have, it is not surprising that they are also vital for cerebellar function. Purkinje cells serve as the sole output of the cerebellar cortex and project directly to cerebellar nuclei neurons to control the rate and pattern of cerebellar output (Chaumont et al. 2013; Witter et al. 2013; White et al. 2014).

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This cortico-nuclear projection is also compartmentalized (Hawkes and Leclerc 1986; Sugihara et al. 2009) raising the possibility that cerebellar function depends on an interplay between extrinsic and intrinsic Purkinje cell factors.

From Zones-And-Stripes to Complex Motor Behaviors At first glance, the cerebellar circuit is organized rather simplistically: structurally identical circuits comprised of Purkinje cells, cerebellar nuclei neurons, afferent inputs, and interneurons are reiterated throughout its entirety. However, the presence of evolutionarily conserved zones-and-stripes raises the possibility that patterning is important for functional compartmentalization, information processing, and the execution of behaviors (Attwell et al. 1999; Horn et al. 2010; Mostofi et al. 2010; Graham and Wylie 2012). This hypothesis is especially intriguing since stripe and zone representations can vary with ecological niche (Corfield et al. 2016), which is perhaps a reflection of species-related functional specializations (tenrec, Sillitoe et al. 2003; star-nosed mole, Marzban et al. 2015). Moreover, severe motor deficits develop in disease models where zone formation is delayed or stripe boundaries are left unrefined (Sarna and Hawkes 2003; Strømme et al. 2011; White et al. 2014, 2016). One reason for why stripes may drive cerebellar function is because Purkinje cells in different stripes have intrinsically different molecular profiles and synaptic properties, which in turn influence learning and behavior (Furuta et al. 1997; Nagao et al. 1997; Dehnes et al. 1998; Mateos et al. 2001; Wadiche and Jahr 2005; Kano et al. 2008; Paukert et al. 2010; Wang et al. 2011). For example, zebrin II+ Purkinje cells are enriched for mGluR1 at parallel fiber synapses and neuronal glutamate transporter (EAAT4) in their cell bodies, dendrites, and spines. Due to increased expression of mGluR1, upon parallel fiber and climbing fiber stimulation, “long latency patches,” or regions of increased Ca2+ release, form at zebrin II+ parallel fiber–Purkinje cell and zebrin II+ climbing fiber–Purkinje cell synapses. These molecular differences are thought to support the compartmental regulation of synaptic plasticity (Wadiche and Jahr 2005; Paukert et al. 2010; Wang et al. 2011). It is interesting that several proteins that are expressed in stripes are required for the expression of long-term depression at parallel fiber – Purkinje cells synapses (Hawkes 2014). Despite these advances in understanding the heterogeneous expression of plasticity, it is only recently that we have begun to appreciate how cellular function might support these differences. Single unit extracellular recordings were used to show that zebrin II+ Purkinje cell cells fire at a relatively low rate and with a regular firing pattern and that zebrin II- Purkinje cells fire at a much higher rate with a more irregular pattern (mouse, Zhou et al. 2014; rat, Xiao et al. 2014). Although the mechanism by which zebrin II+ Purkinje cells maintain lower baseline firing frequencies or more regular spike trains is unknown, an enrichment in VGLUT2 is thought to manifest in longer complex spikes, higher phase amplitudes, and more

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spikelets per complex spike (Paukert et al. 2010; Xiao et al. 2014; Tang et al. 2017). This is because increased VGLUT2 expression has been shown to correlate with a larger ready-release vesicle pool, enhanced multivesicular release, and larger glutamate transients (Paukert et al. 2010). In contrast, zebrin II- Purkinje cells express more active transient receptor cation channels (TRPC3) downstream of mGluR1 than do zebrin II+ Purkinje cells (Hartmann et al. 2008; Zhou et al. 2014; Tang et al. 2017). Blocking TRPC3 results in decreased simple spike frequencies only in zebrin IIPurkinje cells, which supports its role in influencing basal activity (Zhou et al. 2014). Perhaps the biggest unknown is how stripes contribute to motor behavior (Horn et al. 2010; Cerminara and Apps 2011). Among the questions are whether each stripe controls a specific behavior, or if not, how do stripes communicate and cooperate during a particular task? Synchronous activity might play a critical role in either scenario. Synchrony within zones is dependent on olivocerebellar connectivity (Welsh et al. 2002; Schultz et al. 2009). The presence of parallel fibers that disregard stripe boundaries and Purkinje cell collaterals that link neighboring cells and stripes are two possible anatomical substrates for how Purkinje cell activity might synchronize across zones-and-stripes (Tsutsumi et al. 2015; Witter et al. 2016). Parallel fibers span multiple zones and likely connect distant, molecularly heterogeneous Purkinje cells (Valera et al. 2016; Levy et al. 2017). Purkinje cell collaterals, on the other hand, directly connect Purkinje cells to other Purkinje cells, granule cells, interneurons, and Lugaro cells in select lobules. Such local connectivity could provide additional means to regulate cerebellar circuit activity and enhance processing capabilities (Watt et al. 2009; Witter et al. 2016; Guo et al. 2016). Whatever the mechanism, synchronizing Purkinje cells within and across stripes might dynamically control the cerebellar nuclei during motor behavior (Welsh et al. 1995; Gauck and Jaeger 2000; Yamamoto et al. 2001; De Zeeuw et al. 2011; Person and Raman 2012).

Conclusions Every facet of cerebellar structure and function is built around the zone-and-stripe architecture. While the pattern formation process is complex, so is the operation of circuits that are located in the functional maps that ultimately form. Despite these challenges, a simple theme emerges – Purkinje cells are both the scaffold around which other structures organize and the control center from which different outputs are produced; disrupting them can lead to widespread abnormalities in cerebellar topography, function, and behavior. Acknowledgments This work was supported by funds from Baylor College of Medicine (BCM) and Texas Children’s Hospital, BCM IDDRC Grant U54HD083092 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (The IDDRC Neuropathology Sub-Core contributed to the tissue staining experiments), and by the National Institutes of Neurological Disorders and Stroke (NINDS) R01NS089664 and R01NS100874 to RVS. Conflicts of Interest The authors declare no conflicts of interest.

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Roof Plate in Cerebellar Neurogenesis Victor V. Chizhikov

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cellular and Molecular Mechanisms Regulating Development of the 4th Ventricle Roof Plate and Choroid Plexus Epithelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Role of the Roof Plate and Choroid Plexus in the Development of the Cerebellar Rhombic Lip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roof Plate-Derived Bmp Signaling as Regulator of Rhombic Lip Development . . . . . . . . . . . Other Roof Plate-Derived Secreted Molecules as Regulators of Rhombic Lip Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Role of Roof Plate and Choroid Plexus Signaling in Development of the Cerebellar Ventricular Zone and Its Progeny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Roof Plate-Dependent Bmp and Wnt Signals as Regulators of Proliferation of the Cerebellar Ventricular Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shh Signals from the Hindbrain Choroid Plexus Regulate Proliferation of Progenitors in the Late Embryonic Ventricular Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contribution of Bmp Signaling to Migration of Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The roof plate is a distinct group of cells located at the dorsal midline of the developing central nervous system that extends along its entire anterior-posterior axis. In the developing hindbrain, most of the roof plate broadens into a simple epithelial layer covering the dorsal opening of the 4th ventricle. As development proceeds, the 4th ventricle roof plate differentiates into the choroid plexus epithelium, which produces cerebrospinal fluid and serves as a bloodcerebrospinal fluid barrier. A growing amount of evidence indicates that both V. V. Chizhikov (*) Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_4

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the 4th ventricle roof plate and its later derivative the hindbrain choroid plexus produce various secreted molecules that regulate development of the adjacent cerebellum. Bone morphogenetic proteins secreted from the roof plate are crucial to the induction of the cerebellar rhombic lip. Signals from the early roof plate and later secretion of Sonic hedgehog from the choroid plexus promote proliferation of progenitors in the cerebellar ventricular zone. This chapter discusses studies that established the roles of the 4th ventricle roof plate and the hindbrain choroid plexus in cerebellar neurogenesis and the molecular mechanisms of their action. Keywords

4th ventricle roof plate · Choroid plexus epithelium · Rhombomere 1 · Signaling centers · Secreted signals · Dorsal · Hindbrain · 4th ventricle · Cerebellar rhombic lip · Cerebellar ventricular zone · Neuronal progenitors · Cell fate specification · Proliferation · Mouse · In vitro explant experiments · Genetic fate mapping · Mouse mutants · Dreher · Bmp · Wnt · Shh · Lmx1a · Lmx1b · Atoh1/Math1 · Ptf1a · Retinoic acid · Cerebellar GABAergic neurons · Cerebellar glutamatergic neurons · Granule cells · Cerebellar nuclei · Unipolar brush cells · Purkinje cells · Cerebellar molecular layer interneurons · Embryonic development

Introduction During development, neurogenesis in many regions of the central nervous system is regulated by secreted signals produced by specialized groups of cells called signaling centers (Lee and Jessell 1999; Kiecker and Lumsden 2005; Sillitoe and Joyner 2007; Briscoe and Small 2015). One such signaling center that regulates cerebellar development is the isthmic organizer (IsO), located at the mid-hindbrain boundary. As discussed earlier in this book (▶ Chap. 1, “Specification of the Cerebellar Territory”), numerous studies have demonstrated that Fibroblast growth factor (Fgf) signals secreted from the IsO are important for proper establishment of the cerebellar territory during early developmental stages. More recently, another embryonic structure, the 4th ventricle roof plate (RP) has emerged as an additional signaling center critical for cerebellar development. The RP is a transient embryonic signaling center that occupies the dorsal midline of the developing central nervous system along its entire anterior-posterior axis (Lee and Jessell 1999; Chizhikov and Millen 2005; Cheng et al. 2006; Hebert and Fishell 2008). At most anterior-posterior levels of the neural tube, the RP appears as a dorsal stripe of cells. At the level of hindbrain, however, most of the RP broadens into a single-layer sheet of epithelial cells covering the large 4th ventricle (Hunter and Dymecki 2007; Chizhikov et al. 2006). As development proceeds, the 4th ventricle RP differentiates into the choroid plexus epithelium (ChPe), a cuboidal epithelium that produces cerebrospinal fluid and serves as a blood-cerebrospinal fluid barrier (Currle et al. 2005; Lehtinen et al. 2013; Lun et al. 2015a, b) (Fig. 1).

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Fig. 1 Overview of embryonic mid/hindbrain neuroanatomy and cerebellar development. (a) Dorsal view of e9.5–e12.5 mouse mid/hindbrain region. Top is anterior, bottom is posterior. Midbrain – mid, hindbrain – hind, isthmic organizer, which develops at the mid-hindbrain boundary – IsO, rhombomere 1 (the most anterior part of the hindbrain) – rh1. In rh1, most of the RP (blue) broadens into a single-layer sheet of epithelial cells covering the large 4th ventricle (labeled as 4v RPe). In contrast, in most anterior rh1, the RP appears as a dorsal stripe of cells (arrowhead). (b) Sagittal section of the embryonic mid/hindbrain region taken at the level of the dashed line in panel “A.” Top is anterior, bottom is posterior, left is ventral, right is dorsal. 4v – 4th ventricle, cRL – cerebellar (upper) rhombic lip, lower RL – lower rhombic lip. (c) A diagram of the developing cerebellar anlage at e9.5–e12.5, corresponding to the region boxed in panel “B.” RP (blue), cerebellar RL (red), and cerebellar VZ (green) are shown. At this early developmental stage, the cerebellar RL gives rise to glutamatergic neurons of the CN (shown as red circles). These cells migrate tangentially along the dorsal surface of the cerebellar anlage and accumulate at the nuclear transitory zone (NTZ). The early cerebellar VZ gives rise to GABAergic neurons of the CN and Purkinje cells (PC) (both shown as green circles). Around e12.5, a small number of precursors of GABAergic interneurons (int, green circles) also arise from a ventral domain of the cerebellar VZ. All aforementioned cells migrate radially from the cerebellar VZ. (d) A diagram of the developing cerebellar anlage at e14.5–e18.5. Before these stages, RP transforms into the ChPe (blue). Late RL gives rise to granule cell precursors (GC) and unipolar brush cells (UBC) (both shown as red circles). Granule cell precursors migrate tangentially along the dorsal surface of the cerebellar anlage to form the external granule cell layer (EGL). Unipolar brush cells migrate directly into the cerebellar anlage. At these late embryonic stages, the entire cerebellar VZ gives rise to precursors of GABAergic interneurons, which migrate radially from the cerebellar VZ

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During development, the cerebellum is generated from the alar plate of rhombomere 1 (rh1), the region located near the 4th ventricle RP/ChPe. All cerebellar neurons arise from one of two germinal zones in the cerebellar anlage: the cerebellar rhombic lip (RL) and the cerebellar ventricular zone (VZ) (Leto et al. 2016; Chizhikov and Millen 2020) (Fig. 1C, D). Fate mapping studies have shown that the RL gives rise to all glutamatergic cerebellar neurons, including glutamatergic neurons of the cerebellar nuclei (CN), granule neurons, and unipolar brush cells. During development, these neurons arise in distinct, although partially overlapping, birth cohorts. The first cerebellar neurons generated in the RL are glutamatergic neurons of the CN, which in mice exit the RL between embryonic day (e) 10 and e12. They are followed at e13.5 by granule neuron precursors, which continue to be produced until the time of birth, when RL regresses. Unipolar brush cells begin to exit the RL around e15.5 (Fig. 1C, D) (Machold and Fishell 2005; Wang et al. 2005; Fink et al. 2006; Englund et al. 2006). Previously, some studies defined the cerebellar RL as the Atoh1+ progenitor population, because this gene is broadly expressed in the RL, and all RL-derived neurons originate from Atoh1-expresssing progenitors and require Atoh1 for development (Wang et al. 2005; Machold and Fishell 2005; Englund et al. 2006; Fink et al. 2006). Inducible genetic fate mapping studies, however, revealed that RL cells that initiate Atoh1 expression quickly migrate out of the RL leaving no progeny behind, suggesting the existence of Atoh1-negative progenitors that replenish the constantly depleting pool of Atoh1+ RL cells (Machold and Fishell 2005). Supporting this hypothesis, more recent studies showed that some RL progenitors express Lmx1a, Wls, Pax6, and/or Tbr2 but are Atoh1-negative or express Atoh1 at a very low level (Chizhikov et al. 2010; Yeung et al. 2014). It is likely that molecularly distinct progenitors in the RL have different developmental potentials, possibly replenishing the Atoh1+ RL progenitor pool at different developmental stages (Chizhikov et al. 2010; Yeung et al. 2014; Yeung and Goldowitz 2017; Chizhikov and Millen 2020). The cerebellar VZ, defined by the basic helix-loop-helix transcription factor Ptf1a, is located ventrally to the RL (Hoshino et al. 2005; Pascual et al. 2007; Yamada et al. 2014; Millen et al. 2014) (Fig. 1C, D). It gives rise to all GABAergic cerebellar neurons, including GABAergic neurons of the CN, Purkinje cells, Golgi cells, and molecular layer interneurons (basket and stellate cells). In the cerebellar VZ, the first born neurons are small GABAergic CN neurons. In mice, these cells become postmitotic between e10 and e12. Purkinje cells are born from e10.5 to e13.5 (Sudarov et al. 2011). The last cells arising from the cerebellar VZ are GABAergic interneuron progenitors (which give rise to Golgi, basket, and stellate cells as well as glial cells) (Sudarov et al. 2011; Schilling et al. 2008; Parmigiani et al. 2015; Fleming et al. 2013; Cerrato et al. 2018). Around e12.5, GABAergic interneuron progenitors begin arising from a limited ventral Gsx1+ domain of the cerebellar VZ, while most of the cerebellar VZ at that time expresses Olig2 and produces Purkinje cells. As development proceeds, the entire cerebellar VZ becomes Gsx1+ and produces GABAergic interneuron progenitors that populate the cerebellar prospective white matter (Seto et al. 2014; Leto et al. 2016) (Fig. 1C, D).

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Once formed, the 4th ventricle RP and the ChPe produce secreted molecules that regulate the development of both the adjacent RL and the more distantly located VZ. This chapter will discuss the mechanisms that regulate RP/ChPe development, the roles of RPe/ChPe-derived signals in cerebellar neurogenesis, and the mechanisms of their action.

Cellular and Molecular Mechanisms Regulating Development of the 4th Ventricle Roof Plate and Choroid Plexus Epithelium During development, the RP derives from the most lateral edges of the neural plate, which occupy the dorsal midline following transformation of the neural plate into the neural tube (Landsberg et al. 2005; Hunter and Dymecki 2007). As the hindbrain flexes (at e9.0 in the mouse), the RPe flares out laterally to cover the expansive 4th ventricle (Fig. 1A, B). Around e12.5, the RP begins differentiating into the ChPe (Awatramani et al. 2003; Currle et al. 2005; Chizhikov et al. 2006; Hunter and Dymecki 2007) (Fig. 1C, D). In addition, some RP cells become arranged into a narrow longitudinal column that occupies the midline of the developing cerebellar vermis (Wizeman et al. 2019; Cheng et al. 2012). It has been recently suggested that this longitudinal RP-derived dorsal midline group of cells acts as a signaling center that regulates development of the adjacent cerebellar vermis and, therefore, has been named the midline organizer (MidO) (Wizeman et al. 2019). The functional properties and mechanisms of development of this MidO remain poorly understood. Thus, this chapter focuses on the RP that covers the 4th ventricle and its main derivative, the ChPe. Gene expression, genetic fate mapping, and imaging studies have begun elucidating the cellular and molecular mechanisms that regulate induction, expansion, and differentiation of the RP and ChPe. It has been reported that combined but not individual loss of genes encoding transcription factors Lmx1a and Lmx1b prevents the formation of the 4th ventricle RP and ChPe, indicating that Lmx1a/b play a redundant role in the specification of the RP/ChPe lineage (Mishima et al. 2009). Similarly, the hindbrain ChPe does not develop in Otx2 / embryos, suggesting that this gene is necessary for the induction of RP/ChPe as well. In Otx2 / embryos, however, numerous apoptotic cells were detected at the hindbrain dorsal midline, indicating that loss of the RP in these embryos may be due to increased apoptosis and that the primary role of Otx2 may be to promote survival rather than induction of RP/ChPe cells (Johansson et al. 2013). Another transcription factor, MafB, is known to promote both differentiation of RP into ChPe and survival of ChPe cells (Koshida et al. 2017). Proper RP/ChPe size is critical for the development of both the cerebellum and other brain regions; thus, RP/ChPe expansion is precisely regulated during development. Notably, the majority of RPe and ChPe cells are postmitotic during both early and late embryonic development. Experimental activation of Notch signaling, however, increased the number of proliferating cells within the ChPe. This suggests that in addition to differentiating cells, ChPe either contains rare stem cells whose

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expansion is regulated by Notch signaling or that ChPe cells can de-differentiate and proliferate in response to Notch signaling (Hunter and Dymecki 2007). Interestingly, in contrast to most RP/ChPe cells, those located adjacent to both the cerebellar RL and lower RL remain proliferative for an extended period of time and are a major source of RP/ChPe growth during both early and late embryonic development. These marginally located RP/ChPe progenitors not only produce cellular progeny that incorporate into the RP/ChPe but also express high levels of Growth differentiation factor 7 (Gdf7, also known as Bone morphogenetic protein 12, Bmp12) and other secreted molecules that nonautonomously promote maturation of ChPe (Fig. 2). Transplantation and gene expression manipulation experiments in chicken embryos showed that location of the RP/ChPe boundary is determined by DeltaNotch interactions, and proper development of the PR/ChPe progenitor population in this region requires an upregulated expression of Chairy2 (the chick homolog of Hes1) (Broom et al. 2012). Mouse gene expression and conditional knockout studies have revealed that beginning at e12.5-e13.5, differentiated ChPe expresses Sonic hedgehog (Shh), a protein that promotes proliferation of ChPe progenitors located adjacent to the lower RL, contributing to the growth of the ChPe throughout embryonic development (Huang et al. 2009) (Fig. 2). Experiments in zebrafish identified some important cellular characteristics of RP/ChPe progenitors located at the border between the columnar epithelium of the RL and the squamous epithelium of the RP/ChPe. It has

Fig. 2 Mechanisms of 4th ventricle RP/ChPe development. (a) Sagittal section of the developing mouse mid/hindbrain region. Mid – midbrain, cRL – cerebellar rhombic lip, lower RL – lower rhombic lip, rh1 – rhombomere 1, 4v – 4th ventricle. (b) Higher magnification of the region boxed in panel “A.” Marginal RP/ChPe regions (shown in violet) located adjacent to the cerebellar RL and lower RL contain proliferating progenitors (black circles) that produce cells that incorporate into the RP/ChPe (arrows), allowing growth of the RP/ChPe. In addition to producing cellular progeny, RP/ChPe progenitor domains produce secreted factors (including Bmps/Gdf – shown as dashed arrows) that nonautonomously promote maturation of ChPe (differentiating ChPe is shown in blue) and induce Atoh1+ RL progenitors (shown in red). Differentiated ChPe secretes Shh molecules that promote proliferation of RP/ChPe progenitors, at least those located adjacent to the lower RL

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been shown that this progenitor population is morphologically homogeneous and consists of a single type of progenitor – the veil cells. Veil cells serve to generate the RP epithelium via direct transformation and by asymmetric cell division (CampoPaysaa et al. 2019). In addition to induction, differentiation, and expansion of the RP/ChPe, another important developmental process is segregation of the RP/ChPe lineage from adjacent RL cells. Loss of function experiments in mouse embryos demonstrated that Lmx1a plays a unique role in the segregation of the RP/ChPe lineage from neuronal RL derivatives (Chizhikov et al. 2010). Normally, the Gdf7+ cell lineage mostly generates the RP/ChPe, with only a very minor contribution to various cerebellar populations (Currle et al. 2005; Chizhikov et al. 2006; Cheng et al. 2012). In Lmx1a / embryos, the 4th ventricle RP is normally induced, but as development proceeds, cells belonging to the Gdf7+ RPe/ChPe lineage migrate into the adjacent cerebellum and adopt fates of neuronal RL derivatives, including glutamatergic CN neurons, granule cells, and unipolar brush cells, resulting in a severely reduced ChPe (Chizhikov et al. 2010).

The Role of the Roof Plate and Choroid Plexus in the Development of the Cerebellar Rhombic Lip The 4th ventricle RP is most well known for its role in the induction of Atoh1+ RL progenitors via Bmp signaling.

Roof Plate-Derived Bmp Signaling as Regulator of Rhombic Lip Development Several groups of experiments have shown that signals secreted from the 4th ventricle RP are required for the induction of the cerebellar RL. Genetic ablation of the 4th ventricle RP by diphtheria toxin in early (e10–e12.5) mouse embryos resulted in complete loss of the cerebellar RL. In addition, differentiating glutamatergic CN neurons, which normally originate from the RL, were absent, based on the lack of expression of their specific marker Lhx2 (Chizhikov et al. 2006). Co-culturing naïve rh1 neural tissue with exogenous 4th ventricle RP resulted in the appearance of ectopic Atoh1+ RL cells, as well as Lhx2+ cells, suggesting that RP signaling is not only necessary but also sufficient for induction of the RL and production of at least one of its derivatives – Lhx2+ glutamatergic neurons of the CN (Chizhikov et al. 2006). In vitro tissue culture experiments identified Bmps (including Bmp6, Bmp7, and Gdf7) expressed in the 4th ventricle RP and ChPe as major components of RP signaling. For example, when added to culture medium, these proteins induced numerous Atoh1+ cells in naïve rh1 neural tissue, mimicking co-culturing neural tissue with 4th ventricle RP. Moreover, Bmp-treated neural tissue formed mature granule neurons after transplantation into the early postnatal cerebellum, suggesting

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that Bmps not only induce RL progenitors but are also sufficient to initiate generation of granule neurons, the most numerous RL-derived cells (Alder et al. 1999). In addition, electroporation of activated Bmp receptors into chick rh1 neural tissue induced ectopic Atoh1+ cells (Machold et al. 2007), further confirming ability of Bmps to initiate the RL developmental program (Fig. 3). The role of Bmp signaling in RL development was also supported by mouse gene knockout studies, which showed that loss of Bmp receptors or downstream mediators of Bmp signaling Smad1, Smad5, and Smad4 results in cerebellar RL defects, including disrupted expression of Atoh1, Pax6, and Tbr2, reduced proliferation in the RL, and subsequent loss or severe reduction of glutamatergic CN neurons, granule cells, and unipolar brush cells (Qin et al. 2006; Fernandes et al. 2014; Tong and Kwan 2013; Tong et al. 2015). Interestingly, in chicken embryos, RP signaling molecules, such as Gdf7, are not uniformly produced by the RP but instead are highly expressed in the RP progenitor domain located adjacent to the RL. Disruption of this domain abolishes Atoh1 expression in the RL, indicating that at least in early chicken embryos, RP signaling properties depend on its marginal progenitor domain (Fig. 2) (Broom et al. 2012). Whether signaling properties of the mammalian RP (and the ChPe in older embryos) depend on an analogous marginal progenitor domain remains to be investigated. In vitro culture experiments identified an additional role for the choroid plexus in attenuating differentiation of RL progenitors. Co-culturing with ChPe significantly

Fig. 3 Signals secreted from the RP/ChPe regulate development of the cerebellar RL and VZ. Diagram of a sagittal section of the developing mouse cerebellar anlage. RP/ChPe (blue), cerebellar RL (red), and cerebellar VZ (green) are shown. 4v – 4th ventricle. Dashed arrows show signals secreted from the RP/ChPe. At early developmental stages (e9.5–e12.5 in the mouse), Bmp/Gdf signals from the RP/ChPe induce the cerebellar RL (including its Atoh1 expression) adjacent to the RP/ChPe. At the same early stages, RP/ChPe signaling (which likely involves Bmp and Wnt molecules) is also essential for normal proliferation of progenitors in the cerebellar VZ. Wnt5a, secreted from the ChPe into the cerebrospinal fluid, is essential to generate a normally sized cerebellum, possibly regulating development of progenitors in the cerebellar VZ. Beginning at e14.5 in the mouse, ChPe produces Shh molecules, which promote proliferation of progenitors in the cerebellar VZ at this and later developmental stages. Similar to Wnt5a, ChPe-derived Shh is secreted into the cerebrospinal fluid, through which it is delivered to the cerebellar VZ progenitors

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decreased neuronal differentiation of RL cells. Moreover, the addition of purified Bmp7 to culture mimicked this phenotype, while adding a blocking antibody against Bmp7 abolished the inhibitory effect of the choroid plexus, demonstrating casual involvement of Bmps (Krizhanovsky and Ben-Arie 2006). This attenuation of neuronal differentiation by ChPe-derived Bmp signals may be important to maintain a pool of undifferentiated progenitors in the RL during development.

Other Roof Plate-Derived Secreted Molecules as Regulators of Rhombic Lip Development RL development is also regulated by Wingless-related MMTV integration site (Wnt) signaling. In both early and late embryos, several secreted Wnt proteins, including Wnt1 and Wnt3a, are expressed in the RL and in the RP/ChPe marginal progenitor domain (Landsberg et al. 2005; Chizhikov et al. 2006). In addition, Wls, a protein necessary for the secretion of Wnt molecules, is expressed in both the ChPe and RL (Yeung et al. 2014), while another member of Wnt family, Wnt5a, is expressed throughout the ChPe (Kaiser et al. 2019). Conditional knockout of Wls in the mouse cerebellar RL reduced the RL size and the number of the RL-derived unipolar brush cells, implicating RL-derived Wnt signaling in the development of the RL progenitor population (Yeung and Goldowitz 2017). Notably, in RP-ablated mouse embryos, RL expression of Wnt1 was lost, suggesting that RP nonautonomously maintains expression of at least Wnt1 in adjacent RL (Chizhikov et al. 2006). Bmps are potent activators of Wnt1 expression in several experimental systems (Timmer et al. 2002; Zechner et al. 2007; Caronia et al. 2010). Therefore, it is possible that in the developing rh1, Bmp signals from the RPe/ChPe regulate RL development both directly (inducing Atoh1) and indirectly, via activation of Wnt expression in the RL. Whether Wnts produced directly by the ChPe (such as Wnt5a) have a role in RL development remains to be investigated. Beyond Bmp and Wnt signaling, other factors expressed in the 4th ventricle RP and ChPe have been suggested as regulators of the RL, but their roles in RL development have not been firmly established. For example, both the 4th ventricle RP and the hindbrain ChPe synthesize retinoic acid, while the cerebellar RL is a site of active retinoic acid usage (Yamamoto et al. 1996; Wilson et al. 2007). The role of retinoic acid or other RPe/ChPe-derived molecules in RL development has not been experimentally confirmed yet.

The Role of Roof Plate and Choroid Plexus Signaling in Development of the Cerebellar Ventricular Zone and Its Progeny In contrast to the cerebellar RL, induction of the cerebellar VZ does not depend on RP signaling. Signals secreted from the RP/ChPe, however, regulate proliferation of progenitors in the cerebellar VZ during both early and late embryonic stages.

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Roof Plate-Dependent Bmp and Wnt Signals as Regulators of Proliferation of the Cerebellar Ventricular Zone Analysis of RP-ablated mouse embryos was instrumental in uncovering the role of the 4th ventricle RP in VZ development. In e12.5 RP-ablated embryos, the cerebellar VZ was normally induced based on the presence of an appropriate Ptf1a expression domain in rh1. The numbers of Ptf1a + progenitors and their derivative Lhx1/5+ cells, which at this stage likely include differentiating GABAergic neurons of the CN and Purkinje cells (Morales and Hatten 2006; Zhao et al. 2007), were, however, significantly decreased in these RP-ablated embryos (Chizhikov et al. 2006). The decreased numbers of Ptf1a + and Lhx1/5+ cells were associated with reduced proliferation of progenitors in the cerebellar VZ, which was proposed to explain this phenotype (Chizhikov et al. 2006). Since RP-ablated embryos die shortly after e12.5, analysis of neuronal VZ derivatives at later developmental stages could not be performed. Nevertheless, although this analysis was limited to very early developmental stages, studies of RP-ablated embryos strongly suggested that signals secreted from the 4th ventricle RP are critical for normal progenitor proliferation in the cerebellar VZ. Analysis of Lmx1a / (dreher) and Lmx1a/Lmx1b double knockout (Lmx1a / ; Lmx1bcko/ ) mice further confirmed the role of the RPe/ChPe in cerebellar VZ proliferation (Mishima et al. 2009). As mentioned earlier, inactivation of Lmx1a leads to reduction of the 4th ventricle RP and the hindbrain ChPe, which both are even smaller in Lmx1a / ;Lmx1bcko/ mice. Reduction of the RP/ChPe in Lmx1a / or Lmx1a / ;Lmx1bcko/ embryos was associated with gradual decrease in VZ proliferation at e12.5, resulting in a small and mispatterned cerebellum in adult Lmx1a / and Lmx1a / ;Lmx1bcko/ mice (Mishima et al. 2009). Currently, the identity of RP signals regulating proliferation of VZ progenitors at early developmental stages is not completely understood. It is likely, however, that Bmp and Wnt signals are involved (Fig. 3). Potential involvement of Bmp signals is supported by gene expression and mouse transgenic and knockout studies. While several Bmps are expressed in the RPe/ChPe, strong pSmad staining, a readout of active Bmp signaling, was detected in the embryonic cerebellar VZ (Qin et al. 2006). Knockout of the Bmp signaling pathway protein Smad4 reduced the number of VZ-derived Purkinje cells and molecular layer interneurons and was associated with a decreased proliferation in the cerebellar VZ (Fernandes et al. 2014; Zhou et al. 2003). Furthermore, transgenic mice expressing activated Bmp receptor 1a (Bmpr1a) under the control of the nestin promoter demonstrated overproliferation of neuroepithelium throughout the central nervous system, including the cerebellar VZ (Panchision et al. 2001). Several members of the Wnt family are also well-known mitogens, which regulate proliferation of neuronal progenitors in different areas of the central nervous system (Megason and McMahon 2002; Chenn and Walsh 2002; Chesnutt et al. 2004; Ille et al. 2007; Chizhikov et al. 2019). As mentioned earlier in this chapter, Wnt1 and Wnt3a are expressed in the RL, while Wnt5a is expressed in the ChPe. Wnt1 and Wnt3a promote proliferation of neural progenitors by activating expression of

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positive cell cycle regulators, including cyclins D1 and D2 (Megason and McMahon 2002). In RP-ablated mouse embryos, expression of Wnt1 was lost and cyclin D2 was significantly downregulated throughout the cerebellar VZ, implicating a Wnt1cyclin D2 molecular pathway as a potential mediator of this VZ phenotype (Chizhikov et al. 2006). Conditional inactivation of Wnt5a in the ChPe resulted in a small cerebellum. Despite continuous expression of Wnt receptors in cerebellar VZ progenitors throughout embryonic development, proliferation was not affected in Wnt5a knockout embryos at e16.5, suggesting that a smaller cerebellum in these mutants results from reduced proliferation at other, possibly earlier stages, or that this phenotype is mediated by other cellular mechanisms (Kaiser et al. 2019).

Shh Signals from the Hindbrain Choroid Plexus Regulate Proliferation of Progenitors in the Late Embryonic Ventricular Zone Loss and gain of function experiments in mouse embryos have identified Shh secreted from the hindbrain ChPe, as an important regulator of VZ development (Huang et al. 2010). In the cerebellum, Shh activity is not detectable at early developmental stages, but this pathway becomes activated in the cerebellar VZ at e14.5 and remains active in this germinal zone throughout late embryonic development. Additionally, the widespread presence of primary cilia, essential sensors and transducers of Shh signals (Huangfu et al. 2003; Goetz and Anderson 2010; Park et al. 2019), was detected in VZ progenitors in late mouse embryos (Huang et al. 2010). Nestin-cre;Smo f/ embryos, in which Shh signaling is conditionally ablated in all neural cells throughout the developing central nervous system, had a remarkably thin cerebellar VZ at e16.5. This was associated with reduced proliferation of VZ progenitors and decreased levels of cell cycle-promoting cyclin D1. In addition, a dramatic reduction of the GABAergic interneuronal population, which originates from the cerebellar VZ, was detected in these embryos. In contrast, embryos with elevated Shh signaling in the central nervous system (Nestin-cre;SmoM2 embryos) revealed enhanced proliferation in the cerebellar VZ, and increased numbers of GABAergic interneuron precursors were detected in the cerebella of these mice (Huang et al. 2010). Together, these experiments established that Shh signaling is critical for proper proliferation of progenitors in the late embryonic cerebellum. This progenitor pool, in turn, is essential for the generation of the appropriate number of GABAergic interneuronal precursors, which originate from the cerebellar VZ at late embryonic stages. Other VZ-derived neurons, such as Purkinje cells and GABAergic CN neurons, were not significantly affected in embryos with abnormal levels of Shh signaling (Huang et al. 2010), suggesting that these cells are generated from the cerebellar VZ before its development becomes Shh-dependent. Although the cerebellar VZ is molecularly defined by Ptf1a expression (Hoshino et al. 2005; Pascual et al. 2007; Millen et al. 2014; Yamada et al. 2014), Ptf1a + cells in the cerebellar VZ are largely postmitotic, suggesting that they represent committed neuronal progenitors. In contrast, similar to other CNS regions (Anthony et al. 2004), radial glia represent an uncommitted stem cell population in the cerebellar VZ

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(Spassky et al. 2008; Schüller et al. 2008; Huang et al. 2010). Analysis of Nestin-cre; Smo f/ , Nestin-cre;SmoM2, and Ptf1a-cre;Smo f/ embryos revealed that, in the cerebellar VZ, Shh signaling specifically regulates proliferation of radial glia without affecting Ptf1a + progenitors (Yang et al. 2008; Huang et al. 2010). Gene expression studies revealed that before e16.5, the mouse cerebellum itself is not a source of Shh signaling, although this gene is strongly expressed in the hindbrain ChPe beginning at e13.5 (Huang et al. 2009). Specific inactivation of Shh expression in the ChPe resulted in strong defects in the cerebellar VZ proliferation and a reduced number of GABAergic interneurons. These defects were comparable to those observed in Nestin-cre;Smo f/ embryos, in which Shh signaling was ablated throughout the cerebellar VZ neuroepithelium, suggesting the hindbrain ChPe as a likely source of Shh for cerebellar VZ progenitor proliferation (Huang et al. 2010). Interestingly, a significant level of Shh protein was detected in the cerebrospinal fluid, suggesting a transventricular path for Shh ligand delivery from the ChPe to the cerebellar VZ (Huang et al. 2010). Taken together, these data strongly suggest that RP/ChPe-derived signals regulate VZ proliferation not only at early but also at late embryonic stages, and introduce Shh as a major component of this late ChPe-derived signaling (Fig. 3).

Contribution of Bmp Signaling to Migration of Purkinje Cells Loss of Bmp signaling pathway proteins Smad1, Smad5, and Smad4 in the mouse leads to abnormal distribution of Purkinje cells in the embryonic and neonatal cerebellum, suggesting a role for Bmp signaling in regulating the migration of Purkinje cells (Fernandes et al. 2014; Tong and Kwan 2013). Since development of the RL-derived neurons is also severely disrupted in Smad1/5/4 knockout mice, it is possible, however, that Purkinje cell migration abnormalities reported in these mutants are secondary to RL abnormalities rather than due to direct regulation of Purkinje cells by RP/ChPe-derived Bmp signaling.

Conclusions and Future Directions During the last two decades, the 4th ventricle RP and its later derivative, the hindbrain ChPe, have emerged as important signaling centers, which nonautonomously regulate cerebellar development by producing various secreted molecules. This knowledge has been derived from a combination of genetic ablation experiments, mouse mutant analyses, gene expression studies, and in vitro explant experiments. Together, these studies have firmly established roles for RPe/ChPederived signals in several different steps of cerebellar development. In particular, RPe/ChPe-derived signals have been shown to be critical for proper development of two embryonic cerebellar germinal zones: the cerebellar RL and the cerebellar VZ. Bmp signals from the RPe/ChPe induce RL progenitors since early embryonic stages and attenuate neuronal differentiation within the RL at later developmental

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stages, maintaining the RL progenitor pool. Shh and likely other molecules expressed in the RP and ChPe are also important positive regulators of proliferation in the cerebellar VZ. Cerebellar development, however, is a complex multistep process that is not limited to induction of the RL and regulation of proliferation in the VZ. The role of the RP/ChPe in other aspects of cerebellar neurogenesis remains largely unexplored. For example, it is not known whether RP/ChPe signaling regulates cell fate specification decisions in the cerebellar VZ. Similarly, the role of RP/ChPe in neuronal differentiation, migration, or establishing cerebellar circuitry has not been extensively investigated. While most RP studies focused on the epithelial RP covering the 4th ventricle or its main derivative the ChPe, an additional RP-derived population, the longitudinal cellular column that occupies the midline of the developing cerebellar anlage (recently named MidO) (Wizeman et al. 2019) has received little attention, and the mechanisms of its development and function remain understudied. A better characterization of RP-related mechanisms is necessary to improve our understanding of cerebellar development.

Cross-References ▶ Development of Cerebellar Nuclei ▶ Genes and Cell Type Specification in Cerebellar Development ▶ Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip ▶ Specification and Development of GABAergic Interneurons ▶ Specification of Cerebellar and Precerebellar Neurons ▶ Specification of Granule Cells and Purkinje Cells

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Specification of Cerebellar and Precerebellar Neurons Mikio Hoshino, Satoshi Miyashita, Yusuke Seto, and Mayumi Yamada

Contents Specification of Cerebellar Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Specification of Precerebellar Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The cerebellum is thought to participate in the regulation of movement and is comprised of various types of neurons in the cerebellar cortex and nuclei. Each type of neurons has morphologically, immunohistochemically, and electrophysiologically distinct characteristics. In addition, there are two precerebellar afferent systems, the mossy fiber (MF) system and the climbing fiber (CF) system. MF neurons are located in various nuclei throughout the brainstem and send their axons to cerebellar granule cells, whereas CF neurons reside exclusively in the M. Hoshino (*) · S. Miyashita Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan e-mail: [email protected] Y. Seto Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan Laboratory of Developmental Systems, Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan e-mail: [email protected] M. Yamada Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan Laboratory of Brain Development and Regeneration, Graduate School of Biostudies, Kyoto University, Kyoto, Japan © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_5

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inferior olivary nucleus (ION) and project to Purkinje cells. Recently developed genetic lineage-tracing methods as well as gene-transfer technologies have accelerated the studies on the molecular machinery to specify neuronal subtypes in the cerebellum and the precerebellar systems. Keywords

Cerebellum · bHLH · Transcription factor · Atoh1 · Ptf1a · Ngn1 · Ascl1 · Olig3 · Pax6 · Rhombomere · Neuroepithelium · Roof plate · Rhombic lip (RL) · Ventricular zone (VZ) · Glutamatergic neuron · GABAergic neuron · Cerebellar nucleus (CN) · CN-Glu neuron · CN-GABA-ION neuron · CN-GABAinterneuron · Lineage trace · In utero electroporation · Null mutant · Precerebellar systems · Climbing fiber (CF) neuron · Mossy fiber (MF) neuron · Hindbrain · Pontine gray nucleus (PGN) · Reticulotegmental nucleus (RTN) · Lateral reticular nucleus (LRN) · External cuneate nucleus (ECN) · Inferior olive nucleus (ION) · Wnt-1 · BMP · Specification · Subtype · Cochlear nucleus · Dorsal · Grafting study · Mitotic · Postmitotic · Granule cell · Purkinje cell · Golgi cell · Stellate cell · Basket cell

Specification of Cerebellar Neurons The cerebellum consists of three parts: cortex, white matter, and nucleus. The cerebellar cortex contains Purkinje, Golgi, Lugaro, stellate, basket, granule, and unipolar brush cells. The latter two cell types are glutamatergic excitatory neurons, while the others are all GABAergic inhibitory neurons. The cerebellar nucleus (CN) includes three types of neurons: large glutamatergic projection neurons (CN-Glu neurons), midsized GABAergic inhibitory projection neurons (CN-GABA-ION neurons), and small GABAergic interneurons (CN-GABA interneurons). CNGABA-ION neurons extend their axons to the inferior olivary nucleus (ION) (Carletti and Rossi 2008), while CN-Glu neurons send their axons to nuclei outside the cerebellum, including the red nucleus and the thalamus. It is believed that all types of cerebellar neurons are generated from the neuroepithelium of the alar plate of rhombomere 1 (r1) during development (Millet et al. 1996; Wingate and Hatten 1999; Chizhikov and Millen 2003; Zervas et al. 2004). The dorsal-most part of the r1 neuroepithelium, that is, the roof plate, does not produce neurons but cells of the choroid plexus (Chizhikov et al. 2006). Neuroepithelium that produces cerebellar neurons can be divided into two regions: the rhombic lip (RL) and the ventricular zone (VZ). These two regions can be morphologically discriminated by a notch located on the border. Although the history of studies on the cerebellum is very long (Ramón y Cajal 1911), the molecular machinery underlying cerebellar neuron development is still unclear. In 1997, Ben-Arie et al. reported that a basic-helix-loop-helix type (bHLH) transcription factor, Atoh1 (also called Math1), is expressed in the rhombic lip and involved in producing cerebellar granule cells (Ben-Arie et al. 1997). However, the

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development of the other types of neurons in the cerebellum remained elusive until three breakthrough papers were published in 2005. While generating certain transgenic lines, Hoshino et al. found a novel mutant mouse line, cerebelless, which lacked the entire cerebellar cortex. In this mutant, all types of GABAergic neurons are not produced in the cerebellum, which leads to the secondary loss of glutamatergic granule cells and, eventually, the entire cerebellar cortex (Hoshino et al. 2005). The responsible gene was identified as pancreatic transcription factor 1a (Ptf1a), which was known to participate in pancreatic development and to encode a bHLH transcription factor. This gene is expressed in the neuroepithelium of the VZ but not of the RL, and its expression is lost in the cerebelless mutants. Cre-loxP recombination-based lineage-tracing analysis revealed that all types of cerebellar GABAergic neurons are derived from Ptf1aexpressing cells, but glutamatergic neurons, such as granule cells and CN-Glu neurons, are not. Loss of Ptf1a expression in cerebelless as well as Ptf1a-knock out mice resulted in inhibition of the production of GABAergic neurons in the cerebellar primordium. Furthermore, ectopic introduction of Ptf1a by means of in utero electroporation resulted in the abnormal production of neurons with GABAergic characteristics from the dorsal telencephalon that should only produce glutamatergic neurons under normal conditions. In addition, Pascual et al. reported that, in the Ptf1a-null mutants, the fate of neurons produced from the VZ is changed to that of granule cells (Pascual et al. 2007). These observations suggested that Ptf1a, expressed in the cerebellar VZ, determines GABAergic neuronal fate in the cerebellum. PTF1A was also identified as a causative gene for a human disease that exhibits permanent neonatal diabetes mellitus and cerebellar agenesis (Sellick et al. 2004). On the other hand, two other groups revealed a molecular fate map of the derivatives of Atoh1-expressing neuroepithelial cells in the cerebellar RL (Machold and Fishell 2005; Wang et al. 2005). They showed that not only granule cells but also, at least in part, some neurons in the CN are derived from the RL, although they did not discriminate between glutamatergic and GABAergic subtypes in the CN. In their studies, the development of RL-derived CN neurons was shown to be disrupted in the Atoh1-null mice. Because Hoshino et al. reported that GABAergic but not glutamatergic CN neurons are derived from Ptf1a-expressing neuroepithelial cells in the VZ (Hoshino et al. 2005), their findings suggest that cerebellar glutamatergic neurons such as granule cells and CN-Glu neurons are derived from the RL. Accordingly, unipolar brush cells, which are glutamatergic, were also shown to emerge from the RL (Englund et al. 2006). Together, these studies indicate the presence of two molecularly defined neuroepithelial areas in the cerebellum, the Atoh1-expressing RL and the Ptf1aexpressing VZ, which generate glutamatergic and GABAergic neurons, respectively (Hoshino 2006). Correspondingly, if the expression of Atoh1 and Ptf1a is spatially switched, the Ptf1a-expressing RL and the Atoh1-expressing VZ produce GABAergic and glutamatergic neurons, respectively (Yamada et al. 2014). This suggests a hypothesis that the bHLH transcription factors Atoh1 and Ptf1a give distinct spatial identities to the RL and VZ to generate glutamatergic and GABAergic neurons. In the telencephalon, similar regulation by bHLH transcription

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factors takes place. Neurogenin 1/2 (Ngn 1/2) and Ascl1 are involved in producing glutamatergic and GABAergic neurons from ventral and dorsal neuroepithelium, respectively (Wilson and Rubenstein 2000). How are these spatially distinct neuroepithelial areas formed? In general, the roof plate can affect the dorsal structure of the neural tube (Lee et al. 2000; Millonig et al. 2000). Chizhikov et al. revealed that the roof plate plays an important role in the formation of the cerebellar dorsoventral domain formation by analyzing cerebellar mutants that lack the roof plate (Chizhikov et al. 2006). Moreover, it has been suggested that bone morphogenetic proteins (BMPs) secreted from the roof plate as well as Notch signaling are involved in the formation of the RL and the VZ (Machold et al. 2007). A recent study that induced Purkinje cells from ES cells suggested that loss of sonic hedgehog signaling may give the dorsoventral spatial information of the cerebellar VZ to the cerebellar neuroepithelium which eventually leads to the expression of Ptf1a (Muguruma et al. 2010). Birth-dating studies using 3H-thymidine and BrdU (Chan-Palay et al. 1977; Batini et al. 1992; De Zeeuw and Berrebi 1995; Sultan et al. 2003; Leto et al. 2006) as well as adenovirus (Hashimoto and Mikoshiba 2003) revealed that each type of neuron is generated at distinct developmental stages. As to GABAergic neurons, Purkinje cells are produced at an early stage (embryonic day (E) 10.5–13.5 in mice), Golgi cells at middle stages (E14.5~), and stellate/basket cells at a late stage (Perinatal~). Regarding glutamatergic neurons, in addition to the experiment above, molecule-based lineage-tracing analyses (Machold and Fishell 2005; Wang et al. 2005; Englund et al. 2006) have clarified that CN-Glu neurons leave the cerebellar RL at early stages (E10.5–12.5) and granule cells and unipolar brush cells at middle to late stages (granule cell:E12.5~, ubc:E12.5–E18.5). In addition, somatic recombination-based clonal analyses suggested that Purkinje, Golgi, and basket/ stellate cells as well as some CN neurons (probably GABAergic) belong to the same lineage (Mathis et al. 1997; Mathis and Nicolas 2003). These data indicate that some temporal information in the neuroepithelium may be involved in specification of neuronal types in the RL and VZ, respectively. Some scientists tried to divide the structure of the cerebellar primordium into several domains. Chizhikov et al. defined four cellular populations (denoted c1-c4 domains) in the cerebellar primordium by the expression of a few transcription factors (Chizhikov et al. 2006). c1 corresponds to the Atoh1-expressing RL, and c2 is located just above the Ptf1a-expressing VZ (denoted pc2), indicating that c2 cells mainly consist of GABAergic inhibitory neurons. Although c3 and c4 express Lmx1a and Lhx1/5, respectively, their neuronal subtypes remain to be determined. This subdomain structure is disrupted when the roof plate was removed (Chizhikov et al. 2006). Furthermore, at the early neurogenesis stage (e.g., E12.5 in mice), Minaki et al. subdivided the c2 domain into dorsally (c2d) and ventrally (c2v) located subdomains that express corl2 and Pax2, respectively (Minaki et al. 2008). While corl2 is exclusively expressed in immature and mature Purkinje cells (Minaki et al. 2008), Pax2 is expressed in GABAergic interneurons (e.g., Golgi, stellate, basket, CN-GABA neurons) in the cerebellum (Maricich and Herrup 1999; Weisheit et al. 2006). They also subdivided the Ptf1a-expressing neuroepithelial domain (pc2)

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into pc2d and pc2v, which strongly and weakly express E-cadherin, respectively. From the positions of the neuroepithelial and neuronal subdomains, they suggested that the pc2d neuroepithelial subdomain produces cells in the c2d domain which give rise to Purkinje cells, and pc2v subdomain generates cells in the c2v that become GABAergic interneurons (Mizuhara et al. 2010). As development proceeds, pc2d and pc2v subdomains become smaller and larger, respectively, and by E14.5 in mice, the Ptf1a-expressing pc2 domain is comprised only by the pc2v subdomain which expresses E-cadherin weakly. This correlates with the fact that, at E14.5 in mice, Ptf1a-expressing neuroepithelium does not produce Purkinje cells but Pax2positive interneurons (Pax2+ INs) (Maricich and Herrup 1999; Hashimoto and Mikoshiba 2003). Seto et al. reported that there are two types of Ptf1a-positive progenitors in the VZ: Olig2-expressing Purkinje cell-producing progenitors (PCPs) and Gsx1 (also called Gsh1)-expressing Pax2+ IN-producing progenitors (PIPs) (Fig. 1, Seto et al. 2014). At the early stages (E10.5, E11.5), only a small number of PIPs are located at the ventral-most region within the VZ, and a large number of PCPs occupy the remaining regions in the VZ. As development proceeds, PCPs gradually transit to become PIPs starting from ventral to dorsal regions. This temporal identity transition of cerebellar GABAergic neuron progenitor causes the loss of PCPs in the VZ by E14.5, correlating with the observations that Purkinje cells are produced only at early neurogenesis stages (E10.5–E13.5). Deducing from their position and

Fig. 1 Specification of cerebellar neurons in the neuroepithelium. The two bHLH transcription factors, Atoh1 and Ptf1a, confer spatial identities of the RL and the VZ to produce glutamatergic and GABAergic neurons, respectively. Within the VZ, temporal identity transition of GABAergic progenitors from PCPs to PIPs gradually takes place. The speed of the temporal identity transition is negatively regulated by Olig2 and positively by Gsx1 and Ezh2. As Ezh2 is involved in histone methylation, the temporal identity transition seems to be regulated by epigenetic modification

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dynamics, PCPs and PIPs may correspond to GABAergic progenitors in Pc2d and pc2v presented by Chizhikov et al. (2006). The temporal identity transition of cerebellar GABAergic neuron progenitors from PCPs to PIPs is negatively regulated by Olig2 and positively by Gsx1, which may contribute to proper numbers of Purkinje cells and Pax2+ INs being produced (Fig. 1, Seto et al. 2014), while Olig2 is also reported to participate in Purkinje cell differentiation (Ju et al. 2017). The temporal identity transition may also be regulated by epigenetic modification. Ezh2 is a catalytic subunit of polycomb complex 2 for histone tri-methylation (Young 2011). Targeted disruption of Ezh2 resulted in reduction of total H3K27 tri-methylation (H3K27me3) as well as reduced number of Pax2+ INs and increased number of Purkinje cells in the cerebellum (Feng et al. 2016), which can be explained by delayed temporal identity transition. This suggests that the temporal identity transition from PCPs to PIPs is regulated by epigenetic histone methylation. Zordan et al. reported the expression profiles of proneural bHLH transcription factors, such as Ngn1, Ngn2, and Ascl1 in the cerebellar VZ (Zordan et al. 2008). Pax2+ INs, but not Purkinje cells, are reduced in the Ascl1-null cerebellum (Grimaldi et al. 2009), while Purkinje cells are reduced in Ngn1-null mice (Lundell et al. 2009). These findings suggest that proneural factors, such as Ascl1 and Ngn1, may also regulate the temporal identity transition from PCPs to PIPs. In addition, several factors have been reported to participate in the development of a certain type of cerebellar neurons. Double knockout of transcription factors, Lhx1 and Lhx5, as well as the targeted disruption of their cofactor Ldb1 resulted in lack of Purkinje cell production in the cerebellum although Pax2+ INs did not seem to be affected. Because Lhx1 and Lhx5 are expressed in postmitotic cells, this suggests that Lhx1, Lhx5, and Ldb1 are postmitotically involved in Purkinje cell specification (Zhao et al. 2007). Moreover, targeted disruption of Frizzled co-receptors Lrp5/6 caused misexpression of tyrosine hydroxylase in Purkinje cells, suggesting that canonical WNT signaling plays an important role in proper differentiation of Purkinje cells (Huang et al. 2016). Targeted disruption of cyclin D2 caused loss of stellate cells in the cerebellar molecular layer, suggesting its involvement in the development of stellate cells (Huard et al. 1999). Transcriptional factor AP-2 family Tfap2a/2b are downstream targets of Ptf1a and involved in specification of interneurons (Jin et al. 2015; Zainolabidin et al. 2017). From the RL, several types of glutamatergic neurons, such as CN-Glu neurons, granule cells, and unipolar brush cells, are generated. CN-Glu neurons leave the RL at early neurogenesis stages. Some transcription factors, such as Tbr1, Irx3, Meis2, Lhx2, and Lhx9, have been found to be expressed in postmitotic progenitors of CN-Glu neurons, but their roles have not been clarified (Morales and Hatten 2006). Other molecules, such as Zic1 (Aruga et al. 1998), have been reported to play important roles in the migration, maturation, and survival of granule cells, but the molecular machinery underlying the specification of granule cell identity is unknown. It is reported that a transcription factor Meis1 plays crucial roles in granule cell development by regulating Pax6 transcription, BMP signaling, and Atoh1 degradation, but its involvement in granule cell specification is unclear (Owa et al. 2018). Although unipolar brush cells strongly express Tbr2, its function is also

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elusive. In addition, Pax6 and WNT signaling are indicated to be important for the survival and/or specification of UBCs (Yeung et al. 2014; Yeung and Goldowitz 2017). In Ezh2 KO mice, granule cell precursors are severely reduced at late embryonic stages (Feng et al. 2016). This indicates epigenetic modification of histone methylation may also underlie the development of excitatory neurons produced from the RL. In addition to genetic analyses, heterotopic and heterochronic transplantation studies have also provided important clues to understanding cerebellar development (Carletti and Rossi 2008). When tissues from embryonic and postnatal cerebella were mixed and transplanted to the fourth ventricle of an adult mouse, the postnatal-derived cells differentiated only into interneurons such as granule, basket, and stellate cells, but not projection neurons, such as Purkinje cells, whereas the embryonic-derived cells were capable of becoming all types of cerebellar neurons (Jankovski et al. 1996). In addition, it was shown that dissociated cells taken from cerebellar primordium at early neurogenesis stages could differentiate into all major types of cerebellar neurons, but those from postnatal cerebellum differentiated only to Pax2-positive interneurons (Carletti et al. 2002). These findings suggest that the differentiation competence of cerebellar progenitors becomes restricted as development proceeds. Probably, epigenetic regulation such as histone modification may underlie this fate restriction, as was suggested by the phenotype of Ezh2 KO mice (Feng et al. 2016). Interestingly, Leto et al. suggested that pax2+ INs are derived from same progenitor pool and that extrinsic instructive cues in the microenvironment may affect the terminal neuronal type commitment (Leto et al. 2006, 2009). One candidate for the cue may be sonic hedgehog (SHH) (Fleming et al. 2013; De Luca et al. 2015).

Specification of Precerebellar Neurons There are two types of precerebellar afferent systems: mossy fiber (MF) and climbing fiber (CF) systems. MF neurons are located in several nuclei throughout the brain stem and extend their glutamatergic projections to granule cells conveying peripheral and cortical information to the cerebellum. Four major nuclei containing MF neurons are the pontine gray nucleus (PGN), the reticulotegmental nucleus (RTN), the lateral reticular nucleus (LRN), and the external cuneate nucleus (ECN) in the hindbrain (Altman and Bayer 1987). In addition, some MF neurons are also located in the spinal trigeminal nucleus (Sp5) in the hindbrain and Clarke’s column in the spinal cord. In contrast, CF neurons reside exclusively in the inferior olive nucleus (ION), which receive input from the cerebral cortex, the red nucleus, spinal cord, and other brain stem nuclei and send glutamatergic projections to Purkinje cells (Ruigrok et al. 1995). Both types of precerebellar neurons also send branch axons to the neurons in the cerebellar nucleus. These precerebellar systems are thought to transmit the external and internal information to the cerebellar cortex to modulate cerebellar function, including regulation of animal movement. Previous birth-dating studies in mice revealed that CF neurons are generated at relatively early neurogenesis stages (E9.5–11.5) and MF neurons are produced at slightly later stages (E10.5–16.5) (Pierce 1973). Along the rostrocaudal axis, both

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MF and CF neurons in the hindbrain are generated from the caudal hindbrain, around rhombomeres 6–8 (r6–r8), as suggested by avian grafting studies as well as mammalian fate map analyses (Ambrosiani et al. 1996; Cambronero and Puelles 2000; Farago et al. 2006; Kawauchi et al. 2006). By contrast, MF neurons in the Clarke’s nucleus are generated in the spinal cord (Bermingham et al. 2001). Classic anatomical and immunohistochemical studies have suggested that these precerebellar nuclei neurons in the hindbrain emerge from the dorsal part of the hindbrain and migrate tangentially or circumferentially to their final loci (Bloch-Gallego et al. 1999; Yee et al. 1999; Kyriakopoulou et al. 2002). However, they take slightly different paths from each other; MF and CF neurons move extramurally and intramurally, respectively. Introduction of a GFP-expressing vector into the embryonic dorsal hindbrain allowed the dramatic visualization of migrating precerebellar nuclei neurons during development (Kawauchi et al. 2006; Okada et al. 2007; Nishida et al. 2011; Shinohara et al. 2013; Kobayashi et al. 2013, 2015; Hatanaka et al. 2016). Many groups have reported transcription factors that are expressed within the dorsal neuroepithelium of the caudal (r6–8) hindbrain during embryonic development, trying to define domains along the dorsoventral axis. The dorsal-most part expressing Lmx1a corresponds to the roof plate which gives rise to the choroid plexus (Chizhikov et al. 2006). Other than the roof plate, the dorsal neuroepithelium can be divided into six domains (dP1–dP6) according to the expression pattern of the transcription factors, such as Atoh1, Ngn1, Ascl1, Ptf1a, and Olig3 (Fig. 2). As to the precerebellar nuclei neurons, a series of studies have tried to clarify the precise origins of MF and CF neurons by genetic lineage-tracing methods. By analyzing genetically engineered mice that express lacZ or Cre recombinase under the control of the endogenous or exogenous Atoh1 promoter, MF neurons of PGN, RTN, LRN, and ECN were shown to emerge from the Atoh1-expressing

Fig. 2 Neuroepithelial domain structure in the caudal hindbrain. In the caudal hindbrain (r6–8), several transcription factors are expressed within the dorsal neuroepithelium during embryonic development. The dorsal-most part, the roof plate (RP), expresses Lmx1a. Other than the roof plate, the dorsal neuroepithelium can be divided into six domains (dP1–dP6) according to the expression pattern of transcription factors such as Atoh1, Ngn1, Pax6, Ascl1, Ptf1a, and Olig3. While mossy fiber (MF) neurons are derived from the dP1 domain expressing Atoh1, climbing fiber (CF) neurons are generated from the dP4 domain expressing Ptf1a and Olig3

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neuroepithelial domain (dP1, Ben-Arie et al. 2000; Rodriguez and Dymecki 2000; Landsberg et al. 2005; Wang et al. 2005). Targeted disruption of the Atoh1 gene resulted in the loss of these MF neurons, suggesting an involvement of Atoh1 in the MF neuron development. Atoh1 regulates the expression of the transcription factor Barhl1 (Mbh2) that is expressed in MF neurons. Loss of Barhl1 expression resulted in a decrease of MF neurons, leading to a decrease in the size of MF precerebellar nuclei (Li et al. 2004). In addition, Flora et al. reported that one of the E-proteins, Tcf4, interacts with Atoh1 and regulates differentiation of a specific subset (PGN, RTN) of MF neurons (Flora et al. 2007). Landsberg et al. also performed lineage trace analysis by using two variants of FLP (Flipperase recombinase) with different recombinase activities that were expressed under the control of the Wnt-1 promoter whose strength is the highest at the dorsal-most part and gradually decreases ventrally. They demonstrated that CF neurons are derived from the neuroepithelial region where Wnt-1 is very weakly expressed, whereas MF neurons emerge from the strongly Wnt1-expressing region (Landsberg et al. 2005). In addition, Nichols and Bruce generated transgenic mice carrying a Wnt-1-enhancer/lacZ transgene and observed that MF neurons but not CF neurons were labeled by β-gal in those mice (Nichols and Bruce 2006). These findings suggested that CF neurons are generated from the neuroepithelial region ventral to the Atoh1-expressing domain. By Cre-loxP-based lineage trace analysis, Yamada et al. showed that all CF neurons in the ION are derived from the Ptf1a-expressing neuroepithelial region (Yamada et al. 2007). Loss of the Ptf1a gene resulted in the fate change of some CF neurons to MF neurons, suggesting that Ptf1a plays a critical role in fate determination of CF neurons. They also showed an involvement of Ptf1a in migration, differentiation, and survival of CF neurons. Storm et al. reported that not only MF neurons but also CF neurons are derived from the Olig3-expressing neuroepithelial region that broadly expands within the dorsal hindbrain (Storm et al. 2009) by CreloxP-based linage tracing. Targeted disruption of the Olig3 gene caused the disorganized development of MF neurons and complete loss of CF neurons (Liu et al. 2008; Storm et al. 2009). Moreover, the ectopic co-expression of Olig3 and Ptf1a induced cells expressing a CF neuron marker in chick embryos (Storm et al. 2009). These findings suggest that CF neurons emerge from the Ptf1a-/Olig3-expressing neuroepithelial domain (dP4) and that Ptf1a and Olig3 are cooperatively involved in the development of CF neurons. Domain structure of the dorsal neuroepithelium in the caudal hindbrain region is shown in Fig. 2.

Conclusions and Future Directions Various types of neurons are generated from the dorsal hindbrain. As described above, the dorsal neuroepithelium of the rostral hindbrain (r1) produces all types of cerebellar neurons, while the dorsal regions of the caudal hindbrain (r6–r8) generate neurons that include the precerebellar system neurons, such as MF and CF neurons. In addition, histological observations suggested that the dorsal part of the middle

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hindbrain produces neurons of the cochlear nucleus, where auditory information is processed and relayed to the brain (Pierce 1967; Ivanova and Yuasa 1998). More directly, genetic fate-mapping studies using transgenic mice confirmed that neurons of the cochlear nucleus are derived from the dorsal part of r2–r5 in mice (Farago et al. 2006), although in avians, they were shown to emerge from a broader part (r3–r8) by grafting studies (Tan and Le Douarin 1991; Cambronero and Puelles 2000; Cramer et al. 2000). As to neuronal subtypes, Fujiyama et al. identified origins of inhibitory and excitatory neurons of the cochlear nucleus; inhibitory (glycinergic and GABAergic) and excitatory (glutamatergic) neurons are derived from Ptf1a- and Atoh1-expressing neuroepithelial regions, respectively (Fujiyama et al. 2009), and their development is dependent on the corresponding bHLH proteins. In the hindbrain from r1 to r8, there are dorsoventral domain structures defined by several transcription factors, which are longitudinally expressed throughout the hindbrain. Especially, two bHLH transcription factors, Atoh1 and Ptf1a, seem to play important roles in specifying distinct neuronal subtypes. These two proteins are expressed in different neuroepithelial regions throughout the hindbrain (Fig. 3). In both the rostral (r1) and middle hindbrain (r2–r5 in mice), Atoh1 and Ptf1a participate in generating excitatory and inhibitory neurons, respectively. However, this

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Cerebellar anlage cerebellum Glutamatergic neurons GABAergic neurons

Middle hindbrain Cochelear nu. Glutamatergic neurons GABAergic/ glycinergic neurons

Caudal hindbrain Precerebellar systems Mossy fiber neurons Climbing fiber neurons

Fig. 3 Basic HLH proteins and neurons produced from the dorsal hindbrain. Atoh1 and Ptf1a are expressed in distinct neuroepithelial regions throughout the rhombomeres 1–8 (r1–8). Each number represents the rhombomeric number. Upper side is dorsal, and lower is ventral. Left side is rostral, and right side is caudal. Neuronal subtypes generated from the dorsal neuroepithelium of the rostral, middle, and caudal hindbrain regions are shown

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rule is not applicable to the caudal hindbrain. The Ptf1a neuroepithelial domain in the caudal hindbrain (r6–r8 in mice) produces not only inhibitory neurons (local circuit neurons) but also glutamatergic neurons (CF neurons, Yamada et al. 2007), while the Atoh1 domain generates glutamatergic MF neurons. This raises the possibility that the rostral/middle (r1–r5) and caudal (r6–r8) hindbrain subregions have distinct characteristics. Overall, throughout the hindbrain regions, transcription factors, such as Atoh1 and Ptf1a, seem to define neuroepithelial domains along the dorsoventral axis and participate in specifying distinct neuronal subtypes according to the rostrocaudal spatial information (Fig. 3).

Cross-References ▶ Development of Cerebellar Nuclei ▶ Development of Glutamatergic and GABAergic Synapses

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Specification of Granule Cells and Purkinje Cells Thomas Butts, Victoria Rook, Tristan Varela, Leigh Wilson, and Richard J. T. Wingate

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Territorial Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dorsoventral “Compartments” and the Origin of Cell Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Temporal Patterning and Lineage in the Rhombic Lip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Secondary Proliferation and Neurogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diversity of Granule and Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . An Evolutionary Perspective on Neurogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Granule cells and Purkinje cells are the major populations of neurons in the cerebellum. Their specification depends on a combination of regional identity and spatiotemporal cues. These are conferred by patterning systems in the early embryo that determine anteroposterior and dorsoventral positional coordinates and an age-dependent signal (or signals) whose nature is obscure. While a number of important questions remain about the nature of cerebellar progenitor pools and their precise boundaries, a variety of fate-mapping and genetic T. Butts (*) School of Life Sciences, University of Liverpool, Liverpool, UK Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK e-mail: [email protected] V. Rook School of Biological and Chemical Sciences, Queen Mary, University of London, London, UK e-mail: [email protected] T. Varela · L. Wilson · R. J. T. Wingate MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK e-mail: [email protected]; [email protected]; [email protected] © Crown 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_6

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approaches have indicated that both granule cells and Purkinje cells arise from different dorsoventral domains within hindbrain rhombomere 1. Unusually, granule cell precursors undergo a subsequent transit amplification stage regulated by Purkinje cell signals, within a transient superficial germinal layer. Recent evolutionary insights suggest that this phase of Sonic hedgehogdependent transit amplification is only found in amniotes. Evolutionarily, since secondary proliferation arose independently of granule cell specification, it is likely to be an adaptation purely for post-specification regulation of granule cell numbers. Keywords

Cerebellum · Granule neuron · Purkinje neuron · Rhombic lip · Ventricular zone

Introduction Over recent years, the understanding of the mechanisms that systematically pattern neurogenesis in the vertebrate CNS has been revolutionized by molecular insights into CNS patterning. A conceptual framework of Cartesian patterning axes in the early neural tube (Lumsden and Krumlauf 1996) has served as a model for analyzing the development of a number of more complex structures. Of these, the cortex and the cerebellum provide a significant challenge by virtue of their scale and late development with respect to embryogenesis. Relating early patterning events in these regions to adult structure and function is thus a case of reconciling a number of patterning events that take place within territories that are not only growing but undergoing considerable structural reconfiguration during development. Nevertheless, through a history of fate-mapping studies and more recently developed transgenic techniques, the cerebellum has emerged as a comparatively simple developmental structure comprising two main lineages of GABAergic and glutamatergic cell types (reviewed in Wingate (2005)). The most populous representatives of each lineage are Purkinje cells and granule cells, respectively, which also form the conserved synaptic partnership in the molecular layer that is the substrate of cerebellar function. In this chapter, we will discuss how the cerebellum is regionally allocated in the early neural tube as a molecularly distinct territory. Purkinje and granule cells arise from separate dorsoventrally located domains within this territory as part of a temporally orchestrated of pattern of neurogenesis. Finally, we will explore the developmental and evolutionary significance of the secondary proliferation of granule cell precursors within a transient superficial layer, the external germinal layer (EGL). In particular, the emergence of the EGL in amniotes represents a marked shift in the potential interactions of neurogenic pools as granule cell precursors and Purkinje cells are brought into spatial alignment and close proximity.

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Territorial Allocation Of all the regions of the CNS, the cerebellum has perhaps the longest history of study by fate-mapping techniques. Early attempts to define the territorial boundaries of the presumptive cerebellum used microsurgical approaches to generate chimeric embryos from chick and quail tissue (Le Douarin 1993). Interest focused on the structural constrictions that divide the early neural tube into a superficially segmental structure. It was clear that the cerebellum developed from the region at the interface between the presumptive midbrain vesicle (mesencephalon) and the anterior presumptive hindbrain vesicle (metencephalon). Using a combination of grafting conditions, whereby segments of the cephalic neural tube were transplanted between quail and chick embryos, the embryonic constriction corresponding to the division between these vesicles (the midbrain/hindbrain boundary or isthmus) was, surprisingly, found to partition Purkinje cells into an anterior (midbrain derived) and posterior (hindbrain derived) pool (Hallonet et al. 1990). By contrast, the overlying layer of granule cell precursors was exclusively of hindbrain origin. These studies suggested that the adult cerebellum is comprised of cells with different territorial origins. With the advent of molecular labeling techniques, the regional origins of the cerebellum were reassessed in terms of gene expression. In particular, the attention of various groups turned to the most anterior hindbrain segment (rhombomere 1) that comprises the anterior two thirds of the metencephalon. Rhombomere 1 lies between the nested domains of Otx gene expression that define the head, midbrain, and forebrain (Acampora et al. 1995) and the cluster of Hox genes that are expressed in hindbrain and spinal cord (Lumsden and Krumlauf 1996). In this model, the posterior limit of Otx expression defines the anterior boundary of the cerebellum. Its caudal extent is delimited by the boundary of the most anterior Hox gene, Hoxa2 (Fig. 1a, b). Supporting evidence for Hox genes setting a caudal limit to cerebellar neurogenesis came from analysis of the Hoxa2 mutant mouse. Hoxa2 is the most anterior homologue and the only Hox gene to be expressed in rhombomere 2. Its deletion in mice results in a Hox-free territory between rhombomere 1 and rhombomere 3 and a caudal expansion of the cerebellum into the hindbrain (Gavalas et al. 1997), while the complementary overexpression of Hoxa2 within the previously Hox-free rhombomere 1 suppresses the formation of granule cells (Eddison et al. 2004). Molecular evidence for Otx genes comprising an anterior boundary of the cerebellum was initially prompted by an investigation of the expression domain of Otx2 with respect to the morphological constriction that had previously been used as a fate-mapping landmark in avian chimeras. Careful analysis revealed that the molecular boundary of midbrain territory only converges on the morphological landmark of the isthmic constriction, at stages after fate-mapping had previously been carried out (Millet et al. 1996). This raised the possibility that the dual origin of the Purkinje cell epithelium from midbrain and hindbrain resulted from a reliance on morphological rather than genetic regional boundaries. Subsequent fate-mapping of

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Fig. 1 The origins of cerebellum territory and Purkinje and granule cells (a) In situ hybridization for Otx2 and Hoxa2 in an early-stage vertebrate neural tube (Chick, E2) shows the unlabeled region corresponding to rhombomere (r)1. Fate-mapping and experimental studies indicate that this is the source of granule cells and possibly all other cerebellar neurons. (b) Schematic representation of how r1 territory maps onto a later embryo lying between midbrain (mb) and hindbrain (hb) regions. The posterior boundary of cerebellar territory is defined by widest angles of the roof plate of the fourth ventricle (iv). The diamond-shaped rhombic lip lies at the edge of the fourth ventricle roof plate. (c) Granule cell precursors and Purkinje cells are generated from nonoverlapping territories progressively more distal to the roof plate. (d) The standard model of the relationship between progenitors/precursors (solid circle) and their derivatives (empty circle) are shown for Ptf1a (Purkinje) and Atoh1 (granule) lineages. WIs defines a region that may represent the source to progenitors of the Atoh1 migratory precursor pool (Yeung et al. 2014). Patterns of cell movement are shown by arrows: Purkinje neurons and granule precursors migrate along radial (i) and tangential (ii) trajectories, respectively. Roof plate cells are generated predominantly adjacent to the rhombic lip and passively progress into this nonneural epithelium (Currle et al. 2005; Nielsen and Dymecki 2010). The ventricular zone (vz), rhombic lip (rl), and roof plate (rp) produce different lineages and are generally believed to represent different developmental compartments

granule cells with respect to both Hoxa2 expression demonstrated that the precursors of this population are entirely contained within rhombomere 1 (Wingate and Hatten 1999). The designation of rhombomere 1 as the origin of all cerebellar neurons is consistent with a wealth of studies on the molecular patterning of cerebellar territory with respect to the isthmus, an organizer that forms at the midbrain/hindbrain boundary (Joyner 1996). Firstly, deletions of genes whose expression domains

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overlap rhombomere 1 at some stage of development, such as Wnt1 (McMahon and Bradley 1990), Gbx2 (Wassarman et al. 1997), or Engrailed-1 (Wurst et al. 1994) can result in a dramatic loss of the majority of cerebellar neurogenesis. Secondly, disruption of genes expressed specifically at the midbrain/hindbrain boundary such as fibroblast growth factors (FGF) can lead to the loss or severe reduction in size of the adjacent cerebellum in mice (Xu et al. 2000) and zebrafish (Brand et al. 1996; Reifers et al. 1998). These, as well as a number of experiments using protein overexpression, have suggested that FGFs may consequently have an instructive role in cerebellar induction (Martinez et al. 1999; Matsumoto et al. 2004; Koster and Fraser 2006). Others have argued for a more indirect role in patterning through, for example, regulating the position of the rostral boundary of Hoxa2 expression (Irving and Mason 2000) and hence the ultimate size of the cerebellum. Of these latter studies, evidence that FGF can induce cerebellar territory indirectly, by downregulating Otx2 expression (Foucher et al. 2006; Sato and Joyner 2009) and that Otx2 deletion in the midbrain results in an ectopic cerebellar-like structure (Di Giovannantonio et al. 2014), offers strongest support for the cerebellum as the derivative of an Otx-negative domain.

Dorsoventral “Compartments” and the Origin of Cell Types As in the spinal cord, dorsoventral patterning cues play a major part in the allocation of cell types within the presumptive cerebellum. The cerebellum is approximately derived from the dorsal half of the neural tube (Hallonet and Le Douarin 1993), and as might be expected, dorsalizing signals, in particular transforming growth factors-β (TGFβ), play an important role in specifying at least some neuron fates (Alder et al. 1996, 1999; Helms and Johnson 2003). The source of these dorsalizing signals is the roof plate of the fourth ventricle (Lee et al. 2000; Millonig et al. 2000; Chizhikov et al. 2006a), which comprises an expanded nonneural sheet of cells that also secretes a number of potent patterning molecules such as Wnt proteins (Rodriguez and Dymecki 2000). Both gene ablation and genetic fate-mapping techniques have revealed that Purkinje cells and granule neuron precursors are born in distinct domains, respectively, defined by the expression of Ptf1a (Hoshino et al. 2005) and Atoh1 (Ben-Arie et al. 1997; Klein et al. 2005; Wang et al. 2005) (Fig. 1c). The expression of Atoh1 is restricted to the neural margins of roof plate, the embryonic rhombic lip (Wingate 2001) and can be induced by ectopic TGFβs (Alder et al. 1999). Atoh1 is lost following either TGFβ knockdown (Lee et al. 1998) or following a more radical genetic ablation of roof plate (Lee et al. 2000). More recently, the expression of Gdf7, and hence Atoh1, has been found to be dependent on cell-cell interactions between roof plate and neuronal precursors mediated by Notch-delta signaling (Broom et al. 2012). Ptf1a defines a broader territory embryonically ventral to the rhombic lip (Hoshino et al. 2005) and one defining feature of Purkinje and granule cell lineages is their mutual exclusivity. No Mash1 (Kim et al. 2008)/Ptf1a (Hoshino et al. 2005)positive cells give rise to precursors within the rhombic lip (Fig. 1c), and no Atoh1

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(Math1) rhombic lip precursors give rise to GABAergic neurons (Klein et al. 2005; Wang et al. 2005; Rose et al. 2009). Does this reflect a genuine compartmentation of the dorsoventral axis into lineage restriction units, or the segregation of neuroblasts or committed precursors from an uncommitted progenitor or stem cell pool? Determining the answer to this question depends on when bHLH genes are expressed in progenitors (stem cells), precursors (partially or wholly committed dividing cells), and/or neuroblasts (young neurons). Evidence from tamoxifeninduced pulse labeling demonstrates that the expression of at least one bHLH gene, Atoh1(Math1), is confined to young neuroblasts and committed precursors (including the EGL) but not progenitors (Klein et al. 2005): no derivatives of Atoh1positive cells reenter the rhombic lip (Fig. 1d). Extensive mixing of proliferative cells along the DV axis (Wingate and Lumsden 1996; Clarke et al. 1998; Wingate and Hatten 1999) suggests that rhombic lip progenitors should stochastically be drawn from the ventricular zone. However, this would require that both Ascl1 (Mash1) and Ptf1a bHLH genes were similarly restricted to committed precursors (but not progenitors) since neither Ptf1a nor Ascl1(Mash1) expressing cell lineages contribute to the rhombic lip. In support of this argument, tamoxifen-mediated, pulse labeling of Ascl1(Mash1) reveals that few if any Ascl1(Mash1)-positive cells reenter the ventricular zone (Kim et al. 2008). Resolving this discrepancy remains an important question in cerebellar patterning. On the one hand, the observations of Machold and Fishell (2005) could be interpreted as revealing the presence of a spatially compartmentalized population of dedicated rhombic lip stem cells (Fig. 2a). On the other hand, if the rhombic lip was continually replenished from the ventricular zone (Fig. 2b), there is an as yet unidentified progenitor common to all cerebellar neuronal subtypes that might be free to spread across “compartment” boundaries. A variety of evidence favors the latter “replenishment” model over the presence of a committed precursor pool. An analysis of genetic micro-compartmentation within the rhombic lip suggests that the Atoh1 pool is supplied by an adjacent Atoh1negative domain characterized by the expression of Wntless/WIs (Yeung et al. 2014). In vitro evidence suggests that cerebellar stem cell progenitors can generate both GABAergic and glutamatergic lineages (Lee et al. 2005); however, stem cells in vivo seem only to contribute to non-granule cell fates in late embryogenesis (Zhang and Goldman 1996). This apparent contradiction is resolved in a recent study of the regenerative capacity of the developing cerebellum, which shows that nestinpositive cells can give rise to all major cell types (Wojcinski et al. 2017). The cerebellum does therefore contain a multipotent stem cell zone that might also feed the replenishment of bHLH-positive Purkinje and granule cell precursor pools during normal development. Finally, a replenishment model might explain the unusual lineage “violations” that accompany the knockout of both Ptf1a and Atoh1(Math1) bHLH genes. Various fate-maps suggest a low-frequency intermingling of roof plate and neuronal lineages during normal development (Chizhikov et al. 2010; Cheng et al. 2012). Following Ptf1a knockout, cells from the Purkinje cell domain enter the EGL and express Atoh1(Math1) (Pascual et al. 2007). Following the knockout of Atoh1(Math1), cells

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Fig. 2 Alternative models to explain the effects of mutation of bHLH genes in Purkinje and granule cell lineages. The compartmental model where progenitors are lineage restricted (a) is contrasted with a “replenishment” model (b), where progenitors can mix between territories. The location of ectopic cells in bHLH mutant mice is shown on a single composite of cell locations in the Ptf1a (Pascual et al. 2007) and Atoh1(Math1) (Rose et al. 2009) mutant mice. WIs expression is unchanged in the Atoh1(Math1) null mutant (Yeung et al. 2014). In a compartment model (c), ectopic, ventricular zone-derived Atoh1+ve cells that enter the EGL must be derived by aberrant radial migration (Pascual et al. 2007). Ectopic rhombic lip-derived cells must similarly be assumed to enter the roof plate lineage through aberrant tangential migration. In a “replenishment” model where uncommitted progenitors can cross into each of these precursor zones (d), knockout phenotypes interpret the role of bHLHs as simply regulating commitment and differentiation. When Ptf1a is downregulated, precursors can enter the EGL via tangential migration. The final position of ectopic EGL cells may reflect the earlier birth date of GABAergic interneurons with respect to the prolonged assembly of the EGL (cells generated early in the lineage lie most distal to the rhombic lip)

from the rhombic lip can enter the gdf7 roof plate lineage (Rose et al. 2009). In both cases, normal lineage segregation between progenitors has been disrupted. While this has been interpreted as indicating cross-inhibition of expression between bHLH genes (Pascual et al. 2007) (Fig. 2c), it is possible that bHLH genes are upstream of events that segregate precursors and neurons, but that multipotent progenitors themselves are not restricted to lineage compartments (Fig. 2d). This interpretation leaves open the possibility that a progenitor is free to contribute to any lineage, in vivo, depending on patterns of stochastic cell mixing between rhombic lip and the rest of the ventricular zone and/or roof plate.

Temporal Patterning and Lineage in the Rhombic Lip Both granule cell precursors and Purkinje cells represent only a subset of the neurons born within their respective dorsoventral domains. Diversity in cell fate was, until

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recently, only potentially attributable to local regional differences in gene expression. For example, signals secreted from the roof plate (Chizhikov et al. 2006b) and downstream variations in gene expression (Morales and Hatten 2006; Zordan et al. 2008; Mizuhara et al. 2010) have been implicated by association with the fate of subsets of ventricular zone-derived GABAergic neurons. Alongside these spatial distinctions in the ventricular zone, genetic fate-mapping using Ascl1, which like Ptf1a is widely expressed across the cerebellar anlage precursor pool, has demonstrated a temporal sequence in the production of cerebellar nuclei neurons, Purkinje neurons, cerebellar interneurons, and glia at specific stages during cerebellar development (Kim et al. 2008; Sudarov et al. 2011; Ju et al. 2016). Recently, spatial and temporal variety in cell fate have been mechanistically linked through opposing expression of Gsx1 and Olig2 (Seto et al. 2014), associated with interneurons and Purkinje neurons, respectively. A ventral-to-dorsal transition of their expression boundary during development drives the switch from Purkinje neuron production to interneuron production (at around E13.5 in mouse). Thus, the expression of these two transcription factors defines a temporal identity transition in the ventricular zone. Interestingly, long-term fate-mapping using Olig2 has suggested that this fate determination occurs in committed precursors (Ju et al. 2016), consistent with the replenishment model for the rhombic lip (Fig. 2b). For Atoh1-positive precursors, temporal patterning likewise plays a pivotal role in generating cell fate diversity. The rhombic lip gives rise to the excitatory, glutamatergic neurons of the cerebellum, including a subset of cerebellar nuclei (Machold and Fishell 2005; Wang et al. 2005; Fink et al. 2006) and unipolar brush cells (Englund et al. 2006). Early-born, Atoh1-derived rostral hindbrain nuclei initially characterized as rhombic lip derivatives (Gilthorpe et al. 2002; Klein et al. 2005; Rose et al. 2009) have subsequently been shown to be derived from a distinct “isthmic” Atoh1 progenitor pool that is distinct from the rhombic lip (Green et al. 2014), rostral hindbrain nuclei (Gilthorpe et al. 2002; Wang et al. 2005; Rose et al. 2009), and granule cell neurons (Ben-Arie et al. 1997; Eddison et al. 2004). Temporal patterning switches principally control the fate of glutamatergic neurons arising from the rhombic lip. Avian fate-mapping studies showed that there is a temporal sequence of cell production from the rhombic lip (Green and Wingate 2014), which culminates in the granule cell precursors (Gilthorpe et al. 2002). The latter conclusion was later consolidated using an inducible reporter in the mouse, which confirmed the stages and order in which rhombic lip-derived neurons are produced (Machold and Fishell 2005; Wingate 2005; White and Sillitoe 2013). As in the ventricular zone, temporal pattering corresponds to shifting spatial expression domains in the rhombic lip (Chizhikov et al. 2010; Yeung et al. 2014; Yeung and Goldowitz 2017). Heterochronic transplant studies show that rhombic lip cells require exogenous signals to transition between commitment states (Wilson and Wingate 2006). Early in development, signals from the roof plate (Chizhikov and Millen 2004; Chizhikov et al. 2006b) including retinoic acid (Wilson et al. 2007) are conveniently placed to influence the specification of early-born neurons. Later in development, it is possible that circulating hormones, such as thyroid hormone, may influence temporal

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patterning and development of the cerebellum (Delbaere et al. 2015, 2016). Interestingly, the prominent fate transition from the production of cerebellar nuclei to granule cell neuron production at the rhombic lip occurs around E13.5 in mouse. This mirrors the temporal transition that occurs in the ventricular zone as Purkinje neuron production switches to interneuron production, pointing to a common regulation of cerebellar neuronal identity switches at this key point in development. Despite the important advances in understanding cerebellar cell fate specification in recent years, the molecular basis of this common regulation at present remains unclear.

Secondary Proliferation and Neurogenesis Cerebellar granule cell neurogenesis has two very distinctive developmental phases. The first phase of precursor derivation occurs at the rhombic lip (Alder et al. 1996). Committed granule cell precursors migrate tangentially across the surface of the cerebellar anlage (Ryder and Cepko 1994; Wingate and Hatten 1999) and form a transient, superficial proliferative layer called the external granule layer (EGL), that is unique to tetrapods (Chaplin et al. 2010; Butts et al. 2014a, b). In many amniotes, granule cells within the EGL are proliferative. Their cell divisions can be asymmetric, nonterminal symmetric, or terminal symmetric and result in one progenitor and one differentiating neuron, two progenitors, or two differentiating neurons, respectively. The balance of these different types of cell division in the EGL is crucial to the degree of granule progenitor expansion and reflects a fine balance between proliferation and differentiation, which ultimately controls the degree of cerebellar size and foliation. Granule progenitors in the EGL undergo extensive nonterminal symmetric divisions (Nakashima et al. 2015; Espinosa and Luo 2008; Legue et al. 2015; Yang et al. 2015) and are committed to a granule neuron fate (Alder et al. 1996; Klein et al. 2005). These properties, combined with the sheer size of the neuronal population produced (accounting for well over 50% of the neurons in the brain in humans (Azevedo et al. 2009)), make cerebellar granule cells an excellent model for studying the biological significance of transit amplification in the central nervous system. The transit amplification of the granule progenitors in the EGL is driven by signaling from Purkinje cells, which assemble in a layer beneath the EGL. Purkinje cells secrete Sonic Hedgehog (SHH) which in turn stimulates proliferation of the granule progenitors (Alder et al. 1999; Dahmane and Ruiz-i-Altaba 1999; Wallace 1999; Wechsler-Reya and Scott 1999) by enhancing their symmetric divisions (Yang et al. 2015). The amplitude of SHH signaling correlates with the extent of granule cell proliferation (Corrales et al. 2004, 2006), which itself is dependent upon continued expression of Atoh1 in the EGL (Flora et al. 2009). SHH has also been shown to enable the prolonged maintenance of Atoh1 expression in granule cell precursors by inhibiting its degradation (Forget et al. 2014). At the termination of proliferation, definitive granule cells downregulate Atoh1, exit the cell cycle, and initiate NeuroD1 expression (Miyata et al. 1999; Butts et al. 2014a). The onset of

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NeuroD1 expression marks the start of the differentiation process of precursors into mature granule cell neurons. From the EGL, granule cells radially migrate through the Purkinje cell layer, toward to inner granule layer (IGL) where they reside in the adult cerebellum. What triggers the onset of differentiation in a given granule cell progenitor is unclear. In addition to SHH, in vitro and mouse conditional knockout studies have suggested that a number of conserved developmental signaling pathways may be involved in regulating granule neurogenesis. These include the bone morphogenetic protein (BMP) (Ayrault et al. 2010; Rios et al. 2004; Zhao et al. 2008; Fernandes et al. 2012; Tong and Kwan 2013; Tong et al. 2015), Notch (Solecki et al. 2001), Wingless (WNT) (Poschl et al. 2013; Lorenz et al. 2011; Pei et al. 2012; Anne et al. 2013; Miller et al. 2014), and neurotrophin (Zanin et al. 2016) pathways. Interactions between these pathways (Fernandez et al. 2010) and the regulation and posttranslational modification of Atoh1 (Zhao et al. 2008; Forget et al. 2014) may further contribute to regulating the balance between proliferation and differentiation. The transit amplifying function of the EGL also has important clinical relevance as granule cells are often implicated as a cell of origin for medulloblastoma, the most common pediatric brain malignancy. Medulloblastomas are categorized into different genomic classifications, as determined by the causative genetic mutational profile (reviewed in Kumar et al. 2017). One prominent subtype is the SHH-group medulloblastoma, in which ectopic activation of the pathway results in increased EGL proliferation (Goodrich et al.1997; Schuller et al. 2008; Yang et al. 2008). The relationship between Atoh1 and SHH has also been shown to drive dissemination and malignancy of this disease (Grausam et al. 2017). Just as EGL proliferation is intimately linked to Purkinje cell signaling (Fleming et al. 2013), the development of the Purkinje cells is disrupted when EGL formation is interrupted (Jensen et al. 2004). Purkinje cell spatial distribution is systematically disturbed in mice that are chimeric for mutations that disrupt granule cell spatial distribution (Goldowitz et al. 2000), number (Jensen et al. 2002), or maturation (Swanson and Goldowitz 2011). This interdependence may be an efficient mechanism for ensuring an overall uniformity in the anatomy of the cerebellar layers. However, to what extent these reciprocal interactions are a common feature of the relationship between all cerebellar neuron subtypes is unknown.

Diversity of Granule and Purkinje Cells The remarkably uniform, well-conserved circuitry of the adult cerebellum has long been thought to be critical for its function (Cajal 1894; Braitenberg 1961; Dean et al. 2010). Despite the pronounced regularity of its cellular organization, macro and molecular scale partitions fragment the cerebellum into distinct divisions. In avian and mammalian lineages, the cerebellum is divided into a series of transverse folia, seemingly a structural consequence of the considerable cortical expansion gained through EGL proliferation during development (Corrales et al. 2006). These folia can be further divided into several anterioposterior zones based on the expression patterns of specific molecular markers, potentially corresponding to lineage

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differences (Ozol et al. 1999). A parasagittal molecular organization for Purkinje cells has been characterized most notably in the form of rostrocaudally oriented bands of Zebrin II/Aldolase C expression (Hawkes and Herrup 1995). In addition to variations in molecular marker expression, regionalization of the Purkinje cell layer has been reinforced by differences in dendritic morphology and electrophysiological properties, dividing the cerebellar circuitry into functional parasagittal microzones (Zhou et al. 2014; Cerminara et al. 2015). The evolutionary history of these sagittal compartments has recently been examined, with histological studies of Zebrin II in reptilian and paleognath cerebella revealing divergent patterns in certain clades (Aspden et al. 2015; Corfield et al. 2015; Wylie et al. 2016). Together, these observations suggest that the uniformity of cerebellar structure belies significant molecular heterogeneity. How much, if any, of this variation is specified during neurogenesis? Lineage studies in mouse and chick revealed no apparent topographic organization of neurogenesis in the early Purkinje cell precursor pool (Baader et al. 1996; Lin and Cepko 1999), although birth-dating studies in rats suggest an anterior to posterior variation in birth dates of Purkinje cells in different regions of the cerebellum (Altman and Bayer 1985). Several studies have revealed a close correlation between the birth dates of Purkinje cells and sagittal compartmentalization, indicating that Purkinje cells might acquire positional information around the time they leave their progenitor zone (Hashimoto and Mikoshiba 2003). During midline fusion, the mammalian cerebellar anlage undergoes a 90 rotation, converting the early embryonic rostrocaudal axis into an enduring mediolateral arrangement, which, to some degree, might be reflected in sagittal organization (Sgaier et al. 2005). The importance of early maturational gradients is challenged by the absence of this morphological rotation in the avian cerebellum (Alexandre and Wassef 2003), yet both of these amniote classes possess distinct molecular parasagittal patterns. Marker analysis of the distinct, functional clusters of Purkinje cells has recently identified unique molecular expression profiles of these Purkinje cell subsets (Fujita et al. 2012), as early as E14.5 in the developing mouse cerebellum. Although the developmental origins of these clusters remain unclear, tracking the movement of these subsets has revealed a close association to compartmentalization, with specific clusters undergoing complex rearrangements to form stripe patterns in discrete lobules (Vibulyaseck et al. 2017). For granule cells, different elements of morphological and spatial ordering are conferred by the timing of migration and proliferation. The rhombic lip gives rise to temporally patterned lineages that position themselves in successively proximal regions (Gilthorpe et al. 2002). Similarly, temporal cohorts of granule cell precursors might acquire a certain degree of spatial allocation upon leaving the rhombic lip. After the formation of a coherent EGL, migratory inner EGL cells undertake significant tangential movements, traversing large distances, thereby obscuring any potential temporal order in initial EGL deposition (Ryder and Cepko 1994). The establishment of discrete lobules as a result of foliation appears to serve as a physical barrier to migration, as evidenced by clonally related granule cell precursors becoming confined to individual folia, and limited transverse migration across folia troughs

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(Legue et al. 2015). Furthermore, granule cells in the inner granule layer are randomly dispersed through the subsequent addition of newer cells, with younger granule cell clones becoming more dispersed in the inner granule layer as development progresses. Clonally related granule cells have also been found to project their axons to discrete strata within the molecular layer, with a temporal sequence such that younger granule cells project to more superficial sublayers, potentially exposing them to a different interneuron milieu (Espinosa and Luo 2008). Unlike the cerebral cortex however, there is no molecular evidence linking the timing of granule cell birth to the laminar identity of parallel fibers. The relationship between spatiotemporal patterning and specification of cerebellar progenitors and the consequential functional significance of this still requires further investigation. However, developmental mechanisms do confer chronotypic ordering during multiple periods of granule cell development, but the processes that shape each successive developmental stage supersede the order established in the previous phase. This continuous rearrangement of molecular organization as development progresses therefore appears to be feature of cerebellar ontogeny.

An Evolutionary Perspective on Neurogenesis Despite large differences in size and shape, the underlying complement of cerebellar cell types, as well as the derived circuitry, is highly congruent across all vertebrate lineages and, in particular, the absolute ubiquity of granule and Purkinje cells and their interface within a conserved molecular layer (Nieuwenhuys et al. 1998; Sultan and Glickstein 2007). Thus, it is expected that the elements of neurogenesis that regulate the identity of these cells might also be highly conserved. Rhombomere 1 itself is present in all chordates and is defined as a Gbx2-positive region flanked by Otx expression rostrally, and Hox expression caudally (Wada et al. 1998), with recent evidence suggesting further molecular subdivision within this region in basal jawed vertebrates (Pose-Mendez et al. 2015a, b). Granule and Purkinje cells aside, the complement of glutamatergic and GABAergic lineages that, respectively, arise from rhombic lip and ventricular zone has been found to vary between vertebrates (Butler and Hodos 1996; Nieuwenhuys et al. 1998), suggesting that the temporal sequence of cell fate allocation may be a substrate of evolutionary adaptation. These variations are made all the more significant by mounting evidence of GABAergic interneuron contributions to cerebellar function (Dean et al. 2010). While the diversity in the interneuron milieu can account for some of the developmental variability between species, much of the focus has been on changes in cerebellar scale and foliation, and how these factors correlate with ecological and behavioral characteristics (Sultan and Glickstein 2007; Yopak et al. 2007; Lisney et al. 2008; Yopak and Montgomery 2008). These gross morphological differences can be attributed to the adaptations in neurogenic plan in different species, in particular, the presence of an EGL and the extent of proliferation of its component precursors. The EGL appears to have emerged relatively late in evolution, seemingly coinciding with the emergence of tetrapods and the move from aquatic to terrestrial habitats (Gona

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1972). Investigating the cerebellar development of the simplest tetrapods – the amphibians – has afforded greater insight into the origins of this structure. A subpial layer consisting of granule cell precursors can be found in the frog during metamorphosis; however, these cells fail to proliferate (Uray et al. 1987). Molecular analysis has revealed that although these granule cell precursors are positive for Atoh1 (an absolute requirement for suppressing differentiation and undergoing transit amplification in mammals (Flora et al. 2009)), they concomitantly express NeuroD1 (Butts et al. 2014a), which is sufficient to induce granule cell differentiation. The correlation between an absence of proliferation and the co-expression of genes whose expression is normally temporally segregated suggests that heterochronic shifts in transcription factors may operate as an evolutionary tool to control the degree of proliferation and thus the resultant morphology of cerebellar structures. In fish, which lack an EGL, the IGL forms by direct migration of precursors into a deeper layer of the nascent developing cerebellum (Kaslin et al. 2009, 2013; Chaplin et al. 2010). Remarkably, amphibians exhibit this alternative mode of granule cell migration during the tadpole stage (Uray et al. 1988) but then generates a transient EGL at metamorphosis (Gona 1972; Butts et al. 2014a), recapitulating the change in patterning motifs of cerebellar growth in the evolutionary transition of species from water onto land (Fig. 3). Despite the absence of an EGL, some aquatic vertebrates are capable of generating elaborate and sizeable cerebella – notably, the mormyrid fishes, where the cerebellum grows to become the dominant CNS structure, conferring a brain-tobody ratio greater than that of humans (Nieuwenhuys et al. 1974). It is possible, then, that these species possess a transient proliferative structure, or potentially, the continuous developmental period experienced by fishes might be adequate to produce the cell numbers required to form their complex cerebella (Hibi et al. 2017). This, along with the lack of proliferation observed in the frog EGL, raises the question of this layer’s evolutionary requirement. In birds and mammals, its primary function appears to be to exponentially augment granule cell numbers during a discrete developmental period, so what then is the purpose of a nonproliferative EGL in amphibians? One possible role for the primitive EGL might lie in the distribution of cells arising from a relatively remote progenitor zone, allowing for homogeneous dispersal of neurons and optimal integration of new cells into the pre-existing laminar circuitry. Furthermore, the induced proximity of granule cells and Purkinje cells likely expedited the synergy between the two cell types, ultimately resulting in, among other interactions, SHH-dependent transit amplification in the EGL: a convenient proliferative solution for expanding cortical surface area in the amniote lineage.

Conclusions Neurogenesis in the mammalian cerebellum is circumscribed by anteroposterior, dorsoventral, and temporal patterning constraints. The production of the two major cell types, granule cells and Purkinje cells, is dependent on the expression of the bHLH genes Atoh1 and Ptf1a, respectively. While there is evidence for

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Vertebrate radiation

Amniotes

Tetrapods

Sarcopterygians

Osteichthyeans

Gnathostomes

Placental Marsupial Monotreme Birds Crocodiles Lizards/snakes Sphenodon Turtles Frogs Slamander Caecilian Lungfish Coelocanth Teleost Gar Bowfin Sturgenon Reedfish

Shh in Purkinje cells/proliferative EGL Transient superficial granule layer Tangential granule migration

cb Mammals

Birds & reptiles

Mammal & bird mb

hb

Purkinje granule

Frog

Amphibians Lobe-finned fish

Teleost Ray-finned fish

Shark Chimaera Lamprey Hagfish

Cartilaginous fish

Shark

Agnathans (jawless fish)

Sagittal view

Transverse

Adult cerebellar morpholgy

Fig. 3 Developmental innovations in the evolution of the cerebellum. The vertebrate radiation (left) is shown with respect to adult cerebellum morphology (right) and the first appearance of developmental motifs (middle). While tangential migration of granule cells is found in fish, a superficial transient granule cell layer first appears only in frog. Shh expression is absent in fish (and possibly amphibians). Shh is however expressed in sharks although granule cells do not transduce Shh signals (Chaplin et al. 2010). Purkinje cell/granule cell interactions appear to be a feature that may have first evolved in ancestral amniotes and are present in birds and to a greater or lesser extent in other extant reptiles

molecularly distinct developmental compartments in both the rhombic lip (Chizhikov et al. 2010; Yeung et al. 2014) and the ventricular zone (Miller et al. 2014; Zordan et al. 2008), on the whole, neural progenitor cells from these germinal zones are born as a homogenous population of neuroblasts. Later in cerebellar development, additional molecular and spatial cues pattern these progenitors into their functional and molecular microdomains, a property which is largely irrespective of their initial specification. This suggests that cerebellar patterning with respect to function is an ongoing process throughout development. Neurogenesis thus seems mainly to be concerned with making the right number of neurons. To accomplish this, in birds and mammals, a unique phase of granule precursor cell tangential migration brings granule cells into a signaling interaction with Purkinje cells, as the transient EGL. However, the formation of an EGL is not a prerequisite for a large and functionally sophisticated cerebellum, and some anamniote classes have evolved alternative solutions to generating the appropriate number of appropriately deployed granule cells.

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Gliogenesis Valentina Cerrato and Annalisa Buffo

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Origin and Differentiation of Cerebellar Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Phenotypic Heterogeneity of Cerebellar Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Origin of Cerebellar Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lineage Relationship Between Cerebellar Astrocytes and Neurons . . . . . . . . . . . . . . . . . . . . . . . Postnatal Amplification of Intermediate Astrocyte Precursors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differentiation of Cerebellar Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Origin and Differentiation of Cerebellar Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Origin of Cerebellar Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differentiation of Cerebellar Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In the cerebellum, both astrocytes and oligodendrocytes are characterized by a peculiar heterogeneity. Astrocytes include Bergmann glia, granular layer, and white matter astrocyte types, each endowed with specific morphological and functional features; oligodendrocytes derive from multiple embryonic sources and establish neuron type-specific interactions. Nevertheless, while the mechanisms of neuronal diversification have been deeply investigated and in part elucidated, gliogenesis in the cerebellum remains poorly explored. Here, we critically discuss the available knowledge regarding the ontogenesis of the repertoire of glial cells in the cerebellum, their relationships with cerebellar neurons, and the processes regulating the acquisition of their mature morphological and molecular traits, pointing out the open questions that still seek elucidation. V. Cerrato · A. Buffo (*) Department of Neuroscience Rita Levi-Montalcini, University of Turin, Neuroscience Institute Cavalieri Ottolenghi, Turin, Italy e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_108

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Keywords

Astrocytes · Oligodendrocytes · Cerebellum · Development · Morphological and functional diversity Abbreviations

BG EGL PC PCL PWM RG RL VZ

Bergmann glia External granular layer Purkinje cell Purkinje cell layer Prospective white matter Radial glia Rhombic lip Ventricular zone

Introduction The cerebellum is characterized by a remarkable anatomical and functional complexity, mirrored not only by the variety of its neuronal phenotypes but also by a notable heterogeneity of glial cells. Specific morphological features of astrocytes are associated with defined functional properties, unique among the astroglia of the entire central nervous system. Cerebellar oligodendrocytes, by myelin deposition along defined axon subsets, critically shape cerebellar circuit activity. Further, both glia types heavily influence cerebellar circuit development. However, in the last decades, the interest in lineage, differentiation, heterogeneity, and functions of cerebellar glia has lagged behind studies on cerebellar neurons and circuits. As a result, while mechanisms on neuronal diversification have been widely investigated and partially clarified, astrogliogenesis remains poorly explored. Given the increasing relevance of glia in developmental processes and in the correct functioning of mature circuitries, filling this gap is crucial in order to achieve a deeper understanding of the complexity of cerebellar structure and functions. Here we review the current status of research on gliogenesis and highlight crucial questions that remain to be addressed.

Origin and Differentiation of Cerebellar Astrocytes The Phenotypic Heterogeneity of Cerebellar Astrocytes Glial cells of the cerebellum were first described by Ramón y Cajal (1911), who distinguished three main categories, according to their morphology and position in cerebellar layers. In the white matter, (i) glial cells (including both astrocytes and oligodendrocytes) display processes oriented along the direction of axons; the

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cerebellar cortex, on the other side, hosts (ii) the astrocytes of the granular layer, with star-shaped bushy processes, and (iii) the so-called neuroepithelial cells with Bergmann fibers (commonly known as Bergmann glia, BG), with cell bodies aligned to the Purkinje cell (PC) somata, several ascending processes spanning radially into the molecular layer, and terminal end feet contacting the pial surface (Fig. 1). Afterward, electron microscopy analyses confirmed this classification and unveiled another rare type of granular layer astrocytes, called protoplasmic, with thin processes devoid of lamellae (Fig. 1; Palay and Chan-Palay 1974). These studies further showed veil-like appendages emanating from the processes of the major type of granular layer astrocytes (thereby named velate astrocytes; Fig. 1) and described their relationship in the local neuropil with groups of granule cells and glomeruli (see ▶ Chap. 12, “Development of Glutamatergic and GABAergic Synapses”). Similarly, BG processes were shown to ensheath the entire dendritic surface of PCs and their synapses, thereby suggesting that both kinds of cortical astrocytes actively participate in the arrangement of cerebellar cortical synapses and exert specialized functions in the related circuitries. On the other hand, the closer inspection of white matter astrocytes led to their classification as fibrous astrocytes (Fig. 1). A special staining procedure, the Cajal’s gold sublimate technique (Cajal 1926; Globus 1927), also allowed, early in 1916, the identification of a second astroglial phenotype located in the Purkinje cell layer (PCL) and intermingled with BG, with “feathers” of cytoplasmic extensions shorter than processes of BG: these cells were called feathered

Fig. 1 Astroglial subtypes in the cerebellum. The mature cerebellum includes various astroglial phenotypes displaying a typical morphology depending on the layer occupied. Bergmann glia (BG) possess somata in the Purkinje cell layer (PCL) and radial processes extending to the pial surface. In the same layer, the “feathered cells” of Fañanas have short cytoplasmic extensions and are intermingled with BG, but their existence still waits for a full demonstration. In the granular layer (GL), there are two different types of astrocytes: velate astrocytes with fine and elaborated processes and rare protoplasmic astrocytes. Finally, fibrous astrocytes with long processes oriented in the direction of axons are typical of the white matter (WM)

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cell of Fan˜ anas, after the name of their discoverer (Fañanas 1916). Nevertheless, due to their morphological similarity to BG, their identification remained difficult, explaining why these cells were essentially forgotten. Only recently, these neglected cells found a first confirmation in a study that identified a subset of astrocytes in the cerebellar molecular layer showing specific expression of defined potassium channelrelated peptides (Goertzen 2018). In the future, this classification may change to include more subtypes, depending on new neurochemical, topographical, and morphological characterizations, as suggested by a recent detailed investigation on the human cerebellum (Alvarez et al. 2015).

Origin of Cerebellar Astrocytes Ramón y Cajal, early in 1911, investigated cerebellar development of different species and concluded that all cerebellar glia derive from the ventricular zone (VZ) (Ramon y Cajal 1911). This evidence was later demonstrated in mouse by fate-mapping analyses using inducible reporter genes expressed in ventricular radial glia (RG) (Hoshino et al. 2005; Mori et al. 2006; Sudarov et al. 2011). Ramón y Cajal also argued that BG progenitors result from the retraction of the apical processes of RG lining the VZ of the cerebellar primordium that, keeping their end feet attached to the pial surface, subsequently delaminate radially and translocate into the nascent parenchyma, where they settle in the PCL (Ramón y Cajal 1911). Successively, anatomical investigations on neurochemically identified glia provided evidence consistent with this interpretation (Yuasa 1996; Yamada and Watanabe 2002). In further support of this notion, abrogation of protein tyrosine phosphatase Shp2-dependent extracellular signal-regulated kinase (ERK) signaling in ventricular RG perturbed their transformation into BG (Li et al. 2014). Moreover, Gdf10 (growth and differentiation factor 10), a glial marker specific for both developing and mature BG, was shown to be expressed in the VZ according to a precise pattern. In the lateral cerebellar primordium, Gdf10 is expressed in the posterior portion of the VZ, whereas it appears diffusely produced throughout the whole extension of the VZ in the medial cerebellum (Mecklenburg et al. 2014). These observations support a direct derivation of BG from RG and suggest that a restricted subset of RG may generate BG, although the compartmentalization of gliogenic ventricular progenitors remains to be demonstrated. Altman and Bayer (1997) also noted that some delaminating cells continue to divide in the overlying tissue and, therefore, first proposed that cerebellar astrocytes may be generated by a second wave of progenitors that proliferate within the developing cerebellar parenchyma. Indeed, astroglial-like progenitors were successively described to delaminate during late embryonic development and to reach the prospective white matter (PWM), where they proliferate postnatally to produce parenchymal astrocytes and GABAergic interneurons (Yamada and Watanabe 2002; Parmigiani et al. 2015). Thus, these studies suggested that astrocytes of the granular layer and white matter derive from intermediate progenitors amplifying in the PWM, yet without clarifying whether these progenitors could also produce BG. Recent in vivo clonal analyses of astroglial cerebellar lineages shed

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a new light on these issues (Cerrato et al. 2018a), unveiling that postnatal progenitors in the PWM can produce all the three main astrocyte types. Moreover, this study also disclosed an unprecedented bi-potency of BG progenitors in the postnatal PCL, that generate both BG and granular layer astrocytes, but not white matter astrocytes. Therefore, two distinct populations of intermediate progenitors can be found in the postnatal cerebellar parenchyma: PWM progenitors, capable of giving rise to all main astrocyte types, and BG progenitors in the PCL, producing BG and granular layer astrocytes. The delamination of RG and their translocation toward the nascent parenchyma were known to occur soon after the completion of PC genesis and their emigration from the VZ, at around embryonic day (E) 14 in mice, when this germinal layer exclusively gives rise to non-neuronal elements (Yuasa 1996; Yamada and Watanabe 2002). Hence, this developmental time point has always been defined as the start of gliogenesis in the mouse cerebellum. Nevertheless, recent studies on individual embryonic RG unveiled that these cells are gliogenic as early as E12, a developmental phase previously thought to be fully neurogenic, and highlighted a welldefined spatiotemporal pattern of astrocytes generation, characterized by a timedependent allocation of the cells first to the hemispheres and then to the vermis, depending on their origin at E12 or E14, respectively (Cerrato et al. 2018a). This same study also unveiled that astrogliogenesis in the cerebellum occurs according to a remarkably orderly developmental program, where embryonic ventricular progenitors produce either only a single astrocyte type or more types and go through a decline over time in their amplification and lineage potentials. Whether or not also the rhombic lip (RL) and its derivatives populating the external granular layer (EGL) contribute to cerebellar astrogliogenesis still remains controversial (Buffo and Rossi 2013 and references therein). This possibility was first suggested based on 3H-thymidine labeling and immunolabeling for astrocyte markers, but other studies did not confirm this view. However, manipulations of morphogens (Notch, Sonic Hedgehog (Shh), and bone morphogenetic protein 2 (BMP2)) indicated that RL and EGL progenitors have the potential to generate astrocytes. Consistently, the BG-specific gene Gdf10 (see above) was recently detected also in the embryonic RL (Mecklenburg et al. 2014). Moreover, EGL progenitors generate both neurons and glia ex vivo. In turn, a possible relationship between RL-derived neurons and BG was recently highlighted by the new evidence that a subset of nestin-expressing astroglial progenitors in the PCL (i.e., arguably BG progenitors) can switch their fate and regenerate granule cells in mice after ablation of the perinatal EGL (Wojcinski et al. 2017). In summary, a minor contingent of cerebellar astrocytes may derive from RL precursors. However, production of astrocytes from EGL progenitors remains to be unequivocally confirmed in vivo.

Lineage Relationship Between Cerebellar Astrocytes and Neurons The notion that cerebellar neurons and astrocytes are generated from the same germinative niches (i.e., the VZ and, possibly, the RL) raises the hypothesis that

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they might be clonally related. Several fate-mapping analyses, in which embryonic progenitors were targeted and followed based on the expression of specific markers, suggested a common origin between the two lineages. When classical RG markers such as BLBP (brain lipid-binding protein), Glast (glutamate aspartate transporter), and TenascinC were used, the labeled progenies comprised cerebellar inhibitory neurons as well as BG and parenchymal astrocytes (Anthony et al. 2004; Anthony and Heintz 2008; Fleming et al. 2013). Moreover, in vivo targeting of ventricular RG through injections of lentiviral vectors displaying a tropism toward astroglial cells demonstrated that RG can generate astrocytes and interneurons during late embryonic development (Parmigiani et al. 2015). In parallel, in fatemapping studies exploiting the regulatory regions of transcription factors known to be necessary for the specification toward the neuronal lineage (i.e., pancreatic transcription factor 1a (Ptf1a), Neurogenin 2, achaete-scute family BHLH transcription factor 1, Ascl1), some astrocytes could be detected among the offspring cells (Hoshino et al. 2005; Florio et al. 2012; Sudarov et al. 2011). Nevertheless, the low frequency of astroglial cells observed in these studies questions the actual origin of most cerebellar astrocytes from the tagged progenitor populations. Common ancestors for cerebellar neurons and glia were also suggested by functional studies performed at embryonic stages. Manipulation of both Notch/BMP signaling and proneural genes (Ascl1) resulted in an altered balance between the numbers of neurons and astrocytes, with macroscopic cerebellar defects (Buffo and Rossi 2013), indicating lineage contiguities and that proneural genes may act by suppressing default gliogenic differentiation programs in ventricular multipotent precursors. Further, the existence of bipotent precursors for neurons and glia in the postnatal cerebellum was supported by studies reporting the isolation of neurosphereforming cells from perinatal cerebella and describing their capability to differentiate into neurons and astrocytes both in vitro and following transplantation in postnatal cerebella (Klein et al. 2005; Lee et al. 2005). Consistent with these reports, genetic fate-mapping analyses of cerebellar postnatal GFAP-expressing progenitors (Silbereis et al. 2009) and stem cell-like PWM precursors (Fleming et al. 2013) indicated common progenitors for cerebellar astroglia and inhibitory interneurons. However, the most conclusive evidence of bipotent neuroglial progenitors was recently provided by Parmigiani and colleagues (2015). In this study, by in vitro, ex vivo, and in vivo clonal analyses at the single progenitor level, the authors showed that GABAergic interneurons and white matter astrocytes share a common ancestor residing in the postnatal PWM. Examining whether such progenitors also exist at earlier developmental ages and, if so, what neuron and astroglia subpopulations they might generate will be of particular interest in the future.

Postnatal Amplification of Intermediate Astrocyte Precursors Several birthdating studies reliably reported that most cerebellar astrocytes are generated during late embryonic and postnatal development (Miale and Sidman

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1961; Altman and Bayer 1997; Sekerková et al. 2004). Three discrete sites of intense proliferation can be identified in the postnatal cerebellum, comprising the EGL, the PWM, and the PCL (Yuasa 1996; Altman and Bayer 1997; Parmigiani et al. 2015). Not considering the possible, minor, origin of glial cells from the EGL (see above), it is likely that the bulk of cerebellar astrocytes derive from the amplification of intermediate precursors homed in the PWM and PCL, that, as discussed above, represent independent progenitor pools with distinct fate potencies (Altman and Bayer 1997; Yamada and Watanabe 2002; Parmigiani et al. 2015, Cerrato et al. 2018a). Interestingly, recent proliferation and birthdating analyses unveiled distinct layer-dependent rhythms of amplification and cell cycle exit in the postnatal cerebellum. This translates into astrocyte clones with highly stereotyped architectures, resulting from the combination of recurrent modules (i.e., subclones) typically composed of constant relative numbers of different astrocyte types. Namely, white matter astrocytes leave the cell cycle early, while proliferation in cortical layers is more intense and lasts longer, especially in the PCL, in parallel with the tangential expansion of the cerebellar surface (Cerrato et al. 2018a). Distinct molecular machineries could sustain different rhythms, as suggested by the nonoverlapping distribution of distinct cyclins isoforms between BG progenitors in the PCL (expressing cyclinD1) and PWM precursors (expressing cyclinD2) (Leto et al. 2011; Parmigiani et al. 2015), which associates with higher proliferative activity and faster cell cycle reentry of BG compared to PWM cells (Parmigiani et al. 2015). As a further level of heterogeneity between the two progenitor pools, bFGF (basic fibroblast growth factor) and PC-derived Shh are known to promote the proliferation of PWM precursors (Lee et al. 2005; Fleming et al. 2013), while neither of the two appear to affect BG progenitor expansion (Dahmane and Ruiz i Altaba 1999). However, available data on the role of Shh in regulating the proliferation of BG progenitors are conflicting (Wojcinski et al. 2017). Thus, the same factors may influence at various extent and with different outcomes astrocyte progenitors in different layers due to either different intrinsic cell sensitivities or layer-dependent variations in factor concentration, or both. Taken together, these observations indicate that, although all cerebellar astrocyte phenotypes originate from the same germinative neuroepithelium, they have distinct natural histories. BG progenitors initially derive from the morphological transformation of RG and, later during postnatal development, extensively proliferate to match the concomitant expansion of the cerebellar tissue. On the other side, parenchymal astrocytes are posited to derive from proliferative events of RG, whose daughter cells migrate to the overlying parenchyma and here continue to divide.

Differentiation of Cerebellar Astrocytes Early co-culture studies showed that cerebellar neurons profoundly influence the morphology, antigenic profile, and proliferative rates of cerebellar astroglia (Hatten 1985; Nagata et al. 1986). Subsequent studies especially focused on disclosing the

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cellular and molecular mechanisms of BG differentiation (reviewed in Leung and Li 2017), likely because this astroglial type displays a highly specialized morphology, exerts crucial functions in supporting cerebellar development at both the cellular and structural levels, and regulates PC synaptic activity (possible cross-refs: see ▶ Chaps. 8, “Granule Cell Migration and Differentiation,” and ▶ 9, “Purkinje Cell Migration and Differentiation”). Hereafter, we will present available evidences on the acquisition of BG typical morphology and layering and subsequently address BG molecular maturation. Of note, the processes of maturation of the other cerebellar astroglial phenotypes remain essentially undetermined.

Maturation of Morphological Features After withdrawal of their apical process, RG displace their cell body toward the cerebellar cortex and intermingle with PCs. Here, they undergo several morphological changes to produce BG and, together with developing PCs, form a multilayered structure, which later gradually transforms into a monolayer. Different from RG that possess a single basal branch, during maturation, BG extend multiple ascending processes (usually three to six per cell in mice) that cross the molecular layer. These multiple branches emerge during postnatal development: they increase in number until the end of the first postnatal week and then decrease (Yamada and Watanabe 2002), in parallel with the expansion and reduction of the EGL (Shiga et al. 1983), therefore suggesting that granule cells contribute to regulate the formation of BG processes (see below). At early maturation stages, BG fibers are rather smooth with small enlargements and excrescences that progressively grow to bushy expansions covering most of the radial process (Shiga et al. 1983) and establishing tight interactions with PC synapses (Yamada and Watanabe 2002). For the induction of the proper morphological phenotype, BG progenitors need to interact with three components of the cerebellar environment: the subpial basement membrane, PCs, and granule cells (Buffo and Rossi 2013). The basement membrane lies on the surface of the cerebellar cortex, and it is deposited by meningeal elements during early development; for BG correct polarization, process outgrowth, and positioning in the PCL, BG end feet need to be tightly anchored to it. If this anchorage is defective, the fibers fail to form and orient, and BG cell bodies move to the molecular layer, resulting in a severe disruption of cerebellar foliation and layering (Sievers et al. 1994; Li et al. 2014; He et al. 2018). Several receptors and intracellular transduction pathways are implicated in this anchorage, mediating a bidirectional cross talk with components of the extracellular matrix. They include β1-integrins (Graus-Porta et al. 2001; Frick et al. 2012) and other molecules associated with their intracellular domains (integrin-linked kinase ILK) (Belvindrah et al. 2006), the ABL tyrosine kinases (Qiu et al. 2010), RIC-8A (Ma et al. 2012), and members of the dystrophin-dystroglycan complex (Moore et al. 2002; Qu and Smith 2005; Satz et al. 2008). Consistent with their physical interactions with developing BG, PCs strongly impact on BG morphological maturation. This action is exerted through Shh secretion (Dahmane and Ruiz-i-Altaba 1999) and juxtacrine signals based on the Notch pathway (Stump et al. 2002; Eiraku et al. 2005; Weller et al. 2006; Komine et al. 2007; Hiraoka et al. 2013). Moreover, all the transformation events occurring in the shape and number of BG fibers are intimately associated with

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the growth of PC dendrites and afferent fibers rewiring (Yamada et al. 2000). Further influence on BG development is exerted by granule cells, which act through Notch signaling (Stump et al. 2002), the NRG pathway, and the secretion of FGF9, thereby providing additional regulators of BG differentiation (Schmid et al. 2003; Lin et al. 2009). In addition to the extrinsic influence of the surrounding neurons on astrocyte differentiation, several cell-intrinsic determinants are known to be involved in the morphological maturation of BG. Among Sox proteins of group C, known to be important modulators of the maturation of both neurons and glia in the central nervous system, regulated Sox4 levels were demonstrated to be crucial for RG migration into the position normally taken by BG and maintenance of radial fibers projecting toward the pial surface (Hoser et al. 2007), while Sox2 was recently implicated in the correct organization and localization of BG after birth (Cerrato et al. 2018b). Conversely, stellate astrocyte morphologies did not appear to be affected. Moreover, the transcription factor Zeb2 was recently shown to promote BG formation and differentiation likely through alteration of FGF, Notch, and TGFβ (transforming growth factor beta)/BMP downstream targets (He et al. 2018). In addition, PTEN (phosphatase and tensin homolog) deletion in hGFAP-positive cells also induced the disappearance of cells with the typical morphology of BG without affecting other parenchymal astrocytes, thus revealing that active PTEN signaling is intrinsically required for correct BG differentiation and for the maintenance of a polarized phenotype (Yue et al. 2005). Moreover, a misalignment of BG and abortive formation of radial fibers that often do not contact the pial surface was observed in the absence of the ubiquitin ligase Huwe1 (D’Arca et al. 2010). As formerly mentioned, the deletion of Ptpn11, coding for the tyrosine phosphatase Shp2, was also shown to block the transformation of RG in BG and to affect cerebellar foliation, pointing to the critical role of ERK signaling in BG induction (Li et al. 2014). Manipulations of FGF ligands/receptors known to activate ERK or of the transcription factors Etv4 and Etv5 known as FGF targets/mediators also led to BG severe defect demonstrating that the FGF-ERK-ETV axis is important for the induction of BG (Leung and Li 2017 and references therein). Finally, after deletion of the tumor suppressor gene adenomatous polyposis coli (APC) in GFAPexpressing cells, BG differentiation proceeded normally during the first postnatal week, but at later stages, their cell bodies translocated to the molecular layer, then losing contacts to the pial surface and acquiring a stellate morphology (Wang et al. 2011). This indicates that the radial phenotype not only has to be actively promoted but also continuously maintained. Collectively, impairment of these regulatory mechanisms results in BG malpositioning and/or the acquisition of a stellate morphology, which may thus represent a default differentiation pathway for cerebellar astroglial precursors. Yet, it is likely that the refinement of the variety of multipolar morphologies in the granule cell and white matter is instructed by local cues.

Maturation of Molecular Profiles All astrocyte phenotypes in the mature cerebellum display distinct, although partially overlapping, molecular signatures (Fig. 2). Indeed, all of them express, though at distinct levels, some typical astroglial markers such as Sox9, S100β, and GFAP.

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Fig. 2 Molecular heterogeneity of mature cerebellar astrocytes. The schematics represent the molecular features of different types of astrocytes in the adult cerebellum. While all astrocyte phenotypes express Sox9, S100b, and GFAP, they differ in the expression of other astrocyte-specific markers, as indicated in colored panels. PCL Purkinje cell layer

Nevertheless, BG are enriched in the AMPA receptors subunits GluA1 and GluA4, and in GLAST, whereas velate astrocytes have low amounts of these transcripts and large amounts of the water channel aquaporin 4 (AQP4; Farmer et al. 2016). Moreover, some components of the pathway of Shh, comprising the transcription factor Gli1 and the receptors Patched1 and 2 (Ptch1/2), are also enriched in mature BG but not velate astrocytes (Farmer et al. 2016). Shh, secreted by PCs, also regulates the expression of Gdf10, described to be selectively restricted to developing and mature BG (Mecklenburg et al. 2014). Of note, BG are among the very few kinds of astrocytes that constitutively express at adult stages the intermediate filament protein Vimentin, typical of immature and reactive astrocytes (Shaw et al. 1981). On the other hand, the expression of Kir4.1, a pivotal potassium channel subunit, was described to be higher in both BG and granular layer astrocytes than in fibrous white matter astrocytes (Tang et al. 2009; Farmer et al. 2016). But how are these molecular profiles achieved? The mechanisms of molecular maturation of cerebellar astrocytes, which underlie their functional specialization, have been poorly addressed and are mostly unknown. A recent study unveiled the role for PC-derived Shh in regulating the molecular and functional profile of cerebellar cortical astrocytes (Farmer et al. 2016). In BG, Shh signaling sustains the expression of GLAST, Kir4.1, and the AMPA subunits GluA1 and GluA4, thereby maintaining AMPA receptor-mediated currents. Moreover, it prevents AQP4 expression. However, when Shh signaling was constitutively activated in velate astrocytes, these cells could acquire the same molecular and functional signature of BG. Thus, by blocking Shh signaling in BG and by constitutively activating it in granular velate astrocytes, which are physiologically exposed to lower amounts of Shh, the authors showed that the two subtypes are interchangeable under both the molecular and functional point of view. However, these molecular and functional changes were not mirrored by morphological modifications, indicating the role of additional intrinsic/extrinsic cues in the regulation of astrocyte morphological heterogeneity.

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Importantly, first single cell RNA-seq studies on cerebellar development have recently sketched out distinct astrocyte clusters whose molecular identities and regulatory transcriptional networks still remain largely unexplored (Carter et al. 2018; Gupta et al. 2018). The datasets of these studies, therefore, represent very valuable sources to be carefully examined in the future to unveil the still unknown molecular identity of the distinct astrocyte progenitors, and to clarify what regulatory factors for gene expression are implicated both in the precursors’ fate decision and in the specification, maintenance, and function of each cerebellar astrocyte type. On the whole, the available data indicate that BG maturation requires tight and timely regulated stimuli coming from the surrounding environment as well as intrinsically defined mechanisms. An impairment of these regulatory mechanisms often results in a failure in acquiring and/or maintaining a radial morphology and translates in the acquisition of a stellate multipolar shape. On the other side, possible instructors of specific phenotypic traits of the other stellate astroglial phenotypes still need to be deeply investigated.

Origin and Differentiation of Cerebellar Oligodendrocytes Oligodendroglial cells in the mature cerebellum comprise both oligodendrocyte progenitors and fully differentiated myelinating oligodendrocytes. Oligodendrocyte progenitors are dispersed throughout the cerebellar white matter and granular and molecular layers. They maintain a degree of proliferation also at adult stages and are capable of differentiating into oligodendrocytes if myelin is damaged. Moreover, they likely sustain a certain degree of myelin remodeling throughout life (Nishiyama et al. 2009; Young et al. 2013). Myelin deposition is restricted to PC axons and afferent climbing fibers in the white matter and granular layer (Palay and Chan-Palay 1974; Reynolds and Wilkin 1988). Furthermore, despite the abundant presence of oligodendrocyte precursors, the only myelinated processes present in the molecular layer are occasional branches of the recurrent supraganglionic plexus of PC axons (Palay and Chan-Palay 1974; Rossi et al. 2007). This peculiar pattern reflects typespecific interactions between oligodendrocytes and different categories of cerebellar cortical neurons that still have to be elucidated.

Origin of Cerebellar Oligodendrocytes It is well-established that oligodendrocytes are specified and generated at multiple locations along the neuraxis, including both ventrally and dorsally located germinative niches (Rowitch and Kriegstein 2010). Multiple oligodendrocyte sources have also been suggested for the cerebellum and are currently still debated. In avians, chick-quail chimera experiments showed that cerebellar oligodendrocytes are born in the ventral midbrain, followed by migration into the cerebellum (Mecklenburg et al. 2011). Studies in the mammalian brain also supported the view of an extracerebellar source for oligodendrocytes. For instance, in utero electroporations of

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ventricular cerebellar progenitors with a fluorescent reporter resulted in labeling both interneurons and astrocytes, whereas labeled oligodendrocytes were extremely rare (Grimaldi et al. 2009). Consistently, solid cerebellar grafts transplanted in the telencephalon or in the cerebellum became primarily populated by host-derived oligodendrocytes, suggesting that cerebellar oligodendrocytes are derived outside of the cerebellum (Grimaldi et al. 2009). More recent fate-mapping analyses proposed the Olig2-expressing neuroepithelial domain in the ventral rhombomere 1A as the source of cerebellar oligodendrocytes (Fig. 3; Hashimoto et al. 2016). This same study also revealed that a second wave of precursors is generated locally by the cerebellar VZ, but the resulting cells comprise only 6% of the total amount of cerebellar mature oligodendrocytes (Fig. 3; Hashimoto et al. 2016). Phenotypic or functional differences between the two oligodendroglia subsets remain to be explored. Despite the apparent largely independent origins of cerebellar oligodendrocytes and astrocytes, a few evidences support the presence of bipotent gliogenic progenitors. Oligodendrocyte precursors expressing the chondroitin sulfate proteoglycan NG2 were described to generate astrocytes besides oligodendrocytes in cerebellar postnatal ex vivo explants (Leoni et al. 2009). However, these data were contradicted by in vivo genetic fate mapping of NG2-expressing cells showing exclusive production of oligodendrocytes (Zhu et al. 2008). Notably, upon deletion of the polycomb group protein Bmi1 leading to an aberrant and ectopic activation of the BMP pathway, an increased generation of astrocytes was found, associated with a decrease in oligodendrocytes (Zhang et al. 2011). These findings suggested the existence of bipotent progenitors that, however, were not characterized by the authors. Taken together, these studies indicate a major extracerebellar source for cerebellar oligodendrocytes and the presence in vivo of distinct gliogenic subsets for astrocytes and oligodendrocytes.

Fig. 3 Schematic representation of the two waves of oligodendrocyte generation in the cerebellum. At E11.5, oligodendrocyte precursors (red dots) start arising from the metencephalic rhombomere 1 (r1). Afterward, they migrate toward the cerebellar primordium (Cb), where they first arrive at E16.5. In parallel, a second small pool of oligodendrocyte progenitors (yellow dots), born locally in the cerebellar ventricular zone, populates the cerebellar parenchyma. These latter progenitors generate only a minor fraction of cerebellar oligodendrocytes, while the vast majority originates from the extracerebellar source

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Differentiation of Cerebellar Oligodendrocytes Once in the cerebellar parenchyma, oligodendrocyte precursors first occupy the deepest region surrounding the cerebellar nuclei and progressively enter the developing lobules, where they settle both in the intralobular white matter and in the cortical layers. Afterward, they undergo maturation according to the same centrifugal spatiotemporal pattern of dispersion in the cerebellar tissue (Reynolds and Wilkin 1988). Accordingly, myelin is deposited from the deepest to the outermost layers (Reynolds and Wilkin 1988; Gianola et al. 2003) until the end of the second postnatal week in rodents. Despite the mechanisms responsible for this peculiar centrifugal pattern still need to be clarified, it is likely that this precise spatiotemporal schedule results from the proximo-distal gradient of PC maturation along the outgrowing cortical lobules (Gianola et al. 2003). As in other regions of the central nervous system, both cell-autonomous mechanisms and environmental factors cooperate in oligodendrocyte maturation in the cerebellum. Yet, some factors specifically impact on cerebellar oligodendrogenesis. Thyroid hormones, for instance, at early postnatal stages, promote oligodendrocyte progenitor cell cycle exit and commitment to differentiation through indirect actions exerted by PCs and astrocytes. Conversely, at later mature phases, through cellautonomous mechanisms, they directly restrain cell proliferation of oligodendroglial progenitors (Picou et al. 2012). Furthermore, PCs influence oligodendrocyte functioning by release of Shh. During early postnatal development, high amounts of PC-derived Shh stimulate the proliferation of oligodendrocyte progenitors. Then, by the end of the first postnatal week, PCs downregulate Shh and start producing vitronectin, which promotes oligodendrocyte maturation (Bouslama-Oueghlani et al. 2012). Moreover, recent evidence highlighted the role of GABAergic signaling from interneurons in limiting proliferation and stimulating differentiation of oligodendrocyte precursors in the postnatal cerebellum (Zonouzi et al. 2015). These effects were attributed to GABAA receptor-mediated synaptic inputs to oligodendroglial cells. Whether and how other neurotransmitters participate in oligodendrocyte differentiation in the cerebellum remains to be established.

Conclusions and Future Directions The findings discussed above witness the increasing interest of the scientific community toward the understanding of the mechanisms of astroglial ontogenesis and differentiation in the cerebellum. Nevertheless, many features of this process still need clarification. Indeed, while it is now well accepted that cerebellar astrocytes are primarily generated from the embryonic VZ through an intermediate phase of amplification in the PCL and PWM, the precise contribution of these postnatal germinative site to astroglial diversity still needs to be elucidated. Similarly, possible lineage relationships between cerebellar astroglial phenotypes have not been addressed. Clonal analyses at single progenitor level may clarify both these points. Furthermore, much remains to be understood on the regulatory mechanisms, likely

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including epigenetic modifications, that drive the specification and maintenance of the diverse astrocyte phenotypes. In this respect, studies on the well-established heterogeneity of cerebellar astroglia can reveal fundamental mechanisms, exploitable as a reference point to further chart astrogliogenesis in other brain areas, where diversity in astroglia is far less evident and understood. On the other side, many are the open questions on cerebellar oligodendrocytes. The extra-/intracerebellar origin of oligodendrocytes waits to be ultimately and unequivocally demonstrated by time-lapse experiments and/or through abrogation of oligodendrogenesis in regions outside the cerebellum. Moreover, possible selective preference of cerebellar or extracerebellar oligodendrocytes for defined axon types or compartments have not been investigated so far. Similarly, it remains to be understood whether oligodendrocyte progenitors in the molecular layer, where very little myelin is present, engage in functions different from being a source of myelinating oligodendrocytes through the interaction with neurons and BG (Boda and Buffo 2014). Acknowledgments This work was funded by local grants of the University of Turin. VC was partly supported by a FENS fellowship.

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Granule Cell Migration and Differentiation Yutaro Komuro, Tatsuro Kumada, Nobuhiko Ohno, Jennifer K. Fahrion, Kathryn D. Foote, Kathleen B. Fenner, David Vaudry, Ludovic Galas, and Hitoshi Komuro

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Granule Cells Exhibit Different Mode, Speed, and Direction of Migration at Different Cortical Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mechanisms Involved in Granule Cell Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Control of Granule Cell Migration by Intrinsic Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glutamate Accelerates Granule Cell Migration Through the Activation of NMDA Receptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reciprocal Regulation of Granule Cell Migration in the EGL and the IGL by Somatostatin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Y. Komuro (*) Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA e-mail: [email protected] T. Kumada Faculty of Health and Medical Sciences, Tokoha University, Hamamatsu, Shizuoka, Japan e-mail: [email protected] N. Ohno Department of Anatomy, Division of Histology and Cell Biology, School of Medicine, Jichi Medical University, Shimotsuke-shi, Tochigi, Japan Division of Ultrastructural Research, National Institute for Physiological Sciences, Okazaki, Aichi, Japan e-mail: [email protected] J. K. Fahrion Research Support Core, Clinical Research Center, University Hospitals, Cleveland, OH, USA e-mail: [email protected] K. D. Foote · K. B. Fenner Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_7

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Halt of Granule Cell Migration in the PCL by PACAP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ca2+ Spikes Control Granule Cell Migration and Its Termination . . . . . . . . . . . . . . . . . . . . . . . . . Cyclic Nucleotide Signaling Plays a Role in the Control of Granule Cell Migration . . . . . Exposure to Alcohol, Methyl Mercury, and Light Alters Granule Cell Migration . . . . . . . . . . . . Alcohol Adversely Affects Granule Cell Migration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impairment of Granule Cell Migration by Methylmercury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Light Stimulus Controls Granule Cell Migration via Altering Insulin-Like Growth Factor 1 Signaling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Control of Granule Cell Differentiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The developing cerebellum granule cells migrate from their birthplace to their final destination. The active translocation of granule cells is essential for the formation of a well-organized cerebellar cortex. In this chapter, we will review (1) how granule cells migrate from their origin to their resident destination in the developing cerebellum, (2) the cellular and molecular mechanisms underlying granule cell migration, (3) how exposure to toxic chemicals and natural environmental factors affects the migration of granule cells, and (4) the cellular and molecular mechanisms underlying the differentiation of postmigratory granule cells. Keywords

Alcohol · BDNF · Bergmann glia · Ca2+ channels · Ca2+ dyes · Ca2+ signaling pathway · Ca2+ spikes · Caffeine · CaMK · CaN · Cerebellar slice · cAMP · cGMP · Cyclic nucleotide · Desensitization · EGL · Ethanol · Fetal alcohol spectrum disorder · Fetal Minamata disease · GABAA receptor · Glutamate · Granule cells · Granule cell precursor · Insulin-like growth factor 1 · IGL · Intrinsic program · Leading process · Light stimulus · Light-dark cycle · Methylmercury · Neuronal cell migration · Microexplant cultures · NMDA receptor · PACAP · Postmitotic neurons · Radial migration · Rate of migration ·

D. Vaudry Laboratory of Neuronal and Neuroendocrine Communication and Differentiation, Neuropeptides, Neuronal Death and Cell Plasticity Team, Normandie University, UNIROUEN, Inserm, Rouen, France Normandie University, UNIROUEN, Inserm, PRIMACEN, Rouen, France e-mail: [email protected] L. Galas Normandie University, UNIROUEN, Inserm, PRIMACEN, Rouen, France e-mail: [email protected] H. Komuro Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA

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Resting membrane potential · Somatostatin · Tangential migration · Time-lapse recording · tPA · Trailing process

Introduction After final cell division, postmitotic neurons migrate from their sites of origin to their final destination, where they reside during their entire adult life (Rakic 1990; Nadarajah and Parnavelas 2002). This movement of immature neurons is a fundamental cellular event essential for building large neuronal assemblies (Sidman and Rakic 1973; Valiente and Marin 2010; Mangaru et al. 2013). Distinct genetic mutations and environmental toxins can affect neuronal migration in humans, and result in abnormal development of the brain, leading to various neurological disorders (Gressens 2000; Guerrini and Parrini 2010; Huang et al. 2014; Buchsbaum and Cappello 2019; Pan et al. 2019; Schiller et al. 2019). During the last five decades, granule cell migration has been extensively studied and used as a model system for neuronal migration (Komuro and Yacubova 2003; Umeshima and Kengaku 2013; Mulherkar et al. 2014; Sanchez-Ortiz et al. 2014; Trivedi et al. 2014, 2017; Renaud and Chédotal 2014; Komuro et al. 2015; Kullmann et al. 2015; Legué et al. 2015; Men et al. 2015; Yong et al. 2015; Benon et al. 2017; Ryan et al. 2017; Zhang et al. 2017; Estep et al. 2018). This is because the mechanisms underlying granule cell migration are utilized during the migration of immature neurons in other brain regions (Komuro and Rakic 1998b; Jiang et al. 2008; Komuro et al. 2015; Galas et al. 2017). The role of neuron-glia interactions in neuronal migration was first discovered in the migration of granule cells along the Bergmann glial processes in the developing cerebellum (Rakic 1971). This discovery led to the findings that in the developing cerebrum immature neurons use radial glial processes as a scaffold for their migration (Rakic 1972). Likewise, the role of cell adhesion molecules in neuronal cell migration was first discovered in granule cells (Chuong et al. 1987; Chuong 1990; Rakic et al. 1994; Jakovcevski et al. 2009). To date, wide varieties of cell adhesion molecules, which play a critical role in neuronal cell migration, were identified in other regions of the brain (Milner and Campbell 2002; Schmid and Maness 2008). Moreover, the regulation of neuronal cell migration by neurotransmitters was first reported in granule cell migration (Komuro and Rakic 1993), followed by the discovery showing a key role for neurotransmitters in the migration of cerebral neurons (Heng et al. 2007; Luhmann et al. 2015). In this chapter, first, we will describe cortical layer-specific alterations of granule cell migration. Secondly, we will discuss how intrinsic programs as well as extracellular and intracellular signals control granule cell migration in a cortical layer specific manner. Thirdly, we will present the in vitro and in vivo studies examining how exposure to alcohol, methylmercury, and light stimuli affects the migration of granule cells. Lastly, we will review the mechanisms underlying the early differentiation of granule cells.

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Granule Cells Exhibit Different Mode, Speed, and Direction of Migration at Different Cortical Layers Granule cell precursors begin to proliferate in the upper rhombic lip of the mouse embryo by embryonic 10-day (E10). Thereafter, granule cell precursors start to migrate tangentially in a lateromedial and posteroanterior direction to cover the superficial zone of the embryonic cerebellum (Miale and Sidman 1961). By E15, most of the cerebellar surface is covered by granule cell precursors. The cell layer occupied by granule cell precursors is called the external granular layer (EGL). After clonal expansion in the EGL, granule cell precursors begin to produce postmitotic granule cells after birth. Postmitotic granule cells alter their shape concomitantly with changes in the mode and rate of migration as they migrate towards their final destination within the internal granular layer (IGL) (Komuro et al. 2001; Komuro and Yacubova 2003; Bénard et al. 2015). In this section, we will describe the translocation and transformation of postmitotic granule cells from the EGL to the IGL. The cortical layer-specific changes in granule cell migration are schematically represented in Fig. 1. The external granular layer (EGL): In the early postnatal cerebellum of mice, granule cell precursors actively proliferate every ~20 h at the top of the EGL. After their final mitosis, granule cells remain in the EGL for 20–48 h before initiating their radial migration across the molecular layer (ML), but the significance of this latent period is not well understood. A combined use of acute cerebellar slice preparations together with time-lapse imaging revealed that at the middle of the EGL, coincident with the extension of two horizontal processes, postmitotic granule cells start to migrate tangentially in the direction parallel to the longitudinal axis of the folium (Komuro et al. 2001). Their morphology and the speed of cell movement change systematically according to their position within the EGL (Komuro et al. 2001). For example, the rate of tangential cell movement is fastest (~14.8 μm/h) in the middle of the EGL when the cells have two short horizontal processes. As granule cells elongate their soma and extend longer horizontal processes at the bottom of the EGL, they move at a reduced rate (~12.6 μm/h). At the interface of the EGL and the ML, granule cells migrate tangentially at the slowest rate (~4.1 μm/h). During the tangential migration at the EGL-ML border, granule cells begin to extend descending processes from their somata into the ML. Granule cells retain two elongated horizontal processes while their nuclei and surrounding cytoplasm start to enter into the short vertical process descending into the ML (T-shape turning in Fig. 2a). It takes ~30 min for the complete translocation of the nucleus and surrounding cytoplasm from the horizontally extended process to the vertical process. After the completion of the nucleus reorientation within the vertical process, granule cell somata quickly enter the ML. As a result of the soma’s translocation within the leading process at the EGL-ML border, granule cells develop a thin trailing process connected with two horizontal processes (Fig. 8 in Komuro et al. 2001). These horizontal processes emitted from each side of the granule cell somata transform into future parallel fibers. Although the majority of parallel fibers develop from the two preexisting horizontal processes of tangentially migrating granule cells, there is

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Fig. 1 The three-dimensional representation of granule cell migration from the external granular layer (EGL) to the internal granular layer (IGL) in the early postnatal mouse cerebellum. 1, Extension of two uneven horizontal processes near the top of the EGL; 2, Tangential migration in the middle of the EGL; 3, Development of vertical process near the border between the EGL and the molecular layer (ML); 4, initiation of radial migration at the EGL-ML border; 5, Bergmann glia-associated radial migration in the ML; 6, Stationary state in the Purkinje cell layer (PCL); 7, Glia-independent radial migration in the IGL; 8, Completion of migration in the middle or the bottom of the IGL. Abbreviations: P, Purkinje cell; B, Bergmann glia; G, Golgi cell; g, postmigratory granule cell; cf, climbing fiber; mft, mossy fiber terminal

another mechanism for the formation of parallel fibers. For example, during the initiation of radial migration at the EGL-ML border, the tip of horizontally extended leading processes turns towards the ML, which is followed by the granule cell somata (L-shape turning in Fig. 2b). As a result, the horizontal trailing process of granule cells becomes one side of the parallel fibers. Subsequently, granule cells develop a new small process at the rear part of the vertically elongated somata. The new process extends toward the opposite direction of the extension of the horizontal trailing process and becomes the other side of the parallel fiber (Fig. 9 in Komuro et al. 2001). The molecular layer (ML): In the ML, granule cells have vertically elongated cell bodies, thin trailing processes, more voluminous leading processes, and migrate radially along the Bergmann glial processes (Komuro and Rakic 1995; Komuro and Yacubova 2003; Bénard et al. 2015). The rates of granule cell migration in the ML depend critically on the age of the cerebellum: the average rate of cell migration in the ML increases systematically as development proceeds (Komuro and Rakic 1995). Consequently, granule cells traverse the developing ML within a relatively

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Fig. 2 Micrographs showing two different modes of granule cell turning at the EGL-ML border of the P10 mouse cerebellum. (a) T-shape tuning of granule cells. a1–a25, Micrographs showing the extension of the vertical processes into the ML from the cell body of tangentially-oriented granule cells, which had two horizontally-extended axon-like processes. (b) L-shape turning of granule cells. b1–b34, Micrographs showing the turning of the tip of the horizontally-oriented leading process of granule cells towards the ML. Scale bar: 15 μm

constant time despite the doubling in width of the ML during the second postnatal week. Granule cell migration in the ML is characterized by alternations of short stationary phases with movement in a forward or backward direction. The net displacement of the cells depends on the duration and frequency of these phases as well as on the speed of movement (Komuro and Rakic 1995). At the bottom of the ML, the vertically elongated somata of granule cells move towards the Purkinje cell layer (PCL), while the length of their leading process gradually decreases (Komuro and Rakic 1998a). The shortening of the leading process is due to the advance of the granule cell somata within the leading process rather than to its active retraction. The distal portion of the leading process positioned in the PCL begins to extend large motile lamellipodia and filopodia. This is not a characteristic of the leading process of granule cells in the ML, which is invariably associated with Bergmann glial fibers and usually tapers without motile lamellipodia.

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The Purkinje cell layer (PCL): Once the somata of granule cells enter the PCL, its shape abruptly transforms from a vertically elongated spindle to a sphere (Komuro and Rakic 1998a). The rounded somata significantly slow its movement and stop completely in the PCL. The rounded somata remain stationary in the PCL for an average of 115 min, with times ranging from 30 to 220 min (Komuro and Rakic 1998a). However, highly motile lamellipodia and filopodia develop at the distal portion of the leading process, suggesting that the tips of leading processes actively search for potential guidance cues. After a prolonged stationary period, granule cells in the PCL begin to reextend their somata and leading processes. During this transformation, granule cells gradually accelerate the rate of their migration and cross the PCL-IGL border (Komuro and Rakic 1998a). The internal granular layer (IGL): The spindle-shaped granule cells migrate towards the bottom of the IGL at a rate comparable to that recorded for granule cells migrating along Bergmann glial fibers within the ML (Komuro and Rakic 1998a). The long axis of the granule cell somata remains oriented perpendicular to the PCL-IGL boundary line during this radial migration. Once the tip of a leading process approaches the IGL-white matter (WM) border, the granule cell somata become rounded. Granule cells then slow their migration and stop their movement near the IGL-WM border. In the postnatal 10-day-old (P10) mouse cerebellum, the majority of granule cells complete their migration at the bottom stratum of the IGL, while less than 20% of the cells settle in the middle or top strata (Komuro and Rakic 1998a). Although there are large differences in the total migrating distance of granule cells between different species and between different ages in a given species, in the P10 mouse cerebellum, granule cells first move tangentially ~220 μm in the EGL, and then migrate radially ~250 μm to attain their final position in the IGL. The average transit time of granule cells is ~25.0 h in the EGL, ~9.8 h in the ML, ~5.2 h in the PCL, and ~11.1 h to attain their final position in the IGL. Therefore, granule cells move from the top of the EGL through the ML and the PCL to their final position in the IGL within ~2 days (average, ~51 h) after the initiation of their tangential migration in the EGL (Komuro and Rakic 1998a; Yacubova and Komuro 2003).

Mechanisms Involved in Granule Cell Migration In this section, we will review the intrinsic and extrinsic mechanisms that are responsible for the regulation of granule cell migration in a cortical layer-specific manner.

Control of Granule Cell Migration by Intrinsic Programs Although the cortical layer-specific changes in granule cell migration are likely to be induced by responses to local environmental cues, the alterations of migratory

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behavior may also depend, at least in part, on an internal clock or intrinsic programs. This is because in microexplant cultures of the early postnatal mouse cerebellum, isolated granule cells sequentially go through three characteristic phases of migrating behavior and morphology without contacting other cells and processes (Yacubova and Komuro 2002a). This indicates that inherent (intrinsic) programs control alterations of granule cell migration, although molecular and genetic mechanisms underlying the programs remain to be determined. The three characteristic phases (phase I, phase II, and phase III) of sequential changes in migratory behavior of isolated granule cells and their morphology are as follows:

Phase I (PI, a Period of 0–20 h In Vitro) During the early stage of PI, granule cells repeatedly change the shape of their somata from spherical to spindle and vice versa (Fig. 3a). They frequently turn to the left or right without extending leading processes (Yacubova and Komuro 2002a). At the point at which granule cells change their direction of movement, they stop their movement, become round, and then extend their cell bodies in the direction of the upcoming movement. Shortly after the extension, the cells resume their movement parallel to the direction of the longitudinal axis of the cell bodies. During the middle stage of PI, granule cells repeatedly extend and withdraw short leading processes, and move at a fast rate only after the process fully extends. The extension of a new leading process towards a different direction is an essential prerequisite for changing the direction of cell movement (Fig. 3b). Near the end of PI, granule cells start to develop a new mode of turning behavior; the tip of the leading process turns in a new direction and then the cell body follows the changes (Fig. 3c). Granule cells exhibit a dynamic cycle of cell advancement and stationary phase every 3 h; the active cell migration lasts for ~2 h, and the stationary period is ~1 h in length. Phase II (PII, a Period of 20–40 h In Vitro) During the early stage of PII, granule cells develop another mode of turning as follows: (1) the tip of the leading process bifurcates, (2) both branches extend in the opposite direction, (3) one of the branches collapses and retracts, (4) the cell body follows the direction of extension of the remaining branch (Yacubova and Komuro 2002a). Granule cells exhibit this mode of turning behavior throughout PII (Fig. 3d). During the late stage of PII, granule cells become stationary for 2–3 h and retract their processes. Phase III (PIII, a Period of 40–60 h In Vitro) During the early stage of PIII, granule cells start to exhibit the initial signs of termination of their migration, which is a morphological change of the leading process (Yacubova and Komuro 2002a). During the late stage of PIII, granule cells slow down their movement and slightly increase their turnings. At the end of PIII, the cells become permanently stationary, extend a lamellipodium around the soma, and emit several thin processes (Fig. 3e). The majority of granule cells terminate their migration 50–60 h after the initiation of their movement.

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Fig. 3 Schematic representation of autonomous changes in granule cell morphology and different modes of turning in vitro. Isolated granule cells go through three characteristic phases of behavior and morphology without cell-cell contact. Such alterations depend on elapsed time after an initiation of cultures. (a–c) The first phase (PI) is a period of 0–20 h in vitro, when granule cells initiate their migration. (d) The second phase II (PII) is a period of 20–40 h in vitro, when granule cells have their long leading processes and move at the fastest rate. (e) The third phase III (PIII) is a period of 40–60 h in vitro, when granule cells terminate their migration. In the early stage of PI, undifferentiated granule cells, which do not have a leading process, alter the direction of movement by reorientation of the longitudinal axis of their somata (shown in a). In the middle stage of PI, granule cells withdraw their process, and then extend a new process towards the direction of upcoming movement (shown in b). In the late stage of PI, turning of the tip of the leading process to a new direction is followed by their somata (shown in c). In PII, leading process bifurcates, and

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Time-Dependent Changes in Granule Cell Migration and Morphology by Intrinsic Programs There are distinct relationships between the migratory behavior of granule cells, their morphology, and the elapsed time after in vitro (Yacubova and Komuro 2002a). In PI, granule cells migrate at an average rate of 26.0 μm/h and exhibit the highest rate of turning behavior (1.3 turns/h), when the cells have multiple (3.7 processes/ cell) and short (20.8 μm) processes. The length of the cycle of cell movement and stationary state is shortest (218 min). In PII, granule cells extend a long and thick leading process-like process (55.6 μm) and exhibit an elongated cycle (244 min) of cell movement and stationary state. The rate of cell movement is fastest (33.1 μm/h), while the number of turning is lowest (0.3 turn/h). In PIII, granule cells slow down their movement (25.2 μm/h), but slightly increase the turning number (0.5 turn/h). The length of cycle of cell movement further increases to 297 min. These results suggest the existence of intrinsic (inherent) programs for controlling granule cell migration in a developmental stage-dependent manner. Possible Roles of Intrinsic Programs on the Regulation of Granule Cell Migration In Vivo Although the question of whether and how intrinsic programs regulate granule cell migration in vivo remains to be determined, the comparison between in vivo and in vitro migration suggests possible roles of intrinsic programs in granule cell migration in vivo (Yacubova and Komuro 2002a; Komuro and Yacubova 2003). First, in PII (20–40 h in vitro), granule cells have two long processes and move at the fastest rate, while in the ML (25–35 h after the initiation of migration) granule cells have a long leading process and a trailing process and move at an increased rate. This similarity suggests that granule cell migration in the ML is partially regulated by intrinsic programs. Secondly, the 2–3 h stationary state of granule cells at the late stage of PII suggests that the prolonged stationary state (an average of 115 min) of granule cells in the PCL (35–40 h after the initiation of migration) is controlled by intrinsic signals. Thirdly, in PIII (40–60 h in vitro), granule cells terminate their migration without cell-cell contact and start to express the α6 subunit of GABAA receptors, which are expressed only when the cells arrive in the IGL. This suggests that granule cells in PIII are in a similar stage of differentiation with those in the IGL (40–50 h after the initiation of migration). The time schedule for completion of granule cell migration in vitro is quite similar to that for granule cell migration in vivo. This similarity suggests that an internal program (or clock) may be involved in termination of granule cell migration.

ä Fig. 3 (continued) the nucleus and surrounding cytoplasm enter into one of the branches (shown in d). In PIII, granule cells become permanently stationary, extend a lamellipodium around the soma, and emit several thin processes (shown in e). White asterisks indicate first images of granule cells taken during each series of observation. A white circle indicates a postmigratory granule cell in the late stage of PIII. Pseudocolor images of granule cells represent the order of image taken

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Glutamate Accelerates Granule Cell Migration Through the Activation of NMDA Receptors The role of extracellular glutamate in the regulation of granule cell migration was discovered in the early 1990s (Komuro and Rakic 1993, 1998b; Rakic and Komuro 1995). The first evidence came from a study examining whether inhibition of glutamate receptors affects the rate of granule cell migration. Blocking NMDAtype glutamate receptors with D-AP5 or MK-801 significantly decreases the rate of granule cell migration in the ML, while blocking kainate- and AMPA-type glutamate receptors with CNQX does not alter the rate of migration in the ML (Komuro and Rakic 1993). The role of the NMDA receptors in granule cell migration is further supported by evidence that changes in Mg2+ or glycine concentration affect the rate of granule cell movement. Because extracellular Mg2+ blocks NMDA receptor activity in a voltage-dependent manner and application of glycine potentiates NMDA receptor activity, it is expected that they both would influence granule cell migration. Indeed, the removal of Mg2+ from the medium significantly increases the rate of granule cell migration in the ML, whereas the rate of migration is reduced in a high Mg2+ medium in the ML (Komuro and Rakic 1993). Likewise, application of 10 μm glycine significantly increases the rate of granule cell migration in the ML (Komuro and Rakic 1993). These results demonstrate that the speed of granule cell migration is highly sensitive to small fluctuations in extracellular Mg2+ and glycine levels, implying that the activity of NMDA receptors modulates the rate of granule cell migration in the ML. The presence of spontaneous activation of NMDA receptors at the surface of migrating granule cells has been confirmed by patch-clamp analysis (Rossi and Slater 1993). The frequency of spontaneous NMDA receptor-coupled channel activity is low in the EGL, with large increases recorded in migrating neurons of the ML (Rossi and Slater 1993). Furthermore, single-channel recordings reveal developmentally related changes in the biophysical properties of the NMDA receptors during the course of granule cell differentiation (Farrant et al. 1994), suggesting that migrating granule cells express one or more specific receptor subunits that are distinct from those comprising the receptors present in mature granule cells. Indeed, migrating granule cells co-express the NR1 and NR2A or NR2B subunits, whereas postmigratory cells in the IGL express the NR1 and NR2C types (Farrant et al. 1994; Monyer et al. 1994). This progressive alteration in subunit composition could account for a change in NMDA receptor function during development. Moreover, there is evidence that the sensitivity of the NMDA receptors on granule cells in the EGL to glutamate increases during the course of cerebellar development (Rossi and Slater 1993). This increase can account for the acceleration of granule cell migration during the late stages of cerebellar development. The question of how NMDA receptors of migrating granule cells could be activated is intriguing, because the cells do not form synapses before the completion of their translocation in the IGL. One possibility is that endogenous extracellular glutamate may activate the immature form of the NMDA receptor by nonsynaptic means. Interestingly, the elevation of extracellular glutamate concentrations by

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inhibiting glutamate uptake by astrocytes increases the frequency of spontaneous NMDA receptor-coupled channel activity (Rossi and Slater 1993) and significantly accelerates the rate of granule cell movement in the ML (Komuro and Rakic 1993). These results suggest that endogenous extracellular glutamate is an important signal for the activation of NMDA receptors and that the increase of extracellular glutamate levels could enhance the rate of granule cell migration until the concentration reaches a toxic level (Marret et al. 1996). Several possible sources alone or in combination could be sufficient to activate NMDA receptors in migrating granule cells. Glutamate released from cultured astrocytes in response to local signals causes an activation of NMDA receptors in neighboring neurons (Parpura et al. 1994; Pon and Robinson 1994). Therefore, it is possible that Bergmann glial cells, which belong to the astrocyte cell class, release glutamate in response to local signals and influence the rate of granule cell migration by regulating the activity of NMDA receptors. The intimate association and large mutually shared surface area that exists between Bergmann glial processes and adjacent migrating granule cells could considerably facilitate this process. Furthermore, parallel fibers (the axons of postmigratory granule cells) are the most obvious source of extracellular glutamate in the ML (Levi et al. 1991). Because migrating granule cells do not form synapses with other cells, any glutamate released by parallel fibers must activate the NMDA receptor of migrating granule cells in a paracrine manner. Nonsynaptic activation of the NMDA receptor by extracellular glutamate has been observed in migrating granule cells (Rossi and Slater 1993).

Reciprocal Regulation of Granule Cell Migration in the EGL and the IGL by Somatostatin The role of somatostatin (SST), a neuropeptide, in the control of granule cell migration was discovered in the early 2000s (Yacubova and Komuro 2002b). Somatostatin has two bioactive products, somatostatin-14 (SST-14) and somatostatin-28 (SST-28), which is an isoform of SST-14 extended at the N-terminus (Schindler et al. 1996; Patel 1997). Five somatostatin receptors (SSTRs) have been cloned and named SSTR1-5 according to their order of identification. Both SST-14 and SST-28 bind to all five somatostatin receptors. It has been expected that SST may play a critical role in neurogenesis or neural differentiation, because numerous brain regions, including the cerebral cortex and cerebellum, exhibit high levels of SST and its receptor early in development (Maubert et al. 1994; Thoss et al. 1996). Postmitotic granule cells express all five types of SSTRs before an initiation of migration, while differentiated granule cells in the adult cerebellum do not express the receptors (Gonzalez et al. 1990; Viollet et al. 1997). High levels of SST are present along the migratory route of granule cells and at their final destination (Yacubova and Komuro 2002b). During periods of granule cell migration, SST-14 is present in Purkinje cells, Golgi cells, and climbing fibers, while SST-28 is present in Golgi cells and mossy fiber terminals (Yacubova and Komuro 2002b). The use of cerebellar slices obtained from P10 mice reveals that the addition

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of exogenous SST-14 or SST-28 to the medium significantly increases the rate of granule cell migration in the EGL, slightly decreases the rate in the ML, and significantly decreases the rate in the IGL (Yacubova and Komuro 2002b). In contrast, the addition of a SST antagonist (AC-178,335) to the medium significantly decreases the rate of granule cell migration in the EGL, slightly increases the rate in the ML, and significantly increases the rate in the IGL (Yacubova and Komuro 2002b). These results indicate that endogenous SST differentially controls granule cell migration in the EGL, the ML, and the IGL. SST accelerates the tangential migration of granule cells near their birthplace within the EGL, but slows down radial migration near their final destination within the IGL. The next question is whether SST acts directly on migrating granule cells or acts on other cells, which then indirectly influence granule cell migration. The use of microexplant cultures of P0-P2 mouse cerebella demonstrates that the application of exogenous SST-14 or SST-28 significantly increases the rate of granule cell movement at 1 day in vitro, while exogenous SST-14 or SST-28 substantially decreases the rate at 2 days in vitro (Yacubova and Komuro 2002b). These results suggest that SST directly acts on migrating granule cells in a developmental stage-specific manner. The use of Ca2+ indicator dyes reveals that SST-14 increases the size and frequency of Ca2+ spikes of granule cells at 1 day in vitro, whereas SST-14 eliminates Ca2+ spikes at 2 days in vitro (Yacubova and Komuro 2002b). An increase in the rate of granule cell movement follows the enlargement of Ca2+ spikes at 1 day in vitro, while the elimination of Ca2+ spikes at 2 days in vitro decreases the rate (Yacubova and Komuro 2002b). These results suggest that the differential effects of SST at 1 day in vitro and 2 days in vitro on Ca2+ spikes might explain how SST switches its effect on granule cell migration from acceleration at the early phase of migration to deceleration at the late phase of migration.

Halt of Granule Cell Migration in the PCL by PACAP The role of pituitary adenylate cyclase-activating polypeptide (PACAP) in the control of granule cell migration was first discovered in the mid-2000s (Cameron et al. 2007). PACAP, a member of the secretin/glucagon/vasoactive intestinal polypeptide family, is known to control physiological functions of a wide range of cells (Botia et al. 2007; Vaudry et al. 2009). PACAP has two bioactive products, PACAP38 and PACAP27 (Vaudry et al. 2009). PACAP27 is the N-terminal 27-amino acid sequence of PACAP38. There are three types of PACAP receptors (PAC1, VPAC1, and VPAC2), which belong to the class B G-protein-coupled receptor superfamily (Vaudry et al. 2009). There is a unique pattern of endogenous PACAP expression in the developing cerebellum: PACAP is present sporadically in the bottom of the ML, expressed intensively in the PCL, and dispersedly throughout the IGL (Cameron et al. 2007, 2009). PACAP is expressed by Purkinje cell dendrites in the ML, Purkinje cell somata in the PCL, and mossy fiber terminals in the IGL (Cameron et al. 2007). Therefore, endogenous PACAP is highly expressed in the

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route of granule cell migration. Granule cell precursors and postmitotic granule cells are devoid of PACAP (Cameron et al. 2007), but they express high levels of PAC1 receptors prior to the initiation of their migration (Basille et al. 1993, 2000, 2006). After the completion of migration, granule cells start to lose PAC1 receptors. Granule cells and its precursors in the EGL also express VPAC1 receptors at a much lower level than the PAC1 receptors, but do not express VPAC2 receptors. The use of microexplant cultures of early postnatal mouse cerebellum demonstrates that application of exogenous PACAP38 reduces the rate of granule cell migration, while application of its antagonist (PACAP6-38) does not affect the rate (Cameron et al. 2007). Furthermore, the use of cerebellar tissue slices obtained from the early postnatal mouse also demonstrates that the application of exogenous PACAP38 slows down the radial migration of granule cells in the ML (Cameron et al. 2007; Bénard et al. 2015). Collectively, these results indicate that PACAP acts on granule cell migration as a “brake” (stop signal) for cell movement. To our surprise, the use of cerebellar tissue slices reveals that the effect of exogenous PACAP on granule cell migration varies among each cortical layer (Cameron et al. 2007). The application of exogenous PACAP38 significantly reduces granule cell motility in the EGL and ML, but fails to alter their movement in the PCL and the IGL. How does this happen? The answer lies in the differing expression of endogenous PACAP in different cortical layers (Cameron et al. 2007). The use of PACAP6-38 (PACAP antagonist) elucidates the role of endogenous PACAP38 in granule cell migration. The application of PACAP6-38 significantly increases granule cell motility in the PCL, but does not alter motility in the EGL, ML, and IGL (Cameron et al. 2007), suggesting that the reduction of the rate of granule cell migration in the PCL is caused by endogenous PACAP release. At the top of the IGL, where high levels of endogenous PACAP are present, granule cells migrate at a speed comparable to that observed in the ML (Cameron et al. 2007). Furthermore, the application of exogenous PACAP or its antagonist does not significantly alter granule cell migration in the IGL (Cameron et al. 2007). How does this happen? Although the mechanisms underlying the mysterious effects of PACAP on granule cell migration in the IGL remain to be determined, there is a possible explanation. For example, before entering the IGL, granule cells may lose their response to PACAP38 via the desensitization of PACAP receptors. This occurs because PACAP receptors undergo a rapid desensitization after an initial activation, as seen in other G protein-coupled receptors (Vaudry et al. 2009). Although the continuous application of PACAP first reduces the rate of granule cell migration, the cells gradually recover their motility even in the presence of PACAP (Cameron et al. 2007). The average time required for returning the motility of granule cells to control levels under the continuous exposure to PACAP is ~2.1 h (Cameron et al. 2007), which is similar to the stationary period of the cells observed in the PCL (~1.9 h) (Komuro and Rakic 1998a). Furthermore, the recovery from the PACAP-induced reduction of granule cell motility is delayed by inhibiting protein kinase C (PKC). This provides additional evidence that PACAP receptors undergo desensitization in the PCL and IGL, because the G-protein-coupled receptor kinases, which mediate the desensitization of PACAP receptors, are sensitive to changes in the activity of

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PKC (Vaudry et al. 2009). Taken together, these results suggest that after an initial response to endogenous PACAP in the PCL, PACAP receptors on granule cells undergo desensitization, which allows the cells to actively migrate within the endogenous PACAP-rich IGL. Recent studies demonstrate that PACAP stimulates the expression and release of the serine protease tissue-type plasminogen activator (tPA) from granule cells (Raoult et al. 2011). The inhibition of tPA activity by the application of plasminogen activator inhibitor 1 results in a significant reduction of the rate of granule cell migration in the ML and PCL (Raoult et al. 2014). These results suggest dual roles of PACAP in granule cell migration: (1) PACAP decelerates the migration of granule cells via the activation of PACAP receptors (mainly PAC1 receptors) and (2) PACAP accelerates the migration via tPA-induced degradation of the extracellular matrix.

Ca2+ Spikes Control Granule Cell Migration and Its Termination In the early 1990s, the combined use of cerebellar slices of early postnatal mice and pharmacological tools revealed the role of voltage-gated Ca2+ channels, especially the N-type Ca2+ channel, in granule cell migration (Komuro and Rakic 1992). Postmitotic granule cells in the EGL start to express N-type Ca2+ channels prior to the initiation of their migration (Komuro and Rakic 1992). The number of N-type Ca2+ channels on the plasmalemmal surface of granule cells rapidly increases during their migration to the IGL. The blockade of N-type Ca2+ channel activity by a specific antagonist significantly reduces the speed of granule cell migration in the ML, suggesting that the N-type Ca2+ channels play a key role in controlling the speed of granule cell migration in the ML (Komuro and Rakic 1992; Rakic and Komuro 1995). In the middle of the 1990s, the role of intracellular Ca2+ levels in granule cell migration was examined because the activation of N-type Ca2+ channels induces the elevation of intracellular Ca2+ levels by increasing the Ca2+ influx. The use of Ca2+ indicator dyes reveals that migrating granule cells exhibit dynamic changes in intracellular Ca2+ levels of their somata (Komuro and Rakic 1996). In microexplant cultures of early postnatal mouse cerebella, Ca2+ spikes in the granule cell somata occur 4–24 times per hour, with average frequencies of 13/h. There is a positive correlation between the speed of granule cell migration and both the amplitude and frequency components of Ca2+ spikes (Komuro and Rakic 1996). The experimental reduction of the Ca2+ influx by lowering extracellular Ca2+ concentrations or blocking Ca2+ channels results in a decrease in the amplitude and frequency of Ca2+ spikes in the granule cell somata. This reduction is linearly related to the speed of granule cell movement (Komuro and Rakic 1996), suggesting that the migration of granule cells in vitro is controlled by the combination of the amplitude and frequency of Ca2+ spikes. During the mid-2000s, the combined use of cerebellar slices of early postnatal mouse and Ca2+ indicator dye (Oregon Green 488 BAPTA-1) demonstrated that granule cells exhibit a distinct pattern of Ca2+ spikes as they migrate in different cortical layers (Kumada and Komuro 2004; Komuro and Kumada 2005). The

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changes in the frequency of Ca2+ spikes in the granule cell somata in each cortical layer are as follows:

EGL At the top of the EGL, granule cell precursors exhibit Ca2+ spikes in their somata with a low frequency (average frequency, 8.3/h). The intervals of occurrences are regular and the amplitude is uniform. Concomitant with the initiation of tangential migration at the middle of the EGL, postmitotic granule cells significantly increase the frequency of Ca2+ spikes (20.9/h). The Ca2+ spikes gradually decrease in number at the bottom of the EGL (15.9/h) and the EGL-ML border (12.8/h), and the rhythm becomes irregular, containing short, silent periods. ML Once granule cells enter the ML, the cells slightly increase the number of Ca2+ spikes (15.1/h at the top of the ML, and 17.2/h at the middle). However, at the bottom of the ML, the frequency of Ca2+ spikes gradually decreases to 12.2/h and the amplitude of Ca2+ spikes becomes variable. PCL Upon entering the PCL, granule cells significantly reduce the frequency of Ca2+ spikes with long, silent periods and decrease the amplitude of Ca2+ spikes. The average frequencies of Ca2+ spikes are 7.3/h at the top of the PCL and 6.9/h at the bottom. IGL At the top of the IGL, granule cells significantly increase the frequency of Ca2+ spikes (15.1/h), although the rhythms are irregular and the amplitudes are variable. As granule cells migrate through the middle of the IGL, the frequency of Ca2+ spikes gradually decreases to 9.3/h and the amplitude becomes smaller. At the bottom of the IGL, the Ca2+ spikes disappear, or significantly decrease in frequency (2.4/h). The frequency of Ca2+ spikes in the granule cell somata dynamically changes along the migratory pathway and positively correlates with the rate of cell migration (correlation coefficient, 0.85) (Kumada and Komuro 2004). Granule cells reduce the frequency of Ca2+ spikes and the rate of cell movement at each boundary between cortical layers. These results suggest that the frequency of Ca2+ spikes is one of the factors that control the alterations of granule cell migration in a cortical layerdependent manner. There is evidence suggesting that alteration of the frequency of Ca2+ spikes directly affects granule cell migration. Reducing Ca2+ influx and decreasing internal Ca2+ release result in a significant reduction of the frequency of Ca2+ spikes in the granule cell somata and a slowdown of migration at the top of the IGL (Kumada and Komuro 2004). Furthermore, inhibiting Ca2+ signaling-upstream by blocking phospholipase C (PLC) decreases the frequency of Ca2+ spikes and slows down granule cell movement. Likewise, the inhibition of Ca2+ signaling-downstream by blocking protein kinase C (PKC) and Ca2+/calmodulin results in a significant reduction of

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Ca2+ spike frequency and migration rate (Kumada and Komuro 2004). These results demonstrate that reduction of Ca2+ spike frequency in the granule cell somata is accompanied by slowdown of cell movement, implying that the Ca2+ spike frequency provides an intracellular signal for controlling the rate of granule cell migration. At their final destination within the IGL, granule cells lose Ca2+spikes or significantly reduce the frequency (Kumada and Komuro 2004; Komuro and Kumada 2005). The loss (or reduction) of Ca2+ spikes is not caused by physiological deterioration after a prolonged period of observation, because 2–5 h later postmigratory (stationary) granule cells resume spontaneous Ca2+ spikes (Kumada and Komuro 2004; Komuro and Kumada 2005). Time-lapse observation of intracellular Ca2+ levels and cell movement reveals the sequence of the loss of Ca2+ spikes and the completion of granule cell migration (Kumada and Komuro 2004; Komuro and Kumada 2005). At the bottom of the IGL, granule cells initially migrate with variable amplitudes of Ca2+spikes but completely lose Ca2+ spikes before becoming permanently stationary. The average time lag between the loss of Ca2+ spikes and the cessation of migration is 16.8 min with a range of 5–27 min. These results suggest that the loss of Ca2+ spikes is prerequisite for completing granule cell migration at their final destination. The loss of Ca2+ spikes may be induced by external stop signals or contact with other cells and processes, but intrinsic programs may also be responsible. The use of microexplant cultures of early postnatal mouse cerebella reveals that during a period of active cell movement, granule cells exhibit spontaneous Ca2+ spikes in their somata, and the Ca2+ spike frequency depends on the elapsed time after plating (Kumada and Komuro 2004). Importantly, the Ca2+ spikes disappear or significantly reduce their occurrences when granule cells stop migrating at 50–60 h in vitro, although 1–3 h later the postmigratory granule cells resume generating the Ca2+ spikes (Kumada and Komuro 2004). The loss of Ca2+ spikes always precedes the completion of migration. The average time lag between the loss of Ca2+ transients and the cessation of migration is 11.6 m with a range of 3–21 min. The increase of Ca2+ spike frequency by stimulating internal Ca2+ release significantly accelerates granule cell migration at the final phase of migration (50–60 h in vitro), leading to a delay in the completion of migration (Kumada and Komuro 2004). These results suggest that intrinsic programs may set the timing of the loss of Ca2+ spikes in granule cells at approximately 50–60 h in vitro and may trigger the completion of migration. It is not well understood how Ca2+ spikes control granule cell motility, but there are possible scenarios (Kumada and Komuro 2004; Komuro and Kumada 2005; Komuro et al. 2015). One possibility is that Ca2+ spikes regulate the dynamic assembly and disassembly of cytoskeletal elements required for the operation of a force-generating mechanism involved in granule cell movement. Furthermore, Ca2+ spikes may modulate the repetitive formation and elimination of binding sites between granule cells and their migratory substrates. Ca2+ spikes may control conformational changes of cell adhesion molecules, such as integrins, which are expressed on the plasma membrane of granule cells. At present, it is not well known

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about how the loss of Ca2+ spikes induces the cessation of granule cell migration. One possibility is that the loss of Ca2+ spikes might cause changes in the Ca2+-dependent activation of specific enzymes, which in turn affects the phosphorylation state or extent of proteolysis of large number of proteins. These changes could induce the rearrangement of cytoskeletal components that are required for the completion of granule cell migration.

Cyclic Nucleotide Signaling Plays a Role in the Control of Granule Cell Migration Real-time recordings of cell movement in microexplant cultures of the early postnatal mouse cerebellum reveal that cyclic adenosine 30 ,50 -monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) signaling control granule cell migration in opposing ways (Kumada et al. 2006). In the case of cAMP signaling, stimulating adenylyl cyclase (AC) with forskolin, which is upstream of cAMP signaling, decelerates the migration of granule cells (Kumada et al. 2006). In contrast, inhibiting protein kinase A (PKA) with PKI, which is downstream of cAMP signaling, accelerates the migration (Kumada et al. 2006). The application of Sp-cAMPS (a competitive cAMP agonist) decelerates the migration, whereas the application of Rp-cAMPS (a competitive cAMP antagonist) accelerates the migration (Kumada et al. 2006). In the case of cGMP signaling, stimulation with Br-cGMP (a cGMP analogue) accelerates the migration of granule cells, whereas inhibition with Rp-8-pCPT-cGMPS (a cGMP antagonist) decelerates the migration (Kumada et al. 2006). Taken together, these results indicate that cAMP signaling acts as a “brake” on granule cell movement, while cGMP signaling acts as an “accelerator.” cAMP and cGMP signaling may control granule cell migration by altering Ca2+ signaling because both cAMP and cGMP pathway interact with Ca2+ signaling. As expected, stimulating cAMP signaling with forskolin reduces the Ca2+ spike frequency in granule cells, whereas inhibiting cAMP levels with Rp-cAMPS increases the frequency (Kumada et al. 2006). However, stimulating cGMP signaling with Br-cGMP does not alter the Ca2+ spike frequency (Kumada et al. 2006). These results suggest that cAMP signaling controls granule cell migration, at least in part, via altering Ca2+ signaling, whereas cGMP signaling controls migration without affecting Ca2+signaling. Cyclic nucleotide signaling also affects the turning of migrating granule cells in vitro and in vivo (Kumada et al. 2010). In microexplant cultures of the early postnatal cerebellum, inhibiting cAMP production with 9CP-Ade (an adenylyl cyclase inhibitor) increases the frequency of granule cell turning (Kumada et al. 2010). Likewise, inhibiting cAMP signaling with Rp-cAMPS or inhibiting the activity of PKA with PKI increases the frequency of granule cell turning, while stimulating cAMP signaling with forskolin or Sp-cAMPS does not affect the frequency (Kumada et al. 2010). On the other hand, stimulating cGMP signaling with Br-cGMP, or inhibiting cGMP signaling with Rp-8-pCPT-cGMPS or ODQ (a guanylyl cyclase inhibitor), does not alter the frequency of granule cell turning

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(Kumada et al. 2010). In addition, in vivo studies reveal that the injection of Rp-cAMPS into the subarachnoid space between the skull and the surface of the cerebellum of P10 mice increases the number of granule cells turning towards the ML at the EGL-ML border, while the injection of Br-cGMP fails to alter the number of granule cells turning (Kumada et al. 2010). These results indicate that inhibiting cAMP signaling increases the occurrence of granule cell turning, whereas cGMP signaling is not involved in controlling the occurrence of granule cell turning. Cellular mechanisms underlying cAMP-controlled turning of granule cells remain to be examined, but there are some hints. It has been shown that changes in the ratio of cAMP/cGMP or the cytoplasmic cAMP gradients affect neuronal growth cone turning (Nishiyama et al. 2003; Munck et al. 2004), suggesting that alterations of cAMP signaling may induce the turning of the leading process of migrating granule cells (Kumada et al. 2010). Furthermore, it has been reported that cAMP signaling affects the distribution of F-actin in the somata of migrating neurons (Haase and Bicker 2003), suggesting that alterations of cAMP signaling are prerequisite for the reorientation of the soma to a new direction of migration. Moreover, phosphorylation by PKA can switch off the activity of oncoprotein 18, a regulator of microtubule dynamics (Gradin et al. 1998). Thus, the changes in PKA activity may play a role in changing the direction of cell movement by controlling the behavior of the leading process by altering the microtubule dynamics.

Exposure to Alcohol, Methyl Mercury, and Light Alters Granule Cell Migration In this section, we will discuss how toxic chemicals (such as alcohol and methyl mercury) and natural environmental factors (such as light) affect the migration of granule cells.

Alcohol Adversely Affects Granule Cell Migration Alcohol is presently the most common chemical teratogen causing malformation and mental deficiency in humans (Clarren and Smith 1978; Clarren et al. 1978). Prolonged exposure to alcohol during gestation and lactation correlates with a pattern of abnormal development in newborns (Marcus 1987). This developmental disturbance is known as “fetal alcohol spectrum disorder” (FASD) (Sokol et al. 2003). Children with FASD often show neurological signs associated with cerebellar damages such as delayed motor development, problems with fine tasks, and ataxia (Sokol et al. 2003). Multiple aspects of central nervous system development are affected by alcohol (Marcus 1987; Riley and McGee 2005; Welch-Carre 2005). Among them, striking abnormalities involve the impairment of neuronal migration (Miller 1986, 1993). However, until recently, little was known regarding how alcohol affects neuronal cell migration (Kumada et al. 2007). Real-time observation of cell movement in cerebellar slices of early postnatal mice demonstrates that

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application of ethanol immediately slows granule cell migration in a dose-dependent manner (Kumada et al. 2006). Application of 10 mM ethanol (equivalent to blood ethanol level Purkinje cell synapses in the cerebellum. J Neurosci 17:9104–9112 Qiu CH, Shimokawa N, Iwasaki T, Parhar IS, Koibuchi N (2007) Alteration of cerebellar neurotropin messenger ribonucleic acids and the lack of thyroid hormone receptor augmentation by staggerer-type retinoic acid receptor-related orphan receptor-alpha mutation. Endocrinology 148:1745–1753 Rakic P (1972) Extrinsic cytological determinants of basket and stellate cell dendritic pattern in the cerebellar molecular layer. J Comp Neurol 146:335–354 Rakic P (1973) Kinetics and proliferation and latency between final cell division and onset of differentiation of cerebellar stellate and basket neurons. J Comp Neurol 147:523–546 Ramon y Cajal S (1909) Histologie du système nerveux de l'homme et des vertébrés. II. A. Maloine, Paris Richardson CA, Leitch B (2002) Cerebellar Golgi, Purkinje, and basket cells have reduced gammaaminobutyric acid immunoreactivity in stargazer mutant mice. J Comp Neurol 453:85–99 Rieff HI, Corfas G (2006) ErbB receptor signaling regulates dendrite formation in mouse cerebellar granule cells in vivo. Eur J Neurosci 23:2225–2229 Rio C, Rieff HI, Qi P, Khurana TS, Corfas G (1997) Neuregulin and erbB receptors play a critical role in neuronal migration. Neuron 19:39–50 Rodolosse A, Chalaux E, Adell T, Hagege H, Skoudy A, Real FX (2004) PTF1alpha/p48 transcription factor couples proliferation and differentiation in the exocrine pancreas [corrected]. Gastroenterology 127:937–949 Rouaux C, Arlotta P (2010) Fezf2 directs the differentiation of corticofugal neurons from striatal progenitors in vivo. Nat Neurosci 13:1345–1347 Schilling K, Oberdick J (2010) The treasury of the commons: making use of public gene expression resources to better characterize the molecular diversity of inhibitory interneurons in the cerebellar cortex. Cerebellum 8:477–489 Schilling K, Dickinson MH, Connor JA, Morgan JI (1991) Electrical activity in cerebellar cultures determines Purkinje cell dendritic growth patterns. Neuron 7:891–902 Schuller U, Heine VM, Mao J, Kho AT, Dillon AK, Han YG, Huillard E, Sun T, Ligon AH, Qian Y, Ma Q, varez-Buylla A, McMahon AP, Rowitch DH, Ligon KL (2008) Acquisition of granule neuron precursor identity is a critical determinant of progenitor cell competence to form Shh-induced medulloblastoma. Cancer Cell 14:123–134 Sekerkova G, Ilijic E, Mugnaini E (2004) Time of origin of unipolar brush cells in the rat cerebellum as observed by prenatal bromodeoxyuridine labeling. Neuroscience 127:845–858 Sellick GS, Barker KT, Stolte-Dijkstra I, Fleischmann C, Coleman RJ, Garrett C, Gloyn AL, Edghill EL, Hattersley AT, Wellauer PK, Goodwin G, Houlston RS (2004) Mutations in PTF1A cause pancreatic and cerebellar agenesis. Nat Genet 36:1301–1305

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Seto Y, Nakatani T, Masuyama N, Taya S, Kumai M, Minaki Y, Hamaguchi A, Inoue YU, Inoue T, Miyashita S, Fujiyama T, Yamada M, Chapman H, Campbell K, Magnuson MA, Wright CV, Kawaguchi Y, Ikenaka K, Takebayashi H, Ishiwata S, Ono Y, Hoshino M (2014) Temporal identity transition from Purkinje cell progenitors to GABAergic interneuron progenitors in the cerebellum. Nat Commun 5:3337 Shimono T, Nosaka S, Sasaki K (1976) Electrophysiological study on the postnatal development of neuronal mechanisms in the rat cerebellar cortex. Brain Res 108:279–294 Sidman RL, Lane PW, Dickie MM (1962) Staggerer, a new mutation in the mouse affecting the cerebellum. Science 137:610–612 Simat M, Ambrosetti L, Lardi-Studler B, Fritschy JM (2007a) GABAergic synaptogenesis marks the onset of differentiation of basket and stellate cells in mouse cerebellum. Eur J Neurosci 26:2239–2256 Simat M, Parpan F, Fritschy JM (2007b) Heterogeneity of glycinergic and gabaergic interneurons in the granule cell layer of mouse cerebellum. J Comp Neurol 500:71–83 Sotelo C (1977) Formation of presynaptic dendrites in the rat cerebellum following neonatal X-irradiation. Neuroscience 2:275–283 Spacek J, Parizek J, Lieberman AR (1973) Golgi cells, granule cells and synaptic glomeruli in the molecular layer of the rabbit cerebellar cortex. J Neurocytol 2:407–428 Sultan F, Bower JM (1998) Quantitative Golgi study of the rat cerebellar molecular layer interneurons using principal component analysis. J Comp Neurol 393:353–373 Swanson DJ, Steshina EY, Wakenight P, Aldinger KA, Goldowitz D, Millen KJ, Chizhikov VV (2010) Phenotypic and genetic analysis of the cerebellar mutant tmgc26, a new ENU-induced ROR-alpha allele. Eur J Neurosci 32:707–716 Takayama C, Inoue Y (2004a) Extrasynaptic localization of GABA in the developing mouse cerebellum. Neurosci Res 50:447–458 Takayama C, Inoue Y (2004b) Morphological development and maturation of the GABAergic synapses in the mouse cerebellar granular layer. Brain Res Dev Brain Res 150:177–190 Takayama C, Inoue Y (2004c) Transient expression of GABAA receptor alpha2 and alpha3 subunits in differentiating cerebellar neurons. Brain Res Dev Brain Res 148:169–177 Takayama C, Inoue Y (2005) Developmental expression of GABA transporter-1 and 3 during formation of the GABAergic synapses in the mouse cerebellar cortex. Brain Res Dev Brain Res 158:41–49 Tanaka I, Ezure K (2004) Overall distribution of GLYT2 mRNA-containing versus GAD67 mRNA-containing neurons and colocalization of both mRNAs in midbrain, pons, and cerebellum in rats. Neurosci Res 49:165–178 Tidcombe H, Jackson-Fisher A, Mathers K, Stern DF, Gassmann M, Golding JP (2003) Neural and mammary gland defects in ErbB4 knockout mice genetically rescued from embryonic lethality. Proc Natl Acad Sci U S A 100:8281–8286 Uusisaari M, Knopfel T (2010) GlyT2+ neurons in the lateral cerebellar nucleus. Cerebellum 9:42–55 Wall MJ, Usowicz MM (1997) Development of action potential-dependent and independent spontaneous GABAA receptor-mediated currents in granule cells of postnatal rat cerebellum. Eur J Neurosci 9:533–548 Wefers AK, Haberlandt C, Tekin NB, Fedorov DA, Timmermann A, van der Want JJL, Chaudhry FA, Steinhäuser C, Schilling K, Jabs R (2017) Synaptic input as a directional cue for migrating interneuron precursors. Development 144:4125–4136 Wefers AK, Haberlandt C, Surchev L, Steinhäuser C, Jabs R, Schilling K (2018) Migration of interneuron precursors in the nascent cerebellar cortex. The Cerebellum 17:62–71. https://doi. org/10.1007/s12311-017-0900-7 Weisheit G, Gliem M, Endl E, Pfeffer PL, Busslinger M, Schilling K (2006) Postnatal development of the murine cerebellar cortex: formation and early dispersal of basket, stellate and Golgi neurons. Eur J Neurosci 24:466–478

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Development of Glutamatergic and GABAergic Synapses

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Marco Sassoè-Pognetto and Annarita Patrizi

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Mossy Fibers and the Glomeruli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Parallel Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climbing Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Molecular Specificity of PF and CF Synapses and Heterosynaptic Competition . . . . . . . . . . . . . . GABAergic Interneurons of the Molecular Layer: Stellate and Basket Cells . . . . . . . . . . . . . . . . . Golgi Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Inhibitory Interneurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Axon Collaterals of Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deep Cerebellar Nuclei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

More than a century ago, Santiago Ramón y Cajal based on the cerebellum his initial description of neurons labeled with the silver impregnation method, obtaining evidence in favor of the neuron doctrine. It is perhaps less known that Ramón y Cajal also made an accurate description of cerebellar development, laying the foundation for successive studies of cell migration, neuronal differentiation, and synaptogenesis. Building on this work, subsequent analyses of cerebellar development have greatly increased the understanding of cellular and M. Sassoè-Pognetto (*) Department of Neuroscience “Rita Levi Montalcini”, National Institute of Neuroscience-Italy, Turin, Italy e-mail: [email protected] A. Patrizi Chica und Heinz Schaller-Stiftung Research Group, German Cancer Research Center (DKFZ), Heidelberg, Germany e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_12

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molecular events that regulate the assembly of synaptic circuits in the central nervous system. What makes the cerebellum a particularly useful model system is its delayed course of development, largely extending into postnatal life. This chapter describes the current state of knowledge relating to cerebellar synapse development, highlighting recent studies on the molecular and activity-dependent mechanisms that control the spatial specificity of synaptogenesis. Keywords

Ankyrin · Axon initial segment · Basket cells · Cerebellar cortex · Cerebellar glomeruli · Cerebellar mutants · Cerebellin · Cerebellum · Climbing fibers · Deep cerebellar nuclei · Dendritic spines · Dystroglycan · GABA · GABAA receptors · Gephyrin · GluD2 · Glutamate · Glutamate receptors · Glycine · Granule cells · Granule cell layer · Golgi cells · Heterologous synapses · Lugaro cells · Molecular layer · Mossy fibers · Neurofascin · Neurexin · Parallel fibers · Pinceau · Postnatal development · Purkinje cells · Purkinje cell layer · Spinogenesis · Staggerer · Stellate cells · Synapses · Synapse development · Synapse specificity · Synaptic competition · Synaptogenesis · Unipolar brush cells · Weaver

Introduction The cerebellum has a prolonged course of development, which extends abundantly into postnatal life (Wang and Zoghbi 2001; Millen and Gleeson 2008; Hashimoto and Hibi 2012). This feature, together with the availability of several natural mutants (Sotelo 1990) and, more recently, of cell-specific gene-targeting tools (Barski et al. 2000; Ango et al. 2004; Wulff et al. 2007; Briatore et al. 2010), has provided an almost unique opportunity for in vivo experimental analyses of neural circuit development. The cerebellar cortex has a relatively simple organization, consisting of only a few cell types that integrate two major inputs (Fig. 1). Purkinje cells (PCs), which are GABAergic, provide the only output of the cerebellar cortex, sending their axons to the deep cerebellar nuclei (DCN). PCs receive direct connections from climbing fibers (CFs), which originate from inferior olive neurons, and indirect connections from mossy fibers (MFs), which connect to granule cell dendrites within glomeruli in the granule cell layer (GCL). The axons of granule cells ascend to the molecular layer (ML), where they bifurcate and give rise to parallel fibers (PFs), which make synapses with the dendrites of PCs as well as other cerebellar neurons. Local inhibitory interneurons comprise stellate and basket cells, which modulate PC output in the ML, and Golgi cells, which provide feedback and feedforward inhibition to granule cells in the GCL. Despite the apparent simplicity of the cerebellar circuit, detailed quantitative information is not available for all categories of cerebellar synapses, and the appreciation of the spatiotemporal dynamics of synapse development is still incomplete. This kind of information is important for providing a framework for experimental analyses of neural circuit development. This chapter provides an overview of

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Fig. 1 Neuronal elements and basic circuitry of the cerebellar cortex. Unipolar brush cells, globular cells, and candelabrum cells are not represented. Two major afferent systems reach the cerebellar cortex: climbing fibers (CF) provide direct excitatory contacts to Purkinje cells (PC) and mossy fibers (MF) terminate in glomerular structures in the granule cell layer (GCL), in which they establish excitatory synapses (+) with the dendrites of granule cells (GC). A glomerulus is a complex of synapses, consisting of mossy fiber terminals (rosettes), surrounded by granule cell dendrites and Golgi cell axon terminals (gray circle). The ascending axons of granule cells reach the molecular layer (ML) and form parallel fibers (PF), which make glutamatergic synapses with Purkinje, stellate (SC), basket (BC), and Golgi (GO) cells. With the exception of granule cells, all cerebellar cortical neurons, including Purkinje cells, make inhibitory synaptic connections (
). A peculiar assembly of GABAergic axons is the pinceau, which is formed as basket cell axons surround the axon initial segment of Purkinje cells. The recently described Golgi-to-Golgi inhibitory synapses are not indicated in the diagram. DCN deep cerebellar nuclei, LU Lugaro cell, PCL Purkinje cell layer

the organization and development of cerebellar synapses and describes recent findings that are expanding the comprehension of cellular and molecular mechanisms that direct synapse assembly in specific cerebellar networks.

The Mossy Fibers and the Glomeruli MFs represent one of the two major afferent systems conveying information to the cerebellum. They arise from a variety of different sources in the brainstem and spinal cord (Rahimi-Balaei et al. 2015) and terminate forming characteristic “rosettes” within glomeruli in the GCL, where they make glutamatergic synaptic contacts

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with the dendrites of granule cells (Palay and Chan-Palay 1974; Ito 2006; Ito and Takeichi 2009; Kim et al. 2013). MFs originating from vestibular neurons can also contact the dendrites of unipolar brush cells, local glutamatergic neurons particularly abundant in the vestibulocerebellum (Mugnaini et al. 2011). In rodents, MFs start entering the gray matter at postnatal days 3–5 (P3-P5), contributing to the formation and expansion of the GCL. The first MF synapses have been observed at P6 (Fig. 2); however, it is only during the second postnatal week that synapse number increases considerably, reaching a peak at P15 (Altman 1972c; Hamóri and Somogyi 1983). Accordingly, electrophysiological investigations have recorded functional synaptic transmission between MFs and granule cells from P10 (Shimono et al. 1976; Cathala et al. 2005). It should be noted that the GCL expands progressively from the white matter toward the cerebellar surface, implying that at any given stage, deeper glomeruli are more mature than those located closer to the PCs. Cerebellar glomeruli undergo an extensive remodeling during a protracted period of postnatal development, which involves the transition from a “cup-like” to a “claw-like” configuration (Larramendi 1969). Hamóri and Somogyi (1983) have described a primary growth stage (P6–P15), characterized by a rapid enlargement of MF rosettes, an intense proliferation of postsynaptic dendrites and a remarkable increase in the number of synaptic junctions, and a subsequent prolonged stage (P15-P45), during which many synapses are eliminated and long synaptic appositions are segregated into smaller active zones (a process described by Larramendi (1969) as synaptic “waning”). The morphological remodeling of glomerular synapses is accompanied by a developmental acceleration of excitatory postsynaptic currents recorded from granule cells (Cathala et al. 2005). A notable feature of the development of MFs is that these axons never enter the external granular layer (EGL), where immature granule cells proliferate. This has

STELLATE CELLS development of the pinceau

BASKET CELLS PARALLEL FIBERS GOLGI CELLS primary growth stage

synaptic waning

MOSSY FIBERS pericellular nest

somato-dendritic translocation

CLIMBING FIBERS

E19

P0

P5

P7

P9

P12

P15

P21

P30

Fig. 2 Graphic representation of the development of synapses made by different types of cerebellar neurons and by cerebellar cortical afferents. The diagram is based on studies of the mouse and rat cerebellum (see the main text for references). There is still uncertainty about the precise dates of the onset and the conclusion of the synaptogenic period, as symbolized by the grading colors. Significant phases of the development of specific types of synapses are indicated

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been attributed to the fact that granule cell precursors produce a heparin-binding factor-dependent “stop” signal, which arrests MF extension above the PCs (Manzini et al. 2006). By contrast, differentiated granule neurons that have reached the GCL start producing synaptogenic factors, such as Wnt7a, FGF22, and cadherin-7 that stimulate synapse formation with MFs (Hall et al. 2000; Umemori et al. 2004; Kuwako et al. 2014). While developing MFs do not cross the PC layer, they can establish transient synapses with PCs, which are eliminated during the second postnatal week (Mason and Gregory 1984; Takeda and Maekawa 1989). The formation of MF-PC contacts is negatively regulated by retrograde negative signals released by PCs, such as BMP4 (Kalinovsky et al. 2011). Therefore, the specificity of MF connectivity depends on the interplay of positive signals that mediate synapse formation with the appropriate targets, i.e., granule cells, and repulsive factors that prevent the invasion of MFs into the EGL and promote the removal of transient MF-PC synapses. However, in agranular cerebella (e.g., in weaver and reeler mice), aberrant MF-PC synapses are maintained, suggesting that the absence of the correct target neurons can result in a stabilization of mismatched synapses (Sotelo 1990).

Parallel Fibers The axons of granule cells ascend to the ML, where they give rise to PFs, which are oriented perpendicularly to the plane of PC dendrites. PFs establish excitatory synapses with spines located on the distal dendrites of PCs (the so-called spiny branchlets), causing the PCs to discharge single action potentials (simple spikes). In addition, PFs also contact all other types of cerebellar neurons, including Golgi, Lugaro, basket, and stellate cells (Fig. 1). A single PF extends as long as 4–6 mm in the ML, passing through the dendrites of several hundred PCs (Eccles et al. 1967; Coutinho et al. 2004). In this way, one MF can affect thousands of PCs through several hundred PFs. It has been estimated in rats that the number of PF synapses on an individual PC may exceed 150.000 (Harvey and Napper 1991). PF synapses are distinguished by the presence of the postsynaptic δ2 glutamate receptor (GluD2), which is expressed exclusively by PCs. Rather than acting as a glutamate receptor, GluD2 has a fundamental role in mediating synaptic adhesion (Yuzaki 2003, see below). According to electron microscopic investigations, PFs establish the first synapses as soon as PCs start growing their dendrites in the developing ML. In rats, this occurs at the end of the first postnatal week and is followed by a period of intense synaptogenesis in conjunction with the expansion of the ML (Altman 1972a,b). The progressive proliferation of synapses from the bottom upward initially results in a gradient in the density of synaptic contacts across the ML. This gradient is no longer seen after P21 (a stage coinciding with the disappearance of the EGL), when synapse density becomes relatively uniform throughout the ML (Larramendi 1969; Robain et al. 1981). Interestingly, this developmental sequence is accompanied by a progressive switch of the vesicular glutamate transporters, VGlut1 and VGlut2, in PF terminals (Miyazaki et al. 2003). Thus, early PF terminals express VGlut2, which

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is gradually replaced by VGlut1 following an inside-out gradient. This replacement is accomplished by P30, after which PFs and CFs express differentially VGlut1 and VGlut2 (Fremeau et al. 2001; Ichikawa et al. 2002). The reasons for the developmental switching of VGlut subtypes are presently unclear. The analysis of PF synapse development has provided important insights into the sequence of events that occur during the formation of dendritic spines. In his pioneering electron microscopic studies, Larramendi (1969) noted that spines develop before they establish synaptic contacts with PFs, leading to the idea that the axon terminal has a minor role in spinogenesis (Yuste and Bonhoeffer 2004). Indeed, the analysis of mouse mutants with reduced numbers of granule cells, such as weaver, has revealed that spines develop in the distal spiny branchlets of PCs even in the absence of presynaptic input. Remarkably, these spines have apparently normal postsynaptic specializations, despite the fact that they face astrocytic processes (Sotelo 1990). Conversely, the study of the staggerer mouse, in which the formation of the spiny branchlets is selectively impaired, has revealed that PFs can differentiate presynaptic varicosities containing synaptic vesicles in the absence of their normal postsynaptic targets, although these varicosities eventually degenerate (Sotelo 1990). These observations suggest that neurons have an intrinsic capability to differentiate pre- and postsynaptic structures, although synaptic signaling seems to be required to provide long-term stability to synaptic specializations.

Climbing Fibers These cerebellar afferents originate from neurons of the inferior olive and provide direct synaptic input to PCs. CFs make synapses on spines located on the proximal dendritic domain of PCs and normally do not invade the distal dendrites innervated by PFs. CF synapses also differ from those made by PFs in that they do not contain the GluD2 receptor (Landsend et al. 1997), although this receptor is transiently expressed in spines innervated by CFs between P10 and P14 (Zhao et al. 1998). In the mature cerebellum, inferior olivary neurons contact on average seven PCs, while an individual PC is innervated by a single CF (Schild 1970). This one-to-one relationship is the result of the postnatal elimination of supernumerary CFs, which occurs during the second and third postnatal weeks (see below). In rats, one CF bears about 300 varicosities, each innervating a cluster of two to six PC spines (Palay and Chan-Palay 1974). These contacts are so strong that CFs generate a massive burst of action potentials known as “complex spikes.” CFs are crucial for cerebellar function: they convey signals regarding errors in motor control, and they induce long-term depression (LTD) in coactivated PF synapses. As a fact, deprivation of CF inputs causes severe movement disorders that are similar to the defects observed after cerebellum damage (Apps and Garwicz 2005). CFs provide the earliest synaptic inputs to PCs in the developing cerebellar cortex (Fig. 2). In rats, CF excitation of PCs after stimulation of the white matter has been reported at P3 (Shimono et al. 1976). However, other studies have revealed that transient CF-PC synapses may be present already in the prenatal cerebellum (Morara

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et al. 2001; Kita et al. 2014). CF development was divided by Ramón y Cajal (1890) in three stages: a “pericellular nest” stage, characterized by the formation of a dense plexus surrounding the cell body of PCs; a “capuchon” stage, when CFs are progressively displaced toward the developing dendritic stem; and a “young dendritic” stage, when CFs have left their perisomatic location and have invaded the dendritic arbor of PCs. During the “nest” stage (P4-P7 in mouse), multiple CFs make asymmetric synapses on protrusions arising from the PC soma (Larramendi 1969; Altman 1972b; Sotelo 2008; Ichikawa et al. 2011). In the following 2 weeks, a single CF is selectively strengthened relative to the others, becoming the monoinnervating CF in the adult. The “winner” CF eventually translocates from the cell body to the proximal dendrites of the PC, while surplus CFs, which are confined to the PC soma, are eliminated together with perisomatic spines (Crepel et al. 1976; Kano and Hashimoto 2009). The translocation of CFs from the soma to the proximal dendrites starts at P9 and is almost completed by P15 (Sotelo 2008; Hashimoto et al. 2009). This elimination process is one of the best characterized models of activitydependent synapse refinement that occurs during brain development. The elimination of CFs critically depends on neuronal activity and involves competition among afferent CFs, as well as heterosynaptic competition with PFs (see below). Several molecules and signaling pathways that mediate CF elimination have been identified (Kano et al. 2013). For example, the immediate early gene Arc/Arg3.1 in PCs mediates CF elimination downstream of P/Q-type voltage-dependent Ca2+ channels (Mikuni et al. 2013), while Semaphorin7A (Sema7A) mediates CF synapse elimination downstream of type 1 metabotropic glutamate receptors (mGluR1) (Uesaka et al. 2014). According to a recent study, brain-derived neurotrophic factor (BDNF) retrogradely acts on TrkB receptors in CFs and promotes their elimination. Notably, BDNF is regulated by mGluR1 and shares the same signaling with Sema7A for CF synapse elimination (Choo et al. 2017).

Molecular Specificity of PF and CF Synapses and Heterosynaptic Competition Several studies in the last few years have demonstrated that the formation of PF and CF synapses with PCs depends on distinct sets of adhesion proteins and secreted synaptic organizers that control synaptogenesis through distinct signaling pathways. Of particular relevance is GluD2, which is selectively localized in PC spines innervated by PFs and plays a key role in synapse formation and maintenance (Yuzaki 2003, 2010). Mice lacking GluD2 are ataxic and display a severe reduction in the number of PF-PC synapses, with the remaining synapses showing a mismatch between postsynaptic densities and presynaptic active zones, as well as impaired LTD (Kashiwabuchi et al. 1995; Kurihara et al. 1997; Takeuchi et al. 2005). Interestingly, the same defects have been observed in mice lacking cerebellin 1 precursor protein (Cbln1), a glycoprotein of the C1q/tumor necrosis factor family secreted from granule cell axons (Hirai et al. 2005). It has been demonstrated that GluD2 and Cbln1 belong to a tripartite molecular complex also comprising neurexin,

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a presynaptic cell-adhesion molecule, in which Cbln1 released from PFs mediates trans-synaptic interactions by linking postsynaptic GluD2 with presynaptic neurexin (Matsuda et al. 2010; Uemura et al. 2010; Pregno et al. 2013). Notably, Cbln1 also regulates the maturation of presynaptic PFs to match the size of the postsynaptic specialization (Ito-Ishida et al. 2012). Another member of the C1q family, the C1q-like family protein C1ql1, has also been implicated in synaptogenesis in PCs. C1ql1 is expressed in inferior olivary neurons, is secreted by CFs, and interacts in PCs with the cell-adhesion G proteincoupled receptor BAI3 (Sigoillot et al. 2015). BAI3 (from brain angiogenesis inhibitor 3) seems to be a general promoter of spinogenesis that stimulates the formation of both PF and CF synapses. However, the restricted expression of C1ql1 in CFs suggests that the C1ql1/BAI3 interaction mainly contributes to regulate the formation and maintenance of CF synapses and the extent of CF synaptic territory in PCs (Kakegawa et al. 2015; Sigoillot et al. 2015). It thus appears that distinct members of the C1q family are part of specific “protein codes” that control excitatory synaptogenesis in PCs (Sassoè-Pognetto and Patrizi 2017). The calcium channel type 1 inositol triphosphate receptor (IP3R1) also has been identified as an important regulator of spinogenesis in PCs (Sugawara et al. 2013). Mice lacking IP3R1 specifically in PCs show a dramatic increase in spine number and length, as well as impaired cerebellar LTD and severe ataxia. As mentioned above, PFs and CFs compete with each other to establish and maintain their dendritic territories, such that regression of one territory results in expansion of the other (Yuste and Bonhoeffer 2004; Cesa and Strata 2009; Kano and Hashimoto 2009). Notably, this competition is not restricted to the developing cerebellum but has been observed also in adult animals. Thus, a decrease in PF innervation (e.g., in mutant mice with reduced numbers of granule cells or in GluD2 mutant mice) results in retention of multiple CFs and an abnormal extension of CFs into the distal spiny branchlets that are normally occupied by PFs (Uemura et al. 2007; Miyazaki et al. 2010; Ichikawa et al. 2016). By contrast, a selective silencing of CFs (e.g., after lesioning the inferior olive) causes the emergence of supernumerary spines in the proximal dendrites of PCs, which are innervated by PFs. It has been proposed that CFs actively repress spinogenesis in the proximal dendritic domain of PCs, preventing the formation of synapses with PFs (Cesa and Strata 2009).

GABAergic Interneurons of the Molecular Layer: Stellate and Basket Cells PCs receive synaptic inhibition mainly from stellate and basket cells, collectively called molecular layer interneurons (MLIs). MLIs can be distinguished by labeling for parvalbumin and glutamic acid decarboxylase (GAD), although these proteins are also highly expressed in PCs (Celio 1990; Feldblum et al. 1993). On the other side, it is possible to selectively label PCs with antibodies against calbindin (Celio 1990) and carbonic anhydrase VIII (Patrizi et al. 2008). In the last few years, efforts have been made in identifying selective markers to differentiate between stellate and basket cells. Schilling and Oberdick (2009) showed that basket and stellate cells

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have differential expression of a small subset of genes; however, none of these genes have been functionally tested yet. Basket cells provide inhibitory synapses to the cell body and the most proximal dendrites of PCs and also form a unique plexus around the axon initial segment (AIS) called a pinceau (Fig. 1). In contrast, stellate cells make contacts with PC dendrites. These GABAergic cells receive excitatory input from PFs and can also be activated by spillover of glutamate released by CFs (Szapiro and Barbour 2007), causing feedforward and lateral inhibition of PCs (Ito 2006). Feedforward inhibition might serve to increase the temporal fidelity of synaptic integration and action potential generation. Indeed, the firing rate of PCs is strongly modulated by GABAergic inhibition, and selective deletion of GABAARs from PCs causes abnormal patterns of simple spikes, accompanied by impaired cerebellar learning (Wulff et al. 2009). MLIs are reciprocally interconnected by inhibitory synapses. In the mouse cerebellum, synapses between interneurons (including also synapses on Golgi cell dendrites) represent approximately 40% of all GABAergic synapses in the molecular layer (Briatore et al. 2010). This suggests that inhibition between interneurons has an important role in the cerebellar network, although it remains to be investigated how the strong synaptic coupling between MLIs aids cerebellar information processing. The development of GABAergic synapses has been analyzed with antibodies directed against GAD or the GABA transporter, GAT-1 (McLaughlin et al. 1975; Greif et al. 1991; Heckroth 1992; Yan and Ribak 1998; Rosina et al. 1999; Takayama and Inoue 2004, 2005), and more recently with antibodies raised against GABAAR subunits or other postsynaptic molecules (Patrizi et al. 2008; Viltono et al. 2008; Briatore et al. 2010). Mouse strains in which MLIs express the green fluorescent protein (GFP) have also been used to investigate the developmental profile of GABAergic innervation (Ango et al. 2004; Simat et al. 2007a; Sotelo 2008; Watt et al. 2009). These studies have revealed an inside-out sequence in the proliferation of synapses from the PC layer to the cerebellar surface. The period of inhibitory synapse development terminates only in the fourth postnatal week, when synapse density becomes uniform throughout the molecular layer (Patrizi et al. 2008; Viltono et al. 2008). Interestingly, the proportion of synapses on PCs and interneurons is rather constant from P10 to adulthood, suggesting synchronized synaptogenesis among different populations of cerebellar neurons (Briatore et al. 2010). According to Larramendi (1969), basket cells start innervating PCs at around P9. However, Sotelo (2008) has proposed that synaptogenesis between basket cell axons and PCs has already started by P7 (Fig. 2). This is also supported by the fact that GABAAR clusters are visible on the PC soma and the deeper part of the molecular layer already at P5 (unpublished observations), although it cannot be excluded that these early GABAergic synapses are made by PC axon collaterals (see below). The number of perisomatic synapses increases considerably during the second postnatal week, together with a strong decrease in the number of somatic spines innervated by CFs (see also Sotelo 2008; Viltono et al. 2008). The developmental switching of perisomatic innervation from CFs to basket cell axons has been investigated quantitatively in mice by light and electron-miscrocopic analyses (Ichikawa et al. 2011). The density of CF synapses on somatic PC spines peaks at P9, when CFs establish

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88% of perisomatic synapses, and decreases progressively until P20, when practically all CF synapses have been replaced by basket cell perisomatic synapses. The postsynaptic receptor phenotype also gradually changes from glutamatergic to GABAergic concurrently with the presynaptic switching. Interestingly, during the switching period, a substantial number of basket cell axons establish synapses on somatic spines, and GABAARs co-cluster with AMPA-type glutamate receptors beneath single basket cell terminals (Ichikawa et al. 2011). Basket synapses also undergo a process of “waning” (Larramendi 1969), consisting in a fragmentation of long synaptic appositions into multiple shorter active zones. Interestingly, these morphological rearrangements are accompanied by a developmental decrease in the amplitude of IPSCs recorded from PCs (Pouzat and Hestrin 1997). More recently, it has been shown that the synaptic “waning” is coincident with a gradual loss of the scaffolding molecule gephyrin from postsynaptic specializations, which is followed by a reduction in the size of GABAAR clusters (Viltono et al. 2008). Notably, gephyrin is retained at dendritic synapses of PCs, revealing a remarkable selectivity in the process of maturation of postsynaptic scaffolds in distinct subcellular compartments. A remarkable feature of the GABAergic innervation of PCs is the pinceau formation, a peculiar assembly of basket cell axons around the AIS (Ramón y Cajal 1911). The development of the pinceau has been revised recently by Sotelo (2008) using a combination of light- and electron-microscopic analyses. The descending branches of basket cell axons first enwrap the cell body of PCs, making perisomatic synapses (P7), and then reach the AIS by P9. The formation and maturation of the pinceau are a prolonged process that begins in the second postnatal week and extends well after P21 by a progressive recruitment of basket terminals. The targeting of basket axons to the AIS depends on Semaphorin3A (Sema3A) and its receptor neuropilin-1 (NRP1; Telley et al. 2016). Sema3A secreted by PCs attracts basket cell axons expressing NRP1 toward the AIS. Moreover, it appears that NRP1 also mediates subcellular target recognition through trans-synaptic interaction with neurofascin 186 (NF 186), a cell adhesion molecule of the L1 immunoglobulin family which is required for the formation and maintenance of the pinceau (Ango et al. 2004; Zonta et al. 2011; Buttermore et al. 2012). Interestingly, another member of the L1 family of adhesion molecules, the close homolog of L1 (CHL1), is localized along Bergmann glia fibers and stellate cells during the formation of stellate axon arbors. In the absence of CHL1, stellate axons show aberrant branching and orientation, and synapse formation with PC dendrites is impaired (Ango et al. 2008). Thus, different members of the L1 family contribute to regulate the subcellular targeting of basket cell and stellate cell axons on selective PC compartments.

Golgi Cells Golgi cells are interneurons that provide inhibition to the granule cells (Ito 2006; Schilling et al. 2008; Galliano et al. 2010). It has been suggested that Golgi cells act as an adaptable spatiotemporal filter that controls information flow through the

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cerebellar cortex (De Schutter et al. 2000; D’Angelo 2008). Ablation of Golgi cells by immunotoxin-mediated cell targeting impairs motor coordination, revealing a crucial role for cerebellar function (Watanabe et al. 1998). Golgi cell axons are restricted to the GCL and surround the glomeruli, making inhibitory synapses with the dendrites of granule cells and unipolar brush cells. Most Golgi cells contain both GABA and glycine (Ottersen et al. 1988; Kaneda et al. 1995; Watanabe and Nakanishi 2003), although some may be GABAergic only or glycinergic only (Simat et al. 2007b). Interestingly, it has been shown that an individual Golgi cell can mediate GABAergic or glycinergic inhibition based on the differential expression of GABAA receptors (GABAARs) or glycine receptors in the target neurons (Dugué et al. 2005). Immunohistochemical and electrophysiological analyses have revealed that synaptic inhibition mediated by Golgi cells matures with a time course similar to the development of glutamatergic MF synapses. In rats, GABA-positive Golgi cell terminals have been observed in the GCL already in the first postnatal days (Meinecke and Rakic 1990). Accordingly, patch-clamp recordings have shown that granule cells receive functional GABAergic synaptic input as early as P3 (Farrant and Brickley 2003). The axon terminals of Golgi cells develop rapidly during the second postnatal week, forming ring-like arrangements at the periphery of the glomeruli (McLaughlin et al. 1975). During this period, granule cells undergo a marked acceleration of inhibitory postsynaptic currents (IPSCs), which may be due to changes in the subunit composition of GABAARs (Brickley et al. 1999; Vicini and Ortinski 2004). It has been demonstrated that the BDNF receptor TrkB controls the formation and maintenance of synapses between Golgi cells and granule cells (Rico et al. 2002), primarily by regulating the assembly of pre- and postsynaptic adhesion molecules (Chen et al. 2011). Interestingly, MFs have been identified as the primary source of the BDNF that controls inhibitory synaptogenesis in the GCL (Chen et al. 2016). Golgi cells typically give rise to a few branching dendrites that either remain in the GCL (basal dendrites) or ascend into the ML (apical dendrites). The main excitatory inputs come from MFs and PFs, resulting in an anatomical substrate that supports feedforward and feedback inhibition of granule cells (D’Angelo 2008). Golgi cells also receive GABAergic and glycinergic synaptic input, but the origin of these inhibitory synapses is still debated. Traditionally, it was believed that Golgi cells receive synaptic inhibition from MLIs and from Lugaro cells, the latter providing mixed GABAergic/glycinergic input to the apical dendrites (Palay and Chan-Palay 1974; Dieudonné and Dumoulin 2000). However, electrophysiological and optogenetic investigations failed to reveal functional inhibitory connectivity between MLIs and Golgi cells and instead uncovered the existence of inhibitory connections among Golgi cells (Hull and Regehr 2012). Another recent investigation showed that stellate and basket cells very rarely innervate Golgi cell dendrites and suggested that Golgi cells receive the majority of inhibitory inputs from extracortical areas (Eyre and Nusser 2016). Hence, the origin of synaptic inhibition received by Golgi cells is not fully understood, and the organization and developmental profile of these connections need to be investigated in detail.

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Other Inhibitory Interneurons Other types of interneuron that mediate synaptic inhibition in the ML include Lugaro, globular, and candelabrum cells (Schilling et al. 2008). Like Golgi cells, these neurons are situated in the GCL and have a dual GABAergic/glycinergic phenotype. However, unlike Golgi cells, their axons are not restricted to the GCL, but they distribute throughout the ML. Knowledge of the connectivity and physiology of these cerebellar neurons is fragmentary, and virtually nothing is known about their development. The best characterized are Lugaro cells. These cells are innervated by recurrent collaterals of PC axons (Fig. 1) and by basket cells, and their axons make synapses with the apical dendrites of Golgi cells and with MLIs (Sahin and Hockfield 1990; Lainé and Axelrad 2002; Dumoulin et al. 2001). It has been estimated that a single Lugaro cell may establish synapses with more than 100 Golgi cells (Dieudonné and Dumoulin 2000). Lugaro cells receive a prominent innervation from serotoninergic fibers, which cause depolarization. It has been proposed that serotonin, by activating Lugaro cells, plays a role in synchronizing the activity of Golgi cells, thus contributing to regulate the spatial and temporal firing patterns of granule cells (De Schutter et al. 2000; Geurts et al. 2003). Like Lugaro cells, globular cells are robustly inhibited by PC axon collaterals and excited by MFs and by monoaminergic inputs, suggesting that these interneurons play a modulatory role in cerebellar motor coordination (Hirono et al. 2012).

The Axon Collaterals of Purkinje Cells On their course toward the white matter, PC axons give off myelinated collateral branches confined to thin parasagittal planes that project back to the PC layer and also enter the ML. Classical anatomical investigations identified three plexuses of PC axon collaterals: one in the GCL, another dense infraganglionic plexus at the bottom of the PC layer, and a sparse supraganglionic plexus in the ML (Palay and Chan-Palay 1974). The synaptic targets of PC collaterals have been the subject of controversy, although there is substantial consensus that PC axons connect with other PCs, Lugaro and globular cells, and MLIs (Witter et al. 2016 and references therein). Based on electrophysiological analyses, it was proposed that PC-to-PC synapses are ontogenetically transient and represent a substrate for waves of activity that travel along chains of connected PCs in the developing cerebellum (Watt et al. 2009). However, a recent study based on a combination of anatomical, optogenetic, and electrophysiological approaches revealed that both in juvenile and adult mice, the axon collaterals make synapses with other PCs in such way that essentially all PCs are inhibited by other PCs (Witter et al. 2016). In the same study, PC collaterals were found to make synapses with MLIs and Lugaro cells, but not with Golgi cells, which is in agreement with earlier electron microscopic observations (Larramendi and Lemkey-Johnston 1970). However, synapses between PC collaterals and Golgi cells have been reported in the rat cerebellum, suggesting that the organization of the recurrent collateral network differs among species (Chan-Palay 1971). It has also

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been reported that PC collaterals directly inhibit granule cells regulating their excitability on multiple timescales (Guo et al. 2016). Interestingly, these connections are region specific, as they are mostly found in cerebellar lobules involved in regulating eye movements and processing vestibular information.

Deep Cerebellar Nuclei DCN consist of a heterogeneous group of excitatory and inhibitory neurons that receive collateral projections from MFs and CFs, as well as GABAergic input from PCs (Llinás et al. 2004; Voogd 2004; Lu et al. 2016; Najac and Raman 2017). Glutamatergic neurons are large and project to a variety of targets outside the cerebellum. By contrast, GABAergic cells are smaller and project mainly to the inferior olive, thus providing an inhibitory feedback to the source of CFs. PC axons target both large and small cells of the DCN, exerting a tonic inhibitory influence (De Zeeuw and Berrebi 1995, Teune et al. 1998 and references therein). In addition, all DCN neurons receive synaptic inhibition from intrinsic neurons, some of which appear to use as neurotransmitters both GABA and glycine (Chen and Hillman 1993). It has been estimated in rats that 73% of axon terminals in the DCN neuropil are GABAergic and belong to PCs, 16% are GABAergic but do not belong to PCs, and 11% are non-GABAergic (De Zeeuw and Berrebi 1995). Quite similar values have been obtained in mice (Wassef et al. 1986) and cats (Palkovits et al. 1977). The number of glycine-positive terminals contacting DCN neurons is relatively low, accounting for less than 2% of the GABA-containing terminals (De Zeeuw and Berrebi 1995). Only a few studies have specifically investigated the development of synaptic connectivity in the DCN. In vitro anterograde tracing studies in rat brain slices have indicated that PC efferent projections are formed during late embryogenesis, and synaptic contacts with target cells may be established as early as embryonic day 20 (Eisenman et al. 1991). Accordingly, Wassef and Sotelo (1984), using an antiserum against cGMP-dependent protein kinase (cGK) to follow the perinatal development of PCs in rats, reported that at birth, at least some PC axons have already reached the deep nuclear region. More recently, Garin and Escher (2001) have shown that at P1 DCN neurons are reached by calbindin-positive axon terminals, suggesting innervation by PCs. Together, these observations suggest that PC axons reach their target neurons in the perinatal period, before they start growing their dendrites in the ML. Therefore, synaptogenesis may start in the DCN well before the emergence of the first synapses in the cerebellar cortex, although the precise pattern of synapse development in DCN remains to be determined.

Conclusions Due to its limited number of neuronal types and its highly stereotyped structure, the cerebellum represents an exquisite model system for studying mechanisms of neural circuit development. Experimental studies in the cerebellum have contributed to

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understand how the specificity of circuitry arises from multiple developmental processes, which include the spatial and temporal regulation of distinct sets of interacting proteins (Sassoè-Pognetto and Patrizi 2017). New technical advances, such as the introduction of genetically encoded fluorescent markers and nonlinear microscopy (Lichtman and Smith 2008), optogenetic tools (Nagel et al. 2003; Petreanu et al. 2007), and synapse-specific proteomics (Selimi et al. 2009), provide unprecedented capabilities for exploring the complexity of the molecular mechanisms and the dynamics of synapse development. However, considering the intricate structure of the nervous system and the tremendous molecular diversity of synapses, the investigation of neural circuit development remains a formidable challenge. Looking forward, it can be predicted that the cerebellum, with its relative simplicity and delayed maturation, will continue to be at the forefront of research aimed at understanding the mechanisms that control synapse assembly and neural circuit refinement.

Cross-References ▶ Animal Models: An Overview ▶ Axonal Trajectories of Single Climbing and Mossy Fiber Neurons in the Cerebellar Cortex and Nucleus ▶ Cerebellar Granule Cell ▶ GABA and Synaptic Transmission in the Cerebellum ▶ Glutamate Receptor Auxiliary Subunits and Interacting Protein Partners in the Cerebellum ▶ Golgi Neurons ▶ Neurons of the Deep Cerebellar Nuclei ▶ Stellate Cells: Synaptic Processing and Plasticity ▶ Synaptogenesis and Synapse Elimination

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Synaptic Remodeling and Neosynaptogenesis

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Ann M. Lohof, Mathieu Letellier, Jean Mariani, and Rachel M. Sherrard

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climbing Fiber-Purkinje Cell Synaptogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Initial Interactions Between Climbing Fibers and Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . Somatodendritic Translocation of Climbing Fiber Terminals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Selective Synapse Elimination Is Based on Homosynaptic Competition . . . . . . . . . . . . . . . . . . Selective Synapse Elimination Requires Heterosynaptic Competition . . . . . . . . . . . . . . . . . . . . . Purkinje Cell Function Within the Synaptic Network Regulates Climbing Fiber Refinement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Remaining Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differential Effects of Climbing Fiber and Purkinje Cell Maturation on Selective Axon-Target Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reinnervation of Purkinje Cells After Mechanical Lesion in the Early Postnatal Period . . . Climbing Fiber Reinnervation of Mature Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Differential Maturation of Synaptic Partners Alter Climbing Fiber – Purkinje Cell Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Correct neural circuit function requires the development of highly specific interneuronal connectivity. This chapter describes axon-target interactions in the rodent olivocerebellar path, looking at the changes in synaptic contacts between climbing fibers and Purkinje cells, during developmental synapse formation, selective synapse stabilization, and synaptic reformation. Examining the A. M. Lohof (*) · J. Mariani · R. M. Sherrard Sorbonne Université and Centre National de la Recherche Scientifique, Paris, France e-mail: [email protected]; [email protected]; rachel. [email protected] M. Letellier Centre National de la Recherche Scientifique and Université de Bordeaux, Bordeaux, France e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_13

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interactions between climbing fibers and Purkinje cells during normal development and in abnormal circumstances, such as during post-lesion reinnervation, evaluates the relative importance of each synaptic partner in determining the specificity of connections within a network. We briefly describe the formation and refinement of normal developmental climbing fiber-Purkinje cell synapse. Then we examine the relative roles of the maturation and prior synaptic experience of both climbing fibers and Purkinje cells during the reformation of their contacts later in maturation. In this chapter, we show that climbing fibers largely retain their capacity to reproduce the processes of developmental synaptogenesis, whereas Purkinje cells are permanently altered by the process of climbing fiber innervation and synapse selection, so that they cannot reproduce normal developmental events later in maturation. Although these studies increase the understanding of network development and stability, they also provide important information about neosynaptogenesis, which is necessary for neural circuit reorganization after a lesion, and about how it can be maximized for optimal repair. Keywords

Synaptogenesis · Climbing Fiber · Purkinje cell · Multiple innervation · Synaptic maturation · Synaptic repair · Reinnervation

Introduction The specificity of neural connectivity which is established during development underlies the formation of coherent, functional neural networks. Complex processes are involved in creating this specificity, including neurogenesis, synaptogenesis, reorganization, and elimination of some initial contacts and often the death of extraneous neurons. In the cerebellum, the olivocerebellar connection between brainstem inferior olivary axon terminals, the climbing fibers, and their target cerebellar Purkinje neurons refines its specificity during a period when the expression of many proteins is changing, neurons are differentiating, and many different afferents are competing for space on their target Purkinje cell (Altman and Bayer 1997). Because the adult Purkinje cell has an extensive dendritic arbor, on which it receives a single climbing fiber, thousands of granule cell axons (parallel fibers) and inhibitory stellate cell synapses, as well as a large soma and axon initial segment that receives basket cell inhibition (Ito 1984), the specificity of climbing fiber-Purkinje cell connectivity also requires appropriate subcellular targeting. Thus, in view of these complex and concurrent processes, it is difficult to evaluate the relative roles of the afferent climbing fiber and target Purkinje cell in determining synapse specificity. Studies in mutant or transgenic mice are useful to examine these processes, which allow the identification of important genes, but their mode of action is often difficult to determine in models lacking temporal and/or spatial specificity. An alternative approach involves examining the roles of axon and target during the formation of their synaptic connections under specific experimental circumstances, where cellular maturation and prior synaptic experience can be individually controlled (e.g., post-

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lesion reinnervation or innervation of grafted neurons). In cases like this, how do climbing fibers and Purkinje cells interact to form new circuits? These approaches have revealed reciprocal interactions between synaptic partners and the respective roles of these partners during the formation of precise, functional synapses.

Climbing Fiber-Purkinje Cell Synaptogenesis Initial Interactions Between Climbing Fibers and Purkinje Cells Ramon y Cajal was the first to follow the morphological interactions between climbing fibers and Purkinje cells during development (Ramon y Cajal 1911). Climbing fiber contacts with Purkinje cells are first observed at the end of the embryonic period (E19), when Purkinje cells finish migrating into the cerebellar cortex and still have a fusiform morphology (Armengol and Sotelo 1991; Morara et al. 2001). Chedotal and Sotelo (1993) showed that parvalbumin-expressing climbing fibers establish synaptic contacts on the long smooth transient dendrites of the Purkinje cell; this early stage of synaptogenesis was termed the “creeper” stage because the climbing fibers “creep” between the immature Purkinje cell somata (Sugihara 2005). These initial climbing fiber-Purkinje cell synaptic interactions are then dynamically remodeled over the subsequent 2–3 postnatal weeks in the rodent, until the end of the synaptogenesis period. This remodeling involves two distinct processes: (1) transient Purkinje cell multi-innervation by climbing fibers, followed by selective synapse elimination (Mariani and Changeux 1981), and (2) the subcellular targeting of climbing fiber terminals, from the cell body to the proximal dendritic compartment (Mason et al. 1990; Chedotal and Sotelo 1993; Scelfo et al. 2003). It is important to note that these processes begin just before synapse formation with parallel fibers and inhibitory interneurons and coincide with the morphological differentiation of the Purkinje cell. This morphological differentiation requires regression of the transient dendrites of the post-migratory fusiform cell, under the control of RORα (Boukhtouche et al. 2006), to permit polarization of the soma and development of the mature dendritic arbor (Altman 1972; McKay and Turner 2005; Fig. 1).

Somatodendritic Translocation of Climbing Fiber Terminals The translocation of climbing fiber terminals, also described for the first time by Ramon y Cajal (1911), is slightly delayed compared to the Purkinje cell’s dendritic development (Altman 1972; Scelfo et al. 2003). After the first climbing fiber contacts are in place at the end of the embryonic period, climbing fibers ramify and grow around the Purkinje cell soma, as at this stage their permanent dendrites have not yet developed; this is called the “pericellular nest” stage, between P3 and P6 (Ramon y Cajal 1911; Chedotal and Sotelo 1993). At this stage, when the Purkinje cells have a stellate morphology (Armengol and Sotelo 1991), climbing fiber terminals establish synapses on perisomatic protrusions (Morara et al. 2001; Sugihara 2005). During a second phase, the terminals move up to cover the apical

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part of the cell body (“capuchon”; Ramon y Cajal 1911), where they synapse on spines found on both the cell body and the primary dendritic trunk (Chedotal and Sotelo 1993). Finally, in a third phase, around P10–P15, the somatic protrusions disappear and the climbing fiber terminals leave the cell body to climb along the main branches of the developing dendritic arbor, where they are stabilized (Ramon y Cajal 1911; Sugihara 2005; Hashimoto et al. 2009; Fig. 2).

Fig. 1 Differentiation and maturation of the rodent cerebellar cortex, showing Purkinje cell development concurrent with climbing fiber synaptogenesis and translocation as well as granule cell genesis and parallel fiber synaptogenesis on the expanding dendritic tree. (Copyright John Wiley and Sons. Reproduced with permission from Altman 1972)

Fig. 2 Somatodendritic translocation of climbing fiber terminals from the Purkinje cell body to the dendrites, which occurs in parallel with the elimination of supernumerary climbing fibers

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Selective Synapse Elimination Is Based on Homosynaptic Competition At the same time as somatodendritic translocation of the climbing fibers and morphological differentiation of the Purkinje cell, selection of climbing fiber synaptic partners occurs by a process of synapse elimination. The earliest electrophysiological responses to climbing fiber activation were recorded in Purkinje cells in vivo at P2–P3 in the rat (Crepel 1971). During this perinatal period, morphology (Sugihara 2005) and electrophysiology (Crepel et al. 1976; Mariani and Changeux 1981; Hashimoto and Kano 2003) show that climbing fibers converge on Purkinje cells such that nearly every Purkinje cell is innervated by several olivary axons. This multi-innervation reaches a peak at P5–6 in the rat (Mariani and Changeux 1981), with a maximum of 5 and mean of 3.5 climbing fibers per Purkinje cell, then regresses to a state of monoinnervation during the first 2–3 postnatal weeks in the rodent (Mariani and Changeux 1981; Hashimoto and Kano 2003). Very similar to synaptogenesis at the mammalian neuromuscular junction (Lichtman and Colman 2000), the supernumerary climbing fibers are progressively weakened (the amplitude of their synaptic responses decreases) and then eliminated, while the “selected” climbing fiber is stabilized and induces postsynaptic currents with progressively greater amplitudes (Fig. 3). A possible mechanism for differentiation between the different competing climbing fibers is their pattern of activation, which can alter their synaptic strengths (Bosman et al. 2008; Ohtsuki and Hirano 2008), and the activation of P/Q voltage-gated calcium channels, from which the resulting calcium influx could reinforce the effect of the strongest climbing fiber synapses (Hashimoto et al. 2011; Kawamura et al. 2013). Although calcium and sodium imaging studies have shown that several climbing fibers can translocate to the dendritic compartment from the cell body (Scelfo et al. 2003), by the end of synapse selection only a single climbing fiber occupies the proximal dendritic arbor, whereas the other climbing fibers occupy smaller somatic or perisomatic territories (Hashimoto and Kano 2003; Scelfo et al. 2003). Electrophysiology indicates that synapse selection takes place on the Purkinje cell soma and only the stabilized climbing fiber translocates to the dendrites (Hashimoto et al. 2009). This is supported by 2-photon imaging showing that, when climbing fiber selection takes place, only one climbing fiber ever makes total somatodendritic translocation (Nishiyama 2015). However, since climbing fiber synapse elimination can take place in the absence of somatodendritic translocation (e.g., in the hyperspiny Purkinje cell; Mariani 1983; Nishiyama 2015) and somatodendritic translocation can take place in the absence of climbing fiber selection (e.g., hypogranular cerebella; Mariani 1983), climbing fiber selection and synapse elimination seems to be a progressive process, that is followed by, rather than depends upon, somatodendritic translocation.

Selective Synapse Elimination Requires Heterosynaptic Competition In addition to competition for post-synaptic space with other climbing fibers, additional afferents, such as from granule and basket cells, also develop synapses

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Fig. 3 Synaptic competition and elimination of supernumerary climbing fiber synapses in the mouse. (a and b) Climbing fiber responses recorded from Purkinje cells at 3 days (P3) and 12 days (P12) postnatal. At P3, the superimposed traces show that there are several climbing fiber synapses with similar strengths; at P12 the disparity between the two remaining responses is very large, indicating differential maturation of the climbing fiber synapses on a single Purkinje cell. (c and d) The number of climbing fiber synapses per Purkinje cell at P2–3 and at P12–14. (e, g, i) Responses

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on Purkinje cells at the same time (Altman and Bayer 1997; Ichikawa et al. 2011). Indeed, several animal models have shown that parallel fiber synaptogenesis is a critical trigger for selective climbing fiber synapse elimination (see reviews in Crepel et al. 1981; Mariani 1982), as is the Purkinje cell response to their synaptic activity (Hashimoto and Kano 2013). Moreover, conditional knock-out of the GABA synthesizing enzyme GAD67 also shows that GABAergic inhibition controls the late phase of climbing fiber synapse elimination (P10–P16), most likely by influencing calcium transients in the cell body (Nakayama et al. 2012). Studies dating from the 1970s and 1980s showed that animals either lacking cerebellar granule cells or having defective parallel fiber synapses are ataxic, and Purkinje cells have abnormal multiple climbing fiber innervation as well as abnormal long-term synaptic plasticity. These defects are seen, for example, in the spontaneous mouse mutants reeler, weaver, and staggerer; although each of these mutants has different cellular abnormalities such as abnormal granule cell migration, or arrested Purkinje cell development (Mariani 1982). In all of these mutant models, Purkinje cells retain three to four climbing fibers, which suggests a complete block of the synapse elimination process and emphasizes the importance of the parallel fiber synapse in selective climbing fiber elimination. This same block to climbing fiber selection is seen in animals made hypogranular by X-irradiation during the first postnatal week (Crepel et al. 1981; Mariani et al. 1990; Bailly et al. 2018). By restricting the X-irradiation to specific postnatal ages, it becomes clear that disruption to granule cell precursors at P5 has the most severe effect on regression of climbing fiber multiple innervation, resulting in many Purkinje cells in the adult still receiving five climbing fibers (Bailly et al. 2018). Moreover, analysis of different lobules within the irradiated cerebellum revealed that Purkinje cells in the ventral (i.e., more developmentally advanced) lobules I, IX, and X were significantly less multi-innervated (multi-innervation index of 2.0) than the Purkinje cells of the dorsal lobules (VI and VII; multi-innervation index of 3.2), which mature at later chronological ages (Altman and Bayer 1997). In terms of Purkinje cell development, it is the arrival of granule neurons and initial parallel fiber synapses at the immature “stellate” stage (P3–P6), which is critical for initiating the process of climbing fiber synapse elimination (Bailly et al. 2018). Results from the hypogranular cerebellum are confirmed in the mouse lacking the Grid2 gene, coding for the orphan GRID2 ionotropic glutamate receptor, which is specifically expressed at adult parallel fiber-Purkinje cell synapses and yet is not activated by glutamate (Lomeli et al. 1993). GRID2 is necessary for the formation and maintenance of parallel fiber synapses (Takeuchi et al. 2005) through its interaction with Cbln1 (cerebellin precursor protein1; Matsuda and Yuzaki 2010) and presynaptic ä Fig. 3 (continued) recorded from a Purkinje cell induced by stimulating three different climbing fibers. (f, h, j) Pseudocolor images showing calcium influx into the Purkinje cell during the activation of the corresponding climbing fibers. (Modified from Hashimoto and Kano 2003. Copyright 2003, with permission from Elsevier)

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neurexins (Uemura et al. 2010). Thus, in the absence of GRID2 function, in knockout or mutant “hotfoot” mice, there are defects in parallel fiber synapse formation (Kurihara et al. 1997; Lalouette et al. 2001) and Purkinje cell multi-innervation is retained (Hirai et al. 2005). The central role for parallel fibers in the elimination of climbing fiber multiinnervation is reinforced by the suppression of GRID2 from adult Purkinje cells. In these experiments, climbing fibers sprout extensively both into the parallel fiber territory on the distal dendrite, and onto adjacent Purkinje cells which produces multi-innervation (Miyazaki et al. 2010). This shows that heterosynaptic competition between these two types of afferents is dynamic throughout life.

Purkinje Cell Function Within the Synaptic Network Regulates Climbing Fiber Refinement In addition to the formation and stabilization of parallel fiber afferents, the Purkinje cell must also respond normally to this input in order for appropriate climbing fiber synapse elimination to take place. Although the many molecular players will not be discussed here (see adjacent ▶ Chap. 14, “Synaptogenesis and Synapse Elimination” by Kano and Watanabe in this volume), they include the synaptic glutamate receptors GRID2, mGluR1 (Hashimoto et al. 2001), NMDA (Rabacchi et al. 1992; Kakizawa et al. 2000), and P/Q-type voltage-dependent calcium channels (Miyazaki et al. 2004), as well as neuromodulators such as BDNF (Bosman et al. 2006; Sherrard et al. 2009; Choo et al. 2017) and secreted and transmembrane proteins (Hirai et al. 2005; Tohgo et al. 2006; Watanabe et al. 2008; Uesaka et al. 2014; Kakegawa et al. 2015). Considerable work from the Kano laboratory has clarified a role for signaling via the metabotropic glutamate receptor mGluR1, which is highly expressed at parallel fiber synapses (Baude et al. 1993), in the process of climbing fiber synapse elimination. An abnormal proportion of Purkinje cells (about 40%) remains multiinnervated in mice lacking mGluR1 or its downstream signaling molecules Gαq, PLCβ4, or PKCγ (Hashimoto and Kano 2013). In these mice, synapse elimination occurs normally until about P10 but then appears to be blocked, suggesting that there are at least two distinct phases of synapse elimination. The involvement of NMDA receptors in regression of multiple climbing fiber innervation has been suggested by the observation that approximately half the Purkinje cells remain multi-innervated after NMDA receptor blockade during development (Rabacchi et al. 1992; Kakizawa et al. 2000). However, Purkinje cells only transiently express extrasynaptic NMDA receptors during the first postnatal week (Dupont et al. 1987; Cull-Candy et al. 1998) and synaptic NMDA receptors after P21 (Piochon et al. 2007; Renzi et al. 2007), indicating that they express few or no functional NMDA receptors during the phase of climbing fiber elimination. It is therefore not clear where the NMDA receptors involved in the final phase of synapse elimination are located, but a likely candidate would be the NMDA receptors expressed at mossy fiber-granule cell synapses (Cathala et al. 2000). However, in contrast to hypogranular cerebella, it is important to note that these mouse models do not have

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abnormal parallel fiber synapses and that the subcellular targeting of climbing fiber terminals is normal (Hashimoto and Kano 2013). These results showing the role of the mGluR1 and NMDA receptors suggest a role for activity in the mossy fiber-granule cell-parallel fiber-Purkinje cell circuit in the final phase of climbing fiber synapse elimination, which is entirely consistent with activity-dependent mechanisms underlying neural circuit maturation in other areas of the nervous system. Indeed, if Purkinje cell activity is blocked, climbing fiber multi-innervation is maintained and their synapses usually remain on the cell soma (Cesa and Strata 2005). Mechanistically, lack of afferent activity will fail to activate Purkinje cell P/Q-type voltage-dependent calcium channels, which are responsible for the majority of the calcium influx into the Purkinje cell somatodendritic compartment (Usowicz et al. 1992). The calcium influx via these channels could promote the activation of CaMKIV, an enzyme necessary for climbing fiber synapse elimination (Ribar et al. 2000). Moreover, activation of these P/Q-type voltage-dependent calcium channels plays an important role both in homosynaptic competition with other climbing fibers (Hashimoto et al. 2011; see above) and in heterosynaptic competition with parallel fibers (Miyazaki et al. 2004), both of which lead to elimination of supernumerary climbing fibers.

Remaining Questions The observations given above show that there is considerable knowledge about the processes underlying climbing fiber synapse elimination at morphological, electrophysiological, and molecular levels. However, because so many developmental processes are occurring concurrently in different neuronal populations (Altman and Bayer 1997), it is difficult to identify the roles of specific components (e.g., Purkinje cell, climbing fiber, or parallel fiber) at the different stages of synaptogenesis, somatodendritic translocation, climbing fiber selection, and elimination of supernumerary synapses. However, it is clear that the whole process extends over approximately 3 weeks from E18–19 to around P21. Nevertheless, there are remaining questions: 1. When does climbing fiber synapse elimination begin? After initial climbing fiber synapse formation onto transient dendrites of “creeper” Purkinje cells, some of these climbing fibers have to translocate to the Purkinje cell perisomatic processes as their initial target dendrites regress (Armengol and Sotelo 1991). Although this stage is not considered as homosynaptic competition, not all climbing fibers make the transition and climbing fiber degeneration has already begun. Reconstruction of individual axons in P0 rats estimates about 100 developing climbing fibers per olivary axon at the “creeper” stage (P0–3), which dramatically decreases to 10–20 arbors at the “pericellular nest” stage (P3–6), and finally to 6–7 at the mature adult stage (Sugihara 2005). Moreover, during this pericellular nest stage, although the number of climbing fiber branches in a given area decreases, individual climbing

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fiber branches greatly increase the number of their synapses onto a few preferred target Purkinje cells (Wilson et al. 2019). These results suggest either that immature olivary neurons can retract some axon collaterals while actively generating synapses with others or that initial climbing fiber loss is due to developmental death of olivary neurons. Indeed, one period of olivary developmental cell death occurs at this very early stage (P1–P5; Delhaye-Bouchaud et al. 1985). However, electrophysiology shows that the number of climbing fibers innervating a Purkinje cell increases between P3 and P6 (Hashimoto and Kano 2013), which may reflect the detection of different terminal climbing fiber branches of the same olivary axon (called peudo-multi-innervation, Sugihara et al. 2003) due to a greater number of synapses on each branch (Wilson et al. 2019). Electrophysiologically, the actual climbing fiber synapse elimination only begins at P6 (Hashimoto and Kano 2013). Thus, early climbing fiber degenerative phenomena demonstrate that olivary neurons can advance and retract different axon collaterals concurrently and that climbing fiber selection begins earlier than thought. 2. Does maturation of the synaptic partners regulate the process of climbing fiber selection and synapse elimination? During these processes of climbing fiber synaptogenesis and selective stabilization, there is a defined temporal order in changes to the Purkinje neuron, as well as the arrival of parallel and inhibitory afferents. Given that heterosynaptic competition between climbing and parallel fibers continues in adulthood (see above), it seems likely that it is the maturation of the Purkinje cell that directs the order of the different stages. This view is supported in two ways. First, X-irradiation studies show that it is the interaction of granule neurons with Purkinje cells only in their immature “stellate” stage (P3–P6) that permits the onset of climbing fiber selection (Bailly et al. 2018). Second, if normal adult Purkinje cells are induced to regress to a less mature status by the selective knockout of the transcription factor RORα, the mature wild-type climbing fibers sprout so that RORα-deficient Purkinje cells become re-multi-innervated (Chen et al. 2013). However, further experiments are needed to clarify this (see below).

Differential Effects of Climbing Fiber and Purkinje Cell Maturation on Selective Axon-Target Interactions In addition to the insights gained from studies of mutant and transgenic mice, lesion studies provide another approach to understanding the mechanisms underlying the specificity of axon-target interactions in the olivocerebellar path. By disrupting the connection between the axon and its target and observing the reorganization of the pathway, one can draw some conclusions about these synaptic interactions. Two types of climbing fiber lesions have been used to study the effects of Purkinje cell denervation: (1) a physical lesion, sectioning the olivary axons at the level of the inferior cerebellar peduncle (pedunculotomy), and (2) a neurotoxic lesion, using 3-acetylpyridine (3-AP) to specifically kill olivary neurons. These two types of lesions induce a rapid and permanent degeneration of the olivary

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neurons and thus the disappearance of climbing fiber terminals in the molecular layer (Sotelo et al. 1975; Sherrard et al. 1986; Cesa and Strata 2005). The Purkinje cell responds with functional and morphological changes that are similar for both types of lesions. This response involves (1) the development of spines on the proximal dendrites and the soma, upon which parallel fibers establish new synapses, expanding their innervation territory and confirming the existence of heterosynaptic competition between climbing fibers and parallel fibers (Sotelo et al. 1975; Angaut et al. 1982; Rossi et al. 1991a; Cesa and Strata 2005), and (2) a temporary increase in the frequency of parallel fiber responses (simple spikes) recorded in the Purkinje cell (Montarolo et al. 1982). The remarkable plastic properties of the olivary axons allow reinnervation of Purkinje cells after unilateral pedunculotomy or injection of 3-AP by collateral formation within the cerebellum. The amount of this plasticity depends on the type of lesion and the stage of development.

Reinnervation of Purkinje Cells After Mechanical Lesion in the Early Postnatal Period During early development, unilateral pedunculotomy deprives the Purkinje cells in one hemi-cerebellum of climbing fiber afferents, following which the remaining olivary neurons from the contralateral path can reinnervate the additional target cells (Angaut et al. 1982, 1985; Sherrard et al. 1986; Zagrebelsky et al. 1997; Willson et al. 2008) (Fig. 4).

Fig. 4 Schematic diagram representing the normal olivocerebellar pathway (bold line) that originates in the inferior olive, crosses the midline in the medulla, and ascends to the contralateral cerebellar hemisphere through the inferior cerebellar peduncle. If the peduncle is transected (*) prior to P10, the contralateral olive degenerates and new compensatory fibers grow to reinnervate Purkinje cells of the left hemicerebellum (thick dotted line). At later ages, injection into the cerebellum of neurotrophic factors such as BDNF can induce reinnervation (thin dotted line). (Copyright John Wiley and Sons. Reproduced with permission from Willson et al. 2007)

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Anterograde and retrograde tracing experiments have shown that the reinnervating olivary axons come from the surviving inferior olive and cross the midline within the cerebellum to terminate on the Purkinje cells that have lost their normal innervation (Angaut et al. 1985; Sherrard et al. 1986; Sugihara et al. 2003). In this lesion model, the reactive transcommissural climbing fibers distribute themselves in longitudinal bands, coherent with zebrin expression in the reinnervated hemicerebellum, suggesting that the olivocerebellar topography is restored (Sherrard et al. 1986; Zagrebelsky et al. 1997); this is confirmed by the distribution of climbing fibers from individually traced axons in the reinnervated hemicerebellum and the observation that the reformed synapses are functional (Sugihara et al. 2003). New climbing fibers show correct distribution of normal synapses along proximal Purkinje cell dendrites in the molecular layer (Angaut et al. 1982; Sugihara et al. 2003). Although reinnervation is topographically specific, it is also incomplete, as shown by the number of Purkinje cells which are not reinnervated (Angaut et al. 1982; Sugihara et al. 2003). The reinnervation occurs extensively in the vermal cortex, reaching 86% of Purkinje cells, but it is sparse in the lateral regions of the deprived hemisphere, innervating only 40% of Purkinje cells (Angaut et al. 1985; Sherrard et al. 1986; Zagrebelsky et al. 1997; Sugihara et al. 2003). Furthermore, retrograde labeling studies reveal that olivocerebellar axons arise mainly from the intact caudal medial accessory olive (MAO) and, to a lesser extent, from the dorsal accessory olive (DAO) and principal olive (PO) (Angaut et al. 1985; Sherrard et al. 1986), consistent with the topography of the normal olivocerebellar path. The climbing fiber arbors formed onto Purkinje cells are morphologically normal (Sugihara et al. 2003) with appropriate topography (Zagrebelsky et al. 1997); this reformation of specifically targeted synapses could explain the recovery of motor and spatial learning functions observed in these animals (Dixon et al. 2005; Willson et al. 2007, 2008). Consistent with normal developmental processes, the reinnervation of Purkinje cells involves a phase of multi-innervation, which regresses afterward to produce the normal monoinnervation (Lohof et al. 2005). This observation suggests that the developmental state of the Purkinje cell would be a critical factor in determining the process of multiple innervation and regression.

Climbing Fiber Reinnervation of Mature Purkinje Cells Post-lesion Reinnervation of Maturing Purkinje Cells: Similarities and Differences from Neonatal Reinnervation After the normal period of climbing fiber development, reinnervation after pedunculotomy does not occur spontaneously as in the younger animal, but it can be induced by injection of certain neurotrophic factors into the cerebellum (e.g., BDNF; Sherrard and Bower 2001; Dixon and Sherrard 2006; Letellier et al. 2007; Willson et al. 2008). This post-pedunculotomy reinnervation of maturing Purkinje cells recapitulates certain morphological events of developmental synaptogenesis, suggesting a re-expression of certain developmental programs.

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First, Purkinje cells redevelop somatic spines in response to the arrival of new climbing fibers, and close temporal analysis of reinnervation after unilateral pedunculotomy allows identification of Purkinje cell morphological modifications induced specifically by reinnervation. Immunohistochemistry and electron microscopy (Letellier et al. 2007) showed that the first synaptic contacts on reinnervated Purkinje cells are established mainly on temporary somatic spines, structures which are also present during the pericellular nest stage of development (Chedotal and Sotelo 1993). Two observations suggest that these spines are induced by the arrival of climbing fibers: (1) each spine is contacted by a climbing fiber terminal and (2) non-innervated Purkinje cells, like control Purkinje cells at the same age, do not develop somatic spines. Synaptic contacts were also seen directly on the smooth surface of the soma; it is possible that the first synaptic contacts are made on the soma and induce the formation of spines. This observation contrasts with the development of spines contacted by parallel fibers, which is due to cell-autonomous mechanisms and occurs before the arrival of afferents (Sotelo et al. 1975; Cesa et al. 2005). Thus, different mechanisms underlie the development of two different types of spine on the Purkinje cell, according to the type of afferent (Cesa and Strata 2005). Second, also as occurs during development, the somatic spines disappear and the climbing fibers leave the soma to make contacts in the dendritic compartment in the days following initial synapse formation. At the end of the reinnervation process, the climbing fiber terminals are essentially distributed on the proximal dendrites, as in the control animal at the same age (Dixon and Sherrard 2006; Letellier et al. 2007). Thus, climbing fibers are able to reform synapses specifically on the proximal dendrites of Purkinje cells in the relatively mature olivocerebellar system. As during normal development, this specific interaction with the proximal dendrites comes after somatodendritic translocation (Letellier et al. 2007), indicating that the mechanisms permitting guidance between subcellular compartments are maintained or reexpressed by the Purkinje cell at late developmental stages. During normal development, the translocation of climbing fibers occurs in parallel with the elaboration of the dendritic arbor, which suggests that the subcellular guidance is dependent upon dendritic growth. In the pedunculotomy model, however, translocation of mature climbing fibers occurs on Purkinje cells which already have an elaborate dendritic arbor; thus in this case, climbing fiber translocation must be independent of the dendritic growth process. In addition, the new projections induced by neurotrophic factor injection are organized in narrow parasagittal bands (Dixon and Sherrard 2006), suggesting the formation of functional microzones; this reproduces the effect seen during spontaneous plasticity in the neonatal period. Thus, the new connections reformed later during development, in the presence of excess BDNF, appear to be precise and organized. Although the number and extent of these new connections are reduced when compared to spontaneous reinnervation in the early postnatal period, this reduced reinnervation nonetheless allows some functional recovery (Willson et al. 2008). In contrast to the process of reinnervation in the young animal, climbing fiber reinnervation of denervated Purkinje cells does not involve multiple innervation followed by synaptic competition and selective stabilization (Letellier et al. 2007). Instead, Purkinje cells are re-innervated directly by a single climbing fiber, which corresponds to their mature developmental stage.

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Purkinje Cell Reinnervation After Partial Olivary Lesion by 3-Aminopyridine (3-AP) The neurotoxin 3-AP produces partial inferior olive lesion such that only some neurons survive and continue to innervate Purkinje cells in the cerebellar cortex. Under these conditions, the surviving climbing fibers in the cerebellar cortex form collaterals in the molecular layer to reinnervate neighboring Purkinje cells over a distance of several 100 microns (Rossi et al. 1991a, b; Dhar et al. 2016). An extrinsic factor that allows climbing fiber branching in the molecular layer could be that myelin proteins are absent in this layer (Rubin et al. 1994). The increased climbing fiber terminal branches innervated approximately 50 Purkinje cells (Benedetti et al. 1983) compared to the normal adult climbing fiber-Purkinje cell innervation ratio of 1:7 (Sugihara et al. 2001). Morphologically, these terminals extend from the small horizontal branches of intact arbors of surviving climbing fibers and form new climbing fiber arbors over the proximal dendrites of adjacent denervated Purkinje cells (Rossi et al. 1991a, b; Rossi and Strata 1995; Dhar et al. 2016). Climbing fiber branchlets along the Purkinje cell dendrites are rich in varicosities, and their terminal arbors are morphologically very similar to normal climbing fibers (Rossi et al. 1991a; Dhar et al. 2016). Invading their normal territory, these climbing fibers displace the ectopic parallel fiber synapses that form when the climbing fibers were lost; this demonstrates that the effects of deafferentation are reversible (Rossi and Strata 1995). The newly formed climbing fiber synapses are functional; they induce complex spikes (Benedetti et al. 1983) and have normal ultrastructure (Rossi et al. 1991a). Thus, the mechanisms leading to subcellular targeting during development are maintained or re-expressed in the adult. Importantly, climbing fibers densely reinnervate neighboring Purkinje cells within the same parasagittal territory (“zebrin bands”; Zagrebelsky et al. 1996), although a few small climbing fiber arbors are generated beyond the edge of these histochemically defined bands (Dhar et al. 2016). This is coherent with the parasagittally distributed climbing fiber reinnervation after pedunculotomy (Dixon and Sherrard 2006; Willson et al. 2008), suggesting that the mechanisms responsible for the topographical specificity in longitudinal zones are also maintained in the adult. This topographically organized reinnervation, which is also targeted to the appropriate subcellular compartment, could contribute to the functional recovery observed after a partial lesion of the inferior olive (Hess et al. 1988; Voneida et al. 1990), although improvement of complex motor behavior is very limited (Fernandez et al. 1998).

Differential Maturation of Synaptic Partners Alter Climbing Fiber – Purkinje Cell Interactions Mature Climbing Fibers Multi-innervate Immature Purkinje Cells Given that mature climbing fibers mono-reinnervate mature Purkinje cells (see above), it is not clear whether the maturation of one or both synaptic partners is determinant in this process. The respective roles of axon or target maturation can be examined by varying independently the age of the climbing fibers and Purkinje cells.

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The (re)innervation of immature Purkinje cells by mature climbing fibers can be achieved by grafting immature Purkinje cells into a mature host cerebellum and observing the interactions between these grafted target cells and their climbing fiber afferents. For example, studies using grafted embryonic cerebellar cells in the adult mutant pcd mouse, from which Purkinje neurons have degenerated, or into the normal adult rat cerebellum, have shown that immature Purkinje cells are able to integrate into the host cerebellar cortex and to interact with appropriate afferent axons (Gardette et al. 1990; Rossi et al. 1994; Tempia et al. 1996). Climbing fibers synapse onto these grafted Purkinje cells, confirming that these axons can innervate additional targets (Gardette et al. 1990; Rossi et al. 1994; Tempia et al. 1996). Electrophysiology has shown that host climbing fibers multi-innervate the immature grafted cells, even though they are already (mono)innervating their normal adult targets, and that this multi-innervation regresses to establish monoinnervation of the grafted cells (Gardette et al. 1990; Tempia et al. 1996). Moreover, if immature Purkinje cells are grafted into a denervated hemicerebellum after pedunculotomy, BDNF-induced climbing fiber axons will also reinnervate these additional grafted Purkinje cells as well as the denervated adult Purkinje cells in the host hemicerebellum (Letellier et al. 2007). Importantly, while the adult Purkinje cells are only mono-reinnervated, at the same time the embryonic graft Purkinje cells are multi-innervated (Letellier et al. 2007). These heterochronic graft experiments suggest that cell-autonomous mechanisms within the Purkinje cell direct their interactions with specific afferent axons. This “directive” role for the Purkinje cell is further supported by the re-multi-innervation by mature climbing fibers that occurs if the target (adult) Purkinje cell is induced to regress to an immature state by the knockout of RORα selectively from some adult Purkinje neurons (Chen et al. 2013). These studies show that (1) the climbing fibers maintain or re-express their capacity to form additional, permanent, appropriate synapses when presented with new targets (thus confirming the experiments with 3AP); (2) they also retain the processes to compete for these new targets; and (3) it is the maturation status of the Purkinje cell that regulates how many climbing fibers it will receive.

Prior Purkinje Cell Synaptogenesis Determines the Capacity for Neosynaptogenesis The model of post-lesion reinnervation in vivo (see above) shows that the maturation state of Purkinje cells determines whether multi-innervation will occur. However, these experiments cannot identify whether the mono-reinnervation of maturing Purkinje cells is secondary to the mature nature of the Purkinje cell or the fact that it has previously undergone the process of climbing fiber multi-innervation and selective synapse elimination. To address this question, it is necessary to use olivocerebellar explants from mouse embryos, an in vitro model of synapse formation and elimination (Chedotal et al. 1997; Letellier et al. 2009). To obtain these explants, the brain regions between the tecto-cerebellar and medullo-spinal junctions (including the cerebellar plate and the inferior olivary nucleus) are isolated from the brains of mouse embryos at E14, and the resulting explants are cultured en bloc (Fig. 5a). Moreover, it is possible to separate the cerebellar plate from the brainstem

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Fig. 5 Schematic diagram showing the explant model. (a) Procedure for mouse explant cultures at E14. The dashed lines indicate cuts. Hindbrains containing the cerebellum and brainstem are opened (thick arrows) and cultured as “openbooks” on millicell membranes. (b) Denervated cerebellar plates after 21 days in vitro (DIV) are cocultured with intact mature explants. Reinnervating climbing fibers can be visualized with GFP. (c) Denervated cerebellar plates after 21 DIV are cocultured with immature brainstems at 0 DIV (heterochronic coculture). Young climbing fibers, visualized with GFP, reinnervated Purkinje cells in the cerebellar plate. (Modified from Letellier et al. 2009)

either at the time of culture (to develop without climbing fiber afferents) or at later stages (to reproduce cerebellar denervation) and then coculture the cerebellar plate and observe the process of reinnervation (Letellier et al. 2009). This model allows cultures to be grown intact, to study normal synaptic development between climbing fibers and Purkinje cells, or to coculture presynaptic (brainstem) and postsynaptic (cerebellum) tissues of different ages and observe synapses formed in these circumstances. Using this system, normal developmental climbing fiber innervation of Purkinje cells can be observed in intact explants: multiple climbing fibers innervate each Purkinje cell at early stages, and this multi-innervation regresses during the ages equivalent to the first postnatal weeks resulting in monoinnervation at ages equivalent to P15 in vivo (Letellier et al. 2009). In addition, if lesions and cocultures are made with mature cerebellar plates and brainstems of the same age (Fig. 5b), the host climbing fibers directly mono-reinnervate the mature cocultured Purkinje cells; i.e., mature olivary axons, which already contact their normal Purkinje cell targets, are able to reinnervate new target Purkinje cells and do so without a transient phase of multi-innervation (Letellier et al. 2009). This result directly confirms the analogous experiment in vivo, in which mature climbing fibers directly mono-reinnervate mature Purkinje cells after their denervation by pedunculotomy (Letellier et al. 2007). However, interesting differences are observed in “heterochronic” cocultures, in which young brainstems (as a source of immature climbing fibers) are cocultured with mature cerebellar plates (Fig. 5c). In these circumstances, immature climbing fibers were found to multi-reinnervate mature Purkinje cells (Letellier et al. 2009). This result indicates that the maturation state of the presynaptic axon also has a role

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in determining the number of afferents that initially make synaptic contacts on the target neuron. Manipulating the presynaptic and postsynaptic partners separately also allows examination of the influence of prior innervation and synapse elimination as a controlling factor in neosynaptogenesis in the maturing nervous system. Separating the cerebellar plate from the brainstem at the time of explant culture allows the Purkinje cells to develop without climbing fiber innervation (Fig. 6a; Letellier et al. 2009). These mature but “naive” Purkinje cells were then compared to normally developed Purkinje cells of the same age which had undergone the normal process of climbing fiber innervation followed by synapse elimination (Fig. 5b). The “naive” Purkinje cells became multiply innervated by mature climbing fibers, whereas the normally developed Purkinje cells were mono-reinnervated by mature climbing fibers (Fig. 6d). The key factor in these two experimental groups is the process of initial innervation. If either partner is undergoing innervation for the first time (immature climbing fibers or “naïve” Purkinje cells), then there is a process of multiinnervation. This suggests that developmental olivocerebellar synaptogenesis, synapse selection, and elimination induce long-term changes in each synaptic partner, which critically determine their subsequent interactions. Notably, multiple innervation does not take place if both synaptic partners are mature and have already experienced the process of developmental synapse elimination. This absence of multiple innervation means that synaptic competition cannot take place during reinnervation and thus partner selection must be controlled by other mechanisms.

A Critical Period for Synapse Elimination? The experiments mentioned above indicate that the number of climbing fibers that synapse onto an individual Purkinje cell is partly determined by the maturation of each synaptic partner, in particular their prior innervation experience. However, it has previously been shown that the synapse elimination process takes place during a specific critical period (during which NMDA-receptor activation is necessary; Kakizawa et al. 2000). Is there a developmental age after which a Purkinje cell can no longer eliminate supernumerary climbing fiber synapses? Longer post-coculture analysis of “heterochronic” explants showed that mature Purkinje cells which have been multiply (re)innervated (see above) never underwent subsequent synapse elimination and retained multiple climbing fibers (Letellier et al. 2009). The synapse elimination process is thus restricted to a critical period during development, a period which seems to depend upon the age of the Purkinje cell and is independent of prior climbing fiber innervation “experience” (Letellier et al. 2009). This critical period may be cell-autonomous or due to interactions of the Purkinje cell with its other afferents (parallel fibers, inhibitory interneurons). Notably, the presence of parallel fibers, which facilitate supernumerary climbing fiber elimination during development, may have a permissive role, but in mature Purkinje cells, their presence was not sufficient to allow climbing fiber synaptic competition and elimination.

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Fig. 6 (a) “Naive” cerebellar plates, cultured for 21 DIV in the absence of climbing fiber innervation, are then cocultured with either whole mature explants or immature brainstems. GFP-expressing climbing fibers grow into these cerebellar plates. (b) Micrograph illustrating an isochronic coculture of a “naive” cerebellar plate, labeled with calbindin, with an age-matched intact explant expressing GFP. Scale bar ¼ 1 mm. (c) A confocal image of GFP-positive climbing fibers making contacts (arrowheads) with “naive” Purkinje cells (asterisks). (d) Climbing fiber responses recorded in a non-naive (normally developed) Purkinje cell (left) and a “naive” Purkinje cell (right). The “naive” Purkinje cell shows multiple climbing fiber responses, whereas the normally developed Purkinje cell is innervated by a single climbing fiber

Results obtained with this coculture system show that the two synaptic partners must be modified during developmental synapse formation and selective stabilization and that bidirectional recognition signals seem to be put in place during this process; these recognition signals then could allow synaptic partners to recognize one another during post-lesion reinnervation.

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Conclusions Selective synapse elimination is an important developmental process leading to the establishment of functional synaptic circuits. This chapter has described the roles of maturation of each synaptic partner in this process. Specifically, the target Purkinje cell plays a major role in defining afferent selection, both during normal development and during reinnervation in the mature system. Moreover, the Purkinje cell’s prior synaptic experience determines the capacity for multi-innervation and subsequent afferent selection. In contrast, climbing fibers retain a considerable capacity to sprout and (re)innervate multiple Purkinje cell targets and are constrained by the Purkinje cell’s status.

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Synaptogenesis and Synapse Elimination

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Masanobu Kano and Masahiko Watanabe

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climbing Fiber Synaptogenesis on Immature Purkinje Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional Differentiation and Selective Strengthening of Single Climbing Fiber Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dendritic Translocation of Single Climbing Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Early Phase of Climbing Fiber Synapse Elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Late Phase of Climbing Fiber Synapse Elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heterosynaptic and Homosynaptic Competition in Purkinje Cell Synaptic Wiring . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Formation of excess synaptic connections at perinatal stage and subsequent elimination of redundant synapses and strengthening of the surviving ones are crucial steps for functional neural circuit formation in the developing nervous system. Shortly after birth in murine life, excitatory synapses are present on the somata of Purkinje cells (PCs) from climbing fibers (CFs) that originate from neurons in the inferior olive of the contralateral medulla oblongata. At this developmental stage, each PC is innervated by multiple (around five) CFs with almost equal strengths. Subsequently, a single CF is selectively strengthened relative to the other CFs during the first postnatal week. Then, around postnatal

M. Kano (*) Department of Neurophysiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan e-mail: [email protected] M. Watanabe Department of Anatomy, Faculty of Medicine, Hokkaido University, Sapporo, Japan e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_14

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day 9 (P9), only the strongest CF (“winner” CF) starts to extend its innervation to PC dendrites. On the other hand, synapses of the weaker CFs (“loser” CFs) remain on the soma and the most proximal portion of the dendrite, and they are eliminated progressively during the second and the third postnatal weeks. From around P7 to P11, the elimination proceeds independently of the formation of the synapses on PC dendrites from parallel fibers (PFs), the other excitatory afferents to PCs. From around P12 and thereafter, the elimination of weaker CFs requires normal PF-PC synapse formation and is presumably dependent on the PF synaptic inputs that activate type 1 metabotropic glutamate receptor (mGluR1) and its downstream signaling in PCs. Most PCs become mono-innervated by single CFs in the third postnatal week. In this chapter, we will integrate the current knowledge of synaptogenesis and subsequent synapse elimination at CF to PC connections during postnatal cerebellar development. Keywords

Cerebellum · Climbing fiber · Dendrite · Development · Elimination · Granule cell · Inferior olive · Mossy fiber · Parallel fiber · Purkinje cell · Synapse · Synaptic competition · Synaptogenesis

Introduction In the process of neural circuit formation during postnatal development, supernumerary synapses are formed transiently around birth, and then functionally important synapses are strengthened, while unnecessary synapses are weakened and eventually eliminated. This process is known as “synapse elimination” and is widely thought to be an important mechanism to refine initial immature neural circuits into functionally mature ones. Synapse elimination has been studied extensively in the neuromuscular junction and autonomic ganglia (Gan et al. 2003; Walsh and Lichtman 2003). However, it is difficult to perform such detailed analyses in the central nervous system (CNS), because of small size of synapse, heterogeneity, and abundance of synaptic inputs to each neuron, and complexity of synaptic organization. In this respect, the climbing fiber (CF) to Purkinje cell (PC) synapse in the cerebellum is an exceptional case and provides an excellent model to study synapse elimination in the CNS (Crepel 1982; Lohof et al. 1996; Hashimoto and Kano 2005; Kano and Hashimoto 2009). PCs in the adult cerebellum receive two major excitatory inputs, namely, parallel fibers (PFs) and CFs (Palay and Chan-Palay 1974; Ito 1984). PFs are bifurcated axons of cerebellar granule cells (GCs) and form synapses on spines of PC’s distal dendrites. Each synaptic input is weak but as many as 100,000 PFs make contacts on a single PC (Palay and Chan-Palay 1974; Ito 1984). In contrast, the majority of PCs in the adult cerebellum are innervated by single CFs (mono-innervation), but each CF makes strong synaptic contacts on PC’s proximal dendrites (Ito 1984). In early postnatal days, however, all PCs are innervated by multiple CFs (multiple innervation). These surplus CFs are eliminated eventually and mono-innervation is attained in the third postnatal week (Crepel 1982; Lohof

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et al. 1996; Hashimoto and Kano 2005, 2013; Kano and Hashimoto 2009; Watanabe and Kano 2011). In this chapter, we will describe how CF synapses are formed, single CFs are selected and their synapses are strengthened, and synapses of redundant CFs are eliminated during postnatal cerebellar development.

Climbing Fiber Synaptogenesis on Immature Purkinje Cells Axons from inferior olivary neurons reach the primitive cerebellum around E18 (Wassef et al. 1992). They ramify and give rise to thick and thin collaterals. This stage is called the “creeper stage” (Chedotal and Sotelo 1993) at which the thick collaterals, the “climbing fibers,” creep between PCs. At this stage, PCs have bipolar shapes (called “simple- and complex-fusiform cells”) (Armengol and Sotelo 1991) and are organized in a multicellular layer. Initially, each olivocerebellar axon forms about 100 “creeper” CFs, which is much larger (~7) than that in the adult (Sugihara 2005). Then, the three stages of CF to PC synapse formation follow, which are described by Ramón y Cajal in his pioneering studies (Cajal 1911): the “pericellular nest” stage, the “capuchon” stage, and the “dendritic” stage. At the “pericellular nest” stage, CFs surround the cell bodies of PCs which undergo explosive outgrowth of perisomatic protrusions in all directions from the cell bodies (called the phase of “stellate cells”) (Armengol and Sotelo 1991). CFs establish contacts with the abundant pseudopodia stemming from the soma and form a plexus on the lower part of PC somata. Among the 100 “creeper” CFs of each olivocerebellar axon, only around 10 can develop “pericellular nests.” The “capuchon” stage is characterized by the displacement of the plexus to the apical portion of PC somata and main dendrites. Then, the “dendritic” stage is characterized by the upward spread of CF innervation into dendrites. Electrophysiological evidence indicates that functional CF synapses are formed on immature PCs around P3. In juvenile rats and mice in vivo, stimulation in the inferior olive after P3 elicits CF-mediated responses in PCs (Crepel 1971). However, the responses of juvenile PCs are graded in parallel with the increase in the stimulus strength (Crepel et al. 1976), which indicates that PCs are innervated by multiple CFs in juvenile rodent cerebellum. Later studies in vivo clarified that both the percentage of PCs innervated by multiple CFs and the average number of CFs innervating individual PCs decrease with postnatal development and that most PCs become innervated by single CFs by the end of the third postnatal week (Crepel et al. 1981; Mariani and Changeux 1981). Thus, these earlier studies performed in mice and rats in vivo have established that elimination of redundant CF inputs occurs during postnatal development of the cerebellum as in the neuromuscular synapses in the periphery.

Functional Differentiation and Selective Strengthening of Single Climbing Fiber Inputs When recorded from PCs in cerebellar slices at P2–3, clearly discernible excitatory postsynaptic currents (EPSCs) can be elicited by stimulating CFs. EPSCs appear

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with discrete steps by gradually increasing stimulus strength, clearly indicating that PCs at this age are innervated by multiple CFs. The amplitudes of EPSCs elicited by stimulating multiply-innervating CFs at this stage are much smaller than those evoked by mature CFs at later developmental stage (Hashimoto and Kano 2003, 2005; Scelfo and Strata 2005; Bosman et al. 2008; Ohtsuki and Hirano 2008). Therefore, CF inputs become stronger, while redundant CFs are eliminated during postnatal development. In anesthetized animals in vivo, Mariani and Changeux found that CF stimulation elicited in some PCs two CF-mediated responses whose amplitudes were quite different around P10 to P13 (Mariani and Changeux 1981). This result suggests that only one CF is strengthened relative to the others before the completion of synapse elimination. Developmental changes in the synaptic strengths of multiple CFs innervating the same PC were systematically investigated in mice aged P2 to P21 using whole-cell voltage-clamp recordings from PCs in acute cerebellar slices (Hashimoto and Kano 2003). To search CFs innervating the PC under recording, the stimulation pipette was moved systematically and the stimulus strength was increased gradually at each stimulation site. The number of CFs innervating each PC was judged by the number of discrete CF-EPSCs, and the strengths of individual CF inputs were estimated from the sizes of CF-EPSCs. This quantitative study shows that more than five discrete CF-EPSCs with roughly similar amplitudes are present in PCs from mice around P3 (Fig. 1a, ~P3). In contrast, in the second postnatal week, PCs with multiple CF innervation have one large CF-EPSC and a few relatively small CF-EPSCs (Fig. 1a, ~P7 and ~P12). These results suggest that synaptic strengths of multiply-innervating CFs are relatively uniform in neonatal mice, and one CF is selectively strengthened during postnatal development (Hashimoto and Kano 2003, 2005; Bosman et al. 2008; Ohtsuki and Hirano 2008). Quantitative assessments of the disparity among

Fig. 1 Postnatal development of CF-PC synapses. (a) Diagrams of CF-PC synapses at four representative stages of postnatal development in mice. (b) Four distinct phases in postnatal development of CF synapses

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the synaptic strengths (i.e., amplitudes of multiple CF-EPSCs) in individual PCs demonstrate that the disparity progressively increases from P3 to P6 and reaches a stable level at P7. This result indicates that one CF is selectively strengthened among multiple CFs innervating the same PC during the first postnatal week (Fig. 1b, (1) functional differentiation) (Hashimoto and Kano 2003). Meanwhile, it was shown that the innervation pattern of CFs over PCs drastically changed during the first postnatal week in rats (Sugihara 2005), which was consistent with the electrophysiological data in mice (Hashimoto and Kano 2003). At P4 in rat, CFs have many creeping terminals in the PC layer, and their swellings did not aggregate at particular PC somata (creeper type). Then, from P4 to P7, CFs surrounded several specific PC somata and formed aggregated terminals on them (nest type) (Sugihara 2005). Kawamura et al. investigated developmental changes in CF-mediated excitatory responses in rats and mice in vivo (Kawamura et al. 2013). By using in vivo whole-cell recordings and two-photon calcium imaging, they demonstrated that each PC at around P4 received temporally clustered excitatory inputs from multiple CFs that generated burst spiking and accompanying Ca2+ rise in that PC. They also showed that a single CF input closest in time to PC’s spike output selectively became stronger by P8 (Kawamura et al. 2013), which supports the previous in vitro study by Hashimoto and Kano (2003). Recently, Good et al. recorded PC population activity using in vivo two-photon calcium imaging and demonstrated that CF responses were highly synchronized in newborn mice and massively desynchronized during P4 to P8 (Good et al. 2017). This desynchronization of CF population responses appears to reflect the CF network refinement from “creeper type” to “nest type” terminals (Good et al. 2017). There are clear differences in electrophysiological properties between EPSCs elicited by the strongest CF input and those by the other weaker inputs. The sizes of glutamate transient in the synaptic cleft in response to CF stimulation can be estimated by using non-equilibrium inhibition of AMPA receptors by a low-affinity competitive antagonist (Clements 1996). These values were significantly larger for the strongest CF than for the weaker CFs (Hashimoto and Kano 2003). However, in a low extracellular Ca2+ concentration in which CF-EPSCs resulted from one-site one vesicle release, the amplitudes of glutamate transients for the strongest and the weaker CFs were not different (Hashimoto and Kano 2003). This result indicates that the sizes of glutamate transients caused by single synaptic vesicles are the same between the two types of CF inputs. Therefore, the larger glutamate transients by stimulating the strongest CF are thought to result from the higher probability of multivesicular release. Further electrophysiological examination suggests that the release probability is not different between the two types of CF inputs. Therefore, it is thought that the number of release site facing a narrow postsynaptic region of PC is larger in the strongest CF than in weaker CFs. Hashimoto et al. demonstrated that Cav2.1, a pore-forming component of the P/Q-type voltage-dependent Ca2+ channel (VDCC), was crucial for the biased strengthening of a single CF (Hashimoto et al. 2011). The P/Q-type VDCC is one of the high-voltage-activated Ca2+ channels and constitutes >90% of the total Ca2+ current density in PCs (Mintz et al. 1992; Stea et al. 1994). The P/Q-type VDCC is

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abundantly distributed in PC dendrites and spines in addition to presynaptic terminals (Kulik et al. 2004; Miyazaki et al. 2012). In the PC-specific P/Q-type VDCC knockout mice, the selective strengthening of a single CF input during the first postnatal week was severely impaired, and multiple CFs were nonselectively strengthened (Hashimoto et al. 2011). Kawamura et al. showed by in vivo wholecell recordings that a selective strengthening of single CF input closest in time to PC’s spike output was impaired in PC-specific P/Q-type VDCC knockout mice (Kawamura et al. 2013), which supports the in vitro study by Hashimoto et al. (2011). These results suggest that biasing the competition toward a single CF input is mediated by P/Q-type VDCC in PCs (Fig. 2).

Dendritic Translocation of Single Climbing Fibers Morphological evidence indicates that the sites of CF synapses on PCs move from soma to dendrite during early postnatal development, which is known as “climbing fiber translocation” (Altman and Bayer 1997). Hashimoto et al. (2009a) clarified the relationship between the selective strengthening of single CFs and CF translocation by using electrophysiological and morphological techniques (Hashimoto et al. 2009a). The location of synapses along the somatodendritic domains of PCs can be estimated by analyzing the kinetics of EPSCs arising from single synaptic vesicles (termed quantal EPSCs) in CF terminals. In a Sr2+-containing external solution, stimulation of presynaptic axons causes asynchronous release of synaptic

Fig. 2 Molecules involved in key events of postnatal development of CF-PC synapses including the four phases described in Fig. 1b

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vesicles. The quantal EPSCs arising from a stimulated CF can be recorded under this experimental condition (Hashimoto and Kano 2003; Hashimoto et al. 2009a). Under whole-cell recordings from the soma, quantal EPSCs originating from PC dendrites are strongly attenuated by dendritic filtering. Because CFs that have translocated to PC dendrites have synapses with different electrotonic lengths from the somatic recording site, individual quantal EPSCs should undergo different degrees of distortion depending on the locations of CF synapses along PC dendrites. Since the rise time of quantal EPSCs is reported to be proportional to the distance from the synaptic sites to the soma (Roth and Hausser 2001), distribution of the rise of quantal EPSCs for a CF reflects the extent of dendritic translocation of that CF. At P7–P8 when the selective strengthening of single CF in each PC has just completed, there is no significant difference in the distribution of quantal EPSCs’ rise time for the strongest CF and for the weaker CFs. This result indicates that synapses of the strongest CF and weaker CFs are located on the soma at this developmental stage (Fig. 1a, ~P7). At P9–P10, the incidence of quantal EPSCs with slow rise time is more frequent for the strongest CF than for the weaker CFs, suggesting that CFs begin to expand their innervation territories to dendrites (Fig. 1b (3) CF translocation). The difference in the distribution of quantal EPSC rise times for the strongest CF and for the weaker CFs becomes larger from P11 to P14. While the incidence of quantal EPSCs with slow rise time becomes more frequent for the strongest CF with age, the quantal EPSC rise time for the weaker CFs remains almost unchanged from P9 to P14. These electrophysiological data collectively indicate that (1) synaptic competition among multiple CFs occurs on the soma before P7 (Fig. 1a, ~P3 and ~P7, Fig. 1b (1) functional differentiation), (2) only the strongest CF (“winner” CF) starts to translocate to dendrites at P9 and the translocation continues thereafter (Fig. 1a, ~P12, Fig. 1b (3) CF translocation), and (3) synapses of the weaker CFs (“loser” CFs) remain around the soma (Fig. 1a, ~P12). Morphological data also supports these notions of CF synapse development (Hashimoto et al. 2009a; Ichikawa et al. 2011, 2016). When subsets of CFs are labeled by an anterograde tracer, biotinylated dextran amine (BDA), injected into the inferior olive, pericellular nests of CFs are observed at P7, P9, and P12. At P7, in spite of the presence of growing stem dendrites in PCs, CF synapses are confined to the soma and are absent on the dendrites. CF synapses are first found on PC dendrites at P9. At P12 and thereafter, the territory of CF innervation extends progressively along with robust outgrowth of PC dendrites. It should be noted that the strongest CFs translocating to dendrites keep their synapses on PC somata until around P12. In contrast, synaptic terminals of the weaker CFs are confined to the soma and the basal part of the primary dendrite. These weaker CFs are thought to be collaterals of the strongest CFs innervating adjacent PCs. Thus, pericellular nests represent multiple CF innervation of PCs (Hashimoto et al. 2009a). Using the method of staining subsets of CFs by an anterograde tracer and of labeling all CF terminals simultaneously by immunostaining of the CF terminal marker vesicular glutamate transporter 2 (VGluT2), Hashimoto et al. demonstrated that multiple CFs innervated PC dendrites of PC-specific P/Q-type VDCC knockout mice (Hashimoto et al. 2011). This result clearly indicates that the P/Q-type VDCC is

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crucial for dendritic translocation of a single winner CF in each PC (Fig. 2). Carrillo et al. reported the results from two-photon multicolor viral imaging of CFs in developing mouse cerebellum in vivo (Carrillo et al. 2013). Their results largely confirm the conclusions derived from the electrophysiological and morphological data described above. Moreover, their time-lapse imaging in vivo demonstrated that the motility of CF terminals on the soma was much higher than those on dendrites and that the CF which began dendritic translocation indeed became the winner (Carrillo et al. 2013). In addition, Kakegawa et al. recently demonstrated that C1ql1, a member of C1q family proteins, anterogradely strengthened and maintained a single winner CF (Kakegawa et al. 2015) (Fig. 2). They reported that C1ql1 derived from CFs acted on brain-specific angiogenesis inhibitor 3 (Bai3) in PCs and exerted the following three effects: strengthening/maintenance of the strongest CF from around P9, facilitation of dendritic translocation of the strongest CF, and elimination of the weaker CFs from P9 (Kakegawa et al. 2015) (Fig. 2).

Early Phase of Climbing Fiber Synapse Elimination Earlier studies on spontaneous mutant mice (Crepel and Mariani 1976; Mariani et al. 1977; Crepel et al. 1980; Mariani and Changeux 1980) and animals with experimentally induced “hypogranular” cerebella (Woodward et al. 1974; Crepel and Delhaye-Bouchaud 1979; Bravin et al. 1995; Sugihara et al. 2000) have revealed that the presence of intact granule cells and normal formation of PF-PC synapses are prerequisite for CF synapse elimination. Crepel et al. (1981) showed that elimination of surplus CFs consists of two distinct phases, the early phase up to around P8 and the late phase from around P9 to P17 (Crepel et al. 1981). The early phase occurred normally in animals with “hypogranular” cerebella, whereas the late phase was severely impaired by inhibiting granule cell production, indicating that the early phase of CF synapse elimination proceeds independently of PF-PC synapse formation, whereas the late phase is critically dependent on it. However, since the animal models with “hypogranular” or “agranular” cerebella have abnormalities of cerebellar development other than granule cell genesis and PF-PC synapse formation, there remained a possibility that CF synapse elimination might be influenced by such developmental defects. Detailed assessment of the postnatal development of CF innervation in mouse cerebellar slices demonstrated that there was no significant reduction but rather a tendency of increase in the average number of CFs per PC from P3 to P6 when functional differentiation of multiple CFs occurred (Hashimoto et al. 2009b). Then, the value decreased progressively from P6 to around P15 (Scelfo and Strata 2005; Hashimoto et al. 2009b). These results indicate that CF synapse elimination does not proceed in parallel with functional differentiation of multiple CFs but starts after the strengthening of single CFs in individual PCs. The analysis of mutant mice deficient in glutamate receptor GluD2 (GluRδ2) indicates two distinct phases of CF synapse elimination (Hashimoto et al. 2009b). GluD2 is richly expressed at the PF-PC synapse, and its deletion causes impairment

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of PF-PC synapse formation leading to reduction to about half the number of wildtype mice. Nevertheless, GluD2 deletion does not significantly affect the general histoarchitecture of the cerebellum or morphology of PCs (Kashiwabuchi et al. 1995; Kurihara et al. 1997). In GluD2 knockout mice, the average number of CFs innervating each PC was similar to that of control mice from P5 to P11. However, the value was significantly larger than that of control mice from P12 to P14 (Hashimoto et al. 2009b). These results collectively indicate that CF synapse elimination in mice can be classified into two distinct phases, namely, the “early phase” from around P7 to P11 which is independent of PF-PC synapse formation and the “late phase” from around P12 and thereafter which requires normal PF-PC synapse formation (Fig. 1b (2) early phase and (4) late phase of CF elimination) (Hashimoto et al. 2009b). Several reports strongly suggest that PC activity is crucial for CF synapse elimination. Lorenzetto et al. generated transgenic mice that expressed a chloride channel-YFP fusion specifically in PCs to suppress their excitabilities (Lorenzetto et al. 2009). In these mice, the expression of chloride channel was observed in PCs during the “early phase” at P9, and multiple CF innervation persisted up to P90. Therefore, perturbation of PC activity is considered to cause impairment of the “early phase” of CF synapse elimination. Andjus et al. disrupted the normal activity pattern of CF in rat at P9–P12 by administration of harmaline, which induced synchronous activation of neurons in the inferior olive (Andjus et al. 2003). This treatment caused persistent multiple CF innervation of PCs in rats at P15–P87, suggesting that proper activity patterns of PCs during the early phase are important. Hashimoto et al. demonstrated that the early phase of CF synapse elimination was severely impaired in PC-specific P/Q-type VDCC knockout mice (Hashimoto et al. 2011). This result clearly indicates that PC activity and activation of P/Q-type VDCC is essential for the early phase of CF synapse elimination (Fig. 2). As for possible molecular mechanisms, insulin-like growth factor I (IGF-1) was reported to be involved in CF synapse elimination from P8 to P12 (Kakizawa et al. 2003). IGF-1 is thought to enhance the strengths of CF synapses and promote their survival, whereas the shortage of IGF-1 appears to impair the development of CF synapses (Kakizawa et al. 2003). Sherrard et al. reported that the activated and fulllength forms of TrkB, a receptor for brain-derived neurotrophic factor (BDNF), fell, while the expression of the truncated form, which acts as a negative regulator of TrkB signaling, increased around the onset of the early phase of CF synapse elimination (Sherrard et al. 2009). This finding suggests that decrease in TrkB signaling might permit the elimination of surplus CF synapses (but see below about the role of BDNF in the late phase of CF synapse elimination). Oostland et al. reported that CF synapse elimination was delayed in serotonin 3A (5-HT3A) receptor knockout mice from the early phase (Oostland et al. 2013). They claimed that HT3A receptor was expressed in granule cells and deletion of HT3A caused accelerated maturation of PC dendrites, abnormal physiological maturation of PF-PC synapse, and delayed CF synapse elimination (Oostland et al. 2013). On the other hand, Juttner et al. (2013) showed accelerated CF synapse elimination during the early phase in chondroitin sulfate proteoglycan (CSPG)5/neuroglycan C knockout mice (Juttner et al. 2013). They reported that CSPG5/neuroglycan C was

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expressed in PCs at P5 and P10 and the knockout mice displayed impaired presynaptic maturation of inhibitory synapses and acceleration of the early phase of CF synapse elimination (Juttner et al. 2013) (Fig. 2). Furthermore, Kakegawa et al. recently reported that C1ql1-Bai3 anterograde signaling was required for elimination of weaker CFs after P9 (Kakegawa et al. 2015) (Fig. 2) in addition to strengthening/ maintenance of the strongest CF and facilitating dendritic translocation of the winner CF (Fig. 2). Uesaka et al. performed a screening of candidate molecules that potentially mediate retrograde signals from postsynaptic PCs to presynaptic CFs for CF synapse elimination. They found that semaphorin3A (Sema3A) presumably secreted from PCs strengthened CF synapses by retrogradely acting on Plexin A4 (PlxnA4) on CF terminals (Uesaka et al. 2014) (Fig. 2). They showed that microRNA-mediated knockdown of Sema3A in PCs or that of PlxnA4 in CFs in neonatal mice accelerated CF synapse elimination from P8 and reduced the amplitude of CF-EPSC, suggesting that Sema3A to PlxnA4 signaling strengthens CF synapses and therefore opposes their elimination during the early phase (Uesaka et al. 2014). Morphological data indicate that CFs that undergo dendritic translocation keep their synapses on the PC soma during the second postnatal week. In contrast, synaptic terminals of the weaker CFs are confined to the soma and the basal part of the primary dendrite. The characteristic pericellular nest consists of somatic synapses originating from collaterals of a single predominant CF and from weaker CFs and thus represents multiple CF innervation of PCs (Hashimoto et al. 2009a). Therefore, CF synapse elimination is thought to be a process of nonselective pruning of perisomatic synapses, which spares dendritic synapses of a single predominant CF and leads to mono-innervations of that CF (Hashimoto et al. 2009a).

Late Phase of Climbing Fiber Synapse Elimination Quantitative morphological analyses by Ichikawa et al. demonstrated that CFs formed synapses on somatic protrusions and thorns (collectively called spines) of PCs at around P9 and that such somatic CF synapses steadily decreased in number from P9 to P15 and almost disappeared at P20 (Ichikawa et al. 2011). Interestingly, as perisomatic CF synapses decrease, somatic spines appear to be taken over by basket cell axons and Bergmann glia and transient GABAergic synapses are formed on somatic spines from P9 to P15. Then, postsynaptic receptors switch from glutamatergic to GABAergic, somatic spines disappear, and GABAergic terminals of basket cell axons are on the flat somatic membrane (Ichikawa et al. 2011). In the mature cerebellum, PFs form synaptic contacts on spines of PC distal dendrites, whereas CFs innervate their proximal dendrites. In GluD2 knockout mice, the density of PF-PC synapses is decreased to about half of wild-type mice, and about 40% of spines are “naked” spines that are not contacted by PF terminals. Consequently, CFs invades into the distal dendrites and form ectopic synapses there (Hashimoto et al. 2001; Ichikawa et al. 2002; Hashizume et al. 2013). These ectopic CF synapses appeared around P10 when PF synapse formation as well as the

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extension of PC dendritic arbor occur most vigorously. These results indicate that PFs compete for postsynaptic sites on PC dendrites with CFs during development, and confine the CF innervation territories to proximal dendrites (Fig. 3, “(2) confines CF synapses to proximal dendrites”). PF-PC synapses transmit signals from mossy fibers to PCs. In particular, impulses along PFs activate type 1 metabotropic glutamate receptor (mGluR1), and its downstream signaling cascades in PCs, which has been shown to drive the process of CF synapse elimination (Kano and Hashimoto 2009) (Fig. 2). Electrophysiological examination demonstrated that the mutant mice deficient in mGluR1 were impaired in CF synapse elimination (Kano et al. 1997; Levenes et al. 1997). Mice deficient in signaling molecules downstream of mGluR1, Gαq, PLCβ4, or PKCγ were also impaired in CF synapse elimination (Kano et al. 1995, 1998; Offermanns et al. 1997; Hashimoto et al. 2000). Electrophysiological examination of CF innervation following postnatal development demonstrated that the regression of CF

Fig. 3 CF-, PF-, and BG-dependent mechanisms essential for the establishment of CF monoinnervation and territory segregation in PCs. (Right) The CF-dependent mechanism is mediated by the P/Q-type VDCC. CF activity, which induces Ca2+ elevation in PCs through the P/Q-type VDCC, consolidates monopolized dendritic innervation by a single winner CF and eliminates synapses of the other weaker CFs and those of PFs from the soma and proximal dendrites of each PC. (Left) The PF-dependent mechanism consists of two systems. The GluD2-Cbln1-neurexin system consolidates PF synapses and confines CF synapses to proximal dendrites. The mGluR1PKCγ system eliminates CF synapses from the soma and PF synapses from proximal dendrites of each PC. (Upper) The BG-dependent mechanism is mediated by GLAST, which prevents glutamate spillover to neighboring synapse and helps the CF- and PF-dependent mechanisms operate properly

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synapse occurred normally during the first and second postnatal weeks in all of the four mouse strains. However, these mice displayed abnormality in synapse elimination during the third postnatal week. These results suggest that the signaling cascade from mGluR1 to PKCγ is essential for the late phase of CF synapse elimination. Importantly, formation of PF to PC synapses was not impaired in these mutant mice. Gross anatomy of the cerebellum and morphology of PC were largely normal. PCs had well-differentiated dendritic arbors with numerous dendritic spines, which was indistinguishable from wild-type PCs. Furthermore, structure and density of PF-PC synapses were normal in electron microscopic examination. These results indicate that the impaired CF synapse elimination is not caused secondarily by the defect in PF-PC synapse formation. Several lines of evidence indicate that mGluR1 signaling within PC is crucial for CF synapse elimination. The defect in the CF synapse elimination in the mGluR1 knockout mice was restored in the mGluR1a-rescue mice in which mGluR1a, one of the variants of mGluR1 that are generated by alternative splicing (Ferraguti et al. 2008), was introduced specifically into PCs (Ichise et al. 2000). Regression of CF synapses was impaired in mice by PC-specific expression of a PKC inhibitor peptide (De Zeeuw et al. 1998). Furthermore, the distribution of multiply-innervating PCs in the cerebellum of PLCβ4 knockout mouse exactly matched that of the PCs with predominant expression of PLCβ4 in the wild-type mouse cerebellum (Kano et al. 1998; Hashimoto et al. 2000). In contrast to mGluR1a-rescue mice, PC-specific expression of mGluR1b into mGluR1 knockout mice failed to rescue the impaired CF synapse elimination (Ohtani et al. 2014). While mGluR1a has a long C-terminal domain that interact with scaffolding proteins, mGluR1b lacks such long C-terminal domain (Ferraguti et al. 2008). These results collectively indicate the signaling from mGluR1a to PKCγ in PCs, but no other cell types should play a central role in CF synapse elimination. Evidence suggests that mGluR1 activation at PF synapses drives the late phase of CF synapse elimination. It is known that mGluR1 can readily be activated by PF inputs (Batchelor et al. 1994; Finch and Augustine 1998; Takechi et al. 1998), while hardly by CF inputs without blockade of glutamate transporters (Dzubay and Otis 2002). Furthermore, chronic blockade of NMDA receptors within the cerebellum resulted in the impairment of CF synapse elimination (Rabacchi et al. 1992) specifically in its later phase (Kakizawa et al. 2000). NMDA receptors are not present at either PF or CF synapses on PCs, but they are abundantly expressed at mossy fiber to granule cell synapses. These results suggest that neural activity along mossy fiber-granule cell-PFPC pathway and the subsequent activation of mGluR1 are prerequisite for the late phase of CF synapse elimination (Kakizawa et al. 2000). Recent studies have identified molecules that function downstream of mGluR1 to exert CF synapse elimination (Fig. 2). While screening candidate retrograde signaling molecules from PCs to CFs that mediate CF synapse elimination, Uesaka et al. found that microRNA-mediated knockdown of semaphorin7A (Sema7A) in PCs of neonatal mice caused impairment of the late phase of CF synapse elimination (Uesaka et al. 2014). Importantly, double knockdown of mGluR1 and Sema7A in neonatal PCs impaired CF synapse elimination to the same extent as mGluR1

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knockdown alone, indicating that the effect of Sema7A knockdown was occluded by simultaneous mGluR1 knockdown. On the other hand, overexpression of Sema7A into PCs with mGluR1 knockdown restored CF synapse elimination. Knockdown of putative Sema7A receptors, Plexin C1 (PlxnC1) and Integrin B1 (ItgB1), in the inferior olive in neonatal mice caused impairment of CF synapse elimination. Further studies suggest that PlxnC1 and ItgB1 facilitate CF synapse elimination by inactivating cofilin and activating focal adhesion kinase, respectively, in CFs (Uesaka et al. 2014; Uesaka and Kano 2018). Taken together, these results indicate that retrograde Sema7A to PlxnC1/ItgB1 signaling is driven downstream of mGluR1 signaling and facilitates CF synapse elimination after P15 by regulating cofilin and focal adhesion kinase in CFs (Uesaka et al. 2014; Uesaka and Kano 2018) (Fig. 2). In addition to Sema7A, Choo et al. (2017) recently reported experimental data that suggest BDNF derived from PCs downstream of mGluR1 acts retrogradely onto TrkB in CFs and promotes the late phase of CF synapse elimination (Choo et al. 2017) (Fig. 2). Previous studies showed that CF synapse elimination was impaired in mice with global or cerebellum-specific knockout of TrkB (Bosman et al. 2006; Johnson et al. 2007). However, it was unknown how and on which cell-type TrkB is activated to exert CF synapse elimination. Recently, Choo et al. reported that CF synapse elimination after P15 was impaired in PC-specific BDNF knockout mice, in PCs with microRNA-mediated BDNF knockdown, and in PCs surrounded by CFs in which TrkB was knocked down by injecting lentivirus carrying microRNA against TrkB into the neonatal inferior olive. Knockdown of mGluR1 in PCs of wild-type mice and that of PC-specific BDNF knockout mice caused impairment of CF synapse elimination to the same extent, suggesting that mGluR1 and BDNF function along the same signaling pathway. Interestingly, effect of Sema7A knockdown in PCs was occluded in PC-specific BDNF knockout mice, suggesting that BDNF and Sema7A share a common signaling pathway for the late phase of CF synapse elimination (Choo et al. 2017) (Fig. 2). Besides the roles of glutamatergic excitatory synapses, it is now clear that GABAergic inhibition regulates CF synapse elimination (Fig. 2). Nakayama et al. demonstrated that CF synapse elimination after P10 was impaired in mice with deletion of a single allele for the GABA-synthesizing enzyme GAD67 (Nakayama et al. 2012). In GAD67 heterozygous knockout mice, GABAergic inhibition to PCs was attenuated in the second postnatal week. Enhancing GABAA receptor sensitivity by diazepam applied to the cerebellum rescued the impaired CF synapse elimination. The authors further demonstrated that in the GAD67 heterozygous knockout mice, GABAergic inhibition from basket cells to PC somata was specifically attenuated and this reduction caused enhanced Ca2+ transients in PCs following activation of weaker CFs. The authors speculated that the enhanced Ca2+ transients in PCs permitted survival of weaker CFs and caused persistent multiple CF innervation (Nakayama et al. 2012). Mikuni et al. reported that the immediate early gene Arc/Arg3.1 mediated the postsynaptic activity of PCs and facilitated the late phase of CF synapse elimination (Mikuni et al. 2013). They showed that Arc expression in PCs was elevated by Ca2+ influx to PCs through P/Q-type VDCC. microRNA-mediated knockdown of Arc in

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PCs of neonatal mice caused impairment of CF synapse elimination from PC somata after P12 and increase in CF-EPSC amplitudes. Furthermore, in PC-specific TARPγ2 (stargazing) knockout mice in which the amplitudes of EPSCs in PCs were globally scaled down to about 60% of those in wild-type mice, the late phase of CF synapse elimination was impaired because of insufficient activation of Arc in PCs (Kawata et al. 2014). These results indicate that P/Q-type VDCC-induced Ca2+ elevation and subsequent activation of Arc are required for the late phase of CF synapse elimination (Fig. 2). The molecules so far reported to contribute to the late phase of CF synapse elimination are summarized in Fig. 2. As for other molecules that may be involved in CF synapse elimination, a motor protein, myosin Va (Takagishi et al. 2007); a glutamate transporter, GLAST (Watase et al. 1998; Miyazaki et al. 2003); and a novel brain-specific receptor-like protein family, BSRP (Miyazaki et al. 2006), have been reported. Since genetic or pharmacological deletion of these molecules in mice impaired CF synapse elimination in the second postnatal week, these signaling cascades are thought to be involved in the “late phase” of CF synapse elimination. Recently, Miyazaki et al. demonstrated that GLAST was essential for keeping the integrity of Bergmann glia (BG) and for wrapping of PF and CF synapses by Bergmann glial processes. In GLAST knockout mice, mono-innervation of PCs by single strong CFs and segregation of CF and PF territories along PC dendrites did not develop normally (Miyazaki et al. 2017) (Fig. 3, “BG-dependent mechanism”). It was reported that null mutant mice deficient in Ca2+/calmodulin-dependent protein kinase IV (CaMKIV) had persistent multiple CF innervations, but it is unclear at what stage of postnatal development the impairment occurs (Ribar et al. 2000). It was also reported that null mutant mice deficient in αCaMKII displayed multiple CF innervation at P21–P28, but this phenotype disappeared in adulthood (Hansel et al. 2006), suggesting that αCaMKII deficiency delays but not prevent CF synapse elimination. It was reported that Lysotracker-positive structures surrounding PCs, which were presumed to be within BG, were abundant during the second and third postnatal weeks (Song et al. 2008). Lysotracker Red is a marker for the lysosomes and late endosomes of living cells, which positively stains bulb-shaped tips of retreating motor axons and the axon fragments (“axozomes”) engulfed by Schwann cells during synapse elimination of neuromuscular junction (Bishop et al. 2004). In the retinogeniculate synapses of the developing mice, redundant synapses are known to be eliminated through phagocytosis by microglia dependent on complement pathway (Schafer et al. 2012) and by astrocytes via multiple epidermal growth factor-like domain protein 10 (MEGF10) and MER tyrosine kinase (MERTK) pathway (Chung et al. 2013). Therefore, it is possible that retreating CF axons might be digested by microglia and/or astrocytes in a manner similar to the neuromuscular junction and retinogeniculate synapses. In contrast to the early phase, the late phase of CF synapse elimination is critically dependent on normal formation and function of PF-PC synapses (Fig. 3 “PF-dependent mechanism”). As mentioned above, PF-PC synapses play two distinct roles. First, PF synapses are stabilized by GluD2/Cbln1 and occupy the spines of distal dendrites of PCs, which confines the CF synapses to the proximal dendrites (Fig. 3,

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“GluD2/Cbln1”). Second, PFs convey neural activity from mossy fibers through mossy fiber to granule cell synapses. This neural activity activates mGluR1 at PF to PC synapses and drives its downstream signaling to PKCγ in PCs (Fig. 3, “mGluR1PKCγ”). Then the mGluR1 signaling activates two pathways that mediate retrograde signals from PCs to CFs, i.e., Sema7A to PlxnC1/ItgB1 and BDNF to TrkB. These two pathways seem eventually to converge in CFs to facilitate their elimination. These molecular cascades nonselectively eliminate somatic CF synapses from the weaker CFs and from somatic collaterals of the strongest CF (Fig. 3, “mGluR1-PKCγ”). In addition to mGluR1 signaling, the P/Q-type VDCC is important also for the late phase of CF synapse elimination (Fig. 3, “P/Q-type VDCC”). Arc is activated in PCs by Ca2+ elevation mediated by P/Q-type VDCC and facilities elimination of surplus CF synapses from the PC soma after P12. On the other hand, GABAergic inhibition from basket cells to the PC soma regulates elimination of somatic CF synapses after P10 presumably by suppressing Ca2+ elevation in PCs that is elicited by weaker CF inputs. It remains to be investigated how the level of Ca2+ elevation in PCs is controlled such that synapse elimination-promoting signals (such as Arc) and synapse maintenance signals (such as those suppressed by GABAergic inhibition) are balanced to properly accomplish the late phase of CF synapse elimination.

Heterosynaptic and Homosynaptic Competition in Purkinje Cell Synaptic Wiring Mono-innervation by the CF and segregated dendritic innervation by the PF and CF are the two distinguished features of PC circuits (Fig. 4 middle). The construction of the characteristic excitatory wiring depends on competitive equilibrium among afferents promoted by distinct molecular and cellular mechanisms. Surgical, pharmacological, and genetic manipulations that shift the equilibrium significantly alter the PC’s synaptic wiring. While CFs and PFs innervate proximal and distal portions of PC dendrites, respectively, there is an intermediate dendritic portion with overlapping innervation by CFs and PFs. Ichikawa et al. demonstrated that CF and PF territories expanded with marked enlargement of the dendritic regions with overlapping innervation until P15. Then the massive elimination of PF synapses from proximal dendrites occurred from P15 to around P30, and the CF and PF territories became segregated (Ichikawa et al. 2016). Importantly, this massive PF synapse elimination from P15 to around P30 was deficient in both mGluR1 knockout mice and PKCγ knockout mice, indicating that mGluR1 to PKCγ cascade is required for PF synapse elimination (Ichikawa et al. 2016) (Fig. 2). Disruption of GluD2 gene in mice not only impairs PF synapse formation but also affects the mode of CF innervation (Ichikawa et al. 2002). In the molecular layer, CF branches were distributed over the inner four-fifth in control mice, whereas their distribution almost reached the pial surface in GluD2 knockout mice. When the tracer-labeled CFs were followed from the soma to the tips of PC dendrites by serial electron microscopy, this expanded distribution represented distal extension of CF

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Fig. 4 Contrasting alterations in PC’s excitatory synaptic wiring between GluD2/Cbln1 knockout and P/Q-type VDCC knockout mice. (Middle) In wild-type mice, CF and PF territories are sharply segregated, and CF mono-innervation is established. (Left) In GluD2/Cbln1 knockout mice, CF innervation territory expands, and multiple CF innervation occurs frequently by additional wiring at distal dendrites. (Right) In P/Q-type VDCC knockout mice, PF innervation territory expands, and multiple CF innervation occurs at basal dendrites and somata. (Reproduced, with permission, from Tohoku Journal of Experimental Medicine 214:175–190, 2008)

branches to take over free spines on the distal dendritic compartment. Such an aberrant extension occurred toward not only distal dendrites of the innervating PCs but also those of the neighboring PCs. The latter type of spine takeover caused the innervation of a given PC by multiple CFs (Fig. 4, left). This anatomical evidence is consistent with electrophysiological recording combined with Ca2+ imaging. In GluD2 knockout mice, a single strong CF elicited large EPSCs with a fast rise time and high Ca2+ elevation over the entire dendritic tree, whereas weak CFs elicited small EPSCs with slow rise time and low Ca2+ elevation confined to some distal dendrites (Hashimoto et al. 2001). These findings indicate that GluD2 is also essential to restrict CF innervation to the proximal dendritic compartment, which eventually prevents multiple CF innervation at this compartment (Fig. 4, left). Cbln1 knockout mice also manifest similar phenotypes, including impaired PF-PC synaptogenesis, persistent multiple CF innervation, impaired long-term depression at PF-PC synapses, and severe ataxia (Hirai et al. 2005). This is because Cbln1 secreted from granule cells acts as a bidirectional synaptic organizer of PF-PC synapses through interactions with both presynaptic neurexin and postsynaptic GluD2 (Matsuda et al. 2010; Uemura et al. 2010). This synaptic adhesion mechanism is active in the adult cerebellum. The ablation of GluD2 in adulthood also led to disconnection of PF-PC synapses and progressive distal extension of ascending branches of CFs causing multiple CF innervation at distal dendrites (Takeuchi et al. 2005; Miyazaki et al. 2010). Furthermore, transverse

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branches of CFs, which are a short motile collateral forming no synapses in wildtype animals (Rossi et al. 1991; Sugihara et al. 1999; Nishiyama et al. 2007), extended mediolaterally to innervate distal dendrites of neighboring and remote PCs (Miyazaki et al. 2010). Concomitantly, surplus CF-EPSCs with slow rise time and small amplitude also emerged progressively after GluD2 ablation. Likewise, a single injection of recombinant Cbln1 to the subarachnoid space of adult Cbln1knockout mice could rapidly restore PF-PC synapse structure and function and cerebellar ataxia (Ito-Ishida et al. 2008). Therefore, the GluD2-Cbln1-neurexin system is essential to maintain the connection of PF-PC synapses and CF monoinnervation in the adult cerebellum. In contrast, CF innervation regressed, but PF innervation expanded, to the proximal compartment, when olivocerebellar projections were surgically lesioned in adult animals or when activities in the cerebellar cortical neurons were blocked with the sodium channel blocker tetrodotoxin or with the AMPA receptor antagonist NBQX (Bravin et al. 1995; Kakizawa et al. 2005; Cesa et al. 2007). This change often accompanied hyperspiny transformation at the proximal dendritic compartment (Bravin et al. 1995; Cesa et al. 2007). Similar changes were obderved in mutant mice defective in P/Q-type VDCC (Miyazaki et al. 2004). In P/Q-type VDCC knockout mice, hyperspiny transformation was induced at proximal dendrites and somata of PCs, and many of these ectopic spines were innervated by PF terminals. Conversely, the distribution of CFs was regressed to somata and basal dendrites. Furthermore, in more than 90% of P/Q-type VDCC knockout PCs, basal dendrites and somata were innervated by CFs of different neuronal origins. As a result, the proximal somatodendritic compartment in PCs lacking P/Q-type VDCC received chaotic innervation by numerous PFs and multiple CFs (Fig. 4, right). Considering that PCs lack functional NMDA receptors (Yamada et al. 2001), P/Qtype VDCCs in PCs might substitute for NMDA receptors and function as a coincidence detector to regulate synaptic strengthening and elimination. Thus, CF activity leading to AMPA receptor activation and subsequent Ca2+ influx through P/Q-type VDCC is essential for a single main CF to monopolize the proximal dendritic compartment and to expel other excitatory inputs from that compartment. Taken altogether, excitatory synaptic wiring in PCs is formed and maintained through homosynaptic competition among CFs and heterosynaptic competition between PFs and CFs. The P/Q-type VDCC transduces CF activity into force that strengthens a single main CF and promotes its innervation, eliminates redundant CF innervation, and excludes PF synapses from proximal dendrites (Fig. 3, “P/Q-type VDCC”; Fig. 4, right). The GluD2-Cbln1-neurexin system strengthens the connectivity of PF-PC synapses and confines CF innervation territory to proximal two-thirds of PC dendrites (Fig. 3, “GluD2/Cbln1”; Fig. 4, left). The mGluR1 to PKCγ signaling cascade mediates PF activity and drives elimination of surplus CF synapses from the soma and PF synapses from proximal dendrites (Fig. 3, “mGluR1PKCγ”). These three canonical pathways, together with BG that prevents crosstalk of individual synaptic inputs by the action of GLAST (Fig. 3, “GLAST”), cooperate to establish mono-innervation by the CF and territorial innervation by the PF and CF.

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Conclusions and Future Directions In this chapter, we made an overview of postnatal development of CF-PC synapses, which is one of the best studied examples of synapse elimination in the brain. The outline has now become clear from a number of electrophysiological and morphological studies. Shortly after birth, each PC is innervated by multiple CFs with similar synaptic strengths on the soma. Subsequently, a single CF is selectively strengthened during the first postnatal week. Then, around P9, only the strongest CF (“winner” CF) starts to extend its innervation to PC dendrites. In contrast, synapses of the weaker CFs (“loser” CFs) remain around the soma, and they are eliminated progressively during the second and the third postnatal weeks. From around P7 to P11, the elimination proceeds independently of PF-PC synapse formation. From around P12 and thereafter, the elimination of weaker CFs requires normal PF-PC synapse formation. There is a heterosynaptic competition between PFs and CFs for the postsynaptic sites on PC dendrites, which is at work not only during postnatal development but also in adulthood. Molecular and cellular mechanisms of the late phase of CF synapse elimination and the heterosynaptic competition have been elucidated to some extent in the past 20 years by using a number of knockout mice, pharmacological approaches, and microRNA-mediated knockdown of candidate molecules (see Figs. 2 and 3). Moreover, molecules responsible for selective strengthening of single CF, the early phase of CF synapse elimination, and CF translocation are also being elucidated in the past 10 years. The development of RNAi technology to knockdown molecules in cellspecific manner has greatly accelerated the screening of candidate molecules that are involved in the respective phases of CF synapse elimination. Our knowledge about molecular cascades for CF synapse elimination is expected to grow steadily. The cerebellum has been attracting many neuroscientists who pursue the mechanisms of synaptogenesis and synapse elimination. Continuing research on cerebellar microcircuits will elucidate fundamental mechanisms of the formation, elimination, and maturation of neural circuits. Acknowledgments We thank Takaki Watanabe for preparing Fig. 2. This work has been supported in part by Grants-in-Aid for Scientific Research (21220006 and 25000015 to M.K., 19100005 and 24220007 to M.W.) from JSPS, Japan.

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Genes and Cell Type Specification in Cerebellar Development

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Joanna Yeung, Matt Larouche, Miguel Ramirez, Rémi Robert, and Dan Goldowitz

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Structure and Early Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Germinal Zones and Lineage Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ventricular Zone and Cell Type Specification Within GABAergic Lineages . . . . . . . . . . . . . . . . . . Rhombic Lip and Cell Type Specification Within Glutamatergic Lineages . . . . . . . . . . . . . . . . . . . Cerebellar Glial Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bioinformatic Strategies to Identify Novel Genes in the Specification of Cells During Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Gene Regulation in Time and Space (CbGRiTS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The FANTOM5 Consortium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion and Looking Forward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Joanna Yeung and Matt Larouche contributed equally to this work. J. Yeung · R. Robert · D. Goldowitz (*) Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada e-mail: [email protected] M. Larouche Neurology, Neuroscience and Mental Health Institute, University of Alberta, Edmonton, BC, Canada M. Ramirez Department of Medical Genetics, Child and Family Research Institute, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC, Canada Genome Sciences and Technology, University of British Columbia, Vancouver, BC, Canada © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_15

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Abstract

One of the key goals of mammalian neural development is to make specific cell types that originate from multipotent progenitor cells. We are only beginning to understand this process of cell specification; however, evidence suggests that it occurs in a stepwise fashion and it is likely that each step requires the coordinated expression of a unique set of genes working in concert with environmental signals. The cerebellum is an excellent model system for understanding cell fate questions because it contains only a handful of defined cell types that are each located in a specific lamina with distinct molecular signatures and are therefore easily identified. These features have made the cerebellum an ideal model to help us understand the gene networks that give rise to specific cell types during development. In this review, we will discuss recent advances in parsing the molecular pathways necessary to produce specific cerebellar cell types. We will then discuss two open-source cerebellar transcriptomic databases, GRiTS (Gene Regulation in Time and Space) project (www.CBGRiTS.org) and RIKEN FANTOM5 (fantom.gsc.riken.jp/5/), which have amassed whole genome readouts of cerebellar gene expression on a daily basis during embryogenesis and every 3 days postnatally. Finally, we will briefly review our efforts to mine this transcriptomic information using bioinformatic tools to identify new genes that may confer cell type specificity during cerebellar development. Keywords

Cerebellum · Development · Bioinformatics · Phenotype · Gene · Network

Introduction The cerebellum is a well-studied model of neural development largely because it is a simple structure. It contains a limited number of cell types including Purkinje, granule, stellate, basket, Golgi, unipolar brush, and Lugaro neurons, in addition to glial populations that include astrocytes, specialized radial astrocytes known as the Bergmann glia, and oligodendrocytes. This region of the nervous system has been an essential contributor to our understanding of a variety of developmental processes including progenitor proliferation, neuronal specification, differentiation, and migration. Progress in cell fate research has demonstrated that sequential cascades are responsible for defining cell types (Hevner et al. 2006). While the current data supports the sequential model, there are significant missing parts (i.e., certain cell types and a more complete molecular pathway) in our understanding of the genes necessary to specify cell types. For example, while it appears that a common progenitor population (Atoh1+) gives rise to all glutamatergic cells in the cerebellum, the genetic cascades required to produce each specific glutamatergic subtype are largely unknown (see below). In this review, we will first summarize cerebellar development focusing on the various cell types that populate this structure. Next, we will review our current

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understanding of the genes involved in conferring cell identity in the cerebellum. For the purposes of brevity, we will restrict our focus to genes that, when knocked out, produce observable phenotypes in specific cerebellar cell types. Interestingly, there is emerging data that points to key roles for noncoding elements in neurodevelopment, and recent advances in these areas will be discussed in the bioinformatics section at the end of this chapter. Finally, we will also discuss the opportunities that the GRiTS and FANTOM5 gene expression databases can provide for discovering novel genes and networks involved in promoting the development of cerebellar cell types.

Cerebellar Structure and Early Development The cerebellum originates from the alar plate of the neural tube – a region known to give rise to the sensory structures of the brain. Functionally, the cerebellum is at the crossroads between the sensory and motor systems and is essential for coordinating communications between these two systems (Altman and Bayer 1997). The cerebellar cortex has a trilaminar organization (Fig. 1a, adult cerebellum), and each mature layer contains a defined set of cell types – the outermost molecular layer contains stellate and basket interneurons, in addition to glial cells; located beneath the molecular layer, the Purkinje cell layer contains the cell bodies of the eponymous neuron, as well as Bergmann glia and candelabrum cells; and located immediately beneath the Purkinje cell layer is the granule layer which contains granule cells, Golgi cells, unipolar brush cells, and a few other minor cell types (Altman and Bayer 1997). Internal to the cerebellar cortex is the cerebellar white matter, which contains most of the cerebellar astrocytes and oligodendrocytes. Also located in the cerebellar white matter are the cerebellar nuclear neurons, which are restricted to three (in mouse) or four (in primates) bilateral clusters of cells symmetrically distributed on either side of the cerebellar midline. During development, the cerebellar territory is established through the signaling actions of the isthmic organizer (IO). The IO sets up the boundary between the mesand metencephalic vesicles around embryonic day (E) 8.5–9 in the mouse (Li and Joyner 2001). The morphogen Otx2 is expressed rostral to the IO in the mesencephalic vesicles and specifies the midbrain territory. Caudal to the IO, the metencephalic vesicle is marked by Gbx2 expression, and Gbx2 is required for the development of cerebellum. The reciprocal inhibitory interaction of Otx2 and Gbx2 sets up the nonoverlapping expression domains and the proper position of the IO and organizes the spatial expression of Fgf8 and Wnt1 within the IO (Millet et al. 1999; Broccoli et al. 1999; Li and Joyner 2001). Fgf8 is an organizing molecule that provides instructions for the induction of midbrain and hindbrain – ectopic expression of Fgf8 induces abnormal midbrain and cerebellar structures at the diencephalon (Crossley et al. 1996; Martinez et al. 1999). On the other hand, Wnt1 alone cannot induce midbrain-cerebellum structures (Matsunaga et al. 2002; Panhuysen et al. 2004), yet it is required to maintain Fgf8 expression in the IO (Lee et al. 1997). Mutations in these mid-hindbrain genes typically result in the absence of

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Fig. 1 Cerebellar development. (a) Schematic illustration of development of cell types in the cerebellum. The cerebellar anlage arises from the rhombencephalic vesicle of the neural tube. By E10 in mouse, cerebellar neurons are generated from two distinct germinal zones: the ventricular zone that is defined by Ptf1a expression (orange region) and gives rise to all GABAergic inhibitory cerebellar neurons and the rhombic lip that is defined by Atoh1expression (light blue region) and produces all glutamatergic excitatory neurons in the cerebellum. Already by E15, the early-born glutamatergic cerebellar nuclear neurons have left the rhombic lip and populate the nuclear transitory zone (green region). Granule cell progenitors that arise from the rhombic lip migrate along the outer regions of the cerebellum and form the EGL (red region). On the other hand, GABAergic cerebellar nuclear neurons emerge from the ventricular zone and reach the nuclear transitory zone, while the Purkinje cells migrate radially into the cerebellar parenchyma below the EGL (blue region). Postnatally at P7, differentiated granule cells have been migrating inwardly from EGL to populate the IGL. Cerebellar nuclear neurons also migrated to their final destination in the cerebellar white matter. The mature adult cerebellar cortex exhibits a trilaminar organization: the outer molecular layer is made up of interneurons, parallel fibers of granule cells, and dendrites of Purkinje cells; underneath is the Purkinje cell layer that consists of a monolayer of Purkinje cells along with Bergmann glia and candelabrum cells; and the granule layer contains granule cells, unipolar brush cells, Lugaro cells, and Golgi cells (see inset). (b) Schematic illustration of temporal production of cerebellar cell types across embryonic (E10–18) and postnatal (P0–7) timepoints. a – (Sudarov et al. 2011), b – (Obana et al. 2015), c – (Florio et al. 2012), d – (Machold and Fishell 2005), e – (Fink et al. 2006), f – (Englund et al. 2006). CN cerebellar nuclear neurons, CP choroid

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a cerebellum and/or midbrain (Wassarman et al. 1997; Acampora et al. 1995; McMahon and Bradley 1990; Thomas and Capecchi 1990; Meyers et al. 1998). These mutations demonstrate the essential nature of the IO to the development of the caudal CNS. Because of the importance of these genes in the establishment and maintenance of the IO, complete knockout models have not been useful. Therefore, inducible transgenics, which allow temporal control over gene inactivation, have been essential in establishing the role of many of these genes in non-global aspects of cerebellar development (Joyner and Zervas 2006). Around the time that the midbrain/hindbrain territory is established, the neural tube closes completely, rostral to the IO, and remains partially open caudal to this structure.

Cerebellar Germinal Zones and Lineage Specification Cerebellar cell types arise from two anatomically and molecularly nonoverlapping germinal zones: the ventricular zone and rhombic lip (Fig. 1a, E10 embryo). The ventricular zone is located in the roof of the fourth ventricle and is characterized by expression of Ptf1a, a basic helix-loop-helix (BHLH) transcription factor (Hoshino et al. 2005). All GABAergic neurons in the cerebellum, including the GABAergic nuclear neurons, Purkinje cells, and interneurons (Pascual et al. 2007), are generated in the ventricular zone. On the other hand, glutamatergic neurons arise in the rhombic lip. This structure resides in the rostral edge of the neural tube surrounding the fourth ventricle. The rhombic lip germinal zone is defined by the expression of Atoh1, also a BHLH transcription factor (Akazawa et al. 1995). Rhombic lip cells give rise to the cerebellar glutamatergic lineages, consisting of the large glutamatergic nuclear neurons, granular cells, and unipolar brush cells (Machold and Fishell 2005; Wang et al. 2005; Englund et al. 2006). Studies of the loss of key markers in the germinal zones, as in the Atoh1- or Ptf1anull mutants, reveal the absence of glutamatergic and GABAergic lineages, respectively (Hoshino et al. 2005; Ben-Arie et al. 1997). These results indicate that Atoh1 and Ptf1a are necessary to generate the corresponding lineages in the cerebellum. Furthermore, Atoh1 and Ptf1a are also sufficient to generate the glutamatergic and GABAergic lineages, respectively. This is illustrated by a set of ectopic expression studies performed by Yamada et al. (2014). To demonstrate that Atoh1 is able to confer a glutamatergic lineage identity, Atoh1 was ectopically expressed in the ventricular zone either with a transgene that had replaced the open reading frame of Ptf1a with Atoh1 cDNA or transiently expressed Atoh1 in the ventricular zone by in utero electroporation of Atoh1 vector. Glutamatergic neurons, such as Pax6+ granule cells and Tbr1+ cerebellum nuclear neurons, were observed to arise from ä Fig. 1 (continued) plexus, E embryonic, EGL external germinal layer, GL granular layer, IGL internal granular layer, INs interneurons, MB midbrain, mes mesencephalon, met metencephalon, ML molecular layer, NTZ nuclear transitory zone, P postnatal, PCL Purkinje cell layer, RL rhombic lip, RP roof plate, tel telencephalon, VZ ventricular zone, WM white matter

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the ventricular zone that ectopically expressed Atoh1. Vice versa, when Ptf1a was expressed ectopically in the rhombic lip, it gave rise to GABAergic neurons, such as Calbindin+ Purkinje cells and Pax2+ interneurons, indicating that Ptf1a is sufficient to confer GABAergic identity in progenitor cells. It was observed from the lineage analysis of Ptf1a-null mutant cerebellum (Ptf1acre/cre; R26R, in which the cells from ventricular zone are labeled by β-gal) that the ventricular zone progenitors acquired a glutamatergic lineage identity (Pascual et al. 2007; Millen et al. 2014). This finding indicates that Ptf1a normally suppresses glutamatergic phenotypes in the ventricular zone progenitors, probably by inhibiting Atoh1 expression in the ventricular zone, as Atoh1 is found to be ectopically expressed in the Ptf1a-null ventricular zone (Yamada et al. 2014). Ectopic expression of Atoh1 by introduction of Atoh1-expressing vector into the ventricular zone leads to the reduction of Ptf1a expression (Yamada et al. 2014). These findings indicate that Atoh1 and Ptf1a are mutually inhibitory. The cross inhibitory machinery between these two molecules also demarcates the cerebellar neuroepithelium into two nonoverlapping compartments, each specifying a distinct lineage of cerebellar neurons (GABAergic vs glutamatergic). An outstanding question is the molecular mechanism that establishes this compartmental boundary. Similar parcellation of distinct progenitors into spatially and molecularly discrete domains has been observed in the developing hindbrain and spinal cord and plays an important role in fate specification (Landsberg et al. 2005; Takahashi and Osumi 2002). In the following sections, we will discuss the presence of molecular subdomains and cell specification within each germinal zone.

Ventricular Zone and Cell Type Specification Within GABAergic Lineages Genetic inducible fate mapping (GIFM) is a powerful tool that enables us to label progenitor cells at a particular time during development and understand their final position and identity in the mature brain, in vivo. Using the GIFM technique combined with molecules specific for ventricular zone, such as Ascl1, Ngn1, and Ngn2, revealed that the ventricular zone GABAergic lineages arise in temporal sequence (Sudarov et al. 2011; Obana et al. 2015; Florio et al. 2012) (see Fig. 1b). The small GABAergic nuclear neurons are the first GABAergic neurons that arise from the ventricular zone between E10.5 and 11.5 (Sudarov et al. 2011). Purkinje cells arise from the ventricular zone at the same time as the nuclear neurons, but their generation lasts until E13.5 (Obana et al. 2015). This is followed by the genesis of Pax2+ inhibitory interneurons starting at E13.5 and following a temporal sequence that maps to an inside-to-outside position in the cerebellum: Golgi and Lugaro cells that occupy the internal granular layer arise at E13.5–16.5 and E16.5–18.5, respectively; basket cells localized to the inner molecular layer are generated at E17.5postnatal (P) 0, and the stellate cells in the outer molecular layer are born last at P0 (Obana et al. 2015; Sudarov et al. 2011). This recapitulates the classical birthdating studies using tritiated thymidine (Altman and Bayer 1997). The more recently

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identified candelabrum cells (Laine and Axelrad 1994) are found in the Purkinje cell layer, but their birthdate has yet to be determined. Interestingly, there are molecularly distinct compartments within the ventricular zone that generate different cell types at the same time. The characterization of proneural gene expression, Ascl1 (or Mash1), Ngn1, and Ngn2, in the ventricular zone has identified two molecularly distinct compartments (Fig. 2a): a rostral domain of Ngn1
/Ngn2+/Ascl1+ and a ventral Ngn1+/Ngn2+/Ascl1+-expressing domain (Zordan et al. 2008). Lineage tracing using GIFM has shown that Ngn1+ cells give rise to Purkinje cells and inhibitory interneurons, but not small GABAergic nuclear neurons (Obana et al. 2015; Lundell et al. 2009). In contrast, Ngn2+ progenitors are fated to become small GABAergic nuclear neurons and Purkinje cells, but not cortical inhibitory interneurons (Florio et al. 2012). The loss of Ngn2, however, does not affect the generation of Purkinje cells, indicating a redundant role of Ngn2 in specification of Purkinje cell lineage (Florio et al. 2012). Thus, during early development the ventricular zone is demarcated spatially into two distinct molecular compartments, the Ngn1
/Ngn2+ and Ngn1+/Ngn2+, which specify GABAergic nuclear neuron and Purkinje cell fate, respectively. This finding warrants the examination of the requirement of Ngn1 in Purkinje cell specification. A further molecular compartmentation of the ventricular zone is found using antibodies to Corl2 and Pax2, selective markers for Purkinje cells (Minaki et al. 2008) and interneurons, respectively. Corl2 and Pax2 immunocytochemistry has delineated two mutually exclusive domains, one that is Corl2+ and Pax2
and vice versa (see Fig. 2b). This leads to the hypothesis that Purkinje cell and interneuron lineages arise from two distinct progenitor pools in the ventricular zone during early development. A more recent study identified additional distinct progenitor pools in the Ptf1a+ ventricular zone that are demarcated by the nonoverlapping expression of Olig2 and Gsx1 (Seto et al. 2014). It was determined from short-term lineage tracing with green fluorescence protein (GFP) reporter that Olig2-expressing progenitors gives rise to Corl2+ Purkinje cells, while Pax2+ inhibitory interneurons originate from the nonoverlapping Gsx1+ region. Furthermore, the authors observed a dynamic temporal transition in the proportion of Olig2+ and Gsx1+ domains within the ventricular zone. This transition coincides with the production sequence of early-born Purkinje cells and later-born interneurons from the ventricular zone. At E12.5, when Purkinje cells arise from the ventricular zone, Olig2 expression covers most of the ventricular zone where the Gsx1-expressing cells occupy a minor region. Later at E14.5 when production of Purkinje cells has ceased and interneurons are entering into their major neurogenic period, the Olig2+ domain shrinks, and in contrast, the Gsx1 expression expands dorsally and supersedes the Olig2 domain. To determine if Gsx1 is sufficient to specify an interneuron cell fate, Gsx1 has been overexpressed in Olig2+ cells in the ventricular zone at E12.5, when the germinal zone normally expresses Olig2 and produces Purkinje cells (Seto et al. 2014). This overexpression of Gsx1 results in the reduction of Olig2 expression and confers an interneuron cell fate in the progenitors at the cost of Purkinje cell

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Fig. 2 (continued)

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identity. This finding illustrates that Gsx1 promotes the switch to interneuron cell fate by extinguishing Olig2 expression in ventricular zone progenitors. On the other hand, expressing Olig2 ectopically in the Gsx1 domain cannot suppress the expression of Gsx1. However, ectopic expression of Olig2 in the Gsx1+ cells suppresses Pax2, suggesting that Olig2 inhibits Gsx1+ interneuron progenitors from assuming a Pax2+ identity. A marker for GABAergic nuclear neurons, Zac1, has recently been identified (Chung et al. 2011). Expression of Zac1 is found in the ventricular zone and the stream of cells that migrate from ventricular zone toward the nuclear transitory zone and later the medial cerebellar nuclei. The lack of Zac1 during cerebellar development leads to the absence of medially placed GABAergic nuclear neurons indicating that Zac1 is necessary in the generation of this neuron type. Taken together, these studies illustrate that the ventricular zone, as a subdomain within the cerebellar anlage, is further divided into distinct compartments each characterized by a unique combinatorial molecular profile. GIFM and knockout studies further demonstrate that compartmentation in the germinal zone plays an important role in conferring specific cell types, thus allowing a diversity of neurons to be generated from the ventricular zone. ä Fig. 2 Distinct molecular compartments within cerebellar germinal zones during development of the cerebellum. (a) While GABAergic nuclear neurons and Purkinje cells are born in the ventricular zone at the same time, they arise from two molecularly distinct compartments within the ventricular zone. GABAergic nuclear neurons are produced from the Ngn2+/Ngn1
zone, while Purkinje cells arise from the Ngn1+/Ngn2+ compartment. (b) Similarly, Purkinje cells and interneurons arise from nonoverlapping molecularly distinct compartments within the ventricular zone Olig2+ and Gsx1+, respectively. Furthermore, the ventricular zone has a temporal transition that switches from Olig2- to Gsx1-positive cells when the production of interneurons occurs. It is found that Gsx1 inhibits Olig2 expression and promotes the molecular (expression of Pax2) and cell fate transition. (c) In the rhombic lip, four molecularly distinct compartments are defined by the combination of expression of five molecules: Atoh1, Pax6, Wls, Lmx1a, and Tbr2. At the distal tip of the rhombic lip next to the choroid plexus (pink region), cells are expressing high level of Wls and Lmx1a. It has been demonstrated that Wls in this region is required to inhibit Pax6 expression, which is a cell marker for specified glutamatergic progenitors, suggesting this region is populated by cells that are not non-specified. The region abuts this distal tip of the rhombic lip in the E11.5 cerebellum (yellow region) is characterized by strong Atoh1 expression. These Atoh1-positive cells will become the glutamatergic nuclear neurons. In E13.5 or older cerebellum, the neuroepithelium contiguous with the EGL is referred as the “exterior face of the rhombic lip (eRL)” (yellow region). The eRL is populated by cells that strongly express Atoh1 and Pax6 but not Tbr2, suggesting these are cells that have specified to become granule cells. The neuroepithelium surrounding the fourth ventricle refers as the “interior face of the rhombic lip (iRL)” (the green region). The iRL is characterized by strong Wls expression, weak Atoh1, and Pax6 expression. Although this region is found to be Atoh1-independent, short-term lineage tracing suggests that Atoh1+ lineages in the eRL originate from this domain. In between the eRL and iRL is a region that expressed Tbr2 strongly, as well as Atoh1, Pax6, and Lmx1a (blue region). This region only becomes evident by E15.5. The cells in this region are specified to a unipolar brush cell fate. A anterior, D dorsal, CP choroid plexus, EGL external germinal layer, eRL exterior face of rhombic lip, iRL interior face of rhombic lip, P posterior, PCs Purkinje cells, RL rhombic lip, RP roof plate, V ventral, VZ ventricular zone

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Rhombic Lip and Cell Type Specification Within Glutamatergic Lineages Similar to the sequential production of ventricular zone-derived lineages, GIFM of Atoh1 lineages in the cerebellum revealed that cell production from the rhombic lip is also temporally organized (Machold and Fishell 2005). The first wave of cells that emerges from the rhombic lip at E10–12.5 becomes the glutamatergic cerebellar nuclear neurons (Fink et al. 2006), followed by the generation of granule cells between E12.5 and 16.5, in a sequential order from rostral to caudal (Machold and Fishell 2005). Unipolar brush cells arise from the rhombic lip between E15.5 and E18 as determined by BrdU birthdating (Englund et al. 2006). The rhombic lip has been classically defined by Atoh1 expression (Wang et al. 2005; Machold and Fishell 2005). However, studies found Atoh1-negative cells in the rhombic lip that are positive for Lmx1a or Wnt1 indicating that cells of the rhombic lip are molecularly heterogeneous (Chizhikov et al. 2010; Hagan and Zervas 2012). A recent study from our lab characterized Wntless (Wls) expression in the developing cerebellum and identified an Atoh1
/Wls+ domain in the rhombic lip (Yeung et al. 2014). This Atoh1
/Wls+ region was localized to the interior epithelial face of the rhombic lip (iRL), which abuts the fourth ventricle and is adjacent to the ventricular zone (Fig. 2c). Expression of Atoh1 in the rhombic lip is complementary to the Wls+ domain. The Atoh1+ domain is localized to the exterior face of the rhombic lip (eRL) that is continuous with the Atoh1+ EGL. To further characterize the molecular heterogeneity in the rhombic lip, three additional rhombic lip markers, Pax6, Lmx1a, and Tbr2, were studied in relationship to Wls and Atoh1 expression across development. The expression pattern of the foregoing five genes identified four compartments with distinct molecular combinations in the developing rhombic lip (Fig. 2c) (Yeung et al. 2014): (1) A Wls+ domain (pink region in Fig. 2c) localized to the distal tip of the rhombic lip adjacent to the roof plate/choroid plexus is observed from E11.5 to 18.5 in the cerebellum. The cells in this region also express Lmx1a and a low level of Atoh1, while they are negative for Pax6 and Tbr2. (2) An Atoh1+/Pax6+ domain is localized to the eRL (yellow region in Fig. 2c) of E11.5–18.5 cerebellum; this region is devoid of Wls expression. The cells from this domain, however, most likely emanate from the Wls+ domain and have subsequently downregulated Wls expression, as the expression of Wls-reporter protein is observed in these cells. (3) A Wls+ domain is where cells also expressed a low level of Atoh1, Pax6, and Lmx1a (green region in Fig. 2c). This domain maps onto the iRL and is apparent in the E13.5–18.5 cerebellum. It is observed that Atoh1 expression gradually regresses in these cells as development proceeds. (4) This domain is located between the iRL and eRL (blue region in Fig. 2c) and becomes apparent at a later developmental time – E15.5 and beyond. Cells in this domain express Tbr2+/Lmx1a+/Pax6+ but are devoid of Wls expression. Several lines of evidence from mutants and GIFM studies have suggested that each of these four compartments plays a different role in generating glutamatergic lineages in the cerebellum. Cells that expressed Atoh1 are specified to a glutamatergic cell fate, and they are found in the eRL and Tbr2+ domains in the rhombic lip (yellow and blue regions in Fig. 2c, respectively), as well as the subpial

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stream and EGL that emanates from the eRL (Yeung et al. 2014; Wang et al. 2005; Machold and Fishell 2005; Englund et al. 2006). These domains, however, are missing from the Atoh1-null mutant that lacks all glutamatergic lineages (Wang et al. 2005; Jensen et al. 2004; Yeung et al. 2014). It has been shown by GIFM that Atoh1-expressed cells arise from the E10.5 rhombic lip are designated to the nuclear transitory zone, where the nuclear neurons reside transiently before descending into the cerebellar white matter (Machold and Fishell 2005). Thus, the Atoh1+ domain in the E10.5–11.5 rhombic lip (yellow region in Fig. 2c) is comprised of cells that will become glutamatergic nuclear neurons. At E13 and beyond, Atoh1+ cells in the eRL migrate to the EGL, the second germinative zone of granule cells (Machold and Fishell 2005), indicating that the eRL contains cells that are designated to a granule cell fate. Expression of Tbr2 is found only in the region of the rhombic lip between the iRL and eRL (blue region in Fig. 2c) (Yeung et al. 2014). Tbr2 is a cell-specific marker of unipolar brush cells, it is expressed by the progenitors of unipolar brush cell located in the rhombic lip, and Tbr2 expression is maintained in these neurons during adulthood (Englund et al. 2006). When the fate of Tbr2+ cells that originate in between E14 and 16 is followed with GIFM, it is observed that these cells become unipolar brush cells in the adult cerebellum (Pimeisl et al. 2013). Thus, cells in the Tbr2+ domain are specified to become unipolar brush cells. Cells in the yellow and blue domains (Fig. 2c) are also positive for Pax6 (Engelkamp et al. 1999; Yeung et al. 2014, 2016). Pax6 is expressed in the precursors of glutamatergic nuclear neurons, granule cells, and unipolar brush cells and plays crucial roles in the development of these rhombic lip lineages (Engelkamp et al. 1999; Yeung et al. 2014, 2016; Englund et al. 2006; Fink et al. 2006). The Pax6-null mutant results in the cell death of glutamatergic nuclear neuron progenitors (Yeung et al. 2016) and loss of molecular signatures and disorganization in granule cells (Swanson et al. 2005; Engelkamp et al. 1999) and reduced number of unipolar brush cells (Yeung et al. 2016). These findings indicate that Pax6 is needed for the development of the glutamatergic lineages in the eRL and Tbr2+ domains, but are not sufficient. Less is known about the Wls+ iRL domain (the green region in Fig. 2c). The observation that this domain is Atoh1-independent [i.e., unaffected in the Atoh1-null mutant (Yeung et al. 2014; Jensen et al. 2004)] indicates the cells in the iRL have not committed to a glutamatergic cell fate. However, Atoh1 is weakly expressed in these cells and Wls-reporter expression is found in the Atoh1+ cells in the eRL which would argue that Atoh1+ cells in the eRL originate from the Wls+ iRL domain (Yeung et al. 2014). Our thought is that the Wls+ iRL domain is a progenitor pool of cells that replenish the Atoh1 population over time. The fourth domain (pink region in Fig. 2c) is marked by Lmx1a, which is also a marker of the roof plate epithelial lineage during early development (E10.5–12.5) (Chizhikov et al. 2006). The rhombic lip cells adjacent to the roof plate express Wls and Lmx1a. This region is devoid of Pax6 expression (Yeung et al. 2014). In fact, Pax6 expression is normally suppressed by Wls in this region as demonstrated by the ectopic Pax6+ cells in the Wls knockout cerebellum (Yeung et al. 2016). This finding may reflect the existence of a molecular boundary mediated by Wls that segregates

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the Pax6+ rhombic lip neuronal lineages from the choroid plexus epithelial lineage. This is consistent with the previous findings that Lmx1a+/Gdf7+ roof plate lineage has very limited contribution to the cerebellum (Landsberg et al. 2005; Chizhikov et al. 2006). The roof plate/choroid plexus, however, is crucial in inducing neurogenesis from the nearby neuroepithelia (e.g., the rhombic lip or ventricular zone) through signaling molecules such as BMPs and SHH (Krizhanovsky and Ben-Arie 2006; Chizhikov et al. 2006; Huang et al. 2009). For example, conditional inactivation of Smads [Smad1/Smad5 (Tong and Kwan 2013) or Smad4 (Fernandes et al. 2012)], which eliminates canonical BMP signaling in the cerebellum, leads to the loss of glutamatergic nuclear neurons and unipolar brush cells, as well as a reduction in cerebellar granule cells.

Cerebellar Glial Cells Glial cells also play a crucial role in cerebellar development. The cerebellum consists of four major types of glial cells – astrocytes, Bergmann glia (a major subtype of astrocytes), oligodendrocytes, and microglia. Cerebellar glial cells were thought to have a postnatal birthdate (Miale and Sidman 1961). More recently, however, GIFM studies have demonstrated that glial progenitors are born as early as E12 in mouse (Kim et al. 2008; Sudarov et al. 2011; Hashimoto et al. 2016; Cerrato et al. 2018). The origin of cerebellar glial progenitors is less well-defined and has been suggested to arise from multiple regions. Historically, Ramón y Cajal (1960) had found similarities in the morphology of radial glial cells in the embryonic spinal cord and the “neuroglial cells with Bergmann’s radial fiber” in the cerebellum, which led to his suggestion that the cells in cerebellum has an epithelial origin as those in the spinal cord. Based on results with the Golgi impregnation method combined with Ramón y Cajal’s observations, this population of glial cells was termed “Golgi epithelial cells.” The term Bergmann referred, originally, to the radial fibers that emanated from these cells. And with time, this cell population has received the name of Bergmann glia. The advance in molecular genetics and imaging has allowed the identification of cell lineages that arise from a germinal zone. Thus, by using GIFM of ventricular zone markers such as Ascl1 and Ptf1a, glial progenitors have been demonstrated to originate from the ventricular zone (Sudarov et al. 2011; Hoshino et al. 2005). Altman and Bayer noted (Altman and Bayer 1997) that some cells that emigrated from the ventricular zone remained mitotically active in the overlying cerebellar parenchyma during late embryonic and neonatal period. They proposed that the cerebellar parenchyma is a secondary germinal zone that gives rise to cerebellar glial cells. To test if glial cells are generated from the cerebellar parenchyma, Grimaldi and colleagues electroporated GFP plasmids into E14 cerebellar parenchyma and followed the fate of GFP+ cells ex vivo (Grimaldi et al. 2009). GFP+ oligodendrocytes were observed post-electroporation in the ex vivo system, indicating that progenitors of oligodendrocytes reside in cerebellar parenchyma at E14. In other work that used in vivo viral-based fate mapping of cerebellar parenchymal cells at early postnatal days (P1–5, with an eGFP vector), it was found that in

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addition to oligodendrocytes, GABAergic interneurons and astrocytes were also labeled with GFP in the mature cerebellum, indicating that the progenitors of interneurons and glial cells are derived from the cerebellar parenchyma (Parmigiani et al. 2015). Of interest, Grimaldi and colleagues observed that both parenchymal electroporation and solid cerebellar grafts only gave rise to a minor faction of total oligodendrocytes in the cerebellum, suggesting that oligodendrocytes have an extracerebellar origin (Grimaldi et al. 2009). A later study confirmed the minor contribution (approximately 6%) of cerebellar oligodendrocytes being native to the cerebellum and revealed that the rest originate from the Olig2+ neuroepithelial domain in the ventral rhombomere1 (Hashimoto et al. 2016). The generation of three different astrocyte subtypes (based upon location and morphology) in the cerebellum has recently been investigated (Cerrato et al. 2018). In this study, Cerrato and others tagged the developing radial glial cells that arise from the ventricular zone (with the StarTrack cell tagging system) and examined the astrocyte types in adult cerebellum. Their results revealed that radial glial cells are multipotent, in which a particular radial glial progenitor can give rise to all three astrocyte subtypes, but this multipotency is found to decrease over time (i.e., progenitors born at E12 have the tendency to give rise to multiple types versus those born at E14 which tend to give rise to a single type) (Cerrato et al. 2018). The mechanism that governs the generation of astrocyte heterogeneity, whether they arise from a discrete subset of progenitors or the consequence of stochastic events, however, remains unclear.

Bioinformatic Strategies to Identify Novel Genes in the Specification of Cells During Cerebellar Development Over the past decades, the studies of gene function in mutant mice, and other organisms, have taught us greatly about the role of single genes in cerebellar development. Recent advances in high-throughput sequencing and analysis provide the opportunity to study the genetic underpinnings of cell fate and specification at a whole genome level. Here we describe two different whole genome approaches, involving our lab, that utilize the latest technologies for whole transcriptome readout in the cerebellum as a function of developmental time.

Cerebellar Gene Regulation in Time and Space (CbGRiTS) In an effort to better understand cerebellar development from a molecular perspective, we have undertaken a project aimed at assembling a microarray-based developmental transcriptome for various mouse strains. The data collected for this project are publicly available on our Cerebellar Gene Regulation in Time and Space website (www.cbgrits. org). Several strains of mice were analyzed in the CbGRiTS project including two standard mouse strains C57BL6/J and DBA and several mutant strains such as Pax6null Sey, Atoh1-null (also known as Math1-null), and meander tail mutant. Data were collected for each strain across embryonic and postnatal development. For the wild-type

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strains, RNA from cerebellar tissue was obtained each day during embryogenesis (E12-birth) and every third day postnatally, currently until P9. Gene expression in these samples was then analyzed using the Illumina microarray platform. The built-in informatic tools found on the website allow the exploration of gene expression over time as related to developmental events in the cerebellum by use of the DEM Transcriptome Explorer (Ha et al. 2015). Several other informatic algorithms can be accessed such as Paraclique, Helmert, and Polynomial analyses. In addition, there are visualization tools that animate cerebellar development (see www.cbgrits.org/Visualization/ DevelopingCerebellum.aspx). Currently, we are processing these data using bioinformatic tools in order to identify developmentally important genes (Ha et al. 2015). By analyzing the transcriptome of the Pax6-null Sey mutants in this database, we identified a novel molecule – Wntless – a key to cerebellar development (Yeung and Goldowitz 2017). The analysis of Sey transcriptome also revealed the dysregulation of Tbr1 and Tbr2 in the Pax6-null mutant. This dysregulation led us to identify novel roles play by Pax6 in the development of nuclear neuron and unipolar brush cells (Yeung et al. 2016).

The FANTOM5 Consortium More recently, we participated in the FANTOM5 consortium where another set of tissues were dissected, using the same timepoints, from the C57BL6/J inbred line and subjected to deepCAGE processing. CAGE, originally developed by RIKEN (the hosts of the FANTOM consortia), captures short sequences (25–27 bp) from the 50 capped ends of transcripts and which are then subjected to high-throughput sequencing (a HeliScope single-molecule sequencer) and mapped back onto the genome (FANTOM Consortium and the RIKEN PMI and CLST (DGT) et al. 2014). This technique allows the deep sequencing and quantification of the 50 ends of transcripts that exist even at low levels. Three other important attributes of this dataset are that it contains (1) expression data from many different human and mouse tissue and cell lines (Arner et al. 2015; de Rie et al. 2017; Noguchi et al. 2017; Andersson et al. 2014), (2) time course data, and (3) all transcription start sites that are detected including noncoding RNAs in addition to protein-coding RNAs. This is also an open resource, and the RIKEN FANTOM5 data can be accessed at http://fantom.gsc.riken.jp/5. The FANTOM5 dataset can be used to (1) uncover genes not previously associated with development of the cerebellum and (2) elucidate gene regulatory relationships through the establishment of a gene regulatory network (GRN) (Hecker et al. 2009). Network analysis addresses the importance of identifying key regulators in the context of a dynamic transcriptome and can identify genes integral to the proper developmental processes. A novel approach, developed by Gui et al. (2017), has recently been employed to generate a cerebellar development GRN. The approach utilizes the dynamic Bayesian network model for network inference, as it has previously been shown to be efficient in identification of GRNs from temporal data (Zou and Conzen 2005). This method also addresses issues of scalability, allowing analysis of over 10,000 genes by implementing an optimization algorithm “Decomposable Multi-structure

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Fig. 3 Illustration of the bioinformatic approaches to identify genes involved in cerebellar development. A gene regulatory network constructed from the FANTOM5 cerebellar time course data. Genes that demonstrate change in transcript level across developmental timepoints are highlighted in red and genes without significant change in transcript level across time are in blue

Identification” that can handle a network size greater than 20,000 on an average computer (Boyd et al. 2011). A key requirement of GRNs is the ability to extract biologically relevant relationships from the network constructed. However, this is a problem in itself as the number of possible network structures, when utilizing temporal data, is quite high. To aid in the identification of biologically relevant GRN structure, this approach utilizes a background network limit parameter space. The background network was constructed from the RegNetwork database, which contains experimentally observed regulatory interactions from over 20 selected databases and includes physically, chemically, or biologically feasible interactions (UCSC, FANTOM, Enseml, JASPAR, TRANSFAC, KEGG, etc.) (Liu et al. 2015). Among the 10,316 genes quantified in our cerebellar development transcriptomic time course, 82% are referenced by RegNetwork. Finally, the method incorporates topological properties observed in previously constructed large-scale biological networks: structural sparsity (Leclerc 2008) and the existence of hub genes (Barabási and Oltvai 2004). An example of a cerebellar GRN constructed using the FANTOM5 data is shown in Fig. 3. Observed hub genes, nodes with numerous interactors (high degree), may be critical for the activation or suppression of multiple genes, and thus developmental processes, in a temporal specific manner and are thus primary candidates for biological validation and investigation. Other network topological properties, such as betweenness (which is a measure of centrality), can then be used to identify potential genes critical for the proper development of the cerebellum. Of special interest, the resulting cerebellar GRN analysis allows for the identification of genes not previously associated with cerebellar development.

Conclusion and Looking Forward In conclusion, the last decade has proven very fruitful for improving our understanding of the processes of cell specification in brain development. However, only a limited number of genes have been clearly implicated in this process. The

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cytoarchitectural simplicity of the cerebellum that includes a detailed understanding of the birthdates and developmental characteristics of many of its cell types suggests that the cerebellum is a structure that will immeasurably assist us in our understanding of brain development in the coming years. The GRiTS and FANTOM5 timeseries data will be a valuable contribution to this process because of its richness of temporal data and accessibility to the general research community. These unparalleled raw materials combined with the application of novel algorithms for its analysis will help reveal genes and genetic interactions necessary to build a CNS structure – in particular the process of cell specification. This knowledge is a requisite stepping stone to the exciting world of single cell, cerebellar transcriptomics (Wizeman et al. 2019; Carter et al. 2018).

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Hormones and Cerebellar Development

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Noriyuki Koibuchi and Yayoi Ikeda

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thyroid Hormone and Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Molecular Mechanisms of Thyroid Hormone Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Effect of Thyroid Hormone on the Developing Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . Animal Models to Study Thyroid Hormone Action in the Developing Cerebellum . . . . . . . Steroid Hormones and Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Adrenal Steroid Hormones and Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gonadal Hormones and Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Cerebellar development and plasticity involve various epigenetic processes that activate specific genes at different time points, including humoral influences from endocrine cells. Of the circulating hormones, a group of small lipophilic hormones including steroids (corticosteroids, progesterone, androgens, and estrogens) and thyroid hormones help mediate environmental influences on the cerebellum. Receptors for such lipophilic hormones are mainly located inside the cell nucleus (nuclear receptor, NR). They represent the largest family of ligand-regulated transcription factors. In the cerebellum, they are expressed in a N. Koibuchi (*) Department of Integrative Physiology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan e-mail: [email protected] Y. Ikeda Department of Anatomy, School of Dentistry, Aichi Gakuin University, Nagoya, Japan e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_16

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specific temporal and spatial pattern. Of the lipophilic hormones, the impact of the thyroid hormone and gonadal steroids on cerebellar development has been studied extensively. Thyroid hormone deficiency during postnatal development results in abnormal morphogenesis and functional impairment. Estrogen and progesterone also play important roles in this process. In addition to the supply from circulation, several gonadal steroids are produced locally within the Purkinje cells (neurosteroids). This chapter discusses the effect of thyroid and steroid hormones on cerebellar development. Neurosteroids that are locally synthesized in the cerebellum are discussed in a different chapter. Keywords

Environmental influences · Hormone receptors · Steroids · Thyroid hormone · Nuclear Receptor · Coactivator · Corepressor · Triiodothyronine · T3 · Thyroxine · T4 · TRα · TRβ · Retinoid X receptor · Thyroid hormone response element · Hypothyroidism · Perinatal hypothyroidism · Organic anion transporter · Monocarboxylate transporter · Iodothyronine deiodinase · Nongenomic thyroid hormone action · Steroid receptor cofactor-1(SRC-1) · Retinoic acid related orphan receptor (ROR) · Staggerer · Anti-thyroid drug · Pax8 · TR gene knockout · Mutant TR · Resistance to thyroid hormone · Thyrotropin · TSH · Sexual differentiation · Stress responses · Adrenal steroid hormone · Mineralocorticoids · Glucocorticoids · Hypothalamo-pituitary-adrenal (HPA) axis · GR · MR · Oxidative stress-induced cell death · Maternal deprivation (MD) · Non-genomic mechanism · Psychiatric disorders · Testosterone · Estradiol (E2) · Gonadal hormone · Aromatase · Perinatal critical period · Sexually dimorphic neurogenesis · ERα · ERβ · Androgens · Androgen receptor (AR) · Reelin · Neuronal protection

Introduction Brain development involves epigenetic processes that activate specific genes at different time points. Epigenetic influences controlling neuronal development may originate from the neuronal cell itself or from outside of the brain. The former includes spatial and temporal patterning of gene expression that is tightly regulated by their intrinsic molecular programs. The latter includes sensory influence, mediated by the peripheral nervous system, and humoral influence from endocrine cells. Environmental influences, including stressors, social experiences, nutrients, drugs, and environmental chemicals, may affect such processes. The cerebellar cortex forms well-organized structures: a highly specific and uniform arrangement of cells and microcircuitry (Leto et al. 2016). The cerebellum is one of the few sites in the brain where the pattern of intrinsic connections is known in considerable detail, making it ideal for studying the mechanisms of neural development and plasticity. Based on such advantages, a great deal of excellent work has been conducted at various levels, from basic science to clinical disorders.

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On the other hand, although a number of hormone receptors are expressed in the cerebellum, and cerebellar development and function are greatly influenced by hormonal status, a relatively smaller number of studies have examined the role of hormonal signaling on the development and plasticity of the cerebellum. Of the circulating hormones, a group of small lipophilic hormones, including steroids (corticosteroids, progesterone, androgens, and estrogens), and thyroid hormone may serve important roles in mediating environmental influences. Because of their chemical natures, these hormones may be able to cross the blood-brain barrier more easily than peptide hormones, although the existence of specific transporters has been proposed (Suzuki and Abe 2008). Receptors for such lipophilic hormones are mainly located in the cell nucleus (nuclear receptor, NR) and represent the largest family of ligand-regulated transcription factors (Mangelsdorf et al. 1995). Figure 1 is a schematic showing the molecular mechanisms of NR-mediated transcription. NRs are widely distributed in the central nervous system (CNS) as well as in other organs with a specific expression pattern (Bookout et al. 2006). In the cerebellum, NRs are expressed in a specific temporal and spatial pattern (Qin et al. 2007). However, the role of NRs in cerebellar function is not fully understood. NRs act by binding to specific coregulators, such as coactivators and corepressors, to regulate transcription of their target genes (Rosenfeld et al. 2006). Cofactors may alter chromatin architecture by enzymatically modulating histones, via acetylation and methylation, or remodeling chromatin structure. A genetically modified mouse lacking one of these coactivators shows aberrant cerebellar development (Nishihara 2008). This indicates that temporal and spatial expression of these coregulators also play an important role in mediating NR signaling. Of the lipophilic hormones, the impact of thyroid hormone and gonadal steroids on cerebellar development and plasticity has been well studied. Thyroid hormone

Fig. 1 Schematic figure showing the mechanisms of steroid/thyroid hormone receptor (nuclear receptor, NR)-mediated transcription. Nuclear receptor (NR) binds to specific nucleotide sequences known as hormone response element (HRE) as a homodimer or heterodimer with retinoid X receptor. Various coregulators bind to NRs in a ligand-dependent manner. Cofactors may alter chromatin structure by modulating histone acetylation/methylation or stabilization of basal transcriptional machinery (basal TFs). Usually, coactivator complex is recruited in the presence of ligand whereas corepressor complex in the absence of ligand

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deficiency during postnatal development results in impaired cerebellar morphogenesis and function in mammals including humans and rodents (Koibuchi et al. 2003). Estrogen and progesterone also play important roles in this process (Dean and McCarthy 2008). In addition to being supplied from circulation, these gonadal steroids are produced locally within Purkinje cells (Tsutsui 2006). These steroids may not only act through NRs but also through membrane-associated receptors (Sakamoto et al. 2008; Hanzell et al. 2009). Although the functional significance of the rapid action of estrogen and progestin has not yet been fully understood, these steroids may modulate neurotransmitter action such as GABA and NMDA-receptormediated signaling (Belcher et al. 2005; Frye 2001). It should be noted that these thyroid/steroid hormone-mediated pathways may be disrupted by prescribed drugs and environmental chemicals (Nguon et al. 2005; Darras 2008).

Thyroid Hormone and Cerebellar Development Molecular Mechanisms of Thyroid Hormone Action The thyroid hormone (L-triiodothyronine, T3; L-tetraiodothyronine, thyroxine, T4) binds to the thyroid hormone receptor (TR) and regulates transcription of target genes (Vella and Hollenberg 2017). TR genes are encoded in two genetic loci, termed α and β, which are located at chromosomes 17 and 3 in humans and 11 and 14 in mice (Lazar 1993). Each locus produces at least two proteins, which are termed as TRα1 and α2 (or c-erbAα2) and TRβ1, TRβ2, and TRβ3. Furthermore, some introns – such as intron 7 of TRα gene – have a weak promoter activity. Thus, deleting upstream exons may result in the expression of additional TR-related proteins, which is limited under normal conditions (Chassande 2003). So far, at least three additional TR-related proteins may be generated. Such proteins, termed as TRΔα1, TRΔα2, and TRΔβ3, lack N-terminus and DNA-binding domains (DBD). TR and its related proteins, generated from α or β gene loci, are shown in Fig. 2. TR forms a homodimer or heterodimer with a retinoid X receptor and binds to a thyroid hormone response element (TRE) located at the promoter region of target genes. TR binds to TRE regardless of the presence of T3 and regulates transcription in a ligand-dependent manner. In the presence of T3, it recruits protein complexes, called coactivators, to activate transcription, whereas in the absence of T3, it recruits corepressor complexes to repress transcription. Although TRα2 can bind to TRE, T3 cannot. TRα2 may act as an endogenous inhibitor for other TRs. Because of TR’s bidirectional function, the phenotype of the TR gene knockout mouse is different from that of hypothyroid (thyroid hormone-deficient) animals (Koibuchi 2009). Thus, TR-gene knockout and hypothyroid animal models that are induced by thyroid dysgenesis or dyshormonogenesis are equally important for understanding the role of thyroid hormone system in the brain. Animal models to study thyroid hormone action in the developing cerebellum are discussed in more detail later in this chapter.

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Fig. 2 Thyroid hormone receptor and its related proteins generated from α or β gene locus. Numbers indicate the number of amino acids. Hatched region with the same pattern indicates that the amino acid sequence is identical

The Effect of Thyroid Hormone on the Developing Cerebellum As shown in Fig. 3, perinatal hypothyroidism dramatically affects cerebellar development. The growth and branching of Purkinje cell dendrites are greatly reduced by perinatal hypothyroidism (Nicholson and Altman 1972a). The number of synapses between Purkinje cell dendrites and granule cell axons is decreased (Nicholson and Altman 1972a, b). The disappearance of the external granule cell layer (EGL) and migration of granule cells into the internal granule cell layer (IGL) are delayed (Nicholson and Altman 1972c). Myelination is also delayed (Balázs et al. 1971). Furthermore, synaptic connections among cerebellar neurons and afferent neuronal fibers from other brain regions are also affected (Hajós et al. 1973). Such abnormal development cannot be rescued unless TH is replaced within the first 2 weeks of postnatal life in rodents (Koibuchi et al. 2003). As a consequence, various behavioral impairments such as motor coordination and cognitive disorders are caused even by mild hypothyroidism (Amano et al. 2018; Khairinisa et al. 2018). Such abnormal development may be transferred through generations, since maternal behavior is partly impaired by perinatal hypothyroidism (Khairinisa et al. 2018). In addition, a dispersed primary culture system has been developed from a newborn rat cerebellum (Ibhazehiebo et al. 2011a). Using this system, the effect of T4 treatment on Purkinje cell dendrite arborization was studied. As shown in Fig. 4, T4 treatment for 14 days

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Fig. 3 The effect of altered thyroid hormone status during rat cerebellar development. Rats were rendered hypothyroid by administering antithyroid drug (propylthiouracil) starting from day 17 after conception. They were sacrificed at day 15 after birth. Compared with control rat (a, c, e), hypothyroid rat cerebellum is smaller (b). Retardation of dendrite arborization is evident in Purkinje cells, as shown by immunohistochemistry for calbindin (d). Proliferation and migration of granule cell from the external granule cell layer (EGL) to the internal granule cell layer (IGL) is also retarded (f). Also note the decrease in the width of the molecular layer (ML) by perinatal hypothyroidism (arrows in e, f)

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Fig. 4 The effect of thyroid hormone (T4) on Purkinje cell development in rat primary cerebellar culture. Newborn rats were sacrificed on postnatal day 2 to dissect out the cerebellum. Dispersed cells were plated and cultured for 14 days with indicated amount of T4. Immunocytochemistry was performed using anti-calbindin antibody. (a) Photomicrographs of Purkinje cells in culture. (b) Quantitative analysis for the dendritic area of Purkinje cells in culture)

dramatically increases Purkinje cell dendritic areas. Thyroid hormone can also increase neurite extension in purified cerebellar granule cell aggregate culture (Ibhazehiebo et al. 2011b). These findings indicate that thyroid hormone acts directly on cerebellar cells to promote development.

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Thyroid hormone crosses the blood-brain barrier or blood-cerebrospinal fluid barrier through its specific transporters such as the organic anion transporter (Oatp) 1c1 and monocarboxylate transporter (MCT) 8 (Bernal 2005). T4 seemingly crosses such barriers more easily than T3 (Calvo et al. 1990). T4 is then taken up by astrocytes or tanycytes, in which it is converted to T3, an active form of thyroid hormone, by type 2 iodothyronine deiodinase, which is predominantly expressed in these cell types (Guadaño-Ferraz et al. 1997). T3 is then transferred to neurons or oligodendrocytes – mainly through MCT8 – and binds to TR. Impaired thyroid hormone transport, caused by MCT8 mutation, induces severe neurological disorders in humans (Dumitrescu et al. 2004) and model animals (Trajkovic et al. 2007). When T3 is in the neuron/oligodendrocyte, it is converted to T2 for inactivation by type 3 iodothyronine deiodinase, which is predominantly present in neuronal cells (Tu et al. 1999). In the human fetal cerebellum, T3 levels remain low during the first 20 weeks of pregnancy, followed by a gradual increase until birth (Kester et al. 2004). Such a change may occur because of the differential expression of types 2 and 3 deiodinases rather than a change in circulating thyroid hormone levels. In rats, type 3 deiodinase expression is relatively high during fetal life, whereas type 2 deiodinase activity continues to increase until early postnatal life (Bates et al. 1999). Such differential activities in deiodinases are consistent with changes in T3 levels found in the cerebellum. This pattern of changes in T3 content and deiodinase activities in the cerebellum is greatly different from other brain regions, i.e., the cerebral cortex, in which a striking increase in T3 content is seen during the first trimester in the human cerebellum with a very low level of type 3 deiodinase (Kester et al. 2004). Peeters et al. (2013) have shown that type 3 deiodinase-null mice displayed reduced foliation of the cerebellar cortex, accelerated disappearance of the eternal granule cell layer, and premature expansion of the molecular layer. This indicates that deiodinases titrate the thyroid hormone levels in the cerebellum for temporal regulation of the cerebellar development. It has been generally accepted that the TR mediates most thyroid hormone actions in the brain, although non-genomic thyroid hormone actions have also been proposed (Leonard 2007). TRs are widely expressed in the developing and adult cerebella (Bradley et al. 1992). TRβ1 is predominantly expressed in Purkinje cells, whereas TRα1 is expressed in another subset of cells. C-erbAα2 or TRα2, which is produced from the TRα gene by alternative splicing – and which does not bind to thyroid hormone – is also widely expressed, although its physiological role has not yet been clarified. Although TRs are widely expressed in the developing cerebellum, and their levels do not decrease in adults, thyroid hormone regulates many thyroid hormoneresponsive genes, predominantly during the first 2 weeks of postnatal life in rodents. The expression of a wide variety of genes is altered by thyroid hormone status during cerebellar development (Dong et al. 2005). Such responsive genes include neurotrophic factors, adhesion molecules, cytoskeletal proteins, and transcription factors. Furthermore, a recent development of a genome-wide screening technique has enabled a comprehensive search specifically for thyroid hormone target genes (Gagne et al. 2013). Through temporal and spatial regulation of such genes, thyroid hormone may precisely control cerebellar development.

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TR and cofactors, such as steroid receptor coactivator (SRC)-1, are strongly expressed in the adult and developing cerebella (Martinez de Arrieta et al. 2000; Yousefi et al. 2005). SRC-1 disruption results in abnormal cerebellar developments similar to those seen in hypothyroid animals (Nishihara et al. 2003). SRC-1 is predominantly expressed in Purkinje cells and the IGL, whereas only cells located in the premigratory zone express SRC-1 in the EGL (Yousefi et al. 2005). These results are consistent with previous data which show the thyroid hormone is insensitive to proliferating granule cells (Messer et al. 1984). Furthermore, cerebellar SRC-1 protein levels were greatest at P15, when thyroid hormone most strongly affects cerebellar development (Yousefi et al. 2005). These results indicate that the change in coactivator expression may play an important role in TH sensitivity in the cerebellum. Indeed, in addition to SRC-1, other coregulators expressed in the developing cerebellum may also be involved. One such candidate is hairless (Thompson and Bottcher 1997), which is expressed in the developing cerebellum and directly regulated by thyroid hormone (Thompson and Bottcher 1997). It interacts with several NRs, including TRs, and functions as either a corepressor – by recruiting histone deacetylase (Potter et al. 2002) – or as histone H3 lysine 9 demethylase (Liu et al. 2014). Furthermore, developmental alteration of DNA methylation may also play a role in altering thyroid hormone sensitivity (Zhou et al. 2016). These epigenetic processes not only control TR actions but also other NR actions, which also have a distinct critical period to control cerebellar development. In addition to coactivators/corepressors, TR may interact with other nuclear receptors that regulate gene expression. One such example is retinoic acid-related orphan receptor (ROR) α, which is also a member of the steroid/thyroid receptor superfamily. It is strongly expressed in Purkinje cells and plays a critical role in cerebellar development. Cerebellar phenotype and alteration of neurotrophin expression of natural mutant mouse (staggerer) harboring an RORα mutation is similar to that in the hypothyroid mouse (Qiu et al. 2007), although its thyroid function is normal. This indicates that RORα may be involved in thyroid hormone-regulated gene expression in the developing cerebellum. In fact, thyroid hormone regulates RORα expression during the first 2 postnatal weeks (Koibuchi et al. 2001), indicating that thyroid hormone may alter gene expression critical for cerebellar development through RORα regulation. Furthermore, RORα augments TR-mediated transcription, whereas staggerer-type mutant RORα does not have such action (Qiu et al. 2007). Another study has shown that RORα may directly interact with TR without binding to TRE. The DNA binding domain of RORα may play a role in such interaction (Qiu et al. 2009). These results indicate that RORα is required for full TR function in the developing cerebellum.

Animal Models to Study Thyroid Hormone Action in the Developing Cerebellum The cerebellum is the most common brain region used to study the mechanisms of thyroid hormone action on brain development. Since the rodent cerebellum develops mostly during the postnatal period, perinatal hypothyroidism causes various

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cerebellar abnormalities, as discussed above. Perinatal hypothyroidism can be induced easily by administering antithyroid drugs, such as propylthiouracil and methimazole (methylmercaptoimidazole) (Koibuchi 2009), which inhibit thyroid hormone synthesis by inhibiting thyroid peroxidase activity. In addition to druginduced hypothyroid animal models, many mutant or gene-modified animal models showing congenital hypothyroidism have been reported, some of which have been used to study thyroid hormone action in the cerebellum (Koibuchi 2009). One example is the pax8 gene knockout mouse (Poguet et al. 2003). Pax8 is essential for thyroid follicular cell differentiation; thus, its knockout mouse shows a severe hypothyroidism. Morphological development and gene expression in the cerebellum are greatly affected in this mouse. Regarding the TR gene knockout model, these animal models may not always be suitable for studying thyroid hormone action in the cerebellum. As discussed above, TR has bidirectional actions of transcriptional regulation of target genes. Without T3 it represses transcription, whereas with T3 it activates transcription. Since TR deletion abolishes the repressive action of TR, phenotypes of TR knockout mice are greatly different from those of mice harboring low thyroid hormone levels. However, TR knockout mice are essential to study the role of TR in organ development and function. Another issue that may be considered to generate TR knockout mice is that some introns, such as intron 7 of TRα gene, have a weak promoter activity. Thus, deleting upstream exons may result in expression of additional TR-related proteins, which may be limited under normal conditions (Chassande 2003). As discussed above, at least three additional TR-related proteins, TRΔα1, TRΔα2, and TRΔβ3, may be generated. Thus, phenotypes of TR knockout mice may result from combining deletion of a specific TR with overexpression of other TR species. Table 1 shows the list of TR-knockout mice. Possible remaining TR proteins in each animal are also indicated. TRα1 deleted mice showing a limited alterations in behavior and neural circuit are also reported (Guadaño-Ferraz et al. 2003). However, except for aberrant maturation of astrocytes, their cerebellar phenotype appeared normal (Morte et al. 2004). More strikingly, TRα1 deletion prevented the structural alteration of the cerebellum in hypothyroidism induced by methimazole and perchlorate treatment (Morte et al. 2002). These results indicate that the abnormal cerebellar phenotype in thyroid dyshormonogenesis animals may result from the dominant-negative action of unliganded TRα proteins. Interestingly, deleting TRα1 also prevented structural alteration induced by deleting type 3 deiodinase, which inactivates thyroid hormone action by converting T3 to T2. These results indicate that, although the cerebellar phenotype of TRα1 deleted mice is limited, liganded TRα1 plays an important role in cerebellar development. On the other hand, TRα2 knockout mice show both hyper- and hypothyroid phenotype in an organ-specific manner (Saltó et al. 2001). This may be a result of elevated TRα1 expressions in this mouse. TRα1 expression in the brain is also elevated, but the cerebellar phenotype was unclear. Deleting both TRα1 and TRα2 also shows only a limited phenotype in the cerebellum. However, besides the

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Table 1 Thyroid hormone receptor (TR) gene knockout mouse models Targeted exon

Targeted gene TRα TRα1 /

References

Deleted TRs

Remained TRs

Representative phenotypes Normal T3 with slightly reduced T4 level Prevention of hypothyroid phenotype in the cerebellum Overexpression of TRα1, inducing both hyper- (high body temperature, increased heart rate) and hypothyroid phenotype (increased body fat) Aberrant intestine and bone development Aberrant intestine and bone development, but the phenotype is less severe than those in TRα /

exon 9

GuadañoFerraz et al. 2003; Morte et al. 2002, 2004

α1, Δα1

α2, Δα2, all β

exon 10

Saltó et al. 2001

α2, Δα2

α1, Δα1, all β

/

exon 2

Fraichard et al. 1997

α1, α2

Δα1, Δα2, all β

TRα0/0

exon5intron7

Gauthier et al. 2001; Macchia et al. 2001

all α

all β

exon 2

Abel et al. 1999; Ng et al. 2001

β2

β1, (β3, Δβ3) all α

exon 3

Forrest et al. 1996; Sandhofer et al. 1998

all β

all α

See above

Göthe et al. 1999

α1, Δα1

α2, Δα2 all β

/

TRα2

TRα

TRβ TRβ2

/

/

TRβ

Central resistance to thyroid hormone levels Elevated TSH, T3, and T4 levels Selective loss of M-cone in retina Central resistance to thyroid hormone Elevated TSH, T3, and T4 levels Aberrant auditory functional development

TRα and β TRα1

/

TRβ

/

High T3 and T4 levels due to high TSH level Growth retardation. Abnormal bone maturation (continued)

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Table 1 (continued) Targeted gene TRα

/

/

TRβ

TRα0/0TRβ

/

Targeted exon TRα / : see above TRb / : exon 4–5

TRα0/0: see above TRβ / : exon 4–5

References Gauthier et al. 1999

Gauthier et al. 2001

Deleted TRs α1, α2

Remained TRs all β, Δα1, Δα2

all α all β

None

Representative phenotypes Aberrant intestine and bone development (more severe than TRα / ) Elevated TSH,T3 and T4 levels (more severe than TRβ / ) Reduced body temperature and bone maturation (more severe than TRα / ) Aberrant auditory function (more severe than TRβ / ) Aberrant intestine development (milder than TRα / , or TRα / TRβ / )

cerebellar phenotype, the existence of TRΔα1 and/or TRΔα2 shows altered phenotypes in various organs. When TRα1 and TRα2 are deleted but expressions of TRΔα1 and TRΔα2 are not inhibited (TRα / ) (Fraichard et al. 1997), their phenotype is more severe than those of mice in which all TRα proteins are deleted (TRα0/0) (Gauthier et al. 2001; Macchia et al. 2001). The decrease in plasma thyroid hormone levels is greater, and there is a more severe impairment of bone and intestine development. A more limited brain phenotype is observed in TRβ knockout mice. While TRβ1 is widely expressed including in the cerebellum – particularly in Purkinje cells (Bradley et al. 1992) – TRβ2 expression is confined to the pituitary, hypothalamus (TRH neuron), retina, and inner ear. TRβ2 knockout mice show central resistance to thyroid hormone with elevated T3, T4, and TSH levels in the serum (Abel et al. 1999). Furthermore, this deletion causes a selective loss of M-cones in the retina (Ng et al. 2001). However, the abnormal brain phenotype seems to be confined to the hypothalamus, and changes in cerebellar phenotype have not been reported. On the other hand, there is aberrant development of auditory function in addition to central hypothyroidism in TRβ knockout mice (Forrest et al. 1996). However, although TRβ is strongly expressed in the Purkinje cells, its deletion does not alter thyroid hormone-responsive genes in the cerebellum (Sandhofer et al. 1998). In the case of TRα and β double knockout, because the function of one receptor cannot be substituted for the other, their phenotypes are more severe than those of single gene knockout. In TRα1 / TRβ / mice, delayed general growth and aberrant bone maturation, which are not seen in each single knockout mouse, are observed (Göthe et al. 1999). In TRα / TRβ / mice, aberrant intestinal development, which is seen in TRα1 / , and high T3, T4, and TSH levels – which is seen in

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TRβ / – are observed. Both of these are more severe than those of single knockout mice (Gauthier et al. 1999). However, in TRα0/0TRβ / mice, while low body temperature and abnormal auditory function, which are more severe than those of TRα0/0 or TRβ / , respectively, are seen, aberrant intestinal development is milder than those of TRα / TRβ / or TRα1 / (Gauthier et al. 2001). These results indicate the possible contribution of TRα variants (Δα1 and/or Δα2) in generating differential phenotypes. Altered brain development in these double knockout mice has not yet been studied in detail. In addition to TR knockout mice, several knock-in mice, harboring mutant TRs, have been generated (Hashimoto et al. 2001; Fauquier et al. 2011). Such animals are considered models for human syndrome of resistance to thyroid hormone (RTH), which is characterized as reduced thyroid hormone actions in thyroid hormone target tissue (Ortiga-Carvalho et al. 2014). Although most human patients harbor a mutation in the TRβ gene (RTHβ), recent studies have revealed that the patient harboring TRα gene mutation (RTHα) also exists. While RTHβ patients and model animals show elevated serum levels of T3 and T4 with non-suppressed thyrotropin (TSH), RTHα patients and model animals show slightly lower or normal levels of T4, slightly elevated or normal levels of T3, and normal levels of TSH. Such differences may be a result of the difference in tissue distribution of TRα and β, particularly in the hypothalamus and anterior pituitary. Both RTH patients and animal models show various neurological phenotypes. Animal models for both RTHs show abnormal cerebellar development (Hashimoto et al. 2001; Fauquier et al. 2011). These mice show decreased arborization of Purkinje cell dendrites with aberrant locomotor activity and decreased expression of thyroid hormone-responsive genes in the cerebellum. The cerebellar phenotype of RTH animal models is more severe than that of TR knockout animals, indicating that the abnormal cerebellar development seen in hypothyroid animals may be induced mainly by unliganded TRs. Furthermore, the effect may not be a result of generalized TH resistance, but may be because of the cerebellar-cell specific action of TH resistance. This hypothesis is supported by studies using animal models expressing dominant-negative TRs in cerebellar cells (Fauquier et al. 2014; Yu et al. 2015), showing aberrant cerebellar development.

Steroid Hormones and Cerebellar Development General Overview Adrenal and gonadal steroid hormones are known as stress and sex hormones, respectively, and both play important roles in CNS development. They affect various developmental events of neurons, such as survival, differentiation, and remodeling of axons and dendrites. These effects are associated with brain organization, sexual differentiation, and stress responses. Steroid hormones bind cognate ligand-activated receptors, members of the steroid/thyroid superfamily of nuclear receptors, to modulate the transcription of hormone-responsive genes. This review summarizes the published data characterizing the actions of these hormones and the localization

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of the receptors in the developing cerebellum. Most of the information presented here is from rodent studies.

Adrenal Steroid Hormones and Cerebellar Development Mineralocorticoids and glucocorticoids are major adrenal steroid hormones synthesized in the adrenal cortex. Mineralocorticoids help maintain sodium and potassium levels, while glucocorticoids are involved in the stress response and in regulating carbohydrate metabolism. Their levels are controlled via the hypothalamo-pituitaryadrenal (HPA) axis by pituitary adrenocorticotropic hormone and hypothalamic corticotropin-releasing factor. Most of the effects on the brain are mediated via binding to intracellular receptors, the glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) (Rashid and Lewis 2005). Regulation at the genomic level is thought to be responsible for slow and long-lasting effects, such as the actions of corticosteroid hormones on neurogenesis, neuronal morphology, and function in response to chronic stress, while rapid effects (responses within minutes) are regulated by non-genomic action (Evanson et al. 2010). Membrane-associated glucocorticoid and mineralocorticoid receptors may be involved in mediating non-genomic rapid effects (Prager and Johnson 2009). GRs, expressed in the adult brain, are associated with HPA axis activation to regulate physiological neuronal functions (Garabedian et al. 2017). Expression is first detected in the embryonic rat brain, and levels are high and similar as in the developing cerebellum and hippocampus (Lawson et al. 1992). Prenatal glucocorticoids influence Purkinje cell development (Rugerio-Vargas et al. 2007). Another study using chick embryos has reported the presence of GR mRNA in the embryonic cerebellum (Yamate et al. 2010). Furthermore, Yamate et al. also showed that effects after treatment with excess glucocorticoids are mediated via GRs and indirectly influence behavioral activity after hatching. In the mouse, GR immunoreactivity is intense in the EGL, the Purkinje cell layer, and white matter regions but weak in the molecular layer and IGL at postnatal day 7 (P7). These results suggest that glucocorticoids exert actions on cellular differentiation in the developing cerebellum, inducing multiple changes in peripheral responses and brain function. Glucocorticoids can induce positive and negative effects on the developing brain depending on the developmental stage and exposure duration (Malaeb and Stonestreet 2014). In rats, cortisone treatment during prenatal (Velazquez and Romano 1987) and postnatal (Bohn and Lauder 1980) development resulted in fewer cerebellar granule cells. Ahlbom et al. (2000) further showed that cerebellar granule cells exposed to high levels of glucocorticoids during the prenatal period become more sensitive to oxidative stress-induced cell death. A single glucocorticoid injection into the neonatal mouse can also induce apoptotic changes in the cerebellum. This results in permanent reductions in the number of neurons within the internal granule layer, suggesting that there is a limited period of vulnerability to glucocorticoids during development (Noguchi et al. 2008). Stressful experiences, such as maternal deprivation (MD), in the early postnatal period in rats retard

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development of cerebellar-dependent motor coordination and lead to behavioral abnormalities similar to schizophrenia (Llorente et al. 2009). Rats that are maternally separated during P4–P14, which corresponds to the stress-hyporesponsive period characterized by reduced responsiveness of the HPA axis (Walker et al. 2001), have elevated corticosterone levels at P13 and display behavioral alterations in adolescence and adulthood (Viveros et al. 2009). These results support the possibility that abnormally increased levels of glucocorticoids due to neonatal stress during development are associated with structural abnormalities in the cerebellum. In addition, another study using chick embryos suggested that apoptosis, induced in immature granule neurons by corticosteroids, may be mediated via a non-genomic mechanism (Aden et al. 2008). Based on these animal studies, these actions of glucocorticoids on the developing human cerebellum may be related to lower birth weight and may also be responsible for the emotional and behavioral problems observed in children whose mothers are treated with glucocorticoids for respiratory dysfunction during pregnancy (Noguchi et al. 2008). In addition, structural and functional cerebellar abnormalities, such as Purkinje cell loss, have been detected in many psychiatric disorders, such as autism and schizophrenia (Baldaçara et al. 2008; Martin et al. 2010). Interestingly, some effects of neonatal MD are different between the sexes. Effects on cellular degeneration and astrocyte proliferation in the cerebellum of neonatal MD rats were greater in males than females (Llorente et al. 2009). This is attributed to males being more vulnerable to stress and/or a sex difference in the onset of sensitivity to stress. Furthermore, impaired eyeblink conditioning was observed only in MD males. This is thought to be associated with the sexually dimorphic pattern of developmental GR expression in the posterior region of the cerebellar interpositus nucleus, a key region for eyeblink conditioning (Wilber and Wellman 2009).

Gonadal Hormones and Cerebellar Development Testosterone and estradiol (E2) are the two major gonadal steroids synthesized in the testis and the ovary. An important factor for the actions of these gonadal hormones is aromatase, an enzyme that is responsible for producing estrogens from androgens. In the developing brain, gonadal steroids are well known for their functions in forming brain structures that are different between males and females (Lenz and McCarthy 2010). During a limited perinatal period from late embryonic development through the first few days of postnatal life, testosterone is produced in males by the testis, which is differentiated from the indifferent gonad during early embryonic development directed by the testis-determining gene Sry (Koopman et al. 1991). In the brain, testosterone is converted to E2 by aromatase, whereas female ovaries – whose differentiation occurs postnatally – do not secrete E2 during this period. Thus, during the perinatal critical period, significantly higher levels of E2 in males compared to females are thought to act on male brain development. Regulatory mechanisms of E2 action have been reviewed in detail elsewhere (Wright et al.

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2010); however, briefly, E2 regulates apoptosis to produce sexually dimorphic cell numbers, dendritic spine formation, neuronal migration, and synaptic organization in hypothalamic regions, most of which are key regions for regulating male and female sexual functions in the adult brain. In the developing rat hippocampus, gonadal steroids control sexually dimorphic neurogenesis (Zhang et al. 2008). Because of the lack of estrogen exposure during the perinatal period, the female brain was thought to develop without E2. However, studies using knockout mice of the aromatase gene have suggested that E2 produced by the ovaries during a prepubertal period plays a role in the differentiation of the female-typical brain (Bakker and Brock 2010). The two major estrogen receptors (ERs), ERα and ERβ, are expressed in hypothalamic regions where development occurs differently between the sexes. A degree of overlapping distribution and colocalization occurs between ERα and ERβ in some hypothalamic regions, such as the ventromedial hypothalamus, a key region in female reproduction, suggesting the two proteins may interact (Ikeda et al. 2003). Phenotypes of ERα and ERβ knockout mice are different, suggesting distinctive roles (Kudwa et al. 2006). It has also been suggested that rapid plasma membranemediated non-genomic actions of estrogen, which possibly interacts with classical transcriptional regulation (genomic mechanisms), also play important physiological roles in regulating the neural actions of estrogen in the brain (Raz et al. 2008; Vasudevan and Pfaff 2008; Kelly and Qiu 2010). These results suggest complicated interactions of ERα and ERβ by various signaling regulatory mechanisms. Furthermore, it has recently been suggested that epigenetic alterations of DNA methylation patterns on the promoters of ER genes, induced by estradiol during development, are important for sexually dimorphic brain organization. This may be a mechanism by which estradiol regulates ER gene expression to produce permanent masculinization of the brain (Wilson and Westberry 2009). Androgens, directly acting on the androgen receptor (AR), are also thought to play a role in brain masculinization. This is based on studies of human patients with complete androgen insensitivity syndrome and patients with aromatase gene mutations, as well as on studies of rodents with the testicular feminization mutation, which produces a nonfunctional AR (Zuloaga et al. 2008). Gonadal steroids also play an important role in the development of brain regions that are not significantly different between the sexes, including the cerebellum (Lenz and McCarthy 2010; Forger et al. 2016). Estradiol levels in the cerebellum are higher during the first postnatal week than later developmental stages (Sakamoto et al. 2003; Biamonte et al. 2009), and treating newborn rats with estradiol promotes dendritic growth and spine formation of Purkinje cells (Sakamoto et al. 2003). These studies indicate that estrogens play a role in cerebellar development. Higher expression levels of ERα compared to ERβ in the hypothalamus indicate that ERα is predominantly associated with reproduction, whereas ERβ is expressed in nonreproductive regions, such as in the cerebral cortex, hippocampus, cerebellum, and the dorsal raphe. It is thought to play an important role in brain morphogenesis (Fan et al. 2010). Cerebellar development occurs at late embryonic and early postnatal stages in rodents. Both ERα and ERβ are detected in an immature cerebellar granule cell line that was derived from late embryonic mouse cerebellum. Experiments with

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ER-subtype selective agonists and overexpression of ERα and ERβ in this cell line have indicated that ERα, but not ERβ, mediates E2 actions in embryonic cerebellar granule cells (Gottfried-Blackmore et al. 2007). Quantitative RT-PCR studies have shown that both receptors are expressed in the cerebellum from birth through adulthood, but levels of ERβ mRNA in neonatal rats are significantly higher than those of ERα (Ikeda and Nagai 2006). These studies have also shown that ERα levels in the cerebellum during early postnatal development are significantly higher than in the adult; adult levels are only slightly higher than background. In contrast, no significant changes in the level of cerebellar ERβ mRNA occurred during development or in adulthood (Ikeda and Nagai 2006). However, this ERβ expression pattern differs somewhat from that previously studied using western blot analysis, in which the level of ERβ protein decreased transiently at P5 and P7 and then increased dramatically at P10 followed by a subsequent decrease (Jakab et al. 2001). Using in situ hybridization and immunohistochemistry, we have further shown that ERα-positive Purkinje cells are abundant during early postnatal stages, but these cells are reduced to only a few in adulthood. Since considerable outgrowth and differentiation of Purkinje cell dendrites occur during the first 3 postnatal weeks, these results suggest a possible role of ERα in Purkinje cell differentiation (Ikeda and Nagai 2006). ERβ immunoreactivity was detected in various neurons, including Golgi cells, Purkinje cells, and basket cells, and the expression in each cell type occurs at different postnatal days. Jakab et al. (2001) detected additional ERβ-immunoreactive cells, such as differentiating external granular layer cells and glial cells, although we failed to detect protein or mRNA for ERβ in these cells. The cellular localization of ERβ may reflect its role in cellular differentiation and maturation in cerebellar development. As shown in Fig. 5, the different expression profiles of ERα and ERβ suggest that E2 exerts its actions in a cell-type-specific manner via binding to the two ERs, which play distinctive roles in cerebellar development. The possibility of rapid estrogen signaling mechanisms in the developing cerebellum has been recently discussed elsewhere (Belcher 2008). Although no sex differences in architecture have been reported in normal cerebellar development, there is a clear sex difference of cerebellar pathology in several developmental diseases in humans and corresponding animal models. This has been linked to alterations in circulating gonadal steroids during critical periods of cerebellar development (Dean and McCarthy 2008). Estrogens can protect neurons from oxidative stress-induced death (Daré et al. 2000) in several brain regions, including the cerebellum, by modifying neuronal vulnerability (Miñano et al. 2007). The antioxidative action of E2 may be relevant to sex differences in negative symptom scores of schizophrenia, which are higher in males (Goldstein and Link 1988). Another study of reeler mice, which have a mutation in the reelin gene – a candidate gene in neurodevelopmental disorders such as schizophrenia and autism (Fatemi 2001) – indicates that, by interacting with reelin, E2 acts on survival and maturation of Purkinje cells in female mice. Also, the female-specific regulation of the reelin promoter by E2 might be epigenetic (Biamonte et al. 2009). Thus, in addition to their neurotrophic actions in the developing cerebellum, estrogens may play important roles in neuronal protection.

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Fig. 5 Localization of ERα and ERβ proteins during postnatal cerebellar development. Representative images of immunohistochemistry for ERα (a–c) and ERβ (d–f) in the cerebellum at postnatal day (P) 7, P14, and P21. Arrows indicate representative ERα-immunoreactive Purkinje cells. egl external germinal layer, gl granular layer, ml molecular layer, pl Purkinje cell layer. Scale bar, 50 μm

Cerebellar testosterone levels are transiently higher in males than females at P5 (Biamonte et al. 2009). An in vitro study showed the presence of AR protein in cultured P7 cerebellar granule cells, demonstrating that cerebellar granule cells obtained from testosterone-treated neonatal rats are protected from cell death, induced by oxidative stress, via a mechanism mediated by the androgen receptor (Ahlbom et al. 2001). Autism spectrum disorders are more frequent in men than in women, and high fetal testosterone levels may be involved (Knickmeyer and BaronCohen 2006).

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Several studies have reported that aromatase mRNA levels in the cerebellum during the early postnatal period are higher than in later stages (Sakamoto et al. 2003; Lavaque et al. 2006; Biamonte et al. 2009). Lavaque et al. (2006) detected a transient and marked elevation in aromatase mRNA levels at P10 in the male, but not female, cerebellum. They suggested this gene may contribute to the local synthesis of estrogen, which plays an important role in cerebellar development, combined with estradiol derived from the gonads. Higher vulnerability of males to MD stress might be associated with male-specific induction of aromatase, although such mechanisms remain unclear.

Conclusions and Future Directions Although many nuclear hormone receptors are expressed in the developing cerebellum, only a limited amount of data is available regarding the effect of thyroid/steroid hormones on this process. This may be because nuclear receptors act as transcriptional factors to activate or repress the transcription of target genes. Under such circumstances, the response to hormone stimulation is rather slow compared to that mediated by membrane-associated receptors, and various signal transduction cascades may be involved to express their action as a specific phenotype. However, hormonal signaling plays an important role to mediate environmental influences on the developing brain. Thus, hormonal disruptions may cause cerebellar disorders leading to various psychosomatic diseases. This chapter will help increase the understanding of the role of thyroid/steroid hormones in the developing cerebellum.

Cross-References ▶ Analysis of Gene Networks in Cerebellar Development ▶ Endocrine Disorders ▶ Epigenetic Regulation of the Cerebellum ▶ Granule Cell Migration and Differentiation ▶ Specification of Granule Cells and Purkinje Cells ▶ Synaptic Remodeling and Neosynaptogenesis ▶ Synaptogenesis and Synapse Elimination

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Development of Physiological Activity in the Cerebellum

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Sriram Jayabal and Alanna J. Watt

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neuronal Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Physiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Early Influences of Adult Firing Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Influences Physiological State of Developing Purkinje Cells? . . . . . . . . . . . . . . . . . . . . . . . . . . Ion Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Other Regulators of Physiological Activity During Development . . . . . . . . . . . . . . . . . . . . . . . . . Development Gone Awry: Disease States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Autism Spectrum Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ataxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

One remarkable aspect of cerebellar development is that intrinsic physiological activity of several neuronal cell types, including Purkinje cells, can be observed throughout a large portion of the developmental window. Although ion channels primarily drive this intrinsic activity, it can also be influenced by other cellular properties and inputs, including synaptic and neuromodulatory inputs, calcium buffers, and others. Many of the factors that drive or influence intrinsic activity are expressed in a tightly regulated manner during the development of the cerebellum. Here, we review how the ion channels, calcium buffers, synapses, and neuromodulators that are differentially expressed during development give S. Jayabal Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA e-mail: [email protected] A. J. Watt (*) Department of Biology, McGill University, Montreal, QC, Canada e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_111

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rise to activity patterns with unique regulatory properties, which may serve important roles in sculpting the developing cerebellum. We also review recent lines of evidence that suggest changes in synaptic and intrinsic activity may be common developmental changes contributing to the pathophysiology of not only cerebellar ataxias but also neurodevelopmental diseases such as autism spectrum disorders. Finally, we posit that these findings support a hypothesis for an important role for early physiological activity in the formation of the cerebellum and that alterations in this activity can lead to pathology. Keywords

Cerebellum · Purkinje cell · Ion channels · Autism · Ataxia · Development

Introduction Neuronal Development If you were to build a machine that specializes in planning and executing well-timed events – a mechanical cerebellum – you would likely approach the task systematically: assembling it piece by piece, connecting and checking each new addition before you move on to the next, and, at the end, once everything was assembled, you would hook up the electricity to start it, or “turn on the juice.” This is a far cry from the way that biology has evolved for the task of building a cerebellum. The selfassembly of the cerebellum, and, indeed, the entire nervous system, is a complex, tumultuous process – neurons are born at different times in different places, far from their eventual home, and then migrate along neuronal highways like cars in rush hour, eventually making both pre- and postsynaptic connections with an excess of neuronal partners, before pruning away a subset of those connections. Surprisingly, many neurons will not survive this juvenile stage, but die before the circuit is mature. While scientists tend to study individual developmental processes in isolation, there are in fact multiple parallel processes occurring during development, which makes the process of brain development difficult to understand in its entirety. Not only is brain development a complex process, but it is also noisy. The nervous system does not become active only when mature, but is active already throughout much of the assembly process. Activity of neurons arises from fluctuations in the membrane potential due to activation of ligand-gated and voltage-gated channels, causing synaptic signals and action potentials. A large number of ion channels, transporters, and other molecules that influence the activity are expressed in distinct patterns during development. This produces unique activity motifs during the developmental period in the healthy brain. In this review, we focus on the physiological activity of the developing cerebellum in health and cerebellar disease. Much of our review will focus on Purkinje cells, the principal cell and sole projection neuron of the cerebellar cortex and arguably the most studied cell type of the cerebellum. In the interest of space, we unfortunately cannot describe the

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physiological development of all neurons in the cerebellum, although we will touch on the development of their activity when possible.

Cerebellar Physiology One prominent feature of the cerebellum is that several cell types exhibit spontaneous rhythmic activity. This is best studied in Purkinje cells, which exhibit highfrequency rhythmic firing in adults, even in the absence of synaptic input (Arancillo et al. 2015; McKay and Turner 2005; Woodward et al. 1969; Llinas and Sugimori 1980; Nam and Hockberger 1997; Häusser and Clark 1997). However, several other cell types also exhibit spontaneous activity in the cerebellum, including cells of the deep cerebellar nuclei (DCN) (Jahnsen 1986; Llinas and Muhlethaler 1988) (Reviewed in Elsen et al. 2018), molecular layer interneurons (Häusser and Clark 1997), and Golgi cells (Forti et al. 2006; Edgley and Lidierth 1987). In general, a neuron’s capacity for intrinsic activity is due to the constellation of ion channels that are expressed in the membrane of these cells, which for Purkinje cells we will discuss in greater detail below. During postnatal development in mice, the cerebellum undergoes profound developmental changes. Purkinje cells increase their somatic size and dramatically expand their dendritic arbors during postnatal development (Altman 1972). Purkinje cell intrinsic firing emerges during the first few days of postnatal development in rodents at lower firing rates than in adults. Firing frequency then slowly increases during postnatal development until stabilizing at adult levels near the end of the postnatal developmental window (~4 weeks old) (McKay and Turner 2005; Watt et al. 2009; Woodward et al. 1969; Arancillo et al. 2015).

Early Influences of Adult Firing Patterns While we will review the nuts and bolts of how Purkinje cell activity is regulated developmentally below, it is interesting to mention some new studies first that suggest that the ultimate state of Purkinje cell activity is influenced by very early embryonic events. Purkinje cells are born early in the developing embryo (Miale and Sidman 1961; Altman and Bayer 1985 reviewed in Butts et al. 2018). After birth, they migrate to the cerebellar cortex where they populate the early Purkinje cell layer (Altman and Bayer 1985 reviewed in Sotelo and Rossi 2018); in the cerebellar vermis, this occurs along a posterior–anterior axis, where posterior cells are born earlier than anterior cells (Altman and Bayer 1985). Recently, Kim and colleagues have elegantly shown that posterior lobule Purkinje cells in the vermis are less excitable than anterior, later-born Purkinje cells (Kim et al. 2012). How might the birthdate of a Purkinje cell influence its adult excitability? In the mature cerebellum, Purkinje cells can be classified by their zebrin expression profile, which is thought to be determined not long after a Purkinje cell is born (reviewed in Sillitoe and Hawkes 2018). Two groups have recently shown that difference in excitability correlates not

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simply with anterior–posterior axis but with the zebrin expression profile of the Purkinje cells, where zebrin cells fire at higher frequencies than zebrin+ cells, irrespective of their location within the anterior–posterior axis (Zhou et al. 2014; Xiao et al. 2014). Thus, a fundamental property of a Purkinje cell in the adult brain – the rate of their stereotypical high-frequency firing – appears to be influenced by factors established at or shortly after the Purkinje cell is born. How is this firing established during development?

What Influences Physiological State of Developing Purkinje Cells? Ion Channels Sodium Channels During the postnatal period, profound morphological and physiological developmental changes take place, including the molecular identity of the cells. These changes, such as the differential expression of ion channels, can influence firing properties. As firing properties of cells mature (McKay and Turner 2005; Watt et al. 2009; Woodward et al. 1969; Arancillo et al. 2015), an increase in peak sodium conductances has been observed in mouse and rat Purkinje cells (McKay and Turner 2005; Fry 2006). The sodium conductances are produced by voltage-gated sodium channels: adult Purkinje cells richly express voltage-gated sodium channel Nav1.1 (Felts et al. 1997; Black et al. 1994; Gong et al. 1999) and Nav1.6 (Schaller and Caldwell 2000; Schaller et al. 1995; Vega-Saenz de Miera et al. 1997) in both the soma and dendrites. These are thought to be the fast voltage-dependent sodium channels that underlie action potential generation. Purkinje cells also expresses Naβ1 and β2 auxiliary subunits (Shah et al. 2001; Levy-Mozziconacci et al. 1998; Sashihara et al. 1995) that regulate sodium channel function (Oh et al. 1994). Not surprisingly, expression of several sodium channels is regulated during development. Two-day old rodent Purkinje cells do not express sodium channel Nav1.1; however, by the beginning of the 3rd week of postnatal development (~postnatal day (P)15), Purkinje cells express them (Felts et al. 1997; Gong et al. 1999; Westenbroek et al. 1995). In granule cells, expression of Nav1.1 is present in adult granule cells, but the onset of expression is even later than in Purkinje cells (Felts et al. 1997; Gong et al. 1999; Westenbroek et al. 1995). The developmental expression pattern of sodium channel Nav1.2 has been somewhat controversial. Early reports suggested that it was not expressed in the cerebellum (Brysch et al. 1991); however, since then, Nav1.2 sodium channels have been reported in Purkinje cells in a developmental pattern that is almost the inverse of that of Nav1.1, with Nav1.2 expression detected during early postnatal development, but not in adulthood (Felts et al. 1997; Gong et al. 1999; Westenbroek et al. 1995). Similarly, the expression of the sodium channel Nav1.3 is widely observed throughout the cerebellum starting as early as embryonic day 17. Expression declines during development, and by P15 and thereafter, Nav1.3 channels are no longer expressed in rodent cerebellum (Felts et al. 1997).

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Not all sodium channels are regulated during development. For example, sodium channel Nav1.6 has been reported to be expressed at all stages of the development and in adulthood in the Purkinje cell soma and dendrites (Felts et al. 1997; Schaller and Caldwell 2000). This is interesting as these channels are known to be responsible for the resurgent sodium currents which are important in Purkinje cells’ pacemaker firing ability (Raman and Bean 1997, 1999).

Potassium Channels Purkinje cells also undergo an increase in the rate of repolarization during development, which suggests changes in the potassium channel conductance (McKay and Turner 2005). The slow-activating and large-amplitude afterhyperpolarization (AHP) observed during early postnatal development matures into a fast-activating and deactivating smaller-amplitude AHP, suggesting a change in the density of potassium channels as Purkinje cells grow (McKay and Turner 2005). Purkinje cells express a wide variety of potassium channels during the development including voltage-gated channels such as Kv1, Kv2, Kv3, and Kv4 (Drewe et al. 1992; Weiser et al. 1994; Martina et al. 2003). These channels undergo developmental regulation, where the expression of the potassium channel from the Kv3 family first emerges at P8 in rodents, and is then rapidly upregulated during development so that all Purkinje cells express these channels by P12 (Goldman-Wohl et al. 1994). In addition to voltage-gated potassium channels, Purkinje cells also express a rich array of calcium-activated potassium channels, whose expression is markedly regulated during development (Raman and Bean 1999; Womack and Khodakhah 2002, 2003; Womack et al. 2004; Swensen and Bean 2003). The AHP of the Purkinje cell action potential is also influenced by big conductance (BK) and small conductance (SK) potassium channels (Womack and Khodakhah 2002, 2003; Womack et al. 2004; Swensen and Bean 2003). Electrophysiology studies from cultured cells and acute slices suggest BK channels are expressed at low levels in the 1st week of postnatal development, which then are upregulated so that BK channels are highly expressed in the adult Purkinje cells (Muller and Yool 1998; Edgerton and Reinhart 2003; Womack et al. 2009). In contrast, SK channel expression is high during postnatal development and undergoes downregulation during development so that lower SK channel levels are detected in the adult cerebellum (Stocker and Pedarzani 2000; Cingolani et al. 2002). Both SK and BK channels contribute to the pacemaker properties of Purkinje cells (Womack and Khodakhah 2002, 2003; Haghdoost-Yazdi et al. 2008). This suggests that the differences in Purkinje cell action potential properties during development, especially of the AHP, may arise from the differential regulation of both the voltage-gated and calcium-activated potassium channels. Calcium Channels Purkinje cell spontaneous firing is influenced by other ion conductances including calcium. It is well established that rodent Purkinje cells express both high-threshold (L-, P-, R-, and N-type) and low-threshold (T-type) voltage-gated calcium channels at all stages of development and in adulthood (Nam and Hockberger 1997; Kaneda et al. 1990; Meacham et al. 2003), leading one to ask: Is the expression of these

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channels dynamically regulated across development? In the 1st week of postnatal development in mice, more than half of the calcium influx into the Purkinje cell is conducted by the L-type calcium channels that are expressed in the soma (Liljelund et al. 2000). Other calcium channels such as P/Q-, R-, and N-type channels are expressed by the Purkinje cells but were found to contribute less to intrinsic activity (Liljelund et al. 2000; Raman and Bean 1999). However, starting from the 2nd week of postnatal development in mice, P/Q- and R-type channel expression is upregulated, while the expression of the L-type channel decreases (Meacham et al. 2003). In adult Purkinje cells, the majority of the calcium influx in the soma and dendrites comes from the P/Q-type channels, with only a small fraction arising from L- and N-type channels (Mintz et al. 1992; Watanabe et al. 1998), suggesting that L-type calcium channels are downregulated dramatically during development. Are all voltage-dependent calcium channels developmentally regulated? T-type calcium channels are expressed at all ages across development and contribute to a lesser degree to Purkinje cell intrinsic activity, with little evidence of age-dependent regulation (Nam and Hockberger 1997; Raman and Bean 1999; Swensen and Bean 2003; Kaneda et al. 1990). Interestingly, N-type calcium channels have also been reported to be relatively uniformly expressed across development in rodent Purkinje cells where they influence intrinsic activity (Alvina et al. 2016). This is, however, in stark contrast to the developmental expression profile of N-type calcium channels in other cerebellar neurons. In the DCN, N-type calcium channel expression is high in early postnatal development when it is the primary calcium channel type contributing to intrinsic activity (Alvina and Khodakhah 2008; Alvina et al. 2016). By adulthood, however, N-type calcium channels appear to no longer contribute significantly to pacemaker activity in DCN neurons (Alvina et al. 2016). An interesting study by Fletcher and colleagues suggests that the regulation of individual calcium channels may depend on the expression level of other channels. They studied how the cell-specific disruption of one calcium channel (P/Q-type knockout in cerebellar granule cells) influenced expression of other calcium channels and observed that some (L- and N-type), but not all (R-type was not regulated), calcium channels were upregulated (Fletcher et al. 2001). These results suggest that active adaptive mechanisms exist in neurons that help titrate the relative expression levels of similar channels in order to preserve cellular physiological function.

Ion Channels Summary Purkinje cells start firing action potentials spontaneously at low rates early during the 1st week of postnatal development (Arancillo et al. 2015). They then gradually increase their firing rate due to changes in the type and density of ion channels they express (Fig. 1). The age-dependent regulation of multiple ion channels described above suggests that during development, each neuronal cell type regulates its channels in unique patterns which differ across cell types, conferring different properties to the intrinsic activity of the different pacemaker neurons. In addition to changes in the overall ratios of different channel types, it is likely that within a given channel type, subunit composition may change during development, leading to even more molecular diversity. Auxiliary subunits are known to

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Fig. 1 Developmental regulation of ion channels underlies modulation of Purkinje cell firing properties. Schematic shows rodent Purkinje cells during postnatal development at 1 week (left), 2 weeks (middle), and 3 weeks or adult (right) of postnatal development. Purkinje cells grow and their dendritic trees enlarge across development. Multiple types of sodium channels (green), potassium channels (yellow), and calcium channels (blue) are regulated by development, while others (e.g., Nav1.6 sodium channels, T-type calcium channels) are not regulated. Relative size of cartoon channel represents relative expression levels in Purkinje cells

influence channel properties for all three types of voltage-gated ion channels described above (Moreno et al. 1997; Gonzalez-Perez et al. 2014; Ransdell et al. 2017). Furthermore, changes in auxiliary subunits can favor distinct signaling pathways that ion channels interact with (Campiglio and Flucher 2015), as well as other cellular functions (Davis et al. 2004). In adult Purkinje cells, for example, loss of the Navβ4 accessory subunit for voltage-dependent sodium channels alters channel function and cellular firing properties, leading to dramatic deficits in cerebellar-related behavior (Ransdell et al. 2017). Although developmental regulation of channel subunit composition occurs in other brain regions (e.g., in the hippocampus (Schlick et al. 2010)), this has been largely unexplored in the cerebellum to date. Yet the putative regulation of auxiliary subunit composition across development would likely have important functional consequences and thus merits further exploration.

Other Regulators of Physiological Activity During Development Calcium Buffers Purkinje cells possess a large soma and one of the largest and most complex dendritic structures of all neuronal cell types. Given their large dendrites and the corresponding massive excitatory synaptic input they receive, it could be hypothesized that Purkinje cells are particularly susceptible to calcium-mediated excitotoxicity. Yet Purkinje cells stay healthy in part due to an enormous calcium buffering capacity that enables them to handle large calcium influxes (Schwaller

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et al. 2002). Purkinje cells highly express the calcium buffer proteins calbindin and parvalbumin (Celio 1990; Scotti and Nitsch 1992), and their expression is tightly regulated during very early development (Milosevic and Zecevic 1998). In humans, calbindin expression is detected very early during embryonic development in Purkinje cells as early as it has been looked for (~embryonic weeks 4–5) (Milosevic and Zecevic 1998), while parvalbumin expression is found in Purkinje cells only several months later in the human fetus (Fig. 2) (Milosevic and Zecevic 1998). The developmental pattern of expression of calbindin and parvalbumin in rodents is similar to that seen in humans, with calbindin expressed first and parvalbumin expressed later during embryonic development (Altman 1969; Arnold and Heintz 1997; Solbach and Celio 1991). These buffers play a role in several physiological processes. The absence of calbindin in knockout mice leads to altered calcium dynamics in Purkinje cells (Airaksinen et al. 1997), while the absence of parvalbumin causes changes in synaptic release at cerebellar synapses (Caillard et al. 2000), and both are associated with changes in cerebellar-related motor function (Farre-Castany et al. 2007). Evidence suggests that Purkinje cells possess multiple mechanisms to regulate intracellular calcium in order to preserve intrinsic activity: Kreiner and colleagues found that there were alterations in P/Q channel auxiliary subunits from knockout mice lacking calbindin and parvalbumin in a manner that increased voltage-dependent channel inactivation while preserving action potential properties of Purkinje cells (Kreiner et al. 2010). Adaptations like these that are observed in transgenic mice give us a tool with which we can probe the mechanisms underlying the developmental homeostatic plasticity that cerebellar neurons possess and use to stabilize firing output, reminiscent of homeostatic mechanisms described in other brain regions (Turrigiano 1999). Interestingly there is another type of calcium buffer that is extensively expressed in the granule cells and unipolar brush cells but is typically absent from adult Purkinje cells, calretinin (Dino et al. 1999). However, a recent study shows that calretinin expression is transiently observed in Purkinje cells and molecular layer interneurons during human embryonic development (Pibiri et al. 2017). This suggests that the calretinin plays a brief but potentially important role during

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Perinatal calbindin parvalbumin calretinin

Fig. 2 Developmental regulation of calcium buffers in Purkinje cells. Schematic shows human Purkinje cells during embryonic (left) and perinatal (right) development. Calbindin is expressed earliest during embryonic development, followed by parvalbumin. There is transient expression of calretinin in human Purkinje cells during late embryonic development. Both calbindin and parvalbumin are expressed at higher levels postnatally (not shown)

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development in Purkinje cells (Fig. 2), although a similar developmental transition has not been identified to date in rodent models to our knowledge.

Synapses Synaptic development in the cerebellum is a complex process that has been reviewed in other chapters (Kano and Watanabe 2018). Both excitatory (Shim et al. 2016) and inhibitory (Häusser and Clark 1997) synapses can influence Purkinje cell firing output. Protocols that alter the long-term strength of synapses such as long-term depression (LTD) and long-term potentiation (LTP) have been shown to alter intrinsic excitability as well (Belmeguenai et al. 2010; Shim et al. 2017), suggesting that there are strong links between Purkinje cell synapses and intrinsic activity. This is important since changes in Purkinje cell activity have also been shown to causally underlie motor learning behavior (Nguyen-Vu et al. 2013). Interestingly, links between synaptic plasticity and intrinsic excitability have also been observed in other cerebellar neurons in the DCN (Aizenman et al. 1998), suggesting that the relationship between synaptic alterations and intrinsic excitability may be a general feature of cerebellar neurons. How might early synaptic activity influence the development of the cerebellar circuit? Below we will touch upon a few examples of ways in which cerebellar development appears to be shaped by the synaptic input and the resulting physiological activity neurons experience. Molecular layer interneurons are born in the ventricular zone over a relatively long developmental period which in mice spans several weeks perinatal and then migrate to their final location in the molecular layer (Leto et al. 2009; Sudarov et al. 2011). This means that migrating molecular layer interneurons migrate through a network of cells and projections that are already in their final location. A recent study by Wefers and colleagues show that molecular layer interneurons receive both excitatory and inhibitory synaptic input that influences their migration: without it, migration is slow and lacks directional cues (Wefers et al. 2017). This suggests that local synaptic-mediated activity plays an instructive role in neuronal migration in molecular layer interneurons. It is unknown whether earlier-born migrating cerebellar neurons like Purkinje cells receive synaptic input during migration. There are comparatively few neurons in the cerebellar cortex at early embryonic ages when Purkinje cells are migrating (reviewed in (Sotelo and Rossi 2018)). However, there are axons that transiently innervate the cerebellum from the trigeminal ganglia even before Purkinje cells are born (Marzban et al. 2018), which suggests that such a mechanism is theoretically possible. Another way that synapses can play a role in development is through the modulation of network activity, which is widespread across the developing nervous system (Ackman et al. 2012; Blankenship and Feller 2010). In the developing cerebellum, Purkinje–Purkinje synapses, which are mediated by asymmetrically projecting axonal collaterals and are enriched in early postnatal development, produce wavelike activity in the early developing cerebellum (Watt et al. 2009). Similar activity in other brain regions plays a role in sculpting developing circuits (Burbridge et al. 2014; Pratt et al. 2016), and modelling suggests that such wavelike

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activity can play a role in refinement and pattern formation in developing circuits (Bennett and Bair 2015). In support of this, a more recent study observed highly synchronized activity of both climbing fibers and Purkinje cells in vivo during the 1st week of postnatal development in rodents that desynchronized during the second postnatal week. Desynchronization of Purkinje cell activity was abolished when climbing fiber synapse elimination was perturbed (Good et al. 2017), suggesting that proper synapse elimination of climbing fibers influenced circuit activity. Many excitatory synapses in the brain express NMDA receptors throughout development but experience an activity-dependent subunit shift during postnatal development, leading to changes in a synapse’s capacity for plasticity (Yashiro and Philpot 2008). Cerebellar Purkinje cells have a rather more complicated developmental profile. In rodents, functional NMDA receptors are observed in Purkinje cells until the end of the first postnatal week (Rosenmund et al. 1992), after which their expression is decreased to low levels. Initially, it was believed that low expression persisted throughout the rest of the life span (Dupont et al. 1987). Surprisingly, however, this is only a transient feature of excitatory synapses in Purkinje cells, which again express NMDA receptors starting after the 3rd week of postnatal development (Piochon et al. 2007; Renzi et al. 2007), where they play a role in synaptic plasticity (Piochon et al. 2010). Why Purkinje cells experience a transient decrease in the expression of functional NMDA receptors during postnatal development is poorly understood, but given the role of NMDA receptors in excitotoxicity and cell death (Vyklicky et al. 2014), it may be a neuroprotective measure to ensure cerebellar health during this critical period when the parallel fiber input a Purkinje cell receives increases in number dramatically or perhaps is related to some other property of the developing cerebellum. These studies show that synapses are highly developmentally regulated and are important in shaping neuronal activity, directing migrating neurons along their migratory paths, thereby serving important roles in the development of the cerebellum.

Other Influences of Normal Developmental Physiology There are many different regulators of the physiological state of the cerebellum that we are only able to touch upon here. Some, such as the role that hormones play in cerebellar development, are reviewed in other chapters (Koibuchi and Ikeda 2018). Hormones have been shown to modulate several facets of adult Purkinje cell physiology: for example, estradiol modulates Purkinje cell excitability (Smith et al. 1988), while the hormone leptin influences Purkinje cell firing and inhibitory synaptic input (Forero-Vivas and Hernandez-Cruz 2014); however, little is known about how these processes are regulated developmentally. Neuromodulators are another example of molecules that regulate cerebellar physiology that are tightly regulated throughout development. To take just one example, serotonin has been implicated in regulating the physiological properties of several cerebellar neuronal types. Purkinje cell excitability (Wang et al. 1992; Li et al. 1993) and synaptic inputs (Strahlendorf et al. 1984, 1986) are modulated by serotonin in adults. Interestingly, Purkinje cells exhibit changes in their morphology and excitability that are reminiscent of an older stage of development in a knockout

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mouse of the developmentally transiently expressed serotonin type 3 (5HT3) receptors, suggesting that serotonin acts as a brake during normal development (Oostland et al. 2011, 2013). Indeed, several serotonin receptors display tight developmental regulation (Li et al. 2004; Oostland et al. 2011, 2014). Recently, Saitow and colleagues show that in the DCN, effects of serotonin are also developmentally regulated: serotonin modulates inhibitory inputs more strongly during early postnatal development than in the young adult (Saitow et al. 2018). Other neurotransmitters, like acetylcholine, also display developmentally regulated responses in Purkinje cells (Kawa 2002). We may only be in the infancy of understanding the developmental implications of neuromodulator actions in the cerebellum, yet this regulation will likely have profound effects on Purkinje cell physiology, activity, and function. We have a reasonable understanding of the developmental regulation of the channels that directly contribute to intrinsic activity in the cerebellum (see above, Fig. 1). Yet physiological activity is also regulated by many other factors, some of which we have summarized above. Beyond hormones and neuromodulators, there is a vast array of growth factors (Tian et al. 2014; Shakkottai et al. 2009), transporters (Forrest et al. 2012), and other signaling molecules (Smith and Otis 2003), which are also capable of regulating Purkinje cell intrinsic activity. It is also likely that many other as-yet-unidentified factors exist that also modulate the intrinsic or synaptic activity of cerebellar neurons. For example, transient morphological changes in axonal morphology have been observed during cerebellar development whose functional impact remain unexplored (Ljungberg et al. 2016). In most cases, little is known about if and how these changes are regulated during development. Thus, there is much that remains to be discovered for a complete understanding of the mechanistic control of physiological activity in the healthy developing cerebellum.

Development Gone Awry: Disease States Proper function of the cerebellum is crucial for fine motor coordination, motor learning, and memory. More recently it has become clear that cerebellar function extends beyond the motor system to cognitive functions as well (Schmahmann 2004; Stoodley et al. 2012; Koziol et al. 2014). What diseases arise when cerebellar development goes awry? Cerebellar abnormalities have been implicated in autism spectrum disorders (ASD) (Wang et al. 2014), as well as in several rodent models of ASD (Tsai et al. 2012; Peter et al. 2016; Piochon et al. 2014). The developmental onset of autism suggests that abnormal cerebellar development may be implicated in its etiology. We will discuss recent findings about the role that abnormal cerebellar physiological synaptic and intrinsic activity plays in ASD below. Classically, cerebellar dysfunction has been associated with cerebellar ataxias and dystonia (Manto and Marmolino 2009b; Rossi et al. 2014; Anheim et al. 2012). There are several causes of ataxia, including drugs, environmental toxins, and fever (Incecik et al. 2013; Manto 2012). However, the best studied ataxias to date are the rare genetic diseases including autosomal dominant and recessive ataxias.

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The mechanistic underpinnings of ataxias and dystonias have been well studied in rodent models of these genetic diseases (e.g., Manto and Marmolino 2009a; Walter et al. 2006; Watase et al. 2008; Jayabal et al. 2016; Inoue et al. 2001; Hourez et al. 2011; Shakkottai et al. 2009, 2011; Fremont et al. 2015, 2014). Ataxias encompass a diverse group of disorders with variable symptoms that manifest at different ages, from early- or childhood-onset to late-onset (Rossi et al. 2014; Anheim et al. 2012). Recent work that we will review suggests that abnormal cerebellar development may occur in late-onset ataxias and thus may contribute to disease pathophysiology even in these late-onset disorders. Below we will review disorders where abnormal cerebellar development is thought to contribute to disease.

Autism Spectrum Disorders ASD refers to a group of developmental disorders that can be diagnosed as early as 2 years of age. ASD presents with a wide range of symptoms that include cognitive and social impairment, communication problems, and repetitive stereotypic motor movements. Research into ASD have garnered astounding interest in the last decade, and the involvement of cerebellum in ASD has become well established (Wang et al. 2014). Several genes have also been identified that confer susceptibility to ASD (Abrahams and Geschwind 2008). In addition to hereditary mutations, environmental factors that affect the developing brain have been implicated in ASD (Mandy and Lai 2016; Modabbernia et al. 2017). Cerebellar injury or dysfunction during early development has been correlated with ASD (Hashimoto et al. 1995), with cerebellar injury predicted to be the second most common risk factor in developing ASD (Wang et al. 2014). How is cerebellar physiology altered in ASD? Studies from several transgenic mouse models that perturb genes implicated in human ASD have argued that Purkinje cell spontaneous firing and synaptic deficits are implicated in ASD. In a TSC1 genetic mouse model of ASD, Purkinje cell firing rate is reduced in a gene dosage-dependent manner that is correlated with the autistic behavioral deficits (Tsai et al. 2012), and more recently, the restoration of Purkinje cell activity chemically was found to rescue ASD-like symptoms (Stoodley et al. 2017). In a separate Shank2 ASD mouse model, deficits in the regularity of Purkinje cell firing are correlated with autistic-like behavior (Peter et al. 2016). Finally, in another ASD model based on deletion mutations on chromosome 10 (PTEN), Purkinje cell firing rate deficits are observed to be associated with autistic behavior (Cupolillo et al. 2016). These findings suggest that Purkinje cell intrinsic activity is important during cerebellar development and that abnormal firing deficits can contribute to ASD. Furthermore, rescue of firing properties can reduce autism-like behavior in these mouse models. In addition to the firing properties of Purkinje cells, altered Purkinje cell synaptic properties have been observed in several different autism models. For instance, Piochon and colleagues showed that altered plasticity of parallel fiber input and altered development of climbing fiber inputs were associated with motor

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abnormalities in a mouse model that replicates a human duplication that gives rise to ASD (Piochon et al. 2014). Likewise, both excitatory (Ha et al. 2016) and inhibitory (Lim et al. 2017) synaptic deficits have been observed in a Shank2 ASD mouse model. Interestingly, reversing inhibitory synaptic deficits can rescue spatial memory deficits in Shank2 ASD mice (Lim et al. 2017). Additionally, in several of the mouse ASD models described above in which Purkinje cell firing deficits are observed, synaptic deficits in climbing fiber and parallel fiber deficits have also been observed (Peter et al. 2016; Cupolillo et al. 2016) although not in all models (Tsai et al. 2012). Purkinje cell degeneration is observed at later ages in several mouse models of ASD, suggesting that these synaptic and intrinsic alterations in Purkinje cell function may contribute to later cell death (Peter et al. 2016; Cupolillo et al. 2016; Tsai et al. 2012). It is important to understand the full spectrum of cellular alterations of connectivity and intrinsic activity across models of ASD, both genetic and environmental, to understand how they contribute to disease. This may reveal common pathophysiology that might generalize the therapeutic targets for several different types of ASD.

Ataxia Genetic ataxias can be classified in several different ways. We often group ataxias according to the type of root genetic mutation: for example, there are over 40 autosomal dominantly inherited ataxias (Rossi et al. 2014; Mundwiler and Shakkottai 2018) and more than 10 recessive ataxias (Anheim et al. 2012). One of the most studied groups of autosomal dominant ataxias are the spinocerebellar ataxias (SCAs), many of which share a triplet-repeat expansion in their mutated gene, including SCA1, SCA2, SCA3, SCA6, and others (Paulson et al. 2017). Symptoms of SCAs vary greatly, probably owing to the different genes that harbor the mutation (Paulson et al. 2017). For instance, while the most common SCAs are late-onset progressive ataxias that onset after 20 years old – such as SCA1, SCA2, and SCA6 – other SCAs are early-onset disorders that arise during childhood (Paulson et al. 2017). Even for a given disorder with the same genetic mutation, the age of disease onset can vary widely. There are several examples of typically late-onset disorders manifesting earlier during childhood (Globas et al. 2008; Wang et al. 2010; Figueroa et al. 2017), suggesting that no strict division exists between diseases which onset during development and those that onset later, after development. One common feature of many ataxias is that as the disease progresses, cerebellar Purkinje cells undergo severe degeneration (Paulson et al. 2017), although as we have seen in the case of ASDs, Purkinje cell degeneration is by no means limited to ataxia. While certain ataxias such as SCA1 and SCA3 (Machado-Joseph disease) (Durr et al. 1996) involve alterations in other brain regions like brainstem and striatum in addition to the cerebellum, other ataxias, such as SCA6, are considered pure cerebellar disorders, with minimal extra-cerebellar neuronal degeneration (Zhuchenko et al. 1997). Regardless of their onset and symptoms, many studies of mouse models of genetic ataxias show alterations in Purkinje cell firing and/or excitatory synaptic

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inputs at or near the age when motor abnormalities are first observed, including autosomal-recessive spastic ataxia of the Charlevoix-Saguenay (ARSACS) (Ady et al. 2018), episodic ataxia type 2 (EA2) (Walter et al. 2006; Alviña and Khodakhah 2010a, b), SCA1 (Hourez et al. 2011; Inoue et al. 2001; Dell’Orco et al. 2015; Power et al. 2016; Shuvaev et al. 2017), SCA2 (Kasumu et al. 2012; Scoles et al. 2017; Meera et al. 2017), SCA3 (Shakkottai et al. 2011), SCA5 (Perkins et al. 2010), SCA6 (Mark et al. 2015; Jayabal et al. 2016; Du et al. 2013), SCA13 (Irie et al. 2014), and SCA27 (Shakkottai et al. 2009). The fact that similar changes are observed across so many different ataxias suggests that a group of common mechanisms involving aberrant synaptic and intrinsic physiology may underlie motor deficits in many or even all ataxias (Meera et al. 2016). Similar changes have been observed in animal models of dystonia (Isaksen et al. 2017; Fremont et al. 2014, 2015). Furthermore, as we described in the section above, several animal models of ASDs exhibit altered Purkinje cell physiology reminiscent of that seen in ataxias (Fig. 3; Tsai et al. 2012; Peter et al. 2016). Finally, there are mouse models of several other disorders in which similar Purkinje cell changes are reported, including Alzheimer’s disease (Hoxha et al. 2012) and multiple sclerosis (Shields et al. 2012; Mandolesi et al. 2013). How can similar cellular physiological changes manifest across such diverse diseases? This raises the questions of whether Purkinje cell physiological changes give rise to specific disease abnormalities – that is they act causally – or are they observed whenever the cerebellum functions poorly? This is an important question that is yet to be fully answered. In some diseases, Purkinje cell vulnerabilities are restricted to certain populations, such as anterior vermis in ARSACS (Ady et al. 2018;

Health

Disease

Fig. 3 Schematic showing Purkinje cell firing patterns in healthy rodent cerebellum (left) and diseased cerebellum (right), including rodent models of ataxias and ASD. Affected Purkinje cells (red) display lowered firing rates (right). Cells can be affected at specific developmental or adult ages, or in specific spatial patterns; these differences likely contribute to disease manifestation

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Lariviere et al. 2015), posterior vermis in SCA5 (Perkins et al. 2016), and RCrusI in ASD (Stoodley et al. 2017), suggesting that different susceptible pools of cerebellar neurons when affected give rise to different symptoms (Fig. 3). Furthermore, although the presence of Purkinje cell deficits in other disorders may at first suggest that they contribute to other deficits aside from ataxia, ataxia is commonly observed in disorders like multiple sclerosis (Salci et al. 2017; Wilkins 2017), and gait deficits may predict some forms of dementia (Beauchet et al. 2016), arguing that motor control deficits in diverse diseases may nonetheless reflect cerebellar alterations.

Early-Onset Ataxias While many ataxias onset in midlife, there are several that typically onset early, during brain development. The most common early-onset ataxia is Friedrich’s ataxia, an autosomal-recessive slowly progressive ataxia that typically onsets in young schoolaged children (Barbeau 1976). Friedrich’s ataxia is typically characterized as involving multiple parts of the nervous system, including the spinal cord, with only minimal cerebellar alterations that are limited to the dentate nucleus of the DCN (Koeppen et al. 2011). However, a more recent study has demonstrated changes in excitatory parallel fiber synapses made onto Purkinje cells in a mouse model of Friedrich’s ataxia (Lin et al. 2017), which is consistent with reports of structural changes in Purkinje cells in Friedrich’s ataxia patients (Kemp et al. 2016; Stefanescu et al. 2015). Another early-onset disorder, ARSACS, typically onsets during childhood (Bouchard et al. 1978) and is caused by inheriting two mutated copies of the Sacs gene (Thiffault et al. 2013; Engert et al. 2000; Synofzik et al. 2013). Like many ataxias, this is a progressive ataxia that gets worse over time. In a mouse model of the disorder, subcellular changes in protein localization have been detected early during postnatal development (Lariviere et al. 2015). Interestingly, we have also recently reported that both synaptic and intrinsic firing properties of Purkinje cells are altered and that at least some of these changes occur early in development (Ady et al. 2018). This suggests that the pathophysiology of ARSACS may be similar to several lateonset ataxias despite their earlier time of onset. SCA41 is one of the most recently described human ataxias (Fogel et al. 2015), but a mouse model of this disease, called “Moonwalker,” has been studied for years (Becker et al. 2009). This form of ataxia is well described in ▶ Chap. 77, “Moonwalker Mouse,” but for our purposes, it is worth mentioning briefly that the ataxia is accompanied by changes in Purkinje cell dendritic structure and metabotropic glutamatergic synaptic signaling in Moonwalker mice (Becker et al. 2009). One puzzling form of SCA is SCA13, which is classified by mutations to the KCNC3 gene (Waters et al. 2005). Since KCNC3 encodes the Shaw-type potassium channel which is important for action potential spiking in Purkinje cells (as well as other cell types), SCA13 would be predicted to decrease Purkinje cell intrinsic activity. Several different allelic mutations give rise to different forms of ataxia in SCA13: an adult-onset progressive ataxia, as well as a childhood-onset ataxia that is not progressive (Waters et al. 2006; Khare et al. 2017). All the mutations identified to date likely involve changes to channel expression or gating properties that will

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impact firing in Purkinje cells (Waters et al. 2006; Khare et al. 2017). Yet the onset and prognosis of ataxia is different with different ataxia-causing mutations. Earlyonset ataxia is typically caused by mutations that are predicted to have a more pronounced effect on a neuron’s ability to sustain high-frequency firing than lateonset ataxia (Waters et al. 2006; Khare et al. 2017). But why is this early-onset ataxia not progressive like adult-onset ataxia, which worsens with time? In fact, the opposite is typically seen: early-onset SCA13 typically shows lifetime improvement of motor function, suggesting that compensatory mechanisms are employed by the brain to counteract the impact of early ataxia. This difference may arise because the developing brain is more adept at plasticity and thus better able to compensate for changes in Purkinje cell function than the adult brain. Further research into these two forms of SCA13, nonprogressive early-onset ataxia versus progressive late-onset ataxia, may be a powerful means to identify the compensatory plasticity mechanisms that the developing brain is able to employ. If we understand these mechanisms during development, perhaps we can find tools to redeploy them in the case of lateonset diseases to counteract disease progression.

Altered Cerebellar Development in Late-Onset Ataxias? Most SCAs have a late onset of disease symptoms and are classically thought of as neurodegenerative diseases, where pathophysiology slowly builds up over a time scale of years to decades. Yet the brain harbors the pathogenic mutation from conception, so one may wonder why development proceeds normally. Do developmental changes occur in late-onset diseases, and could they contribute to later behavioral deficits? We recently reported that in a mouse model of SCA6, developing Purkinje cells display enhanced firing rate and firing precision (Jayabal et al. 2017), contrary to the firing properties observed at the age when motor symptoms emerged (Jayabal et al. 2016). Additionally, deficits in climbing fiber synapse elimination, similar to those observed in some models of ASD (Piochon et al. 2014), were also observed (Jayabal et al. 2017). Interestingly, these changes were transient in SCA6 mice as the firing properties and climbing fiber synapses appear normal in young adult SCA6 mice (Jayabal et al. 2017). This suggests that the developing SCA6 brain has the capacity to overcome certain developmental abnormalities and function normally for a time, before motor dysfunction emerges in midlife (Fig. 4) (Watase et al. 2008; Jayabal et al. 2015). Mechanistically, it is at present unknown how this developmental adaptation occurs. However, it has been reported that cerebellar granule cells can upregulate specific voltage-gated channels to compensate for the loss of P/Q calcium channels (Fletcher et al. 2001), suggesting that similar mechanisms may be employed in cerebellar Purkinje cells, since the underlying mutation in SCA6 is in a P/Q-type calcium channel subunit (Zhuchenko et al. 1997). Do these early changes contribute to later disease onset? While we do not currently have an answer for this in SCA6, evidence from another late-onset ataxia, SCA1, suggests that they may. Using a conditional mutant mouse strain that allows researchers to turn on or off expression of the mutated SCA1 gene (Zu et al. 2004), researchers tested whether development was involved in the manifestation of ataxia

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young adult

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Fig. 4 Altered firing properties during development prior to disease onset in a mouse model of SCA6. Purkinje cells display elevated firing rates during the second postnatal week of development (left) that are restored to normal levels by the time mice are young adults (middle). Although Purkinje cells display normal morphology during both development and young adult time periods, the complement of ion channels they express may be different from wild-type mice (illustrated by red outline). Ataxia onset occurs at 7 months and is accompanied by reduced Purkinje cell firing rate and precision (red, right panel). Summary of findings from (Jayabal et al. 2017)

(Serra et al. 2006). In this study, researchers delayed expression of the pathogenic SCA1 mutation until the mice were young adults and development was complete. One would predict that if the disease were purely neurodegenerative and did not involve development, the absence of expression during development would have little impact on disease prognosis. On the contrary, however, the age of onset was delayed, and the severity of motor symptoms was reduced when the mutated gene was not expressed during development (Serra et al. 2006; Ibrahim et al. 2017), suggesting that development influences disease progression in SCA1. Conditional mutant animal models allow researchers to study disease onset while dissecting the relative contributions of different temporal periods and will be an important tool for elucidating the role that altered cerebellar development plays in ataxia onset. This will have important implications for screening, diagnosis, and treatment of these inherited diseases.

Conclusions and Future Directions Physiological synaptic and intrinsic activities are present in the developing cerebellum over a wide period of development and may be influenced by factors determined not long after neurons are born. Since the factors that shape this activity are highly developmentally regulated (Figs. 1 and 2), it suggests that although superficially similar, the nuts and bolts of the activity observed at different time points during the

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maturation of the cerebellum has unique properties. This may in part explain our hypothesis that activity likely serves several functions during development; for example, synaptically mediated activity can direct migrating neurons to their proper terminal location (Wefers et al. 2017). When physiological activity is altered in development, there can be adverse consequences. Interestingly, developmental changes in synaptic and intrinsic activity in several mouse models of ASD mimic the alterations observed around the onset of motor symptoms in late-onset ataxias, suggesting that while alterations in these properties are typically pathological, it may be in part the timing of their onset that predicts which types of pathophysiological changes manifest in different disorders, although other factors such as the regional expression of these changes (Ady et al. 2018) contribute as well (Fig. 3). Understanding the role that pathophysiological activity plays in the developing cerebellum, and how this contributes to disease, is an important avenue that requires further study. While we do not fully understand how mature Purkinje cells encode information in the timing or rate of their action potentials (Eccles 1973; Person and Raman 2012; Hong et al. 2016; Abbasi et al. 2017), we have even less understanding of how this activity contributes to information transfer during development. However, understanding information transfer in the developing brain is an important question that demands further study. Given the differences in the underlying mechanisms contributing to this activity, it is possible that information is encoded differently in the developing and mature cerebellum. It remains important for scientists to continue to study how the cerebellum “turns on the juice” during development as well as why and how this goes wrong in several diseases and disorders.

Cross-References ▶ Moonwalker Mouse

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Epigenetic Regulation of the Cerebellum

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Yue Yang, Tomoko Yamada, and Azad Bonni

Contents A Brief Introduction to Epigenetic Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genome-Wide Changes in the Epigenetic Landscape in the Developing Cerebellum . . . . . . . . Families of Epigenetic Regulators in Mouse Cerebellar Development . . . . . . . . . . . . . . . . . . . . . . . . ATP-Dependent Chromatin Remodeling Enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Histone Tail Modifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DNA Methylation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Perspectives on Epigenetic Regulators in the Mouse Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . Epigenetic Control of Cerebellar-Dependent Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Epigenetics in Human Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Epigenetic regulators play fundamental roles in the control of gene transcription. Recent studies have uncovered key functions and underlying mechanisms for diverse epigenetic regulators in the development and function of the mammalian cerebellum. As powerful drivers of gene expression, epigenetic proteins recognize and alter chromatin including genomic DNA and the tightly bound histone proteins. Changes in chromatin structure reshape the local genome environment to control access of the transcriptional machinery to genes. Chromatin enzymes are highly expressed in neural precursors and postmitotic neurons in the developing cerebellum. Genetic studies have uncovered novel roles for epigenetic

Y. Yang · A. Bonni (*) Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA e-mail: [email protected]; [email protected] T. Yamada Faculty of Medicine, University of Tsukuba, Tsukuba, Japan e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_110

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regulators in distinct phases of cerebellar circuit assembly as well as cerebellardependent behavior. Moreover, studies of epigenetics in the cerebellum in some cases have led to entirely new mechanistic insights of how chromatin enzymes regulate the genome. Notably, mutations of epigenetic regulators often trigger neurodevelopmental disorders including autism spectrum disorder and intellectual disability, generating wide interest in understanding how epigenetic regulators govern the development and function of brain neural circuits including in the cerebellum. Keywords

Epigenetics · Chromatin · Histone · Histone modification · Histone acetylation · Histone methylation · Histone variant · DNA methylation · Chromatin remodeling · Gene expression · Genome · DNA · Promoter · Enhancer · Bivalent modification · Immediate early genes · Granule neuron · Purkinje cells · Precursor · Cell proliferation · Dendrite growth · Dendrite pruning · Presynaptic differentiation · Degeneration · Calcium signaling · Cerebellar-dependent behavior · CHARGE syndrome · Coffin-Siris syndrome · Rett syndrome · Intellectual disability · Autism spectrum disorders · PRC2 · Chd7 · Snf2h · Snf2l · NuRD complex · BAF complex · Kdm6a · Kdm6b · Kdm5c · HDACs · HATs · Tet enzymes · MeCP2 · Dnmt3a

A Brief Introduction to Epigenetic Mechanisms Genomic DNA in the nucleus of eukaryotic cells is organized by histone proteins into a macromolecular structure termed chromatin. The basic building blocks of chromatin are nucleosomes, each of which comprises an octamer of histone proteins including histones H2A, H2B, H3, and H4 wrapped by ~147 base pairs of DNA (Kornberg 1974; Luger et al. 1997). Whereas transcription factors directly bind to specific DNA sequences to control gene expression, epigenetic regulators introduce changes to chromatin that alter the genome environment. The enzymatic activities of epigenetic regulators may be divided into three main categories, posttranslational modification of histones, DNA methylation, and nucleosome remodeling (Allis et al. 2015.) (Fig. 1). The first two mechanisms involve the covalent attachment of molecules to proteins or DNA, whereas the latter mechanism involves an ATP-dependent movement or alteration in histone composition of nucleosomes. Chromatin modifications come in wide varieties, but share similar roles in genome control. First, posttranslational modification of histones, particularly on the N-terminal tail, include acetylation, methylation, phosphorylation, and ubiquitination (Li et al. 2007). Histone tail modifications strengthen or weaken DNA-histone interactions and serve as landmarks to recruit additional epigenetic regulators. Second, DNA methylation occurs at the fifth position of the pyrimidine ring of a cytosine followed by guanine (5mCG) or non-guanine nucleotide (5mCH) (Kriaucionis and Heintz 2009; Smith and Meissner 2013). Methylcytosine may be

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Epigenetic Regulation of the Cerebellum

Epigenetic mechanism

Enzymes

Histone modification

Ac Ac

Ac Ac

Ac Ub Ac

Ac

Ac

Ac

Ac

Me

Me

Me

Ac Ub Ac

Ub Ac

Genes coding enzymes in cerebellar development

Histone acetyltransferase Histone deacetylase Histone methyltransferase Histone demethylase

PRC2 (Ezh1/2) Kdm6b Kdm5c Hdac1/2 Hdac3 Gcn5

ATP-dependent chromatin remodeling enzymes

NuRD complex BAF complex Chd7 Snf2h, Snf2l

Ac Ac

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Nucleosome remodeling Nucleosome density

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DNA methylation DNA methyltransferase DNA dioxygenase

Tet 1/3 Dnmt3a

Fig. 1 Epigenetic mechanisms and enzymes in the cerebellum

modified to generate 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC). Like histone modification, DNA methylation serves as a marker to recruit or block the binding of transcription factors and epigenetic regulators that distinguish between methylated and unmodified DNA (Yin et al. 2017). Finally, nucleosome remodeling encompasses changes in nucleosome spacing, density, or subunit composition (Narlikar et al. 2013). Adjacent nucleosomes are positioned at specific genomic distances from one another in order to assemble into higher-ordered chromatin fibers. The canonical histone subunits of nucleosomes may also be exchanged for histone variants including histone H2A.x, H2A.z, and H3.3. Altering the positioning or structure of nucleosomes modulates the accessibility of transcription factors to genomic DNA sequences or may recruit additional epigenetic regulators that recognize specific histone variants. Together, these mechanisms represent a common theme in transcription, whereby groups of chromatin enzymes operate in concert to drive large-scale changes in the epigenetic landscape. Gene expression is directly controlled by chromatin modifications at their transcriptional start site (TSS) or promoters, at neighboring regulatory genomic DNA elements termed enhancers, or along the entirety of gene bodies. At least three major transcriptional states – active, poised, or repressed – at these regulatory loci are marked by distinct chromatin modifications (Hirabayashi and Gotoh 2010). Active genes have ongoing transcription, while poised genes are silent but may be turned on upon exposure to a stimulus or with cellular differentiation (Voigt et al. 2013). Repressed genes in the brain are constitutively silenced for the long-term in

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postmitotic cells (Pereira et al. 2010; Yamada et al. 2014). Chromatin features at both active and poised genes include histone H3 lysine 4 tri-, di-, and mono-methylation (H3K4me1/2/3), low nucleosome density, and the presence of mCA and 5hmC at promoters, enhancers, or gene bodies. High levels of histone H3 lysine 9, 14, and 27 acetylation (H3K9/14/27 ac) typically distinguish active genes from unstimulated, poised genes. Finally, the presence of histone H3 lysine 9 or 27 trimethylation (H3K9me3 or H3K27me3), mCG, and high nucleosome density mark constitutively repressed genes. In the next section, we will discuss how these transcriptional states are regulated in the developing cerebellum as neurons differentiate and assemble into neural circuits.

Genome-Wide Changes in the Epigenetic Landscape in the Developing Cerebellum The mouse cerebellum undergoes significant growth in the first few postnatal weeks. From postnatal day 3 to day 30, the cerebellar vermis alone expands over fourfold in area, due to increases in cell number and neuropil (Wojcinski et al. 2017). Cerebellar precursors originate from two distinct zones in early development. Excitatory neurons including granule neurons, unipolar brush cells, and excitatory deep cerebellar nuclei neurons are generated from precursor cells that originate in the rhombic lip. Inhibitory GABAergic neurons including Purkinje cells and inhibitory deep cerebellar nuclei neurons are generated from precursor cells in the ventricular zone. Following cell cycle exit, the stereotyped pattern of differentiation and maturation of granule neurons has been well-characterized since the days of Santiago Ramón y Cajal (Ramón y Cajal 1995). Granule neurons migrate from the external granule layer to the internal granule layer, where they transiently form exuberant dendritic processes that are subsequently pruned (Palay and Chan-Palay 1974). At the final stage of differentiation, presynaptic boutons in the molecular layer and postsynaptic dendritic claws in the internal granule layer are formed, providing specialized structures for synaptic neurotransmission. Thousands of genes encoding proteins involved in cell proliferation, neurite growth, and synaptogenesis are switched on and off during this period to support cerebellar development (Pal et al. 2011; West and Greenberg 2011; Zhu et al. 2016). The two major groups of genes important for cerebellar development include genes that are permanently turned on or off with neuronal differentiation and signaling genes that are repeatedly and transiently activated and shut off in response to extrinsic cues. Genome-wide regulation of chromatin modifications at promoters and enhancers directly control these patterns of gene expression. Because granule neurons represent the most populous cell type in the cerebellum (~70–80% of all cells) (Bandeira et al. 2009), with few exceptions, studies of epigenetics in the cerebellum have largely focused on developing granule neurons (Fig. 2). In proliferating granule neuron precursors, cell cycle genes are maintained in an active state by the presence of H3K4me3 at their promoters, while genes necessary

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Precursor proliferation Chd7, Snf2h, Ezh2, npBAF, Hdac1/2, Hdac3, Gcn5 EGL

ML

Presynaptic differentiation NuRD PCL

IGL Dendrite growth nBAF

Dendrite pruning NuRD

Fig. 2 Epigenetic regulation of distinct phases of cerebellar development. EGL external granule layer, ML molecular layer, PCL Purkinje cell layer, IGL, internal granule layer

for postmitotic neuron differentiation are kept silent by the bivalent modification of H3K4me3 and H3K27me3 (Bernstein et al. 2006). In newly born granule neurons, genes important for cell cycle and proliferation are constitutively repressed as their regulatory loci are marked by increases in H3K27me3, H3K9me3, 5mCG, and nucleosome density (Frank et al. 2015; Pal et al. 2011; Yang et al. 2016). Differentiating granule neurons turn on genes important for synapses, ion channels, and cell adhesion by marking promoters and enhancers with H3K4me3, H3K9/14/27 ac, 5hmCG, and 5hmCA, removing H3K27me3, and maintaining low nucleosome density (Frank et al. 2015; Pal et al. 2011; Song et al. 2011; Szulwach et al. 2011; Yang et al. 2016). The increased chromatin accessibility at these developmentally upregulated genes facilitates the recruitment of transcription factors including the Zic family to promote granule neuron maturation (Frank et al. 2015). A comprehensive analysis of histone modifications and transcriptional regulators in the adult mouse cerebellum and other tissues shows that active enhancers are expressed in a tissue-specific manner and are bound by different groups of transcription factors (Shen et al. 2012). The unique epigenetic landscape and expression patterns of active

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genes in mature granule neurons define their identity by presumably determining their unique morphology and physiological properties. A distinct class of genes are quiescent under baseline conditions but rapidly respond to extracellular signaling including growth factors and neuronal activity. These stimulus-responsive genes including immediate early genes (IEGs) enable neurons to sense changes in the local environment and consequently determine the correct time and place for differentiation or plasticity (Herschman 1989; Morgan and Curran 1989). Although genes marked by the H3K4me3/H3K27me3 bivalent histone marks may also respond to extracellular signals (Shi et al. 2014; Voigt et al. 2013), a key difference is that IEGs are activated and shut off over the lifetime of the neuron. At baseline, IEGs maintain poised promoters marked by H3K4me3, H2A.z, 5hmCG, and 5mCA and low levels of H3K9/14/27 ac (Kaas et al. 2013; Rudenko et al. 2013; Stroud et al. 2017; Yang et al. 2016). When neurons are activated, H2A.z is evicted and H3K9/14/27 ac levels increase at promoters, resulting in robust increases in gene expression (Yang et al. 2016; Zovkic et al. 2014). Networks of transcription factors including NeuroD, AP1, CREB, and MEF2 play critical roles in coupling extrinsic signals to epigenetic regulation and gene expression (Shalizi and Bonni 2005; West and Greenberg 2011). The stimuli-responsive target genes are often expressed in specific cell types or tissues (Lin et al. 2008). Together, the inducible expression of poised genes and the constitutive expression of active genes represent the major nuclear mechanisms that integrate cell-extrinsic cues with cell-intrinsic genetic programs to drive granule neuron differentiation. We will next discuss the epigenetic regulators that shape the nuclear landscape and orchestrate precise programs of gene expression in the cerebellum.

Families of Epigenetic Regulators in Mouse Cerebellar Development To study the molecular and biological functions of epigenetic regulators in cerebellar development, mouse genetics approaches have been employed. Because chromatin enzymes are often essential for early embryogenesis, conditional knockout approaches such as the Cre-LoxP system are required to conditionally delete genes in cell type-specific populations and at specific developmental timepoints. The Nestin-Cre driver is used to knockout genes broadly in neural precursors (Tronche et al. 1999), while the Math1-Cre driver silences genes of interest in granule neurons and deep cerebellar nuclei progenitors (Machold and Fishell 2005; Wang et al. 2005). Gabra6-Cre transgenic mice are used to target postmitotic granule neurons (Funfschilling and Reichardt 2002), and Pcp2-Cre targets postmitotic Purkinje cells (Barski et al. 2000). Most studies have focused on studying the roles of epigenetic regulators in cerebellar precursors or postmitotic granule neurons because these cells are more abundant, thereby facilitating molecular characterization. However, since knockout of epigenetic regulators frequently impairs progenitor proliferation or survival in vivo, in vitro cell culture methods have also been used to study the enzymatic functions of these genes. In this section, we discuss current understanding

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of how chromatin enzymes operate in the cerebellum to orchestrate gene expression and drive neuronal differentiation.

ATP-Dependent Chromatin Remodeling Enzymes Chd7 is an ATP-dependent chromatin remodeler that is particularly highly expressed in the cerebellum (Feng et al. 2017). Within the cerebellum, Chd7 is specifically expressed in granule neuron precursors and postmitotic granule neurons (Feng et al. 2017; Whittaker et al. 2017). Chd7 maintains chromatin accessibility at thousands of regulatory loci across the genome in cultured granule neuron precursors, including at the reelin gene and long neuronal genes, though how Chd7 operates at the genomic level in these cells in vivo remains to be elucidated. Chd7 interacts with other chromatin regulators including DNA topoisomerase 1/2α/2β (Top1/2a/2b), Brg1, and Chd8 to potentially co-regulate gene expression, a feature commonly observed among chromatin enzymes. Conditional Chd7 deletion in granule neuron precursors results in impaired progenitor proliferation, differentiation, or survival, culminating in cerebellar hypoplasia (Feng et al. 2017; Whittaker et al. 2017). At earlier developmental stages, Chd7 controls the expression of the midbrain and hindbrain organizers Fgf8, Otx2, and Gbx2, but the epigenetic mechanisms by which Chd7 regulates early hindbrain patterning remain unknown (Yu et al. 2013). The mammalian ISWI family proteins, Snf2h and Snf2l, are ATP-dependent chromatin remodeling enzymes that are highly expressed in the developing cerebellum. Whereas Snf2h is abundant in cerebellar precursors, Snf2l is expressed specifically in postmitotic neurons (Alvarez-Saavedra et al. 2014). Knockout of Snf2h in cerebellar precursors impairs chromatin organization in cerebellar precursors and Purkinje cells, resulting in global decreases in active histone modifications including H3K4me3, H3K18ac, and H3K36me2. These chromatin organization phenotypes may reflect dysregulation of the nucleosome spacing functions of ISWI (Ito et al. 1997; Varga-Weisz et al. 1997). Depletion of Snf2h in cerebellar precursors leads to cell death and reduced proliferation, culminating in cerebellar hypoplasia. Knockout of Snf2h specifically in postmitotic Purkinje cells impairs dendrite growth, leading to Purkinje cell degeneration (Alvarez-Saavedra et al. 2014). Beyond cell proliferation and survival, ATP-dependent chromatin remodelers also have important functions in terminal granule neuron differentiation. The nucleosome remodeling and deacetylase (NuRD) complex is a multi-subunit ATP-dependent chromatin remodeling enzyme that has both histone deacetylase and nucleosome remodeling activities (Zhang et al. 1998). Subunits of the NuRD complex including the core ATPase subunit Chd4 are highly expressed in the developing cerebellum (Yamada et al. 2014). Chd4 binds genome-wide to active or poised promoters and enhancers, but the NuRD complex harbors distinct enzymatic functions at the regulatory sites of different classes of genes. At developmentally downregulated genes, the NuRD complex triggers promoter decommissioning via removal of the histone modifications H3K9/14/27 ac and H3K4me3 and increases in H3K27me3 (Yamada et al. 2014). As granule neurons mature, NuRD-

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triggered promoter decommissioning leads to chronic silencing of a set of developmental genes expressed in granule neuron precursors and immature granule neurons including Nhlh1 and Elavl2. Knockout of Chd4 impairs granule neuron presynaptic differentiation and parallel fiber/Purkinje cell neurotransmission, whereas knockdown of Nhlh1 and Elavl2 in immature granule neurons triggers precocious presynaptic differentiation (Yamada et al. 2014). These results reveal important functions for the NuRD complex and developmental promoter decommissioning in releasing a break on synaptic connectivity between granule neurons and Purkinje cells. Besides chronic silencing of a key set of developmental genes, the NuRD complex also plays a critical role in dynamic regulation of transcription in granule neurons. Neuronal activity and growth factor signaling in neurons rapidly and transiently induce the expression of immediate early genes (IEGs), which in turn mediate neuronal plasticity (Bonni and Greenberg 1997; West and Greenberg 2011). Following the cessation of extracellular signaling, IEG expression is rapidly shut down but may be quickly reactivated by new stimuli. Remarkably, the NuRD complex is required for the shutdown of IEG expression following cessation of stimulation by depositing the histone variant H2A.z at gene promoters (Yang et al. 2016). H2A.z-containing nucleosomes may serve as a scaffold for the recruitment of additional epigenetic regulators (Dann et al. 2017; Hu et al. 2013), which may mediate shutoff of IEGs. Thus, the NuRD-H2A.z pathway represents an epigenetic mechanism that actively drives the shutoff of activity-dependent transcription in the cerebellum. Immature granule neurons require calcium signaling for dendrite growth (Gaudilliere et al. 2004; Okazawa et al. 2009). Granule neurons that have migrated to the internal granule layer undergo a ~2-day period of exuberant dendrite growth in vivo, followed by dendrite pruning (Huynh et al. 2011; Yang et al. 2016). Loss of Chd4 results in prolonged IEG expression after transient neuronal depolarization and a failure in dendrite pruning. Overexpression of the IEGs c-fos and nr4a1 phenocopy the Chd4 knockout-induced effects on dendrite patterning in vivo (Yang et al. 2016). Consistent with the abnormally exuberant dendrites, Chd4 knockout granule neurons exhibit hyperresponsivity to sensory stimuli in awake, locomoting mice (Yang et al. 2016). Together, these findings illuminate the dual epigenetic functions of the NuRD complex at stimulus-responsive genes and developmental genes to control afferent and efferent granule connectivity in the cerebellar cortex. The BAF complex is a large multi-subunit ATP-dependent chromatin remodeling complex that interestingly exhibits antagonistic functions with the NuRD complex. The BAF complex enhances chromatin accessibility at promoters or enhancers by reducing nucleosome density (Kwon et al. 1994; Morris et al. 2014). In addition, the core ATPase subunit Brg1 directly suppresses polycomb-mediated induction of the modification H3K27me3 at promoters and thereby opposes silencing of developmentally downregulated genes (Stanton et al. 2017). At early stages of development, the neural progenitor BAF (npBAF) complex is necessary for the proliferation of neural precursors. Accordingly, conditional knockout of BAF complex subunits in granule neuron precursors results in cerebellar hypoplasia and ataxia (Moreno et al. 2014). Several BAF complex subunits are then switched with other family members

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upon cell cycle exit in later development. The neuronal-specific subunits BAF53b and BAF45b/c replace the progenitor-enriched subunits BAF53a and BAF45a, respectively (Lessard et al. 2007; Wu et al. 2007). In granule neurons, the neuronspecific BAF (nBAF) complex containing BAF53b is necessary for dendrite growth (Wu et al. 2007). The BAF subunit calcium-responsive transactivator (CREST) interacts with the CREB-binding protein (CBP) to couple calcium signaling with gene activation and dendrite growth (Qiu and Ghosh 2008; Wu et al. 2007). Finally, conditional deletion of the BAF subunit Bcl7a specifically in postmitotic neurons impairs dendrite arborization in Purkinje cells (Wischhof et al. 2017). The opposing roles of BAF and NuRD complexes in activity-dependent and developmental gene activation and repression, as well as dendrite growth and pruning, reveal the critical functions of these enzymes at multiple stages of neuron maturation. Together, these findings highlight the important functions of ATP-dependent chromatin remodelers in controlling nucleosome structure in neuron progenitors and postmitotic neurons to ensure proper cerebellar development.

Histone Tail Modifiers In addition to ATP-dependent chromatin remodeling, epigenetic regulators stimulate posttranslational histone modifications on histone tails. Among these regulators, the multi-subunit polycomb repressive complex 2 (PRC2) has emerged as a major transcriptional repressive complex that developmentally decommissions gene promoters. PRC2 stimulates the modification H3K27me3 at the promoters and distal regulatory sites of genes to permanently silence gene expression in postmitotic neurons, including in the cerebellar primordium (Feng et al. 2016). PRC2 may be recruited to gene promoters following NuRD-mediated deacetylation of H3K27 (Reynolds et al. 2012). Knockout of Ezh2, a core methyltransferase subunit of PRC2, in cerebellar precursors results in reduced precursor proliferation and Purkinje cell number, but increased interneuron cell number (Feng et al. 2016). These mice also exhibit severe cerebellar hypoplasia. Knockout of both Ezh1 and Ezh2 specifically in Purkinje cells derepresses gene expression and impairs the survival of adult Purkinje cells, resulting in cerebellar degeneration (von Schimmelmann et al. 2016). The histone lysine demethylase enzymes Kdm6a and Kdm6b counteract polycomb activity by inducing the demethylation of H3K27. Kdm6b expression is significantly upregulated in differentiating granule neurons (Shi et al. 2014; Wijayatunge et al. 2017; Yang et al. 2016). In response to the extrinsic cues, sonic hedgehog (SHH) in the external granule layer and brain-derived neurotrophic factor (BDNF) in the internal granule layer, Kdm6b promotes the expression of granule neuron progenitor proliferation or postmitotic granule neuron terminal differentiation genes, respectively (Shi et al. 2014; Wijayatunge et al. 2017). Kdm6b activates gene expression by inducing H3K27me3 demethylation and recruiting histone H3K4 methyltransferases to gene promoters (Shi et al. 2014). Global knockout of Kdm6b impairs cerebellar growth, whereas paradoxically conditional knockout of

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both Kdm6a and Kdm6b specifically in granule neuron precursors fails to alter their proliferation (Shi et al. 2014; Wijayatunge et al. 2017). These results suggest that Kdm6b may function at earlier stages in brain development or via non-cell autonomous mechanisms to regulate the expansion of cerebellar granule neuron precursors. In addition, in view of the role of Kdm6b in activation of synaptic genes necessary for terminal granule neuron differentiation (Wijayatunge et al. 2017), it will be interesting to assess the physiological properties of cerebellar cortical circuits in conditional Kdm6b knockout mice. The histone demethylase enzyme Kdm5c induces H3K4me2/3 demethylation at promoters and enhancers of lowly expressed, but not highly expressed or promoter decommissioned genes (Iwase et al. 2007, 2016; Scandaglia et al. 2017). The lysine demethylase family members Kdm5a and Kdm5b may mediate demethylation of H3K4me3 at transcriptional start sites during promoter decommissioning (Yang et al. 2016). Lowly expressed genes that are regulated by Kdm5c include IEGs, which are inhibited under baseline, unstimulated conditions (Scandaglia et al. 2017). Kdm5c is necessary for dendrite growth in cerebellar granule neurons (Iwase et al. 2007). These findings highlight the distinct transcriptional repressive mechanisms deployed by different chromatin enzymes to regulate granule neuron differentiation. Histone deacetylases (HDACs) remove acetyl groups from lysine residues on histone tails to repress transcription, while histone acetyltransferases (HATs) add acetyl to histone tails to stimulate gene expression (Shahbazian and Grunstein 2007). The Class I HDACs, Hdac1/2/3, associate with several transcriptional repressive complexes including the NuRD complex, Sin3a, CoREST, and NCoR. HATs such as Gnc5 and Pcaf are part of SAGA-like transcriptional activator complexes. While the genome-wide chromatin activities of HDACs and HATs in the cerebellum are poorly understood, knockout of Hdac1/2, Hdac3, or Gnc5 in neural precursors results in cerebellar hypoplasia (Martinez-Cerdeno et al. 2012; Montgomery et al. 2009; Norwood et al. 2014). By contrast, knockout of the Class II HDAC, Hdac4, in neural precursors appears to have little effect on overall cerebellar development (Price et al. 2013). It will be important in future studies to determine the epigenetic mechanisms and biological roles of distinct HDAC and HAT complexes in cerebellar precursors and postmitotic neurons during development.

DNA Methylation Epigenetic regulators may also directly modify DNA by methylating or demethylating cytosine base pairs. In proliferating cells, 5hmC, 5fC, and 5caC are intermediate, unstable products generated during cytosine demethylation (Wu and Zhang 2017). The epigenome of postmitotic neurons in the brain including Purkinje cells and granule neurons in the cerebellum uniquely harbor high, stable levels of 5hmCG (Kriaucionis and Heintz 2009; Szulwach et al. 2011). 5hmCG is enriched, whereas 5mCG is depleted along the gene bodies of active genes (Mellen et al. 2012). The expression of ten-eleven translocation (Tet) family of dioxygenases that convert 5mC to 5hmC is upregulated in the developing cerebellum (Zhu et al. 2016).

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Activation of Tet enzymes with vitamin C increases the levels of 5hmC across the body and particularly at exon start sites of axon guidance and ion channel genes in ESC-derived granule cells. The Tet enzymes Tet1/3 are necessary for the expression of these axon guidance and ion channel genes and promote dendrite arborization in developing granule neurons in ex vivo cerebellar slices. Two common forms of 5mC are 5mCG and 5mCA. Among all tissues, 5mCA levels are found highest in postmitotic neurons in the brain, while 5mCG is present ubiquitously (He and Ecker 2015). DNA methyltransferase 3A (Dnmt3a) deposits 5mCA preferentially at lowly transcribed genes in the developing brain, including at long brain-enriched genes that span hundreds to thousands of kilobases (Gabel et al. 2015; Guo et al. 2014; Stroud et al. 2017). Dnmt3a and 5mCA maintain the low expression of these genes for the lifetime of the animal (Gabel et al. 2015; Stroud et al. 2017). The brain-enriched methyl-CpG-binding protein 2 (MeCP2) binds to the transcriptionally repressive modifications 5mCG, 5mCA, and 5hmCA, but not the transcriptionally active mark 5hmCG in the cerebellum (Gabel et al. 2015; Mellen et al. 2012, 2017). MeCP2 may function as a transcriptional repressor or activator by interacting with HDACs or p300, respectively (Ben-Shachar et al. 2009; Chahrour et al. 2008; Ebert and Greenberg 2013). However, once bound to methylated DNA, MeCP2 appears to primarily downregulate gene expression (Gabel et al. 2015; Mellen et al. 2017). These results are consistent with the role of MeCP2 in suppressing global histone H3 acetylation in the cerebellum (Shahbazian et al. 2002). Blocking 5mCA methylation or increasing oxidation of 5mCG to 5hmCG along gene bodies releases MeCP2 from chromatin and increases gene expression (Gabel et al. 2015; Mellen et al. 2017). Despite the rich literature on the chromatin mechanisms of MeCP2 and Dnmt3a, their biological functions in the cerebellum are just beginning to be characterized. Mutant mice expressing a truncated MeCP2 gene at R308 have reduced Purkinje cell dendritic spine density (Kloth et al. 2015). These findings are consistent with dendrite arborization and spine number abnormalities in MeCP2 transgenic mice elsewhere in the brain (Jiang et al. 2013).

Perspectives on Epigenetic Regulators in the Mouse Cerebellum Several themes have emerged from studies of epigenetic regulators in cerebellar development. In cerebellar precursors, knockout of multiple chromatin enzymes disrupts proliferation and results in cerebellar hypoplasia. Future experiments should address whether these enzymes control distinct phases of the cell cycle and how epigenetic modifications are regulated in neural precursors. In addition, it will be interesting to determine whether different chromatin enzymes exert distinct effects on subpopulations of granule neuron precursors in a temporally or spatially defined manner. In postmitotic granule neurons, different chromatin enzymes control distinct phases of dendrite morphogenesis including dendrite growth and pruning. To support these transitions in postmitotic neuron development, the expression of chromatin enzymes is subject to regulation. For example, the core BAF subunit Brg1 that

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promotes dendrite growth is sharply downregulated after the first postnatal week, whereas the core NuRD subunit Chd4 that stimulates dendrite pruning persists in expression through the second postnatal week (Zhu et al. 2016). Hundreds of chromatin enzymes are highly expressed in the developing cerebellum (Yamada et al. 2014; Zhu et al. 2016), and much work still needs to be done to understand how these families of proteins collaborate to pattern the cerebellum. Finally, despite these first insights into epigenetic control of granule neuron differentiation, how chromatin enzymes regulate the epigenome of other cerebellar neurons including Purkinje cells, deep cerebellar nuclei neurons, molecular layer interneurons, unipolar brush cells, and others is virtually unknown. All of these cell types play critical and unique roles in cerebellar circuit function and organismal behavior. In the next section, we will discuss recent efforts to understand how epigenetic control of neuronal connectivity and cerebellar development influences mouse behavior.

Epigenetic Control of Cerebellar-Dependent Behavior A major goal in neuroscience has been to tease apart the cell type and circuit-specific mechanisms that drive behavior. The cerebellum plays diverse roles in motor coordination, motor learning, and cognitive functions. A key question is how do the molecular and cellular phenotypes observed in knockout mice affect behavior. Furthermore, are there differences in behavioral outcome with major cerebellar architecture deficits as compared to more specific deficits in cerebellar cortical connectivity? Knockout of epigenetic regulators in neural progenitors often results in brain malformation and severely impaired motor function or death. Neural progenitor knockouts of Hdac1/2 and Hdac3 have reduced brain size and are embryonically lethal, precluding assessment of motor function (Montgomery et al. 2009; Norwood et al. 2014). Induction of cerebellar hypoplasia by knockout of Chd7 or knockout of components of the BAF complex in granule neuron precursors causes deficits in motor coordination (Moreno et al. 2014; Whittaker et al. 2017). These findings are consistent with neurological symptoms observed with impaired cerebellar development in humans. Failure in dendrite arborization or progressive degeneration of Purkinje cells due to knockout of BAF, PRC2, or Hdac3 in postmitotic Purkinje cells also results in ataxia (Moreno et al. 2014; Norwood et al. 2014; von Schimmelmann et al. 2016). Paradoxically, conditional knockout of Snf2h in Purkinje cells leads to partial degeneration of these neurons in adult mice, but has no effects on motor coordination (Alvarez-Saavedra et al. 2014). It will be interesting to test if compensatory mechanisms that increase the activity of surviving Purkinje cells are at play in these knockout animals. In the absence of gross cerebellar malformation or Purkinje cell degeneration, changes in neuronal connectivity may specifically impair cerebellar-dependent motor learning. Conditional knockout (cKO) of Chd4 in mature postmitotic granule neurons disrupts granule neuron to Purkinje cell connectivity and synaptic neurotransmission (Yamada et al. 2014). Conditional Chd4 knockout mice have delayed

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and impaired associative learning in the eyeblink conditioning paradigm but have little or no changes in motor coordination or general locomotion behavior (Yang et al. 2016). Global, constitutive expression of mutant MeCP2 in mice reduces Purkinje cell dendritic spine density and also decreases the amplitude of the conditioned response in eyeblink conditioning, but not the probability of conditioned responses (Kloth et al. 2015). These studies suggest epigenetic regulators are important for the functions of cerebellar circuits that drive associative motor learning in mice. Recently, increasing attention has been placed on functions of the cerebellum beyond motor control, including in cognition and social behavior (Stoodley et al. 2017; Wagner et al. 2017). Widespread cortico-cerebellar loops via pontine and thalamic relays connect the cerebellum and forebrain. The Purkinje cell-specific Snf2h knockout mice discussed above have reduced interactions with novel mice but have normal exploratory behavior with inanimate objects (Alvarez-Saavedra et al. 2014). Furthermore, these mice have impaired contextual fear conditioning but normal cued fear. These and other mouse genetic studies raise the intriguing hypothesis that the cerebellum may play important roles in social interaction and that perturbations of Purkinje cell activity may result in autistic phenotypes (Stoodley et al. 2017; Tsai et al. 2012). Furthermore, from gross cerebellar malformation to fine-scale changes in cerebellar circuits, epigenetic regulation has proven to be a key step in the development and behavior of mice. We next turn to the development of the human cerebellum to illustrate the devastating impact of misregulation of chromatin enzymes in human neuropathology.

Epigenetics in Human Disease Just as in the mouse brain, epigenetic regulators play fundamental roles in orchestrating human brain development. Mutations in epigenetic regulators cause a wide range of neurological disorders, ranging from intellectual disability to autism spectrum disorders to epilepsy (RK et al. 2017; Ronan et al. 2013; Weiss et al. 2016). Neuroimaging of affected individuals has often revealed cerebellar dysplasia, hypoplasia, or agenesis in these disorders (Stevenson et al. 2013). We will highlight some of the key epigenetic regulators that are genetically linked to neurodevelopmental disease and cerebellar malformation. Mutations in the ATP-dependent chromatin remodeler Chd7 cause CHARGE syndrome, manifesting with coloboma of the eye, heart defects, atresia of the choanae, retarded growth and development, genital anomalies and ear malformations or deafness. A key clinical feature observed in over 50% of CHARGE patients with mutations in Chd7 is cerebellar malformation, consistent with mouse genetic studies (Feng et al. 2017; Whittaker et al. 2017; Yu et al. 2013). The cerebellar vermis is often underdeveloped and mispositioned, resulting in an enlarged fourth ventricle. In addition, 3 out of 20 patients have broad or ataxic gait, consistent with gross cerebellar dysfunction.

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In addition to Chd7, other ATP-dependent chromatin remodelers are commonly associated with human neurodevelopmental disorders. Mutations in Chd2 cause myoclonic encephalopathy together with intellectual disability, speech delay, and developmental regression that correlates with the severity of seizures (Thomas et al. 2015). Progressive cerebellar atrophy is observed in several severe cases, presenting with ataxia. The neurodevelopmental disorder Coffin-Siris syndrome (CSS) is caused by mutations in components of the BAF ATP-dependent chromatin remodeling complex (Tsurusaki et al. 2014). The primary clinical feature in CSS patients is intellectual disability, and a subset of affected individuals have seizures, microcephaly, and cerebellar hypoplasia. These findings reveal that neurodevelopmental syndromes linked to distinct chromatin enzymes often have shared neurological phenotypes. Besides ATP-dependent chromatin enzymes, other epigenetic regulators are also necessary for normal human brain development. Rett syndrome is an X-linked disorder that affects primarily females and is due to mutations in the DNA methylation binding protein MeCP2. Males carrying the mutation only have one copy of the X-chromosome and rarely survive birth. Girls born with Rett syndrome initially exhibit normal behavior but regress in development starting 6 months of age. The anterior cerebellar lobules I–IV display mild hypoplasia at younger ages, and more severe cerebellar degeneration is observed in adults (Zanni and Bertini 2011). Common phenotypes are impaired motor coordination, communication, and cognitive function that persist for the lifetime of the individual. Mutations in the lysine demethylase Kdm5c cause an X-linked intellectual disability syndrome. Males are more severely affected, but females may present with milder phenotypes. Some male patients have seizures and cerebellar atrophy starting at 4 years of age (Fujita et al. 2016). Additional mutations in epigenetic regulators have been reported in neurodevelopmental diseases. For example, missense mutations in Chd4 and Gatad2b, subunits of the NuRD ATP-dependent chromatin remodeling complex, result in general developmental delay and intellectual disability (Weiss et al. 2016). Mutations in methyl-CpG-binding domain 3 (MBD3), another subunit of the NuRD complex, are found in autism spectrum disorders (Cukier et al. 2010). The ATP-dependent chromatin remodeling enzymes Chd8 and nBAF are also implicated in autism spectrum disorders (Mahfouz et al. 2015; Yuen et al. 2017). These findings demonstrate that epigenetic regulators are powerful drivers of brain development and function in humans.

Conclusions and Future Directions In the past decade, great strides have been made in uncovering the molecular mechanisms and biological roles of epigenetics in the development of the brain. Recent advances in next-generation sequencing have revealed that epigenetic regulators are often mutated in human neurodevelopmental diseases. Clinical diagnosis of human patients and characterization of mouse models have confirmed the pivotal

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role of these enzymes in brain development and function. Understanding the in vivo functions of epigenetic regulators is necessary for improved understanding of debilitating neurodevelopmental brain disorders. Emerging new technologies in the fields of functional genomics and systems neuroscience will be required toward this goal. Several exciting areas of epigenetics research should be anticipated in the upcoming years. Current methods require measuring bulk changes in the epigenome of millions of cells and with poor temporal resolution, i.e., on the tens of minutes to hours timescale. However, the ability to isolate and profile the epigenome of low abundance cell types is critical in the cerebellum where the functions of epigenetic regulators in rare cell types including unipolar brush cells and Lugaro cells and in inhibitory interneurons are unknown. Significant advances have been made in singlecell transcriptome profiling, and similar technological breakthroughs in single to hundred cell epigenomic profiling are anticipated. Another approach is to track the dynamics of epigenetic regulation in single cells using imaging. For example, in transcriptomics, by tagging mRNAwith fluorescent tags, the real-time expression and degradation of single mRNA molecules can be visualized. Similarly, efforts are underway to detect changes in histone modifications and nucleosomes live in single cells (Stasevich et al. 2014). These tools will greatly aid our understanding of how the epigenome is regulated in cell type-specific neural circuits with temporal precision. In the developing and adult cerebellum in vivo, neurons encounter a diverse set of extrinsic signals that encode for changes in the local cellular environment or animal behavioral state. A newly born granule neuron that migrates from the external granule layer to internal granule is exposed to at least dozens of secreted factors that act as a global positioning system (Komuro and Rakic 1992). Epigenetic regulators in the nucleus integrate these extrinsic signals to drive long-lasting changes in neuronal identity, i.e., from a migratory to post-migratory state. However, most in vivo signals and their downstream pathways remain poorly understood. Single-cell approaches together with laser capture microdissection, which retains spatial information, may permit discovery of how the local environment in the cerebellum controls specific epigenetic changes during neuronal differentiation and plasticity. By also applying pharmacological tools, we can elucidate the transmembrane receptors that couple extrinsic signals to epigenetic regulation in vivo. In addition to epigenetic mechanisms including histone modification, chromatin remodeling, and DNA methylation, recent attention has focused on a new level of epigenetic programming, the regulation of three-dimensional genome architecture. Recent studies primarily using cell culture systems have uncovered novel mechanisms that create or suppress long-distance interchromosomal and intrachromosomal interactions to control gene expression. One such mechanism involves CTCF insulator proteins, which restrict the interactions of distal enhancers to specific gene promoters. However, how epigenetic regulators control genome architecture in the brain in vivo remains an open mystery. Understanding the relationship between gene expression and genome architecture and how these are dynamically controlled in the developing and adult cerebellum might reshape the way we think about gene regulation in neuroscience.

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Finally, an essential but often underappreciated problem that must be solved is how we bridge the gap between genes and behavior. After identifying mutations in genes encoding epigenetic regulators as causative for human brain disorders, how can we understand the roles of these enzymes in learning and memory, motor functions, and social behaviors, all of which are at risk with disease? The answer to this question may lie in a suite of new systems neuroscience tools that allow characterization of functions of each and every genetically accessible neural circuit in behavior. An example is using genetically encoded calcium indicators to monitor neural circuit activity of cerebellar neurons in behaving control and mutant mice. Subsequently, the complementary approaches of optogenetics and chemogenetics may shed light on requirements for cerebellar circuits for the expression of a behavior or the acquisition of a learned response. This line of new research will reveal how a dysregulated epigenome in specific cell types of the cerebellum may lead to the pathogenesis of motor and cognitive disorders. In summary, current research on the cerebellum has revealed the fundamental principle that epigenetic regulators control every facet of neuronal differentiation in the early postnatal brain. Rapid advances in functional genomics and neuroscience fueled by state-of-the-art molecular and genetic tools promise to further clarify the functions of neuroepigenetic programming of the cerebellum in health and disease.

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John Oberdick

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Transcription Factor Targetomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . En2 (Engrailed-2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atoh1 (Math1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rora (RORα) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physiological and Metabolic Control of Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cell Type Specific Genes and Gene Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The purpose of this chapter is to provide a brief overview of the major gene networks that control cerebellum development. To simplify this task, all developmental control genes relevant to the cerebellum have been grouped into four categories based on 13 spontaneous mouse mutations with cerebellar developmental defects and for which the aberrant gene has been identified. These categories include genetic switch genes and genes for morphogenesis, physiology, and metabolism. Three distinct gene targetome studies are discussed in order to introduce some signature networks of major importance to cerebellum development based on the genetic switches En2, Atoh1 (Math1), and Rora (RORα). Similarly, array approaches have begun to reveal gene expression changes due to mutations in physiology and metabolism genes, such as Kcnj6 (Girk2) and Agtpbp1 (Nna1), respectively. These studies are revealing the interplay between transcription, morphogenetic factors, physiology, and metabolism during development. Lastly, genomics and informatics approaches are uncovering new J. Oberdick (*) Department of Neuroscience and Center for Molecular Neurobiology, The Ohio State University, Columbus, OH, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_8

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markers of all cerebellar cell types at all stages that will be useful in the future for further clarifying the complex and often reciprocal nature of developmental mechanisms in the nervous system. Keywords

Purkinje Cell · Granule Cell · Cerebellum Development · Proneural Gene · Genetic Switch

Introduction The cerebellum has been a central source of information concerning the identity and function of key gene networks controlling brain development and function. The explosion of knowledge about such networks began with the visionary analysis and cataloging of spontaneous cerebellar mouse mutants starting in the 1950s and 1960s, surged with the availability of positional cloning and reverse genetics approaches available in the mouse in the late 1980s and 1990s, and now continues with the development of high-throughput methods for the identification of hundreds to thousands of gene expression changes resulting from single gene lesions as well as the creation of public data repositories that can be mined for structure, sequence, and expression information for all genes. The purpose of this chapter is to summarize some key cerebellar gene networks that are known to date. It is not meant to be all-inclusive, but will serve as a foundation to expand on in future editions. Consideration of the spontaneous cerebellar mutants for which the target gene or molecular mechanism has been identified is a natural starting point and organizational guide for this chapter. The kinds of genes that have been identified in this group represent most of the major developmentally important classes into which all other key cerebellar development genes can be fit. In some of these spontaneous mutants, the type of identified gene is consistent with the predicted mechanism of mutant gene action that was hypothesized early on, based solely on observation of morphological features of mutant cerebellar cells, and in others gene function is less obviously related to these features. For example, reelin is an extracellular matrix protein with a function in neuronal migration that is consistent with the disrupted neuronal lamination that was observed throughout the brain, including cerebellum, in the classic studies of reeler (rl) mutants (Caviness and Rakic 1978; Falconer 1951; Miao et al. 1994). Similarly, before the gene was identified the cellular phenotype in the weaver (wv) mutant was mainly described as a defect of the inward migration of postmitotic granule cells (e.g., (Rakic and Sidman 1973)) leading most investigators into the early 1990s to hypothesize a defect in neuron-glial guidance or in other neuron-glial interactions affecting granule cell differentiation. Instead, rather than a cell surface ligand or receptor involved directly in cell–cell recognition, the target gene of wv is now known to encode a K+ channel, Kcnj6 (Girk2) (Patil et al. 1995; Rossi et al. 1998). The latter example illustrates the intimate interplay between electrophysiological and developmental mechanisms, due no doubt to complicated

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gene networks incorporating receptors, channels, second messengers, transcription factors, guidance molecules, cytoskeletal and synaptic structural proteins, and cell death factors.

Transcription Factor Targetomes During development of the nervous system, transcription factors act as switches that progressively restrict the fate of neuronal and glial precursors. Each switch has its own unique set of targets, and these targets can be identified en masse using overexpression or inactivation of the factor in vivo combined with gene array or deep sequencing methods that can reveal downstream expression changes resulting from the genetic perturbation. Direct targets can be validated using a number of chromatin analysis tools. The signature targets that are revealed can indicate a developmental program unique for that factor and for the type of cell or tissue and the stage of development under consideration. Three cerebellar targetomes will be considered: Engrailed-2 (En2), Atoh1 (Math1), and Rora (RORα) representing distinct stages and types of cerebellar cells. For the purposes of this chapter, the genes that will be discussed are divided into 4 main categories based on those defined by 13 classic spontaneous cerebellar mutants for which the target gene is now known (those in red font in Fig. 1). This is partly for simplicity’s sake, but also because it is likely that this categorization represents a fundamental hierarchical relationship that applies to all developing neuronal systems.

En2 (Engrailed-2) Analysis of mutations of the Drosophila segment-polarity gene, Engrailed, were originally described as showing defects in cell affinities that normally proscribe En-expressing cell clones to the posterior compartment of each segment (Lawrence and Struhl 1982). Inactivation of the En1 gene in mice results in a segment-like phenotype resulting in the deletion of the caudal midbrain and cerebellum, and fate mapping studies of the cerebellum indicate that all cerebellar cell types are specified by early expression of the En genes from about E8-E11 (Sgaier et al. 2005; Wurst et al. 1994). Expression of En1 and En2 is dependent on expression of the mid/hindbrain organizer, Fgf8, which emanates from a tight band at the isthmus (Liu et al. 1999). The formation and positioning of this so-called mid/hindbrain junction region is dependent on the mutually exclusive expression of the homeodomain proteins Otx1,2 and Gbx2, and occurs at the boundary between the expression domains of these two factors ((Broccoli et al. 1999); for details see ▶ Chap. 1, “Specification of the Cerebellar Territory” in this volume; see also Fig. 1). Analysis of Wnt-1 mutants (the first knockout mouse ever reported (McMahon and Bradley 1990; Thomas and Capecchi 1990)) which roughly phenocopy En1 mutants, and the observation that En1 expression can rescue the Wnt-1 phenotype indicates that Wnt-1 maintains expression of En1 and that this is a highly conserved carry over

Fig. 1 Schematic diagram illustrating the major gene networks involved in cerebellum development. Genes that are the known targets of spontaneous mutations affecting cerebellar development in mice are indicated in red font. These genes fall into four distinct functional categories: Transcription/Genetic switches, Physiology, Morphogenesis, and Metabolism. Genetic switch genes are indicated in light blue fill. Morphogens are indicated in orange fill. Genes specifically affecting cell cycle/proliferation are indicated in yellow. Grey lines indicate a relationship between connected genes, not necessarily direct. Relevant citations are indicated numerically in parentheses, and are listed below. Blue lines indicate a prominent Ca2+ gene network through the Rora genetic switch. ([1] Broccoli et al. 1999; [2] Liu et al. 1999; [3] Danielian and McMahon 1996; [4] Chung et al. 2009; [5] Wurst et al. 1994; [6] Sgaier et al. 2005; [7] Holst et al. 2008; [8] Wilson et al. 2011; [9] Schulz et al. 2010; [10] Millonig et al. 2000; [11] Ben-Arie et al. 1997; [12] Machold and Fishell 2005; [13] Flora et al. 2009;

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from Drosophila En-Wg signaling (Danielian and McMahon 1996). Wnt-1 is the gene target of the spontaneous cerebellar mutant swaying (sw) ((Thomas et al. 1991); see Fig. 1). Furthermore, another homeodomain protein called Lmx1a, which is the target gene of the spontaneous mouse mutant Dreher (dr), is required for the formation of roof plate and specification of dorsal neuronal fates including granule cells (Millonig et al. 2000). At least in the midbrain Lmx1a and Wnt-1 form an autoregulatory loop required for this dorsalization function ((Chung et al. 2009); see Fig. 1). Evidence for a prominent adhesive and/or guidance function of En genes comes from studies on midbrain axonal pathfinding in the mouse visual system in which perturbation of En expression resulted in axonal guidance defects (Friedman and O’Leary 1996; Retaux et al. 1996). Likewise, expression of En genes in the cerebellum during the late embryonic period is found in a pattern of sagittally oriented bands of cells that are in some cases similar to and in others complementary to the expression of known morphogenic or guidance factors (Millen et al. 1995; Wilson et al. 2011). These bands of cells are thought to reflect an important organizational framework that directs the zonal arrangements of the two major cerebellar afferent systems, mossy and climbing fibers. In fact, using ectopic overexpression of En2 (L7-En2) in cerebellar Purkinje cells during the late embryonic/ early postnatal period it was shown that mossy fiber organization is disrupted (Baader et al. 1999), and this has also been confirmed using conditional inactivation of the En genes (Sillitoe et al. 2010). Using the L7-En2 transgenic mouse a search for target genes of En2 during the neonatal period using an array approach has revealed a major target gene cluster encoding protein and vesicle trafficking proteins, and also defects in the morphological organization of Golgi stacks and ER in the mutant were observed (Holst et al. 2008). In addition, the axonal guidance factor EphA4 has emerged as a likely gene target of En2 from this and other studies, being complementary in expression pattern to En2 in wild-types and downregulated in L7-En2 mutants (Table 2 and Suppl. Figure 1 in Holst et al. (2008); Wilson et al. (2011); see Fig. 1). Likewise, the anxiogenic and metabolic peptide, Cck, is strongly downregulated in L7-En2 mutants ((Holst et al. 2008); see Fig. 1), which may be relevant to the proposed role of the En2 gene in autism (Gharani et al. 2004). In contrast, the gene NF2 is strongly upregulated in the L7-En2 mutants, and the encoded mitogenic protein known as Merlin is thought to be inhibitory of dendrite growth and development ((Holst et al. 2008; Schulz et al. 2010); Fig. 1). All of these expression changes observed on gene arrays have been confirmed by protein and mRNA expression analysis, but so far it is not known if these are direct or indirect targets ä Fig. 1 (continued) [14] Klisch et al. 2011; [15] Wechsler-Reya and Scott 1999; [16] Thomas et al. 1991; [17] Hamilton et al. 1996; [18] Gold et al. 2003; [19] Serinagaoglu et al. 2007; [20] Kinoshita-Kawada et al. 2004; [21] Kallen et al. 2002; [22] Vogel 2011; [23] Qiao et al. 1996; [24] Díaz et al. 2002; [25] Li et al. 2006; [26] Lu and Tsirka 2002; [27] Murtomäki et al. 1995; [28] Li et al. 2010; [29] Fernandez-Gonzalez et al. 2002; [30] Ford et al. 2008; [31] Klein et al. 2002; [32] Koibuchi 2008; [33] Pascual et al. 2007). Targetome and gene chip studies that are a major focus of this chapter are indicated in bold

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of En2 (for example, by ChIP). Nevertheless, it should be noted that although stages from birth to adulthood were analyzed no target genes involved in cerebellar electrophysiology were revealed in the gene array study (Holst et al. 2008). However, many genes in the category of lipid and protein metabolism were detected consistent with a protein and membrane trafficking function. The general conclusion from these studies is that En2 contributes to the early specification of all cerebellar neurons and is required for late embryonic morphogenesis by virtue of a mainly negative role exerted in bands of cells: inhibitory to the final migration, process growth, and differentiation phase of cerebellar development. These studies are all consistent with the very earliest analysis of the mutant phenotype in Drosophila indicating a primary function of En genes in cell place preference.

Atoh1 (Math1) The mammalian homologue of Drosophila atonal, Atoh1, is a proneural gene of the helix-loop-helix transcription factor class required for the generation of the glutamatergic cerebellar lineage including granule cells, unipolar brush cells and deep cerebellar nuclear projection neurons generated from the dorsal germinal anlage of the rostral rhombic lip ((Ben-Arie et al. 1996; Ben-Arie et al. 1997; Machold and Fishell 2005; reviewed in (Carletti and Rossi 2008)); see ▶ Chaps. 4, “Roof Plate in Cerebellar Neurogenesis” and ▶ 6, “Specification of Granule Cells and Purkinje Cells” in this volume). It has been previously shown that the mitogen Shh expressed by Purkinje cells induces the proliferation of overlying granule cell precursors and this is dependent on expression of the Shh receptor Patched (Ptc) and Ptc signaling via the protein Gli2 in granule cells, and aberrant Shh signaling plays a central role in the formation of medulloblastoma (Wechsler-Reya and Scott 1999). Inactivation of the Atoh1 gene in mice prevents medulloblastoma by disrupting Shh signaling in granule cells due to loss of Gli expression in granule cell progenitors ((Flora et al. 2009); see Fig. 1). In order to systematically identify the developmental genetic program governed by Atoh1 expression in the cerebellum a recent study was performed in which deep sequencing was used to identify genes differentially expressed in late embryonic wild-type versus Atoh1
/
cerebellum (Klisch et al. 2011). To increase the reliability of the data ChIP-Seq with antibodies to Atoh1 was also used to pull down target gene promoters, in addition to Histone-Seq to confirm the activation state of the target gene chromatin. Amongst the genes which were validated by ChIP-PCR a large number of cell proliferation genes were identified including Ptc and Gli2 involved in Shh signaling, Mycn (N-Myc), cell cycle genes like Gas1 and Ccnd2 (CyclinD2), and also many metabolism genes like Acadm (acyl-CoA dehydrogenase) and Cs (citrate synthase) and genes for nuclear-encoded mitochondrial proteins like Mrpl11 and 34 (see Fig. 1). These genes may be critically important to support the metabolic requirements associated with the high proliferation rate of granule cell progenitors. The third key cluster that was identified was genes involved in differentiation such as the bHLH transcription factor gene, NeuroD2, Pax6, and the NFkB activators, Akt2 and Grb2 (see Fig. 1). The fourth cluster was genes involved in

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migration, such as Sema6a and Unc5c (see Fig. 1). Inactivation of Sema6a in mice results in a cessation of granule cell migration, and Unc5c, which encodes a repulsive netrin receptor, is the target locus of the spontaneous Rostral Cerebellar Malformation (rcm) mutant with defects in anterior lobe granule cell migration including midbrain ectopia (Ackerman et al. 1997; Kerjan et al. 2005). Thus Atoh1 does not appear to be solely a factor for granule cell proliferation, which might be predicted based on its localization in the external germinal layer (EGL), but also for differentiation and migration. Conspicuously absent from the list of targets of the Atoh1 gene (and for that matter of En2) are genes related to glutamatergic transmission or to cerebellar physiology in general. Thus, Atoh1 must be at least one transcriptional switch removed from the final determination of the glutamatergic cell fate.

Rora (RORα) RORα was identified as the target of the spontaneous cerebellar mutation in mice known as staggerer (sg), and encodes an orphan member (i.e., no confirmed ligand) of the nuclear receptor superfamily of lipophilic hormone-binding transcription factors (Hamilton et al. 1996). This family includes the glucocorticoid and retinoic acid receptors, as well as the estrogen, androgen, and thyroid hormone receptors. In addition to their metabolic regulatory functions, some members of this family play important developmental roles including, for example, the thyroid hormone receptor in cerebellum development (Li et al. 2004; Nicholson and Altman 1972). In the staggerer mutants, the phenotype is very similar to Rora
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targeted mutants (Dussault et al. 1998; Steinmayr et al. 1998). One of the first observable defects is thinning of the EGL from the day of birth onward and abnormal Purkinje cell dendritogenesis with dendritic branchlets devoid of spines, followed by progressive loss of about 80% of the Purkinje cells and secondary loss of granule cells (Landis and Sidman 1978; Sidman et al. 1962; Sotelo and Changeux 1974). The mutant defect is intrinsic to Purkinje cells based on studies of mouse chimeras (Herrup and Mullen 1979). The Rora gene is expressed very abundantly in Purkinje cells, weakly in basket and stellate cells, even more weakly in dispersed cells within the deep nuclei ((Hamilton et al. 1996); see also Allen Brain Atlas), and is expressed outside the cerebellum in the suprachiasmatic nucleus and thalamus (Sato et al. 2004), and outside the brain in thymus and bone marrow ((Meyer et al. 2000); reviewed in (Jarvis et al. 2002)). It does not appear to be expressed in proliferating Purkinje cell precursors in the VZ and is first apparent around E12.5 in a region proximal to the VZ, presumably mainly postmitotic Purkinje cells ((Gold et al. 2003); see also Allen Brain Atlas). This is of relevance since, due to its preponderance in GABAergic Purkinje and basket/stellate cells, one possibility is that Rora may lie downstream of the Ptf1a HLH factor gene, which is expressed in the VZ and drives a lineage that gives rise to all GABAergic neurons in the cerebellum and is required to suppress the Math1/glutamatergic lineage in these cells ((Hoshino et al. 2005; Pascual et al. 2007); see Fig. 1 and ▶ Chaps. 2, “Proneural Genes and Cerebellar Neurogenesis

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in the Ventricular Zone and Upper Rhombic Lip,” ▶ 5, “Specification of Cerebellar and Precerebellar Neurons,” ▶ 6, “Specification of Granule Cells and Purkinje Cells,” and ▶ 11, “Specification and Development of GABAergic Interneurons” in this volume). If this is the case, and there is currently no evidence one way or the other, then RORα may participate only in the postmitotic phase of development of this lineage and is highly biased with respect to expression levels toward Purkinje cells. To better understand the genetic program directed by the Rora gene a microarray study was performed in neonatal cerebellum of Rora
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mutants to identify prospective target genes (Gold et al. 2003). This early stage was selected since it predates any observable degeneration of cerebellar cells. Target genes identified by array analysis were validated by Q-PCR and ISH to confirm differential expression, and by ChIP to confirm RORα interaction with target gene promoters in vivo. About 25% of the earliest expression differences that were observed were in proliferation markers in the EGL (where Rora is not expressed), such as Ccna2 (CyclinA2), Mycn, Pcna, etc., supporting a mitogenic influence of Purkinje cells that is lost in staggerer. Consistent with this, Shh, known to be expressed in Purkinje cells as described above, was identified as one of the target genes (Fig. 1). In addition, a cluster of Ca2+ and glutamate signaling genes with enriched or specific expression in Purkinje cells was identified including Calb1 (calbindin D28K), Itpr1 (Type 1 IP3 receptor), Slc1a6 (EAAT4), and Grm1 (mGluR1). In addition, the GoLoco protein, Pcp2(L7), was identified as a direct target (Gold et al. 2003; Serinagaoglu et al. 2007), which has been shown to play a role in Purkinje cell somatic spikelet waveform generation in vivo and to bidirectionally “tune” the P/Q-type Ca2+ channel in vitro by virtue of its modulatory effects on Gi/o inhibition of the channel ((Iscru et al. 2009; Kinoshita-Kawada et al. 2004); see Fig. 1). This illustrates the inclusion of signaling pathway genes in the network hierarchy depicted in Fig. 1, probably not just in the Physiology super-category but within and interconnecting other super-categories (for example, the NFκB activators Akt2 and Grb2 are transcriptional targets of Math1 (Klisch et al. 2011); see Fig. 1). Based on the nature of its target genes, the authors of this targetome study concluded that RORα controls reciprocal developmental signaling between Purkinje cells and granule cells: controlling both an outgoing signal that stimulates proliferation of granule cells and a collection of genes required for Purkinje cell responses to incoming glutamatergic input from granule cells and possibly climbing fibers. One developmental correlate of these physiological response genes may be the normal process of climbing fiber regression, which is dependent on mGluR1 during the first few postnatal weeks (Kano et al. 1997). It should be noted that cholesterol was fortuitously observed in the ligand binding domain of the crystal structure of RORα, and transcriptional activity of the protein was induced by cholesterol and derivatives (Kallen et al. 2002). Thus RORα function is likely linked to cholesterol metabolism. There is also some evidence of sexual dimorphism in the staggerer phenotype suggesting a possible relationship of the gene to sex steroids (Boukhtouche et al. 2006; Doulazmi et al. 1999).

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Physiological and Metabolic Control of Development The preceding discussion of RORα illustrates one example of a developmental switch that includes a prominent physiology gene cluster. Conversely, as indicated in Fig. 1, 4 of the 13 spontaneous cerebellar mouse mutants considered in this chapter have mutations in channel genes, and 3 others are in genes with metabolic functions. As the example of weaver illustrates, all of these channel mutants have clear-cut developmental phenotypes that precede cell death. The reciprocal nature of development mechanisms and electrophysiology comes as no surprise, the so-called developmental handshake whereby electrophysiologically relevant channels and receptors are developmentally regulated and they in turn regulate development (Spitzer 1991). A good example of this relationship is the effect of numerous physiology mutations on climbing fiber regression during the first several postnatal weeks in mice. For example, mGluR1 mutants show extranumerary innervation of Purkinje cells by climbing fibers (Kano et al. 1997). Purkinje cells in Lurcher mutants (dominant mutation in Grid2) have related phenotypes: multiple primary dendrites as opposed to one in wild-types, they retain somatic spines well beyond the normal time, they show an apparent recognition defect between climbing fibers and Purkinje cell dendrites such that the former synapse primarily on the Purkinje cell soma and do not reach into the dendrites, and basket cells fail to form their characteristic “pinceau” around the base of the Purkinje cell (Caddy and Biscoe 1979; Dumesnil-Bousez and Sotelo 1992; Heckroth et al. 1990). Physiologically, Lurcher Purkinje cells have a depolarized resting potential and unusually high membrane conductance suggesting the cause of death, thought to be apoptotic at least within a subset of Lc+/
Purkinje cells, may be glutamate excitotoxicity (Vogel 2011; Zuo et al. 1997). But precisely how these electrical changes lead to developmental effects prior to cell death is unknown. Voltage dependent Ca2+ channels (VDCC) and Ca2+ have been implicated in many developmental processes including neuronal migration, neuronal process outgrowth, and synaptogenesis. The spontaneous leaner (ln) mutation in the Cacna1a gene that encodes the pore forming subunit, α1a, of the P/Q-type Ca2+ channel results in early apoptosis of many granule cells starting around P10 and a relatively late and gradual loss of about 80% of Purkinje cells ((Herrup and Wilczynski 1982); see Fig. 1). This is consistent with the expression of the Cacna1a gene, which is most abundantly expressed in Purkinje cells but is also expressed in granule cells ((Fletcher et al. 1996); see also Allen Brain Atlas). In this and another less severe mutant of the Cacna1a gene, tottering (tg), there is an increased synaptic index of Purkinje cell spines with granule cell axon (parallel fiber) varicosities, and decreases in Purkinje cell soma size and molecular layer thickness were also reported (Isaacs and Abbott 1992; Rhyu et al. 1999). In addition, while the densities of Purkinje cell terminals in the deep nuclei are normal in tottering, the terminals are enlarged with an increased number of vacuoles, whorled bodies, and mitochondria (Hoebeek et al. 2008). These changes may be responsible for altered postsynaptic activities in the deep nuclei.

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Another VDCC subunit, γ2, encoded by the Cacng2 gene, is the target of the spontaneous waggler and stargazer mutations (see Fig. 1). Like tottering and leaner mutants, these animals are ataxic and have absence seizures. However, the morphology of the cerebellar cortex is grossly normal. Nevertheless, granule cells have electrophysiological defects that are mainly related to the role of the γ2 protein in AMPA-receptor localization (Chen et al. 2000). In spite of the normal morphology and migration of granule cells in these mutants, they show a selective loss of BDNF mRNA expression ((Qiao et al. 1996); see Fig. 1). It has also been shown that γ2 may play some role in cell–cell adhesion (Price et al. 2005), and therefore, further analysis of synapse morphology may be called for in the future. Stargazer mice do have defective cerebellum-dependent eyeblink conditioning which may be consistent with a synaptic defect (Qiao et al. 1998). One potential avenue to further unravel the interrelationships between physiology and development may be to examine gene expression changes in response to mutations in physiology genes. For example, the spontaneous mutant ducky, which lacks another P/Q-type channel subunit, α2δ-2 (Cacna2d2 gene), shows a marked increase in tyrosine hyroxylase gene expression and a decrease in tenascin-C expression (Donato et al. 2006). A more global array approach was used to identify gene expression changes due to loss of a functional Kcnj6 gene that encodes Girk2 channels (weaver) (Díaz et al. 2002). A central observation of this study is that a granule cell proliferation gene cluster, which is normally downregulated during development, is maintained at high levels in P21 weaver cerebellum with little effect on fate specification genes like Math1. In contrast, markers for late development of granule cells like α6 GABAA receptor are decreased in weaver. This is interpreted as evidence that a developmentally downstream gene, Kcnj6 (Girk2), can control selected clusters of upstream genes and that, for granule cells, proliferation genes are particularly sensitive to Girk2. Whether Girk2 inactivation prolongs the period of proliferation or rather leads to reentry of postmitotic cells into the cell cycle is unknown. One problem with this analysis is the difficulty in assigning direct versus indirect action of a gene like Kcnj6. This is not a problem with the array studies described above in which transcription factor target genes could be validated by genomic approaches such as ChIP. Nevertheless, transcription factor genes like Mad3 were included in the proliferation target gene cluster of Girk2, and this could allow for further refinement of a specific genetic pathway in the future that links Girk2 through Mad3 to transcriptional target genes ((Díaz et al. 2002); see Fig. 1). Some of the spontaneous channel mutants described above likely have metabolic deficiencies as evidenced by some of the earliest morphological defects that are observable. Purkinje cells in Lurcher, for example, show a rounded mitochondrial morphology, similar to that seen in nervous mutants, and in addition both mutants show a large increase in cerebellar tPA levels that may possibly be the causative genetic change in nervous (Caddy and Biscoe 1979; Li et al. 2006; Lu and Tsirka 2002). tPA is also substantially increased in weaver mutants and tPA may facilitate both granule cell migration and cerebellum-mediated motor learning (Murtomäki et al. 1995; Seeds et al. 1999, 2003). Similarly, the mutated gene that is the primary

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genetic target in Purkinje cell degeneration (pcd) mutants, Nna1, encodes a carboxypeptidase that appears to play a central role in neuronal process outgrowth and polarity as well as neuronal survival (Fernandez-Gonzalez et al. 2002; Li et al. 2010). Using microarray analysis of laser capture microdissected Purkinje and granule cell mRNA from P20 cerebellum the calreticulin 3 (Calr3), lysyl oxidase (Lox), and Bim genes were found to be upregulated more than 50-fold in Pcd relative to wild-types. Further experiments in this study showed that Lox upregulation in Purkinje cells reduces NFkB RelA expression, which subsequently reduces expression of Map2 and Map1B mRNAs with a resulting defect in dendritic outgrowth ((Li et al. 2010); see Fig. 1). Based on these studies, it is concluded that Nna1 participates in a pathway linking Lox propeptide and NFkB to dendritic growth as well as to cell degeneration through the proapoptotic gene Bim. As marked degeneration is already clearly observable in Pcd mutants at this fairly late age one wonders whether these changes are direct or indirect actions of the Nna1 gene mutation. In another microarray study performed using cerebellum tissue from about 1 week earlier in development Akt2 and Cdk5 were upregulated and PTEN downregulated in Pcd relative to wild types indicating key developmental nodes at this earlier stage that may be different than at later stages, and the pro-apoptotic gene Bad was also highly upregulated, which was confirmed in Purkinje cells by immunohistochemistry (Ford et al. 2008). Although not discussed in detail in this study, the mutant gene in tottering/leaner, Cacna1a, was the most downregulated in Pcd, more than fourfold. Therefore, in conjunction with the other study in which Calr3 gene was shown to be highly upregulated in Pcd, Ca2+ signaling genes may be a common cluster that links Pcd, Staggerer, and Tottering/Leaner gene mutants (Fig. 1). The spontaneous mouse mutation known as harlequin was found to be in a gene, Aifm1, encoding Apoptosis Inducing Factor (AIF; (Klein et al. 2002)). AIF is an NADH oxidase flavoprotein normally confined to the mitochondrion, but which shuttles to the nucleus in response to apoptotic signals. The harlequin mutation reduces but does not eliminate expression of AIF, and a complete null mutation of the Aifm1 gene results in embryonic lethal growth retardation with apparently normal patterning up till the time of embryo death (Brown et al. 2006). The harlequin mutant, however, is viable, and shows a late onset cerebellar ataxia amongst other problems (hair loss, optic tract dysfunction, cardiomyopathy), and granule cells from the mutant are susceptible to peroxide-mediated apoptotic cell death (Klein et al. 2002). Prior to death granule cells reenter the cell cycle as also observed in Lurcher (Grid2) and weaver (Kcnj6/Girk2) mutants. Therefore, the Aifm1 gene may be a critical linchpin linking aberrant physiology genes such as Kcnj6wv to the activation of a cell cycle gene cluster (Díaz et al. 2002) and ultimately to cell death as discussed above. It is also quite clear that metabolic regulation through the nuclear receptor superfamily is very important for cerebellum development as indicated by the importance of the Rora gene as discussed above. Furthermore, it is likely that some of the known effects of hypothyroidism on cerebellum development are due to dysregulation of neurotrophins as well as loss of synergistic interactions between

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Rora and thyroid hormone receptors ((Koibuchi 2008); see Fig. 1 and also ▶ Chap. 16, “Hormones and Cerebellar Development” in this volume).

Cell Type Specific Genes and Gene Networks In most of the foregoing discussion, the focus has been on categorizing the key genes that affect cerebellum development and their putative direct and indirect effector gene networks. Genetic switches encode and progressively restrict developmental potentials and in so doing activate as well as respond to extracellular signals and physiological and metabolic changes. Deciphering these complex mechanisms has largely been enabled through the simplicity of cerebellar structure on the one hand and the relatively recent explosion of a virtual treasure trove of markers of specific cell types at specific times on the other. The use of genetic fate mapping, for example, and BAC transgenic mice combined with a battery of immunohistochemical markers has made it possible to examine the dynamic movements in space and time of genetically and molecularly labeled cell types or subsets of cell types in the cerebellum (Machold and Fishell 2005; Morales and Hatten 2006; Sgaier et al. 2005). It is now known that while Purkinje cells and deep nuclear projection neurons finish their final mitosis prior to embryonic day 14, local interneurons are generated after this time well into the postnatal period. By E15 discrete cellular territories within the cerebellar primordium can be visualized by a variety of cell- and stageselective markers: Meis1 labels the presumptive deep cerebellar nuclei (but also subsequently continues to label granule neuron progenitors in the EGL), Lhx1 labels Purkinje cells at various stages of migration throughout the cortex, Math1 labels the formative external germinal layer (EGL) on the cerebellar surface that postnatally gives rise to granule cells, and Pax2 labels precursors of the GABAergic interneurons, Golgi and basket/stellate cells, deep within the presumptive cortex (Fig. 2; data from Allen Mouse Brain Atlas (Lein et al. 2007)). At this time and postnatally, superficially migrated Purkinje cells and EGL cells are ideally situated to mutually influence one another’s development, such as via the Rora, Shh, Ptc reciprocal signaling pathway described above, Shh being produced by Purkinje cells and granule cells expressing the Shh receptor, Ptc (Fig. 1). Discovery of the many markers of Purkinje cells and granule neurons was made by various strategies. For example, Pcp2(L7) was discovered in 1988 using a plusminus cDNA library screen using Purkinje cell deficient cerebellar tissue as a source of mRNA for the “minus” condition (Nordquist et al. 1988; Oberdick et al. 1988). The GABAA-α6 receptor (Gabra6 gene) was discovered as a specific granule neuron marker in expression studies of 13 GABAA receptor genes in the early 1990s (Laurie et al. 1992). Ptf1a was discovered as a major transcriptional switch governing the cerebellar GABAergic lineage by fortuitous integration of a transgene in mice (Hoshino et al. 2005). Math1 was initially discovered as a major granule cell and glutamatergic neuron lineage switch based on vertebrate homology screens of the Drosophila proneural gene, atonal (Ben-Arie et al. 1996). Recently, two approaches have been utilized to reveal new markers that may be useful for studying the development and physiology of unique subsets of the

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Fig. 2 Gene expression domains determined by in situ hybridization indicate distinct developmental fields giving rise to unique neuronal subpopulations at embryonic day 15.5 (a–d). By P28 unique markers distinguish GABAergic projection neurons (e, Purkinje cells) and spatially distinct subsets of GABAergic interneurons (f, basket/stellate cells and g, Golgi neurons) in the cerebellar cortex. All images are sagittal. Images in e–g are dorsal lobule VIII. All images were acquired from the Allen Mouse Brain Atlas and the Allen Developing Mouse Brain Atlas (http://mouse.brainmap.org and http://developingmouse.brain-map.org). Scale bar: a–d ¼ 250 μm; e–g ¼ 130 μm. EGL external germinal layer, DCN deep cerebellar nuclei, GCL granule cell layer, PC Purkinje cells, B/S basket/stellate interneurons, Go Golgi interneurons

GABAergic cerebellar interneurons and which should be broadly applicable to any cell types or brain regions. In the first, a translational profiling approach incorporating cell type-specific BAC transgenic expression of a translational probe was used to identify expressed Purkinje cell, granule neuron, basket/stellate, and Golgi cell marker genes (Doyle et al. 2008). This approach is fairly high-throughput and likely unbiased, but does have the downside that many of the identified genes are in the very low expression but high complexity pool of all expressed genes, and therefore may not be useful as cell type markers. Another approach took advantage of some public gene expression resources, such as GenePaint and Allen Brain Atlas. In this study, some 2500 genes with neuron- or cerebellar-enriched expression were screened by visual inspection of the cerebellar expression data and roughly 90 genes were identified that were expressed in Purkinje cells and/or GABAergic interneurons or subsets thereof. Four genes, including Accn1 that encodes the amiloride-sensitive cation channel 1, neuronal, a member of the DEG/EnaC family, were identified to be basket/stellate cell-specific within the cerebellar cortex ((Schilling and Oberdick 2009); see Fig. 2). Likewise, ten genes preferentially expressed in Golgi interneurons were found, including, as one example, Slc6a5, the sodium- and chloride-dependent glycine transporter 5 ((Schilling and Oberdick 2009); Fig. 2). Fortuitously during the course of this analysis a novel marker, Snca (α-Synuclein), was identified that is specific for presumed unipolar brush cells based on their lobule IX/X position. In addition, Trpc3, which has heretofore been described as Purkinje cell-specific, was found to be expressed in presumed UBCs. The following are some

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known genetic switches and fate markers of the main cell types in the cerebellum with each gene listed left to right in approximate order of temporal expression: • • • • •

Purkinje cells: Ptf1a, Lhx1, Lhx5, Rora, Rgs8, Pcp2, Calb1 Granule cells: Math1, Zic1, Zic3, Pax6, Meis1, Gabra6 Basket/Stellate: Ptf1a, Pax2, Lypd6, Accn1 Golgi cell: Ptf1a, Pax2, Cdh13, Grm2 (mGluR2), Grm5 (mGluR5), Slc6a5 Unipolar Brush Cells: Math1, Tbr2, Trpc3 (also in Purkinje cells), Snca, Gria2 (GluR2) (also Purkinje cells and basket/stellate cells), Grm1 (mGluR1)

Early markers of the deep cerebellar nuclei, without consideration of order of expression, include: • DCN: Meis1, Meis2, Irx3, Lhx2, Lhx9

Conclusions and Future Directions The foregoing discussion has illustrated three genetic switches and their distinct targetomes. These switches act at three different levels. En2 contributes to the specification of the entire cerebellar field and all cerebellar cell types beginning at the very early rhombomeric stage of hindbrain development. However, it also acts to delay and/or inhibit neuronal process outgrowth in the late embryonic period in a zonal pattern that somehow relates to guidance of cerebellar afferents. Atoh1 acts to selectively control the neurogenesis of granule neurons and other glutamatergic cerebellar neurons by activating a targetome that includes proliferation, metabolism, and migration gene clusters. Rora is a switch that controls physiological and metabolic functions of subsets of GABAergic neurons and defines a Ca2+-dependent reciprocal signaling gene network that mutually coordinates Purkinje cell and granule cell development. Further array studies have revealed that physiological mechanisms such as the Kcnj6 gene can affect an upstream proliferation gene cluster in granule cells and may help to further unravel the interrelationship between cell cycle and cell death genes. Similarly, array analysis of metabolic mutants with cerebellar defects has begun to reveal the importance of metabolic controls in development. Further growth in our knowledge of how development leads to function in the cerebellum, and how genetics and environment both contribute in the normal and disease states, will be fueled in the future by the continuing growth in informatics and genomics approaches which have enabled a boom in the availability of useful cell type-specific markers for each and every known cerebellar cell type.

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Part II Anatomy, Connections, and Neuroimaging of the Cerebellum

Vascular Supply and Territories of the Cerebellum

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Louis Caplan

Contents Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Posterior Inferior Cerebellar Arteries (PICAs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anterior Inferior Cerebellar Arteries (AICAs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Superior Cerebellar Arteries (SCAs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The cerebellar arteries are distributed rostrocaudally so that the posterior inferior cerebellar arteries (PICAs) arise from the intracranial vertebral artery, a component of the proximal intracranial posterior circulation territory; the anterior inferior cerebellar arteries (AICAs) originate from the basilar artery, a component of the middle intracranial posterior circulation territory; and the most rostral arteries, the Superior cerebellar arteries (SCAs), arise near the basilar artery bifurcation and are included in the distal intracranial territory. The PICAs and the SCAs, the two largest arterial pairs, have medial branches that supply mostly the vermian and paravermian portions of their respective regions of the cerebellum and lateral branches that supply the cerebellar hemispheres. Infarcts in the cerebellum are often limited to the territory of one of these branches. The AICAs supply only a small part of the anterior inferior cerebellum and the flocculus, but their major supply is to the lateral pontine tegmentum and the brachium pontis. The AICAs do not divide into medial and lateral major cerebellar branches but give off twigs to various structures.

L. Caplan (*) Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_17

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Keywords

Vertebral · Basilar · Dentate · Posterior inferior cerebellar artery · Anterior inferior cerebellar artery · Superior cerebellar artery

Overview Within the posterior circulation, my colleagues and I have characterized brain and vascular structures as involving the proximal, middle, and distal posterior circulation territories. (Caplan 1996; Caplan 2000; Caplan et al. 2004; Caplan et al. 2005; Chaves et al. 1994; Savitz and Caplan 2005) The proximal intracranial posterior circulation territory includes regions supplied by the intracranial vertebral arteries (ICVAs) – the medulla oblongata and the posterior inferior cerebellar artery (PICA)-supplied region of the cerebellum. The ICVAs join at the medullo-pontine junction to form the basilar artery (BA). The middle intracranial posterior circulation territory includes the portion of the brain supplied by the BA up to its superior cerebellar artery (SCA) branches – the pons and the anterior inferior cerebellar artery (AICA)-supplied portions of the cerebellum. The BA divides to form the two posterior cerebral arteries (PCAs) at the junction between the pons and the midbrain, just beyond the origins of the superior cerebellar arteries (SCAs). The distal intracranial posterior circulation territory includes all of the territory supplied by the rostral BA and its SCA, PCA, and their penetrating artery branches – midbrain, thalamus, SCA-supplied cerebellum, and PCA territories. This distribution is shown diagrammatically in Fig. 1. The three surfaces of the cerebellum are: tentorial (or superior) facing the tentorium cerebelli, petrosal facing towards the petrous bone, and suboccipital facing the suboccipital bone located between the lateral and sigmoid dural sinuses (Lister et al. 1982). The PICAs encircle the medulla and supply the suboccipital cerebellar surface; the AICAs course around the pons and supply the petrosal surface of the cerebellum, and the SCAs encircle the midbrain and supply the tentorial, superior surface of the cerebellum. (Lister et al. 1982) The arteries to the cerebellum are distributed rostrocaudally so that the posterior inferior cerebellar arteries (PICAs) arise from the ICVAs, the anterior inferior cerebellar arteries (AICAs) arise from the BA, and the most rostral arteries, the SCAs, arise near the BA bifurcation (Fig. 2). The PICAs and the SCAs, the two largest arterial pairs, have medial branches that supply mostly the vermian and paravermian portions of their respective regions of the cerebellum and lateral branches which supply the cerebellar hemispheres. Infarcts in the cerebellum are often limited to the territory of one of these branches, for example, medial PICA (mPICA), lateral SCA (lSCA), etc. These cerebellar branch territory infarcts correspond to functional regions such as the inferior vermis or superior lateral neocerebellum. The AICAs, in contrast, supply only a small part of the anterior inferior cerebellum and the flocculus, but their major supply is to the lateral pontine tegmentum and the brachium pontis. The AICAs do not divide into medial and lateral major cerebellar branches but give off twigs to various structures.

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Fig. 1 Schema of the proximal, middle, and distal intracranial territories of the vertebro-basilar arterial system. Drawn by Laurel Cook-Lowe, modeled after a figure in Duvernoy HM, Human Brainstem Vessels. Berlin. Springer-Verlag 1978;p41

Posterior Inferior Cerebellar Arteries (PICAs) The PICAs usually originate from the ICVAs about 2 cm below the origin of the basilar artery, and, on average, about 8.6 mm above the foramen magnum (Marinkovic et al. 1995). The site of origin, however, varies from 14 mm below the foramen magnum to 26 mm above the foramen magnum (Marinkovic et al. 1995). About 10% arise from the basilar artery (Amarenco and Hauw 1989) size varies; the diameters varied between .58 mm and 2.10 mm in one analysis (Amarenco and Hauw 1989). Some ICVAs end in PICA, and PICA can be absent in which case there usually is a large artery that arises from the proximal basilar artery that supplies both the PICA and AICA territories. Occasionally PICA is duplicated. After coursing laterally and downward to go around the lateral medulla (the lateral medullary segment), the PICAs make a cranially directed loop and ascend

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Fig. 2 Schematic diagram of the cerebellar arteries (Caplan 1996). Superior cerebellar artery (SCA); 2) medial branch of the SCA; 3) lateral branch of the SCA; 4) Anterior inferior cerebellar artery (AICA); 5) Posterior inferior cerebellar artery (PICA); 6) medial branch of PICA; 7) lateral branch of PICA; 8) basilar artery; 9) vertebral artery. From Amarenco P. The spectrum of Cerebellar infarctions. Neurology 1991;41:973–979

between the dorsal portion of the medulla and the caudal part of the cerebellar tonsil on that side (the tonsillo-medullary segment). (Lister et al. 1982; Marinkovic et al. 1995) They then make a second loop above the cranial portion of the tonsil and descend along the inferior vermis coursing between the inferior medullary velum and the rostral portion of the tonsil (the telovelotonsillar segment). Finally the artery becomes superficial and supplies branches to the tonsil, medulla, choroid plexus, and cerebellar cortex. Medial and lateral branches (mPICA and lPICA) arise from the main trunks (Fig. 3) at variable locations between the two PICA loops. mPICA supplies the inferior vermis including the nodulus, uvula, pyramis, tuber, and sometimes the declive and the medial portions of the semilunar lobule, gracile lobule, and the tonsil (Chaves et al. 1994; Amarenco and Hauw 1989; Amarenco et al. 1993; Amarenco 1991; Gilman et al. 1981; Duvernoy 1978; Amarenco et al. 1989). mPICA often sends a supply to the dorsal medulla. lPICA supplies the inferior two thirds of the biventer, most of the inferior portion of the semilunar and the gracile lobules, and the anterolateral portion of the tonsil (Chaves et al. 1994; Amarenco and Hauw 1989; Amarenco et al. 1993; Amarenco 1991; Gilman et al. 1981). Figs. 4, 5, and 6 show diagrammatically the supply territories of PICA, mPICA, and lPICA. The PICAs sometimes supply the deep cerebellar structures including the fastigial nuclei and may also supply the ventral portion of the dentate nuclei (Amarenco and Hauw 1989). Postmortem dye injections into the SCA and PICA show SCA irrigation of dorsal dentate and PICA irrigation of ventral dentate (Schmahmann 2000).

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Fig. 3 Sketch showing course and branching of the Posterior inferior cerebellar artery (PICA) (Caplan 1996). PICA; 2) lateral branch of PICA; 3) medial branch of PICA; 4) cerebellar hemisphere; 5) cerebellar vermis; 6) cerebellar tonsil. Reproduced with permission from Amarenco P, Hauw J-J, Caplan LR. Cerebellar infarctions in Handbook of Cerebellar disease, New York, Marcel Dekker, 1993;251–290

Although many equate the Wallenberg syndrome with an occlusion of PICA causing infarction in the lateral medulla, PICA does not supply the lateral medullary tegmentum. This region is supplied by a group of parallel small arteries that originate directly from the intracranial vertebral artery and pass through the lateral medullary fossa to supply the lateral medulla. (Figure 7) Duvernoy 1978. The medial branch of PICA supplies a small area in the dorsal medulla that includes vestibular nuclei and the dorsal motor nucleus of the vagus. Figure 8 is a sagittal section MRI showing a PICA infarct. Figure 9 shows a brain specimen with a medial PICA territory infarct.

Anterior Inferior Cerebellar Arteries (AICAs) The AICAs are nearly constant arteries but their origins, sizes, and supply zones vary greatly. They have the smallest territory of supply of any of the cerebellar arteries. The AICAs usually arise about 1 cm above the vertebrobasilar artery junction (Fig. 10), but they can sometimes arise directly from the ICVA, or from a common trunk with PICA. The internal auditory arteries are usually branches of the AICAs but in some individuals they arise directly from the basilar artery. Asymetry and reciprocal size relationship of AICA and PICA are common. In one study, the diameters of AICA ranged from 0.38 mm to 1.8 mm (mean 1.1 mm). (Marinkovic et al. 1995) After arising from the basilar artery, the AICAs travel towards the

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Fig. 4 The supply zone of PICA. Reproduced with permission from Amarenco P. The spectrum of Cerebellar infarctions. Neurology 1991;41:973–979

cerebellopontine angle, passing below the Vth nerve, crossing the VIth nerve, and meeting the VIIth and VIIIth nerves at the cerebellopontine angle. (Marinkovic et al. 1995; Amarenco and Hauw 1989; Amarenco et al. 1993; Amarenco 1991; Gilman et al. 1981; Duvernoy 1978; Amarenco and Hauw 1990a; Perneczky et al. 1981) After crossing the VIIIth nerve, the AICAs give rise to the internal auditory arteries and then divide into two branches. One branch courses laterally and inferiorly to supply the anterior inferior portion of the cerebellum on the petrosal surface. The other branch loops around the bundle made by the VIIth and VIIIth nerves and supplies the flocculus, brachium pontis, and the lateral part of the pons (Marinkovic et al. 1995; Amarenco and Hauw 1989; Amarenco et al. 1993; Amarenco 1991; Amarenco and Hauw 1990a; Perneczky et al. 1981). The internal auditory arteries supply the facial and vestibulocochlear nerves as well as the structures of the inner ear. Fig. 11 is a schematic drawing of the AICA and its supply (Perneczky et al. 1981). Fig. 12 shows the brainstem and cerebellar distribution of the AICA supply territory. Figure 13 is a necropsy specimen showing an AICA territory infarct at the level of the pons.

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Fig. 5 The supply zone of the medial branch of PICA. Reproduced with permission from Amarenco P. The spectrum of Cerebellar infarctions. Neurology 1991;41:973–979

Fig. 6 The supply zone of the lateral branch of PICA. Reproduced with permission from Amarenco P. The spectrum of Cerebellar infarctions. Neurology 1991;41:973–979

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Fig. 7 Right lateral medullary fossa (Caplan 1996). Vertebral artery; 2) posterior inferior cerebellar artery (PICA); [3) Accessory Nerve WHAT IS 3?]; 4) lateral medullary fossa; 5) vagus nerve; 6) IV ventricle choroids plexus; 7) glossopharyngeal nerve; 8) vestibulo-cochlear nerve; 9) facial nerve; 10) lateral pontine vein; 11) pons; 12) abducens nerve; 13) olive; A, A’. rami arising from PICA; B. rami arising from the vertebral artery to supply the lateral medulla; C. rami arising from the basilar artery; C0 and D. rami arising from AICA. From Duvernoy HM, Human Brainstem Vessels. Berlin. Springer-Verlag 1978; p 70

Superior Cerebellar Arteries (SCAs) The SCAs arise as the last pair of branches from the basilar artery just before the basilar artery bifurcates into the paired PCAs (Fig. 14). The third cranial nerves run between the SCAs and the PCAs near the posterior communicating arteries. In about 15% of patients, there are bifid SCAs. In one series, the diameters ranged from 0.7 mm to 1.93 mm (mean 1.1 mm). (Marinkovic et al. 1995) The SCA encircles the brainstem close to or within the ponto-mesencephalic sulcus, just below the third nerve and just above the trigeminal nerve. While coursing around the midbrain, the SCAs give off branches that supply the brainstem including the superior portion of the lateral pontine tegmentum and the pontine and mesencephalic tectum. The SCAs

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Fig. 8 MRI sagittal T2-weighted scan showing a PICA territory infarct. From Caplan LR. Posterior Circulation Disease. Clinical findings, diagnosis, and management. Boston, Blackwell Science, 1996

Fig. 9 Necropsy specimen showing an infarct in the territory of the medial branch of the posterior inferior cerebellar artery. From Amarenco P, Hauw J-J, Henin D et al. Les infarctus du territoire de l’artère cérébelleuse postéro-inférieure; étude clinico-pathologique de 28 cas. Rev. Neurol 1989;145:277–286 with permission

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Fig. 10 Base of the brain at necropsy showing the origin of the anterior inferior cerebellar arteries

Fig. 11 Blood supply of the caudolateral pons from the Anterior Inferior Cerebellar Artery (AICA). The shaded area to the right is the supply of a lateral branch of AICA. A-basilar artery; B-medial pontine segment of AICA; C-loop segment of AICA around flocculus; D-paramedian basilar artery branches; E-brainstem branches of AICA; F-flocculus; G-dentate nucleus; H- IV ventricle; i.-brachium pontis; J-medial lemniscus; K- lateral spinothalamic tract; L- motor nucleus of V; M- spinal tract and nucleus of V; N-main sensory nucleus of V; O- Vll and Vlll cranial nerves; P- internal acoustic meatus. From Perneczky A, Perneczky G, Tschabitscher M, Samec P. The relation between the caudolateral pontine syndrome and the anterior inferior cerebellar artery. Acta Neurochirurgica 1981;58:245–257 with permission

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Fig. 12 Diagrammatic depiction of the supply zones of the anterior inferior cerebellar arteries. A shows the pontine territory. 1 ¼ flocculus, 2 ¼ brachium pontis, 3 ¼ restiform body, 4 ¼ brachium conjunctivum, 5 ¼ dentate nucleus, 6 ¼ vestibular nuclei, 7 ¼ spinothalamic tract, 8 ¼ central tegmental tract, 9 ¼ medial lemniscus, 10 ¼ cerebellar nodulus. B shows the cerebellar supply on a lateral view of the cerebellum and C shows the supply on cut sections of the cerebellum and brainstem. The supply zones are shaded. Reproduced with permission from Amarenco P, Hauw J-J, Caplan LR. Cerebellar infarctions in Handbook of Cerebellar disease, New York, Marcel Dekker, 1993;251–290

have an early division within the cerebello-mesencephalic cistern where it divides into the mSCA and lSCA branches. Figure 15 shows the usual branching of the SCAs and the course of the lateral and medial branches. The mSCA branch extends more laterally than the mPICA. Occasionally these branches arise directly from the basilar artery and the SCAs. Both the major branches of the SCAs course towards the pedunculo-cerebellar sulcus and reach the superior and anterior aspects of the cerebellum above the horizontal fissure. The mSCAs mostly supply the superior portions of the vermis including the central, culmen, declive, and folium lobules; the lSCAs supply

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Fig. 13 Necropsy specimen (H & E stained) showing an anterior inferior cerebellar artery territory infarct

Fig. 14 Brain at necropsy showing the superior cerebellar arteries circling the midbrain and giving off branches

mostly the lateral portions of the cerebellar hemispheres including the anterior, simplex, and superior portion of the semilunar lobules. The SCAs also supply the cerebellar nuclei (dentate, fastigial, emboliform, and globose) as well as the bulk of

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Fig. 15 Schematic diagram of the superior cerebellar artery (SCA) and its medial (mSCA) and lateral (lSCA) branches. The top branch is the mSCA and the lower branch is the lSCA. From Amarenco P, Roullet E, Goujon C et al. Infarction in the anterior rostral cerebellum (the territory of the lateral branch of the superior cerebellar artery). Neurology 1991;41:253–258. with permission

Fig. 16 The SCA supply territories are shaded. From Amarenco P, Hauw J-J. Anatomie des arteres cerebelleuses. Rev Neurol 1989;145:267–276

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Fig. 17 Supply zones of the superior cerebellar arteries. A shows the superior pontine supply. 4 ¼ brachium conjunctivum, 11 ¼ lateral lemniscus, 9 ¼ medial lemniscus, 13 ¼ locus coeruleus, 13 ¼ mesencephalic tract of V, 7 ¼ spinothalamic tract, 8 ¼ cortico-tegmental tract, 12 ¼ decussation of IV, 15 ¼ medial longitudinal fasciculus. B shows an antero-posterior view and C a lateral view of the cerebellum. From Amarenco P, Hauw J-J. Anatomie des arteres cerebelleuses. Rev Neurol 1989;145:267–276. [Note that the numbers referred to here in the legend are not in the figure, and the numbers in the figure are not in the legend]

Fig. 18 Necropsy specimen showing SCA territory infarct in the rostral pons. The pontine tectum and a small part of the dorsolateral pontine tegmentum are involved. From Amarenco P, Hauw JJ. Cerebellar infarction in the territory of the superior cerebellar artery: a clinicopathologic study of 33 cases. Neurology 1990;40:1383–1390, with permission

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Fig. 19 MRI T2-weighted scans. From Caplan, L.R.: Posterior Circulation Disease: Clinical Findings, Diagnosis, and Management. Boston: Blackwell Scientific, 1996. (a) Sagittal view showing SCA territory infarct (b) Axial section showing small vermal cerebellar infarct in the territory of the medial branch of the superior cerebellar artery (mSCA) (c) Coronal section showing a bilateral SCA territory infarct appearing like “icing on a cake”

the cerebellar white matter (Amarenco and Hauw 1989; Amarenco et al. 1993; Amarenco 1991; Amarenco and Hauw 1990b; Amarenco et al. 1991). Figs. 16 and 17 show the cerebellar and brainstem supply territories of the SCA. Figure 18 is a necropsy specimen showing a large SCA territory infarct. Figure 19 shows three MRI scans that illustrate the imaging distribution of various SCA territory infarcts. The distribution of the supply territories of the cerebellar arteries as found on CT and MRI scanning has been illustrated and reviewed. (Savoiardo et al. 1987; Courchesne et al. 1989; Press et al. 1989; Press et al. 1990)

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References Amarenco P (1991) The spectrum of cerebellar infarctions. Neurology 41:973–979 Amarenco P, Hauw J-J (1989) Anatomie des arteres cerebelleuses. Rev Neurol 145:267–276 Amarenco P, Hauw J-J, Henin D et al (1989) Les infarctus du territoire de l’artère cérébelleuse postéro-inférieure; étude clinico-pathologique de 28 cas. Rev Neurol 145:277–286 Amarenco P, Hauw J-J (1990a) Cerebellar infarction in the territory of the anterior and inferior cerebellar artery. Brain 113:139–155 Amarenco P, Hauw JJ (1990b) Cerebellar infarction in the territory of the superior cerebellar artery: a clinicopathologic study of 33 cases. Neurology 40:1383–1390 Amarenco P, Roullet E, Goujon C et al (1991) Infarction in the anterior rostral cerebellum ( the territory of the lateral branch of the superior cerebellar artery). Neurology 41:253–258 Amarenco P, Hauw J-J, Caplan LR (1993) In: Lechtenberg R (ed) Cerebellar infarctions in handbook of cerebellar diseases. Marcel Dekker, New York, pp 251–290 Caplan LR (1996) Posterior circulation disease: clinical findings, diagnosis, and management. Blackwell Scientific, Boston Caplan LR (2000) Posterior circulation ischemia: then, now, and tomorrow the Thomas Willis lecture – 2000. Stroke 31:2011–2013 Caplan LR, Wityk RJ, Glass TA et al (2004) New England Medical Center posterior circulation registry. Ann Neurol 56:389–398 Caplan LR, Wityk RJ, Pazdera L et al (2005) New England Medical Center posterior circulation stroke registry: II. Vascular lesions. J Clin Neurol 1:31–49 Chaves CJ, Caplan LR, Chung C-S, Amarenco P (1994) In: Appel S (ed) Cerebellar infarcts in current neurology, vol 14. Mosby-Year Book, St Louis, pp 143–177 Courchesne E, Press GA, Murakami J et al (1989) The cerebellum in sagittal plane-anatomic-MR correlation: 1. The vermis. AJNR 10:659–665 Duvernoy HM (1978) Human brainstem vessels. Springer-Verlag, Berlin Gilman S, Bloedel J, Lechtenberg R (1981) Disorders of the cerebellum. FA Davis, Philadelphia Lister JR, Rhoton AL, Matsushima T, Peace DA (1982) Microsurgical anatomy of the posterior inferior cerebellar artery. Neurosurgery 10:170–199 Marinkovic S, Kovacevic M, Gibo H, Milisavljevic M, Bumbasirevic L (1995) The anatomical basis for the cerebellar infarcts. Surg Neurol 44:450–461 Perneczky A, Perneczky G, Tschabitscher M, Samec P (1981) The relation between the caudolateral pontine syndrome and the anterior inferior cerebellar artery. Acta Neurochir 58:245–257 Press GA, Murakami J, Courchesne E et al (1989) The cerebellum in sagittal plane-anatomic-MR correlation: 2. The cerebellar hemispheres. AJNR 10:667–676 Press GA, Murakami JW, Courchesne E et al (1990) The cerebellum:3. Anatomic-MR correlation in the coronal plane. AJNR 11:41–50 Savitz SI, Caplan LR (2005) Current concepts: Vertebrobasilar disease. N Engl J Med 352: 2618–2626 Savoiardo M, Bracchi M, Passerini A, Visciani A (1987) The vascular territories in the cerebellum and brainstem: CT and MR study. AJNR 8:199–209 Schmahmann JD (2000) Cerebellum and Brainstem. In: Toga A, Mazziotta, J, eds. Brain Mapping. The Systems. San Diego, Academic Press. pp. 207–259

Vestibulocerebellar Functional Connections

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Neal H. Barmack and Vadim Yakhnitsa

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vestibular Primary Afferent Fibers Project to Vestibular Nuclei and Vermal Lobules IX– Lobule X . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vestibular Secondary Mossy Fiber Afferents Terminate Bilaterally in the Cerebellum . . . Vestibular Climbing Fibers Project to Vermal Lobules IX–X . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Purkinje Neurons Generate Two Different Action Potentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vestibular Stimulation Modulates the Discharge of CSs and SSs Antiphasically . . . . . . . . . . CSs and SSs Are Aligned in Sagittal Zones in Vermal Lobules IX–X . . . . . . . . . . . . . . . . . . . . Granule Cells and Unipolar Brush Cells (UBCs) Discharge in Phase with Mossy and Climbing Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stellate and Golgi Cells Are Oppositely Modulated by Vestibular Stimulation . . . . . . . . . . . A Unilateral Microlesion of β-Nucleus Reduces Vestibular Modulation of Contralateral CSs and SSs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Microlesions of ß-Nucleus Reduce the Modulated Discharge of Contralateral Stellate and Golgi Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A Unilateral Labyrinthectomy (UL) Blocks Vestibular Primary Afferent Input to Ipsilateral Vermal Lobules IX–X, but Leaves Intact Vestibular Modulation of Ipsilateral SSs and CSs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vestibularly Modulated Discharge of Stellate and Golgi Cells Is Reduced by a Contralateral UL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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N. H. Barmack (*) Department of Physiology and Pharmacology, Oregon Health and Science University, Portland, OR, USA e-mail: [email protected] V. Yakhnitsa Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, USA © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_18

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Functions of Climbing and Mossy Fiber Circuitry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Three Distinct Climbing Fiber-Evoked Pauses in the Discharge of SSs . . . . . . . . . . . . . . . . . . . Cerebellar Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abnormal Cerebellar Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The vestibular system projects onto the cerebellum via three major pathways that are composed of primary and secondary vestibular mossy fiber afferents and vestibular climbing fibers. Vestibular primary afferent mossy fibers project to the ipsilateral vermal lobules IX–X and to the base of the sulci of several other vermal lobules. Secondary vestibular mossy fibers originate from the classic vestibular nuclei, lateral, medial, descending and superior vestibular nuclei (DVN, LVN, MVN, and SVN). These mossy fibers terminate in vermal lobules IX–X (uvula-nodulus) and hemispheric lobule X (flocculus). The vestibular nuclei receive convergent vestibular, optokinetic, and neck proprioceptive information. Vestibular afferents project to vermal lobules IX–X as climbing fibers that originate from two sub-nuclei of the inferior olive, the dorsomedial cell column (DMCC) and β-nucleus. These sub-nuclei receive secondary vestibular afferent projections from the ipsilateral parasolitary nucleus (Psol). The Psol receives primary afferent vestibular afferent projections from the ipsilateral vertical semicircular canals and otoliths, but not from the horizontal semicircular canals. Functionally, vestibular climbing fiber projections are arrayed in sagittal zones, establishing a mediolateral map on vermal lobules IX–X that encodes all possible head angles during movement. Electrophysiological evidence shows that climbing fiber signals are preeminent in modulating both the CSs (complex spikes) and SSs (simple spikes) of cerebellar Purkinje cells. This discharge is fed back onto neurons in the dorsal aspect of the DVN, LVN, MVN, prepositus hypoglossal nucleus (NPH) and nuclei within the ventral brainstem. The vestibulocerebellum imposes a climbing fiberconstructed coordinate system on postural responses and permits adaptive guidance of movement. Keywords

β-nucleus · CAG repeat disease · Cerebellum · Climbing fiber · Complex spike (CS) · Dorsomedial cell column (DMCC) · Descending vestibular nucleus (DVN) · Lateral reticular nucleus (LRN) · Lateral vestibular nucleus (LVN) · Mossy fiber · Medial vestibular nucleus (MVN) · Nodulus · Optokinetic · Otoliths · Parallel fiber · Parasolitary nucleus (Psol) · semicircular canals · Serotonin 5-HT1A receptor · Simple spike (SS) · Spinocerebellar ataxia (SCA) · Purkinje cells · Superior vestibular nucleus · (SVN) · Vestibular nucleus · Primary afferent · Vestibular system · Y-Group

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Introduction The vestibulocerebellum participates in sensorimotor integration and motor control. This organizational feature of the cerebellum, first demonstrated electrophysiologically, has generated interest in how its circuitry is used to modify simple reflexive movements (Eccles et al. 1967; Ito 2002). Reflexive and centrally initiated movements can be executed with or without an intact cerebellum, but the cerebellum adds accuracy and flexibility to movements by calibrating feedback under different sensory and motor conditions. The cerebellum may even reorganize hierarchies of sensory-motor feedback during apparently simple reflexive movements. An analysis of vestibular cerebellar circuitry in vermal lobules IX–X has three distinct advantages for investigating cerebellar function: (1) Vestibular projections to the cerebellum by both climbing and mossy fiber pathways have been welldocumented; (2) The lateralization within the brainstem of vestibular climbing and mossy fibers enables experimental strategies to test the role of each pathway in modulating discharge of the output neuron of the cerebellum; the Purkinje cell; and (3)The activity in either of these fiber pathways can be evoked parametrically by the use of natural vestibular stimulation that can activate independently each of the three semicircular canal and macular endorgans.

Vestibular Primary Afferent Fibers Project to Vestibular Nuclei and Vermal Lobules IX–Lobule X The vestibular nerve branches into two fiber bundles of unequal thickness as the nerve approaches the brainstem. The thicker branch enters the medulla where its axons terminate in the descending, lateral, medial, and superior vestibular nuclei (DVN, LVN, MVN, and SVN), as well as the parasolitary nucleus (Psol) (Brodal and Pompeiano 1957; Brodal 1972) (Fig. 1b). The thinner collateral limb branches again within the cerebellar cortex and distributes its synaptic terminals both sagittally and mediolaterally within vermal lobules IX–X (Sato and Sasaki 1993) (Figs. 1a and 2). This mossy fiber projection accounts for ~90% of the mossy fiber projection to vermal lobules IX–X (Korte and Mugnaini 1979; Kevetter and Perachio 1986; Gerrits et al. 1989; Sato et al. 1989; Barmack et al. 1993a; Akaogi et al. 1994; Purcell and Perachio 2001; Newlands et al. 2002, 2003; Maklad and Fritzsch 2003). This projection includes the entire lobule X and the lower folium in lobule IX. In rabbits, this folium is IXd, and in mice, this folium is IXc. A similar branching pattern is observed in BDA-labeled mossy fiber terminals (MFTs) that project to the anterior cerebellar vermis from the lateral reticular nucleus (LRN) (Wu et al. 1999) (Fig. 1d). A typical mossy fiber branch forms ~40 MFTs that contact one of a granule cell’s 3–6 dendrites in as many as ~15 granule cells. These synapses are tripartite and include a descending Golgi cell axon terminal (Fox et al. 1967). In total, a single mossy fiber makes synaptic contact with ~600 granule cells (Palkovits et al. 1972).

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Fig. 1 Projections of vestibular primary afferents to the cerebellum. (a) Cerebellar folium illustrates the different afferent projections of climbing and mossy fibers as well as seven neuronal cell types. Inhibitory interneurons are indicated in red. Arrows indicate direction of signal propagation. Modified from Barmack and Yakhnitsa (2012). (b) Horizontal section through the vestibular complex illustrates the terminal fields of five horizontal semicircular canal afferents, intra-axonally labeled with HRP. Modified from Sato and Sasaki (1993). (c) Several climbing fibers, labeled by BDA injections to the medial accessory olive, project as narrow sagittal bands to contralateral lobules IX–X. Modified from Sugihara et al. (2001). (d) A single cell in the lateral reticular nucleus is labeled with BDA. It projects bilaterally as a profusely branching mossy fiber, terminating across the entire width of the anterior vermis. Modified from Wu et al. (1999). Abbreviations: Ba basket cell; Bg Bergmann astrocyte; cf climbing fiber; Gc granule cell; Go Golgi cell; icp inferior cerebellar peduncle; IntP interpositus nucleus; LCN and MCN lateral and medial cerebellar nucleus; DVN, LVN, MVN, and SVN descending, lateral, medial, and superior vestibular nuclei; Lu Lugaro cell; mf mossy fiber; NG2+ glia; Pc Purkinje cell; pf parallel fiber; Sc stellate cell; UBC unipolar brush cell; Psol parasolitary nucleus

Although vestibular primary afferent mossy fibers project unilaterally to granule cells in vermal lobules IX–X, the projection is topographically diffuse. A single primary afferent mossy fiber not only projects onto multiple folia within vermal lobules IX–X. Its synaptic terminals are widely distributed mediolaterally within each folium (Maklad and Fritzsch 2003). Saccular and utricular afferents project mainly to the vermal lobule IX. Semicircular canal afferents project mainly, but not

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Fig. 2 Vestibular mossy and climbing fiber pathways to lobules IX–X. Primary afferent mossy fibers (mf) project to the ipsilateral parasolitary nucleus (Psol), medial, descending, superior vestibular nuclei (MVN, DVN, and SVN), Y-group (Y) and cerebellar granule cells (Gc, green lines). GABAergic Psol neurons project to the ipsilateral β-nucleus (β) and dorsomedial cell column (DMCC) (dashed red lines). Neurons in the β-nucleus and DMCC project as climbing fibers (cf) to contralateral lobules IX–X (dark blue lines). Y-group neurons project to contralateral dorsal cap (dc), β-nucleus and DMCC (light blue lines). Abbreviations: Fl flocculus; IntP interpositus nucleus; LCN and MCN lateral and medial cerebellar nucleus; Pc Purkinje cell; PFl paraflocculus; pf parallel fiber; 8n vestibular nerve. (Modified from Barmack and Yakhnitsa (2012))

exclusively to vermal lobule X (Kevetter and Perachio 1986; Purcell and Perachio 2001; Newlands et al. 2002, 2003; Maklad and Fritzsch 2003). This dispersion of information conveyed by vestibular primary afferents is heightened by granule cell parallel fibers that project mediolaterally within a folium for distances of 3–7 mm (Brand et al. 1976; Mugnaini 1983; Pichitpornchai et al. 1994). While the vestibular primary afferent mossy fiber projection is exclusively ipsilateral, the length of parallel fibers assures that some parallel fibers extend across the midline. A small number of granule cells have axons that ascend through the molecular layer and make synaptic contacts with the overlying Purkinje cell dendritic tree prior to bifurcating into parallel fibers. These ascending axons could potentially reduce parallel fiber dispersion by making preferential synapses on overlying Purkinje cells (Cohen and Yarom 1998; Gundappa-Sulur et al. 1999). However, the density of synapses made by ascending granule cell axons on a Purkinje cell is small (
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relative to the total number of parallel fibers (~1000) that make ~175,000 synaptic contacts as they pass through the Purkinje cell dendritic tree (Napper and Harvey 1988a, b). Furthermore, the strength of the synaptic signal evoked by activation of a single parallel fiber is equivalent to the strength of the synaptic signal evoked by activation of a single ascending axon (Isope and Barbour 2002). Clearly, the lack of specificity of the vestibular primary afferent mossy fiber pathway to granule cells and the lack of discrete projections of parallel fiber terminals onto Purkinje cell dendrites is an important design feature. Both anatomical and electrophysiological data suggest that the topography of vestibular primary afferent mossy fiber projections onto granule cells and the projection of parallel fibers onto Purkinje cells is too diffuse to account for the specificity of Purkinje cell discharge.

Vestibular Secondary Mossy Fiber Afferents Terminate Bilaterally in the Cerebellum In contrast to the ipsilateral projections of vestibular primary afferents, vestibular secondary afferents project from the caudal aspects of the DVN, MVN, and SVN bilaterally to vermal lobules IX–X and flocculus (Brodal and Torvik 1957; Kotchabhakdi and Walberg 1978; Yamamoto 1979; Brodal and Brodal 1985; Thunnissen et al. 1989). WGA-HRP injections into the caudal MVN and DVN reveal that vestibular secondary afferent mossy fibers terminate in the granule cell layers of lobules IX–X in a pattern similar to that of vestibular primary afferents (Fig. 1d). The projection pattern of secondary vestibular secondary afferent mossy fibers is not restricted to lobules IX–X. Caudal aspects of the DVN and MVN project to several other cerebellar lobules, including the anterior vermis and paraflocculus (Thunnissen et al. 1989; Epema et al. 1990). Most of these ascending projections are cholinergic (Tago et al. 1989; Barmack et al. 1992a, b, c).

Vestibular Climbing Fibers Project to Vermal Lobules IX–X Vestibular climbing fibers receive their inputs from a small cluster of neurons at the caudal end of the classic vestibular complex; the parasolitary nucleus (Psol). Psol neurons receive vestibular primary afferent projections from the ipsilateral vertical semicircular canals and otoliths, but not from the ipsilateral horizontal semicircular canals. Psol neurons are GABAergic and project ipsilaterally to two sub-nuclei of the inferior olive, the β-nucleus and dorsomedial cell column (DMCC) (Nelson et al. 1989; Barmack et al. 1993b, 1998). Vestibular climbing fibers from the β-nucleus and DMCC cross the midline to terminate contralaterally on Purkinje cells in vermal lobules IX–X (Alley et al. 1975; Groenewegen and Voogd 1977; Hoddevik and Brodal 1977; Tan et al. 1995; Voogd et al. 1996; Fushiki and Barmack 1997; Barmack and Yakhnitsa 2003; Voogd and Barmack 2005) (Fig. 2).

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In contrast to the diffuse projections of vestibular primary and secondary mossy fibers, vestibular climbing fibers terminate in narrow, functionally distinct, sagittal zones (Figs. 1c and 3d) (Voogd et al. 1996; Sugihara et al. 2001). The width of these zones ranges from ~400 μm in mice (Barmack and Yakhnitsa 2003) to ~800 μm in rabbits (Barmack and Shojaku 1995). Within these sagittal climbing fiber zones, most of the climbing fiber terminals convey information from the utricular otolith and the vertical semicircular canals. This is not surprising since an endorgan-specific

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Fig. 3 Roll-tilt vestibular stimulation modulates CSs and SSs in vermal lobules IX–X. (a) CSs are discriminated from SSs on the basis of their multi-peaked action potentials of longer duration. Five superimposed traces for each waveform are shown here with a fast time base. (b) Sinusoidal roll-tilt modulates the discharge of CSs and SSs. The modulation is affected by the head alignment about the vertical axis. This changes the alignment of vertical semicircular canals and utricular otolith with respect to the axis of rotation. CSs and SSs are modulated during roll-tilt in the optimal plane, but not in the null plane. The figurines illustrate head alignment during roll-tilt. (c) Sagittal projections of vestibular mossy and climbing fibers to vermal lobules IX–X. Vestibular primary afferent mossy fibers project to vermal lobules IXd–X, the region delineated in green. Vestibular climbing fibers project to vermal lobules IX–X. (d) Optimal planes for CSs in 205 Purkinje cells are distributed on a two-dimensional representation of lobules IX–X. Cells with optimal planes that are coplanar with the ipsilateral posterior semicircular canal (LPC) are green. Cells with optimal planes that are coplanar with the ipsilateral (left) LAC are illustrated as red squares. Open symbols indicate cells in which the optimal plane is not tested statically for otolithic responses. Filled symbols indicate cells tested for static sensitivity and are positive. Black diamonds indicate cells that are not responsive to vestibular stimulation but are modulated by horizontal optokinetic stimulation (HOKS) of the ipsilateral eye in the P ! A direction. Figurines indicate different postural responses evoked by vestibular and optokinetic stimulation in different planes. Vestibular stimulation in the plane of LAC evokes a forward and lateral extension of the ipsilateral fore- and hind-paws. HOKS of the left eye in the P ! A direction evokes a lateral extension of the contralateral paws. Vestibular stimulation in the plane of the ipsilateral (left) PSC a backward extension of the ipsilateral paws. (Modified from Barmack and Shojaku (1995))

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topography is also present in both the β-nucleus and DMCC (Barmack et al. 1993b; Barmack and Yakhnitsa 2000). Three interesting consequences emerge from the vestibular climbing fiber projection to vermal lobules IX–X. First, Purkinje cells receive climbing fiber signals that are driven primarily by the contralateral labyrinth. This anatomical configuration means that a Purkinje cell receives a vestibular mossy fiber signal that arises mainly from the ipsilateral labyrinth while receiving a climbing fiber signal that arises from the contralateral labyrinth. Second, the activity of climbing fibers is controlled mostly by an inhibitory signal from the ipsilateral Psol. Third, because of the separate vestibular origins of vestibular climbing fibers and mossy fibers, it is possible to investigate separately the influence each of these inputs on the modulated discharge of Purkinje cells recorded in vermal lobules IX–X (Fig. 2). The general scheme of separate labyrinthine origins of vestibular mossy and climbing fiber projections is compromised, in part, by the existence of a small descending pathway from the dorsal Y-group that terminates in the contralateral β-nucleus and DMCC (Fig. 2). This pathway is glutamatergic (Kevetter and Perachio 1986; De Zeeuw et al. 1993; Wentzel et al. 1995; Blazquez et al. 2000). The dorsal Y-group receives both primary and secondary vestibular projections.

Purkinje Neurons Generate Two Different Action Potentials Cerebellar Purkinje cells have two action potentials, termed complex and simple spikes (CSs, SSs). CSs are evoked by the explosive action of a single climbing fiber that wraps around the Purkinje cell proximal dendrite (Granit and Phillips 1956; Eccles et al. 1966a). CSs are an amalgam of dendritic spikes that have a long duration (~ 5 ms) and discharge at a rate of 0.1–5.0 imp/s (Fig. 3a). Each Purkinje cell receives synaptic contacts from only one climbing fiber. However, a single climbing fiber branches sagittally to synapse upon 7–15 Purkinje cells. In contrast to the long duration and infrequent discharge of CSs, SSs are single peaked short duration action potentials (0.75–1.25 ms) that discharge at 20–60 imp/s. The origin of the synaptic signals that modulate the discharge of SSs is less understood than the origin of the climbing fiber signal that modulates the discharge of CSs. It has been argued that since climbing fibers evoke CSs, SSs must be evoked by mossy fiber!granule!cell-parallel fibers (Ebner and Bloedel 1981; Armstrong and Edgley 1988; Nagao 1989; Kano et al. 1991; Lisberger et al. 1994; Ghez and Thach 2000; Apps and Garwicz 2005; Walter and Khodakhah 2006; Bloedel and Bracha 2009). However, many factors contribute to the modulated discharge of SSs. Spontaneous SSs occur in isolated Purkinje cells in the absence of any parallel fiber input (Llinás and Sugimori 1980; Raman and Bean 1999). Interneurons in the molecular layer, basket and stellate cells, exert inhibitory control of SSs (Andersen et al. 1964; Midtgaard 1992a; Pouzat and Hestrin 1997; Carter and Regehr 2000; Szapiro and Barbour 2007). Golgi cells indirectly influence SS discharge by inhibiting the discharge of granule cells (Eccles et al. 1966b). Unipolar brush cells in the granule cell layer appear to combine with mossy fiber input to excite neighboring granule cells (Rossi et al. 1995; Diño et al. 2000, 2001).

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Vestibular Stimulation Modulates the Discharge of CSs and SSs Antiphasically The discharge of CSs and SSs in ~90% of the Purkinje cells recorded in vermal lobules IX–X in either rabbits or mice is modulated by sinusoidal roll-tilt vestibular stimulation about the longitudinal axis (Barmack and Shojaku 1995; Fushiki and Barmack 1997; Yakhnitsa and Barmack 2006) (Fig. 3b). A step rotation or static rolltilt stimulus is used to measure whether induced activity is modulated by a gravitationally evoked otolithic signal. If, following a step roll-tilt, activity is maintained longer than 20 s, it can be attributed, to the stimulation of a utricular otolith. Interestingly, in mice, more than 90% of recorded Purkinje cells have a mixed signal from both the semicircular canals and utricular otoliths. They respond to sinusoidal and step-roll tilt. In both rabbits and mice, the discharges of CSs and SSs recorded from Purkinje cells in lobules IX–X are not modulated when the animal is rotated about the vertical axis (Barmack and Shojaku 1995; Barmack and Yakhnitsa 2003). These observations are consistent with the finding that rotation about the vertical axis fails to modulate the discharge of Psol neurons (Barmack and Yakhnitsa 2000) and neurons in the β-nucleus and DMCC (Barmack et al. 1993b). Does the modulation of SSs correspond to the modulation of vestibular primary afferent mossy fibers? No, roll-tilt onto the left side increases the discharge of left primary vestibular afferent mossy fibers that project exclusively to left vermal lobules IX–X (Goldberg and Fernandez 1971; Fernandez and Goldberg 1976) (Figs. 2 and 3c). It also decreases the discharge of primary afferents in the right labyrinth thereby reducing the excitation of right Psol neurons. Reduced excitation of the GABAergic right Psol neurons withdraws inhibition of neurons in the right β-nucleus and DMCC, causing an increased climbing fiber discharge of olivary neurons that project to the contralateral (left) vermal lobules IX–X (Barmack et al. 1993b, 1998; Barmack and Yakhnitsa 2000) (Fig. 2). A functional consequence of this circuitry is that leftward roll-tilt increases the discharges of both left CSs and right primary afferent mossy fibers in the left vermal lobules IX–X. While mossy fibers and climbing fibers discharge in phase with each other, sinusoidal roll-tilt modulates the discharges of SSs that are ~180 deg out of phase with vestibular primary afferent mossy fibers (Barmack and Shojaku 1995; Yakhnitsa and Barmack 2006; Barmack and Yakhnitsa 2008a) (Fig. 3d–f).

CSs and SSs Are Aligned in Sagittal Zones in Vermal Lobules IX–X The response planes of vestibularly driven CSs and SSs can be characterized physiologically using a “null method.” During sinusoidal roll-tilt, the head-body axis is changed systematically until a plane of rotation is found at which the recorded neuronal activity is not modulated. This defines a “null plane.” On either side of this “null plane,” the phase of this activity shifts by 180 deg. The “optimal plane” is orthogonal to the “null plane” (Fig. 3b). The orientation of optimal planes of CSs and SSs usually align with the anatomical orientation of the anterior and posterior

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semicircular canals (Fig. 3d). A two-dimensional representation of rabbit vermal lobules IX–X shows 205 Purkinje cells with optimal planes aligned with either the ipsilateral (left) posterior semicircular canal (LPC) (green circles) or the ipsilateral (left) anterior semicircular canal (LAC) (red squares). These two types of responses are organized into preferred sagittal zones ~800 μm wide in the rabbit. Inserted between these two zones are Purkinje cells whose CSs are driven by horizontal optokinetic stimulation (HOK) of the ipsilateral eye in the posterior!anterior (P ! A) direction. The HOK zone is derived from climbing fibers that originate in the dorsal cap of the inferior olive (Alley et al. 1975; Graf et al. 1988; Takeda and Maekawa 1989; Barmack and Shojaku 1995). Figurines indicate different postural responses evoked by vestibular and optokinetic stimulation in different planes. Vestibular stimulation in the plane of LAC evokes a forward and lateral extension of the ipsilateral fore- and hind-paws. HOKS of the left eye in the P ! A direction evokes a lateral extension of the contralateral paws. Vestibular stimulation in the plane of the ipsilateral posterior semicircular canal evokes a backward extension of the ipsilateral paws. In the mouse cerebellum, sagittal zones for optimal planes of SSs and CSs are consistent with the zones found in rabbit (Fig. 4a, b). These zones are ~400 μm wide and consistent with the anatomical projections of climbing fibers, but inconsistent with the termination patterns of mossy fibers (Voogd and Barmack 2005) (Fig. 4c, d). The optimal planes of CSs and SSs can be quantified separately and displayed as a polar vector in which the length of the vector corresponds to depth of modulation (M) and the angle (φ) corresponds to the phase of M relative to head position. For example, when φ ¼ 0 deg indicates that M is in phase with peak leftward head tilt (Fig. 4e). When φ ¼ 180 deg, M is in phase with peak rightward head tilt. Note that the population vector for CSs leads head position by 56 deg. The vector for SSs lags that of CSs by 164 deg.

Granule Cells and Unipolar Brush Cells (UBCs) Discharge in Phase with Mossy and Climbing Fibers If the mossy fiber!granule cell!parallel fiber inputs to Purkinje cells in vermal lobules IX–X were responsible for the modulation of SSs, then one would expect that interneurons in the granule cell layer (granule cells or unipolar brush cells) or molecular layer (Golgi or stellate cells) could reverse the phase of SSs with respect to mossy fiber afferents. With the advent of juxtacellular labeling techniques, it is possible to record from cerebellar interneurons, mark them with neurobiotin and subsequently identify the recorded cell type and its location within the cerebellar cortex. Granule cells are identified by their small soma (4–6 μm) and 3–4 dendritic branches (Mugnaini and Floris 1994; Diño et al. 2000) (Fig. 5a). Granule cells respond in phase with ipsilateral side down head rotation (Fig. 5b, c) (M ¼ 0.1.90 imp/s; φ ¼ 2 deg). Often superimposed on granule cell discharges are phase locked high frequency bursts of activity. Such phase-locked bursts suggest that granule cells

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Fig. 4 Modulated CSs and SSs are aligned in sagittal zones in mouse lobules IX–X. CSs and SSs of Purkinje cells in mouse lobules IX–X respond antiphasically during sinusoidal roll-tilt and are organized in sagittal zones. (a) CSs and SSs of a Purkinje cell in lobules IX–X right of the midline are modulated during roll-tilt. Upper trace is the raw record. CSs are indicated by red arrowheads. The bottom trace indicates roll-tilt head position. Intermediate traces show 10– 50 cycles of vestibular stimulation at 0.2 Hz converted to peristimulus histograms fitted with a cosine function by a least squares method. The histogram for SSs is plotted as light gray bars fitted with a green cosine function. CSs are plotted with black bars fitted with a blue cosine function. (b) Response planes of CSs and SSs are plotted on a two-dimensional representation of lobules IX–X. Filled green circles indicate CSs whose optimal response planes are consistent with the anatomical angle of the ipsilateral (left) posterior semicircular canal (LPC). They are confined mostly to a medial sagittal zone (0–400 μm). Filled red squares indicate CSs consistent with the anatomical angle of the ipsilateral (left) LAC. They are confined mostly to a lateral sagittal zone (400–800 μm). Open circles indicate CSs with vestibularly modulated Purkinje cells, but whose optimal response planes are not measured. X’s indicate Purkinje cells with vestibularly unresponsive CSs and SSs. (c) Purkinje cells with optimal planes consistent width alignment with the ipsilateral (left) PSC are plotted in a sagittal

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may sum inputs over a wide range of frequencies. Clearly, a primary afferent mossy fiber signal is not reversed at the granule cell synapse. UBCs are found in abundance in the granule cell layer, particularly in vermal lobules IX–X and are identified by their large somata (8–10 μm) and characteristic brush-like endings (Fig. 5d). Like granule cells, UBCs discharge in phase with ipsilateral roll-tilt (Fig. 5e, f). Unlike granule cells, UBCs have a regular spontaneous discharge (10.0  11.6 imp/s) that provides an important clue to their physiological identity (Ruigrok et al. 2011). The response profiles of both granule cells and UBCs indicate that they do not account for the antiphasic modulation of SSs during vestibular stimulation.

Stellate and Golgi Cells Are Oppositely Modulated by Vestibular Stimulation If Golgi, stellate, basket, or Lugaro cells were responsible for shaping the responses of SSs, then vestibular stimulation should modulate the discharge of each in phase with the discharge of CSs and out of phase with the discharge of SSs. In the mouse, the molecular layer contains ~15 stellate cells/Purkinje cell. Parallel fibers synapse upon the dendrites of stellate cells, like those of basket and Golgi cells. Stellate cell axons have lengths of ~250 μm and make contact with the dendrites of several Purkinje cells (Eccles et al. 1967). Stellate cell axon terminals release GABA onto GABAAα1 receptors on Purkinje cell dendrites. Like basket cells, stellate cells receive no direct synaptic contacts from climbing fibers (Hámori and Szentágothai 1980; Pouzat and Hestrin 1997). Climbing fiber-evoked glutamate “spillover” as well as the possible excitatory input from parallel fibers could modulate the discharge of stellate cells and this discharge could potentially inhibit Purkinje cell SSs, accounting for the antiphasic discharge of CSs and SSs (Andersen et al. 1964; Midtgaard 1992a; Pouzat and Hestrin 1997; Carter and Regehr 2000; Szapiro and Barbour 2007). Stellate cells have a mean spontaneous discharge of 10  11 imp/s. They respond to sinusoidal roll-tilt in phase with the vestibular primary afferent mossy fiber and climbing fiber signals (Fig. 6a–c) (M ¼ 1.65 imp/s; φ ¼ 13 deg). The phase of the stellate cell population vector indicates that stellate cells could account for either a parallel fiber or a climbing fiber-evoked inhibition of Purkinje cells, thereby decreasing the discharge of SSs antiphasically. ä Fig. 4 (continued) reconstruction of the medial zone. (d) Purkinje cells with optimal planes consistent with alignment with the ipsilateral (left) LAC are plotted in a sagittal reconstruction of the lateral zone. (e) Polar plot for 146 Purkinje cells indicates responses of CSs (blue) and SSs (green). The arrows indicate population vectors for CSs (red) and SSs (yellow). Note that the population discharge of CSs leads the head position by 56 deg. The discharge of SSs lags that of CSs by 164 deg. (Modified from Barmack and Yakhnitsa (2003) and Barmack and Yakhnitsa (2013))

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The classic glomerular plexus in the granule cell layer consists of a ~40 granule cell dendrites, Golgi cell axon terminal, and a mossy fiber terminal rosette (Eccles et al. 1966b; Fox et al. 1967; Hámori and Szentágothai 1980). Golgi cell axon terminals also contact unipolar brush cells (Dugué et al. 2005). Golgi cells are the only cerebellar interneurons onto which climbing fibers synapse (Hámori and Szentágothai 1966; Desclin 1976). Consequently, Golgi cells are in a unique position to modulate the activity of thousands of granule cells. If Golgi cells responded in phase with climbing and mossy fibers, their discharge could account for the observed antiphasic modulation of SSs. However, Golgi cells are driven in phase neither with CSs nor mossy fiber afferents. Rather, they respond in phase with the discharge of SSs and out of phase with the discharge of CSs as indicated by the mean population vector (M ¼ 0.58 imp/s; φ ¼ 174 deg) (Fig. 6d–f). This could mean that vestibularly driven stellate cell synapses on Golgi cells have a greater weight than do either parallel or climbing fiber synapses.

A Unilateral Microlesion of β-Nucleus Reduces Vestibular Modulation of Contralateral CSs and SSs The left vermal lobules IX–X receive primary vestibular mossy fiber projections from the left labyrinth and climbing fiber projections from the right β-nucleus and DMCC. Because these two fiber systems originate from opposite sides of the brainstem, one can examine how cerebellar circuitry behaves when it is deprived of one or the other of these fiber projections. Placement of an electrolytic unilateral microlesion in the right caudal β-nucleus leaves intact the vestibular primary and secondary afferent mossy fiber projections, but blocks climbing fiber signals from reaching the left vermal lobules IX–X (Fig. 7a–c). Three distinct consequences of unilateral β-nucleus microlesions on Purkinje cell discharge are noted: (1) Partial unilateral microlesions of the β-nucleus result in loss of climbing fiber input to a subset of contralateral Purkinje cells. Consequently, CSs in some Purkinje cells are absent and only SSs can be recorded (Fig. 7b). Lacking the iconic CSs, all such Purkinje cells are identified by juxtacellular labeling. Without a climbing fiber input, SSs are not driven by vestibular stimulation. (2) Microlesions may not damage all neurons in the β-nucleus but disrupt presynaptic input to these neurons from the Psol. Consequently, some Purkinje cells retain CSs, but these CSs are not modulated by roll-tilt vestibular stimulation. In Purkinje cells lacking modulated CSs, SSs are ä Fig. 5 (continued) cosine function (blue line). (c) The population response vector (red arrow) responds to ipsilateral roll-tilt and has a depth of modulation (M ¼ 0.67 imp/s) and a phase (φ ¼ 3 deg). Filled circles indicate driven cells. Open circles indicate non-driven cells. (d) UBC with a characteristic dendritic brush is labeled juxtacellularly in left vermal lobule X. (e) Raw traces and peristimulus histogram indicate that this UBC responds to ipsilateral roll-tilt. (f) The population vector for 32 UBCs responds to ipsilateral roll-tilt (M ¼ 1.0 imp/s; φ ¼ 31 deg). (Modified from Barmack and Yakhnitsa (2008a))

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Fig. 6 Stellate and Golgi cell interneurons respond oppositely to vestibular stimulation. (a) Stellate cell is juxtacellularly labeled and localized to molecular layer (ml) of left vermal lobule IX. (b) This stellate cell responds to ipsilateral roll-tilt (left side down). The population of 47 stellate cells has a mean spontaneous discharge of 10  11 imp/s. Peristimulus histograms are fitted with a cosine function (red line). (c) Thirty-six of the 47 recorded stellate cells respond to sinusoidal rolltilt. Thirty of the 36 responsive stellate cells discharge in phase with ipsilateral roll-tilt. Filled circles indicate driven cells. Open circles indicate non-driven cells. The population vector for the entire population of stellate cells, M ¼ 1.65 imp/s; φ ¼ 13 deg. (d) Golgi cell is juxtacellularly labeled and localized to the granule cell layer (gl) of left lobule IX. (e) This Golgi cell responds to contralateral roll-tilt (right side down). The population of Golgi cells has a mean spontaneous discharge rate of 2.7  2.1 imp/s. The peristimulus histograms are fitted with a cosine function (purple line). (f) 18/23 Golgi cells respond to sinusoidal roll-tilt. 13/18 responsive Golgi cells discharge in phase with contralateral roll-tilt. For the entire population of Golgi cells, M ¼ 0.58 imp/s; φ ¼ 184 deg. Abbreviations: gl granule cell layer; ml molecular layer; Pl Purkinje cell layer. (Modified from Barmack and Yakhnitsa (2008a))

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also not modulated by vestibular stimulation (Fig. 7c). (3) Incomplete microlesions of the β-nucleus – the DMCC remains intact – allow some Purkinje cells in vermal lobules IX–X to retain modulated CSs. In these cells, SSs remain modulated and are driven antiphasically (Fig. 7d) (Barmack and Yakhnitsa 2003, 2011). These three examples demonstrate that vestibularly modulated climbing fiber signals are essential for the modulation of SSs.

Microlesions of ß-Nucleus Reduce the Modulated Discharge of Contralateral Stellate and Golgi Cells In normal mice, the discharge of stellate cells is modulated in phase with mossy and climbing fiber afferents. By making unilateral microlesions of the β-nucleus, one can test whether climbing fiber inputs are necessary to modulate the discharge of stellate and Golgi cells during roll-tilt. In stellate cells contralateral to an intact inferior olive, the population vector is in phase with ipsilateral roll-tilt and in phase with CSs, but 180 deg out of phase with SSs (M ¼ 1.65 imp/s; φ ¼ 13 deg) (Fig. 6c). This suggests that stellate cells could regulate SSs. Lacking climbing fiber input from the contralateral β-nucleus few stellate cells are modulated by vestibular stimulation. The population vector shifts by ~140 deg (M ¼ 0.9 imp/s; φ ¼ 154 deg) (Fig. 7e). This change in the population vector suggests that vestibularly modulated discharge of the stellate cells depends on an intact climbing fiber input. In normal mice, Golgi cells are driven by sinusoidal roll-tilt. Unlike stellate cells, Golgi cells discharge out of phase with mossy and climbing fiber signals (M ¼ 0.58; φ ¼ 184 deg) (Fig. 6f). This excludes the possibility that Golgi cells account for the antiphasic discharge of CSs and SSs. After unilateral microlesions of the β-nucleus,

ä Fig. 7 Unilateral microlesions of inferior olive reduce modulation of SSs in contralateral vermal lobules IX–X. Unilateral electrolytic microlesions of the β-nucleus and DMCC reduce the number of functionally intact climbing fibers that project to contralateral vermal lobules IX–X. (a) The illustration of the caudal aspect of a microlesion shows that it partially destroyed the left β-nucleus while leaving intact the right β-nucleus. (b) After an olivary microlesion, 37 contralateral Purkinje cells lack spontaneous CSs. 29/37 of these cells have spontaneous SSs not driven by sinusoidal roll-tilt. Filled circles indicate driven cells. Open circles indicate non-driven cells. (c) After an olivary microlesion, 61 contralateral Purkinje cells have spontaneous CSs, but these CSs are not driven by sinusoidal roll-tilt. In none of these Purkinje cells are the SSs driven. (d) In 24 contralateral Purkinje cells, CSs are present and driven by sinusoidal roll-tilt. In 23/24 of these cells, SSs are driven antiphasically. (e) The discharges of only 4/15 stellate interneurons contralateral to the microlesion are driven by roll-tilt. (f) The discharges of 15/22 Golgi cells contralateral to the microlesion are driven by roll-tilt, but the responses are equally represented in all four quadrants, thereby reducing the population vector. Abbreviations: py pyramidal tract. (Modified from Barmack and Yakhnitsa (2011))

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the modulation of Golgi cell activity is reduced by an order of magnitude (M ¼ 0.05 imp/s; φ ¼ 261 deg) (Fig. 7f).

A Unilateral Labyrinthectomy (UL) Blocks Vestibular Primary Afferent Input to Ipsilateral Vermal Lobules IX–X, but Leaves Intact Vestibular Modulation of Ipsilateral SSs and CSs If vestibular primary afferents modulate the discharge of SSs, then blocking these afferents should abolish vestibularly modulated discharge of SSs. Vestibular primary afferent mossy fibers projecting to ipsilateral vermal lobules IX–X can be blocked by making a surgical UL that severs all vestibular primary projections to the ipsilateral vestibular nuclei and to ipsilateral lobules IX–X, while leaving intact vestibular climbing fiber projections from the contralateral β-nucleus and DMCC. Post-UL, the numbers of driven CSs and SSs recorded in the ipsilateral vermal lobules are reduced relative to the driven CSs and SSs observed in mice with intact labyrinths (95%-intact; 57%-UL-ipsilateral). Nevertheless, CSs are driven with population vectors comparable to those observed in mice with intact labyrinths (UL-ipsilateral CS: MCS ¼ 0.24 imp/s; φCS ¼ 56 deg; intact labyrinth CS: MCS ¼ 0.4 imp/s; φCS ¼ 56 deg) (see Fig. 8a vs. Figure 4e). The population vectors for SSs are comparable to those of mice with intact labyrinths (UL-ipsilateral SS: MSS ¼ 1.17 imp/s; φSS ¼ 204 deg; intact labyrinth SS: MSS ¼ 1.70 imp/s; φSS ¼ 220 deg). Not surprisingly, the main deficit observed after a UL is that the percentage of driven CSs in Purkinje cells contralateral to the UL is reduced from 95% in mice with intact labyrinths to 21% (Fig. 8b) (UL-contralateral CS: MCS ¼ 0.03 imp/s; φCS ¼ 40 deg). The percentage of driven SSs in contralateral Purkinje cells is reduced from 88% in mice with intact labyrinths to 21% for Purkinje cells contralateral to a UL (Fig. 8b) (UL-contralateral SS: MSS ¼ 0.31 imp/s; φSS ¼ 216 deg). While the relative phase of CSs and SSs remains normal, the depth of modulation of both CSs and SSs contralateral to the UL is reduced (Fig. 2).

Vestibularly Modulated Discharge of Stellate and Golgi Cells Is Reduced by a Contralateral UL The vestibularly modulated discharge of stellate and Golgi cells is also reduced following a contralateral UL. In mice with intact labyrinths, 37/47 stellate cells are driven in phase with ipsilateral side down rotation (M ¼ 0.65 imp/s; φ ¼ 13 deg) (Fig. 6c). After a UL, ipsilateral stellate cell activity remains modulated, but with no consistent phase, resulting in a significantly reduced population vector (M ¼ 0.21 imp/ s; φ ¼ 147 deg) (Fig. 8c). In six stellate cells recorded contralaterally, only one was driven (M ¼ 0.21 imp/s; φ ¼ 356 deg) (Fig. 8d). This suggests that modulation of stellate cell discharge is largely dependent on a climbing fiber signal, but that a global mossy fiber input may also contribute.

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Fig. 8 Unilateral labyrinthectomy impairs vestibular modulation of Purkinje, stellate, and Golgi cell discharge in vermal lobules IX–X. A unilateral labyrinthectomy (UL) severs all vestibular primary afferent input to the ipsilateral vestibular nuclei and to vermal lobules IX–X.

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In mice with intact labyrinths, Golgi cells are driven out of phase with ipsilateral side down rotation (M ¼ 0.58 imp/s; φ ¼ 183 deg) (Fig. 6f). Although the discharge of fewer Golgi cells remains modulated following an ipsilateral UL, Golgi cells retain a population vector comparable to that observed in recordings from mice with intact labyrinths (M ¼ 0.64 imp/s; φ ¼ 202 deg) (Fig. 8e). Post-UL, contralateral Golgi are driven but with a reduced population vector (M ¼ 0.33 imp/s; φ ¼ 66 deg) (Fig. 8e). In sum, the disruption caused by a UL on Golgi cell discharge, like that of stellate cells, is greater contralaterally than ipsilaterally, emphasizing the importance of a functional climbing fiber pathway.

Functions of Climbing and Mossy Fiber Circuitry Since the discharge of primary vestibular afferent mossy fiber projection to vermal lobules IX–X discharges 180 degrees out of phase with the discharge of SSs, mossy fiber afferents cannot account for the observed modulation of SSs. Rather, climbing fibers appear to modulate SSs indirectly by exciting inhibitory stellate interneurons through “spillover” of glutamate released by climbing fiber synapses on Purkinje cells (Midtgaard 1992b; Dzubay and Jahr 1999; Carter and Regehr 2000; Szapiro and Barbour 2007). Several observations support the idea that climbing fibers are largely responsible for the vestibular modulation of both CSs and SSs. During sinusoidal roll-tilt, primary afferent mossy fibers discharge out of phase with SSs (Barmack and Shojaku 1995; Fushiki and Barmack 1997; Barmack and Yakhnitsa 2003). SSs recorded from Purkinje cells in vermal lobule IXa are modulated by roll-tilt even though Purkinje cells in these regions do not receive a projection of vestibular primary and secondary mossy fiber afferents, but do receive a vestibular climbing fiber projection (Barmack et al. 1993a; Maklad and Fritzsch 2003). Sinusoidal rotation about the vertical axis (yaw) fails to modulate the discharge of SSs or CSs recorded from Purkinje cells in vermal lobules IX–X even though vestibular primary afferent mossy fibers from the horizontal ampullae project to these lobules. This observation suggests that the influence of the vestibular primary ä Fig. 8 (continued) The effects of an UL are observed acutely in Purkinje, stellate, and Golgi cells. (a) In ipsilateral Purkinje cells, the post-UL-driven discharge of CSs and SSs is maintained. Filled circles indicate driven cells. Open circles indicate non-driven cells. (b) Post-UL, the driven discharge of CSs and SSs recorded from Purkinje cells contralateral to the UL is reduced. The number of driven CSs and SSs in contralateral Purkinje cells is reduced from 95% in mice with intact labyrinths to 21% in mice with a UL. (c) Post-UL, the number of driven stellate cells ipsilateral to the UL is maintained, but the population vector is reduced and out of phase with ipsilateral side down rotation. (d) Post-UL, the number of driven stellate cells contralateral to the UL is reduced from 77% in mice with intact labyrinths to 17%. (e) Post-UL, 14/25 ipsilateral Golgi cells are driven and the population vector remains antiphasic (M ¼ 0.58 imp/s; φ ¼ 198 deg). (f) Only 5/11 contralateral Golgi cells are driven. The population vector is reduced in amplitude and phase shifted (M ¼ 0.33 imp/s; φ ¼ 66 deg). (Modified from Barmack and Yakhnitsa (2013))

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afferent mossy fiber!granule cell!parallel fibers on the discharge of SSs is weak. Rather, climbing fibers evoke activity of interneurons, particularly stellate cells which in turn modulate SSs (Barmack and Shojaku 1995; Yakhnitsa and Barmack 2006; Yakusheva et al. 2007). Microlesions of the inferior olive reduce the modulated discharge of SSs in Purkinje cells located in vermal lobules IX–X contralateral to the microlesions even though vestibular mossy fibers to these lobules remain intact (Barmack and Yakhnitsa 2011). Again, this observation emphasizes that intact vestibular primary afferent mossy fiber!granule cell!parallel fiber synapses do not modulate the discharge of SSs. Climbing fiber zones in the mouse vermal lobules IX–X are ~400 μm wide. Within these zones, CSs and SSs respond antiphasically during roll-tilt. The functional specificity of a climbing fiber zone cannot be achieved by mossy fibers because of distribution of their synaptic terminals is too divergent. In fact, when parallel fiber synapses on the dendrites of 2–4 Purkinje cells are labeled discretely with neurobiotin, more than 60% of the granule cells that take up the neurobiotin retrogradely are located outside of the climbing fiber zone occupied by the neurobiotin-labeled Purkinje cells (Barmack and Yakhnitsa 2008b). To reiterate, parallel fibers have an average length of 5 mm in the rat cerebellum, more than 10 the width of a climbing fiber zone (Napper and Harvey 1988b; Barmack and Yakhnitsa 2008a). A unilateral labyrinthectomy (UL) disrupts the modulated discharge of CSs and SSs in contralateral vermal lobules IX–X more than in ipsilateral vermal lobules IX– X. This occurs because a UL blocks a modulated primary vestibular afferent signal to the ipsilateral parasolitary nucleus, disrupting the Psol inhibitory signal to the subjacent β-nucleus and DMCC and preventing a modulated climbing fiber signal to Purkinje cells in contralateral lobules IX–X. Another way of differentiating the effects of climbing and mossy fibers on the discharge of CSs and SSs is to examine the effects of mutations that alter the projections of one or both of these pathways to the cerebellum. In Ptf1a::cre; Robo3(lox/lox) mice, the normal crossed projection of climbing fibers to the contralateral cerebellum is converted into an ipsilateral projection (Badura et al. 2013). Mossy fiber projections remain undisturbed. This mutation reverses the responses of optokinetically evoked CSs and SSs recorded from floccular Purkinje cells. Optokinetically modulated CSs and the associated antiphasically modulated discharge of SSs persist. However, they are directionally reversed due to the rerouted climbing fibers. If the modulated discharge of SSs was caused by an intact mossy fiber!granule cell!parallel fiber projection, its polarity would not reverse.

Three Distinct Climbing Fiber-Evoked Pauses in the Discharge of SSs At least three separate mechanisms account for climbing fiber-evoked decreases in the discharge of SSs. First, climbing fiber synapses on Purkinje cells trigger inactivation of SSs by a Ca+2-activated increased K+ conductance (McKay

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et al. 2007). This climbing fiber-evoked pause lasts 5–10 ms and occurs even when GABAergic transmission by interneurons is blocked (Wulff et al. 2009; Johansson et al. 2014). A second, longer duration, climbing fiber-evoked pause is evoked by molecular layer interneurons, most likely through climbing fiber glutamate spillover onto stellate cells (Barmack and Yakhnitsa 2008a). This pause is independent of the fast changes in Purkinje cell conductance and lasts 5–100 ms (Midtgaard 1992b; Dzubay and Jahr 1999; Carter and Regehr 2000; Szapiro and Barbour 2007). A third, longer lasting climbing fiber evoked decrease in SS discharge is exemplified by long-term depression (LTD) (Ito et al. 1982; Sakurai 1987; Ito and Karachot 1989; Crépel and Jaillard 1991; Narasimhan and Linden 1996). Climbing fiber-evoked LTD selectively reduces the efficacy of conjunctively activated mossy fiber!granule cell!parallel fiber synapses on Purkinje cells. LTD is specific to the topographical projection of the climbing fiber, but independent of the anatomical origins of the parallel fibers. In lobules IX–X, the mediolateral dispersion of vestibular information conveyed by the mossy fiber!granule cell!parallel fiber pathway provides all Purkinje cells with information from each vestibular end organ, a virtual cafeteria of vestibular signals. LTD conjunctively suppresses parallel fiber signals that are associated conjunctively with climbing fiber discharge. The information most likely to be suppressed is conveyed by parallel fibers that are modulated in phase with climbing fibers. Collectively, the excitatory influences of mossy fiber!granule cell!parallel fibers on Purkinje cells establish an operating level of background excitation of SSs. The discharge of SSs is immediately reduced by climbing fiber signals acting directly on the Purkinje cell. The discharge of SSs is indirectly reduced by climbing fiber-evoked stellate cell inhibition of Purkinje cells within a sagittal zone. The discharge of SSs is reduced adaptively by the conjunctive interaction of climbing fiber, parallel fiber, and inhibitory interneuron signals on Purkinje cells.

Cerebellar Functions wThe cerebellum may predict spatial environments. If an animal is oscillated linearly along the interaural axis for an extended period of time, oscillatory eye movements persist for several hours after the oscillation is stopped (Kleinschmidt and Collewijn 1975). Information about such eye movement oscillations may already be contained within vestibular climbing fiber signals, since the activity of vestibular climbing fibers continues to oscillate for 10–60 s at the frequency of vestibular stimulation after the vestibular stimulation is stopped (Barmack and Shojaku 1992). Behaviorally, this predictive climbing fiber function might apply to the common experience of making a transition from standing on land to standing on a boat at sea. At sea, the vestibulocerebellum may adapt to a new set of otolithic inputs and predict the spatial environment better than either visual or proprioceptive senses. Returning to land, the vestibulocerebellum may once again adapt to a new spatial environment or be replaced in a sensory hierarchy by visual and

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proprioceptive signals. In this instance, the cerebellum may be used to suppress or recalibrate sensory signals. The vestibular climbing fiber projection to vermal lobules IX–X represents a three-dimensional map of vestibular space (Foster et al. 2007). The optokinetic climbing fiber projection to hemispheric lobule X represents a three-dimensional map of optokinetic space. Both maps correspond to the orientation of the three semicircular canals and utricular otoliths. These maps and these brainstem projections provide anatomic substrates for specific modulation of postural reflexes and movements evoked by vestibular and optokinetic stimulation. Mossy fiber signaling, although lacking in topographic specificity, contributes to the total background activity of SSs. When CSs are superimposed on a higher background of SSs, they evoke a greater modulation of SSs than when CSs are superimposed on a lower background activity of SSs (Barmack and Yakhnitsa 2008a). The stimulus specificity of this background activity may itself be changed by climbing fiber-evoked LTD or by climbing fiber-evoked inhibitory interneurons. It is the prospect of LTD tuning of parallel fiber signaling that has focused thought about reducing “noise” in mossy fiber!granule cell!parallel fiber throughput. However, the vestibular primary afferent input to lobule X is in phase with the climbing fiber input. This leads to the conclusion that the strongest primary vestibular afferent input to lobule X is the one that is most suppressed by LTD. This makes no sense if the circuitry is meant to reinforce mossy fiber!granule cell!parallel fiber throughput. Rather, it seems possible that the interaction of climbing and mossy fiber signals is necessary to modify the three-dimensional vestibular space configured by vestibular climbing fiber zones in vermal lobule X and the three-dimensional optokinetic space configured in hemispheric lobule X. These spatial arrays are then superimposed on target cell groups in the vestibular and cerebellar nuclei thereby facilitating posture and movement under a variety of vestibular and optokinetic stimulus conditions.

Abnormal Cerebellar Function While most cerebellar dysfunctions can be the consequence of chronic alcoholism (Schapiro et al. 1984), genetic mutation (Zee et al. 1976; Falk et al. 1999; Koeppen 2005), immunological disorders (Hida et al. 1994; Sakai et al. 1995), and neural trauma, our understanding of the contributions of the cerebellum to normal and abnormal movement could be enhanced by efforts to expand our knowledge of factors that contribute to the regulation Purkinje cell discharge. The importance of climbing fiber activity to the regulation of discharge of both CSs and SSs has only recently been demonstrated. The role of climbing fibers in the control of cerebellar signaling may be reflected in the etiology and treatment of cerebellar disease. Specifically, spinocerebellar ataxia (SCA), a CAG repeat disease, is not always restricted to the cerebellum. In SCA-6, degeneration in pre-cerebellar regions also occurs (the vestibular complex, motor cortex, and inferior olive) (Ishikawa et al. 1999; Watase et al. 2008). Detailed analysis of cerebellar disease may implicate the

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inferior olive in other cases, such as in Leigh’s disease (Cavanagh 1994) or in other forms of SCA (Koeppen 2005). The neurological disorder, “mal de debarquement” (Cha et al. 2020), a persistent vertigo, lasting weeks and provoked by a vestibular or visual stimulation, may reflect a challenge to the circuitry of lobules IX and X. In particular, it would seem to indicate a reduced ability to adapt to changed vestibular environments. Serotoninergic 5-HT1A receptor agonists are often administered to provide patient relief from ataxia (Takei et al. 2005). It is assumed that the 5-HT1A therapeutic effects are mediated by Purkinje cell 5-HT1A receptors. However, the therapeutic effects could be mediated by 5-HT1A receptors on olivary neurons that receive serotoninergic projections from neurons in the nucleus reticularis paragigantocellularis (Bishop and Ho 1986). It is possible that circumscribed damage to the brainstem (including the inferior olive) could influence the expression of cerebellar symptoms usually attributed to cerebellar cortical pathology.

Conclusions and Future Directions With the use of recording and cellular labeling techniques in conjunction with controlled vestibular and visual stimulation, it has been possible to identify functional regions of lobules IX–X. Within these regions, the responses of Purkinje neurons and interneurons have been categorized, leading to an enhanced understanding of how the microcircuitry of the cerebellar cortex contributes to antiphasic responses of Purkinje cell complex and simple spikes. Specifically, hemispheric lobule X, the flocculus, can be divided functionally into three discrete regions in which Purkinje cells and molecular layer interneurons are excited by optokinetic stimulation in one of three different directions (Schonewille et al. 2006). An important consequence of anatomical organization is that it is now experimentally feasible to extract stimulus-specific floccular cell types for subcellular analysis. This makes it possible to examine how changes in optokinetic stimulation evoke changes in transcription of mRNA and expression of signaling proteins (Qian et al. 2012; Barmack et al. 2014). With these prospects in mind, the future of cerebellar research begins to embark on a more fundamental effort to understand cerebellar microcircuitry at a molecular level.

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Jan Voogd, Yoshikazu Shinoda, Tom J. H. Ruigrok, and Izumi Sugihara

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cerebellar Nuclei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Subdivision of the Inferior Olive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Afferent Connections of the Inferior Olive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Projections from Spinal Cord, Trigeminal Nuclei, and Dorsal Column Nuclei . . . . . . . . . . . . Projections from the Sensory Nuclei of the Trigeminal Nerve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Projections from the Dorsal Column Nuclei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Optokinetic and Vestibular Projections to the Inferior Olive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Afferents from Tectum and Pretectum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nuclei at the Mesodiencephalic Border: The Central and Medial Tegmental Tracts . . . . . . The Corticonuclear and Olivocerebellar Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Corticonuclear Projection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Olivocerebellar Projection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Nucleo-Olivary Pathway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Olivocerebellar and Corticonuclear Projections in Primates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cerebellar Nuclei: Efferent Connections and Recurrent Climbing Fiber Paths . . . . . . . . . . . The Fastigial Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anterior Interposed Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Posterior Interposed Nucleus and Interstitial Cell Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dentate Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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J. Voogd (*) · T. J. H. Ruigrok Department of Neuroscience, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands e-mail: [email protected]; [email protected] Y. Shinoda · I. Sugihara Department of Systems Neurophysiology, Graduate School of Medicine, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_19

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Abstract

The cerebellar nuclei, together with certain vestibular nuclei, are the target of the axons of the Purkinje cells of the cerebellar cortex. Each of these nuclei receives a projection from a longitudinal Purkinje cell zone. Climbing fiber projections are organized according to the same zonal pattern. In this chapter, we will review the morphology and the circuitry of the cerebellar nuclei and the inferior olive and the recurrent pathways connecting them. Keywords

Cerebellum, corticonuclear connections · Cerebellum, olivocerebellar connections · Inferior olive, afferent commections · Nucleoolivary pathways · Purkinje cell zones

Introduction The cerebellar nuclei, together with certain vestibular nuclei, are the target of the axons of the Purkinje cells of the cerebellar cortex. The projections of the cerebellar nuclei to the brain stem and the distribution of the cerebello-thalamo-cortical paths determine the sphere of influence of the cerebellum. Jansen and Brodal (1940, 1942) were the first to notice that the topographical organization of the Purkinje cell projections to the cerebellar nuclei and the olivocerebellar climbing fiber system is very similar. Marr (1969) formulated this similarity in his learning theory of the cerebellar cortex as “the olivary cell should respond to a command for the same elemental movement as is initiated by the corresponding Purkinje cell.” In this chapter, we will review the morphology of the cerebellar nuclei and the inferior olive, the afferent connections of the olive, the zonal organization of the corticonuclear and olivocerebellar projection, and the efferent connections of the cerebellar nuclei and the presence of recurrent cerebellar-brain stem circuitry.

The Cerebellar Nuclei Four cerebellar nuclei, known as the fastigial emboliform, globose, and dentate nucleus, were distinguished in the human cerebellum by Stilling (1864). The same four nuclei can be distinguished in different mammalian species, where they are known as the medial, anterior interposed, posterior interposed, and lateral cerebellar nucleus (Ogawa 1935; Weidenreich 1899) (Fig. 1). The cerebellar nuclei are arranged in two groups. The rostrolateral group consists of the anterior interposed nucleus (emboliform) that is connected with the lateral (dentate) nucleus. The caudomedial group consists of the medial (fastigial) nucleus with the posterior interposed (globose) nucleus. A fifth cerebellar nucleus, located at the border of the fastigial and posterior interposed nucleus, known as the “interstitial cell groups”

Fig. 1 The cerebellar nuclei of the rat, Macaca fascicularis, and the human cerebellum: dorsal aspect and selected transverse sections. Abbreviations: AI anterior interposed nucleus, bc brachium conjunctivum, CO cochlear nucleus, D micro microgyric part of the dentate nucleus, D dentate nucleus, DLH dorsolateral hump, DLP dorsolateral protuberance, D macro macrogyric part of the dentate nucleus, DV descending vestibular nucleus, E emboliform nucleus, F fastigial nucleus, G globose nucleus, ICG interstitial cell groups, icp inferior cerebellar peduncle, int.nu. basal interstitial nucleus, L lateral cerebellar nucleus, LV lateral vestibular nucleus, Mcm caudomedial subdivision of the medial nucleus, Mn medial subdivision of the medial nucleus, MV medial vestibular nucleus, PI posterior interposed nucleus, SV superior vestibular nucleus, Y group Y

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was distinguished by Buisseret-Delmas and Angaut (1993) in the rat but appears to be present in other mammals (Fig. 1a, b). Three populations of neurons have been distinguished in all cerebellar nuclei. The main population consists of excitatory relay cells with widespread, branching axons, terminating in the brain stem, the spinal cord, and the thalamus. They constitute a mixed population of cells of all shapes and sizes (Courville and Cooper 1970). Most relay cells of the cerebellar nuclei are glutamatergic. Large, glycinergic neurons that give rise to the ipsilateral projections of the fastigial nucleus were identified in mice (Bagnall et al. 2009). Small GABAergic neurons, that project exclusively to the inferior olive, constitute a second population, present in all nuclei (Graybiel et al. 1973; Mugnaini and Oertel 1985) (see also section “The Nucleo-olivary Pathway”). A third population of small interneurons was identified by Chan-Palay (1977) on morphological grounds in the monkey, by Chen and Hillman (1993) as glycinergic neurons, and by Leto et al. (2006) as GABAergic neurons, all in rodents. Glycinergic neurons, with projections to the cerebellar cortex, were described in the mouse lateral cerebellar nucleus (Uusisaari and Knopfel 2010). Before, all recurrent projections from the cerebellar nuclei to the cortex were supposed to originate as collaterals from the relay cells (McCrea et al. 1978). The fastigial nucleus is located next to the midline. In rodents, a prominent protrusion, known as the dorsolateral protuberance (Goodman et al. 1963), is present that is lacking in carnivores and primates (Fig. 1a). The rodent anterior interposed nucleus includes a lateral portion, indicated as the dorsolateral hump that sometimes is allocated to the lateral cerebellar nucleus. A parvocellular subnucleus occupies the ventral part of the lateral cerebellar nucleus in these species. The primate dentate nucleus has the shape of a “crumpled purse” (Chan-Palay 1977) with its hilus directed ventromedially and rostrally. In the human cerebellum, two parts of the nucleus can be distinguished, a microgyric and a macrogyric portion (Fig. 1c). The dorsomedial, microgyric portion is folded in rather narrow, rostrocaudally directed ridges. The ridges in the ventrolateral, macrogyric portion of the nucleus are broad and subdivided, and the cell band in this part of the nucleus is wider than in the microgyric part. The cells of the microgyric part of the dentate are larger than those in the macrogyric position of the nucleus (Demolé 1927a, b), but both subdivisions also contain small neurons. This subdivision had already been noticed by Vicq d’Azyr in the first accurate description of the nucleus lateral, dating from the eighteenth century (Glickstein et al. 2009). The ontogenetic development of the macrogyric portion lags far behind the microgyric (Weidenreich 1899). Unfortunately, there are no indications how the two parts of the human dentate are represented in the monkey dentate. A prominent Y nucleus is present, ventral to the dentate, in the monkey cerebellum (Fig. 1b). It should be distinguished from ill-defined groups of small acetylcholinesterase-positive cells dispersed in the white matter of the flocculus and the nodule and ventral to the dentate and the posterior interposed nucleus, in the roof of the fourth ventricle known as the basal interstitial nucleus (Fig. 1b). The basal interstitial nucleus is reciprocally connected with the flocculus (Langer et al.

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1985) and, possibly, with the nodulus. The group Y is a lateral extension of the superior vestibular nucleus that gives rise to projections to the oculomotor nuclei (Graybiel and Hartwieg 1974; Stanton 1980a; Steiger and Büttner-Ennever 1979; Yamamoto et al. 1986). Langer’s basal interstitial nucleus and the group Y are welldefined nuclei in the monkey cerebellum but have not yet been recognized in the human cerebellum.

Subdivision of the Inferior Olive The inferior olive derives its name from the olive-shaped prominence on the ventrolateral surface of the medulla. The first description of the nuclei of the inferior olive dates from Stilling (1843). He identified the principal olive, the medial accessory olive (as the “grossen Pyramidenkern”), and the dorsal accessory olive (his “Oliven Nebenkern”) in sections through the human medulla oblongata. Sections through the inferior olive of the human brain and of different species that have been used in experimental studies of the connections of the inferior olive are illustrated in Figs. 2 and 3. Diagrams of surface projections of the olivary nuclei, first constructed by Brodal (1940) showing the position of the sections, are included in these figures. Subdivisions of the principal and the accessory olives have been distinguished by inspection of the shape and contour of these nuclei, but their definite identification depends on the recognition of their connections. Moreover, species-specific subdivisions may occur. The medial accessory olive can be subdivided into caudal (MAOc) and rostral (MAOr) parts. The MAOc often has been further subdivided into the mediolaterally disposed subgroups a, b, and c (Fig. 1, rat Section 2, marmoset, Sections 1–3; Fig. 2, macaque monkey, Section 3). This subdivision is not distinct at all levels. Moreover, in the rat, subgroups a–c were distinguished, in addition to the group beta, which forms a fourth, medial subdivision of the MAOc, whereas in the macaque monkey, subgroup c is identical to the group beta. The group beta was first distinguished by Brodal (1940). In the cat and the rabbit, it is aligned with the more rostrally located dorsomedial cell column (DMCC). The DMCC was first distinguished by Bertrand and Marechal (1930) in the human inferior olive as a rostrally located cell group, attached to the medial pole of the DAO and, ventrally, to the medial lamella of the principal olive (Fig. 3, Section 48). This position is even more distinct at late fetal stages (Fig. 3, inset). In the cat and the rabbit, Brodal (1940) identified a cell group with a different position, located dorsomedial to the rostral MAO, as the DMCC (Fig. 2). In the rat, Brodal’s DMCC is present, but it should be distinguished from another subgroup, the dorsomedial group (Azizi and Woodward 1987). The dorsomedial group in the rat is attached to the medial pole of the ventral lamina of the principal olive, a position it shares with the DMCC from Marechal’s original description. In macaque monkeys, the cell group identified as the DMCC is attached to the medial lamella of the PO and/or the medial pole of the DAO and, therefore, occupies the same position as the

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Fig. 2 Diagrams of selected transverse sections through the inferior olive and surface projections of its subnuclei of different mammalian species. (Redrawn from Brodal (1940), rabbit and cat; Ruigrok and Voogd (1990), rat; and Fujita et al. (2010), marmoset). Abbreviations: a, b, c subnuclei a, b, c of the caudal medial accessory olive, ß group beta, DAOc caudal dorsal accessory olive, DAOdf dorsal fold of the dorsal accessory olive, DAOr rostral dorsal accessory olive, DAOvf ventral fold of the dorsal accessory olive, dlPO dorsal lamina of the principal olive, dm dorsomedial group, dmcc dorsomedial cell column, MAOc caudal medial accessory olive, MAOr rostral medial accessory olive, MDO medial part dorsal accessory olive, vlo ventrolateral outgrowth, vlPO ventral lamina of the principal olive

Fig. 3 Diagrams of selected transverse sections through the human inferior olive and of transverse sections and a surface projection of its subnuclei of the macaque monkey (human inferior olive redrawn from Marechal (1934)). Abbreviations: llPO lateral lamina of the principal olive, mlPO medial lamina of the principal olive. For other abbreviations, see Fig. 2

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human DMCC and the rat dorsomedial group (Bowman and Sladek 1973; Brodal and Brodal 1981; Whitworth and Haines 1986a, b) (Figs. 2 and 3). In the marmoset, both cell groups can be distinguished (Fujita et al. 2010). The connections of the two cell groups are different: the DMCC as present in cat, rabbit, and rat receives vestibular input; the dorsomedial group and the monkey DMCC (Fig. 3, right panel, Sections 5 and 6) are innervated by somatosensory systems. A cell group corresponding to the cat DMCC, innervated by the vestibular system, has not been identified in monkeys. At the level of the MAOc, the dorsal cap (DC) of Kooy (1917) is located dorsal to the group beta. More rostrally, it extends medially as the ventrolateral outgrowth (VLO). The dorsal accessory olive can be divided into caudal (DAOc) and rostral (DAOr) parts. In the rat, the DAOc is folded over the DAOr, and the two divisions of the DAO are known as the dorsal and ventral fold of the DAO (Azizi and Woodward 1987). In surface projections, the DAOc typically forms a caudomedially directed extension of the DAO. The principal olive generally is subdivided into dorsal (dlPO) and ventral (vlPO) laminae. In rat, cat, rabbit, and marmoset, the cell band of the vlPO is thinner than the broad cell band of the dlPO. At some levels, a gap or a constriction separates the vlPO from the dlPO in rat and cat. In artiodactyles, the ventral lamina is always separated from the rest of the PO (Whitworth and Haines 1986b). In the macaque monkey, an additional lateral lamina or “bend” was distinguished. In monkeys, the great apes, and in the human inferior olive, the dorsal (dlPO), lateral (llPO), and the lateral portion of the ventral lamina, indicated as the vlPO, display the typical convolutions of the inferior olive. In monkeys, the thin, nonvoluted portion of the vlPO is indicted as the mlPO (Fig. 3). In the human inferior olive, Kooy (1917) and Bertrand and Marechal (1930) described a narrow, medial lamina (mlPO), located medial to the MAO (Fig. 3, Sections 38–51). In rabbit and rat, the medial pole of the DAOr is connected with the dlPO. In the cat and the marmoset, a similar connection exists with the vlPO. In the human and macaque inferior, the DAOr and the laminae of the principal olive remain isolated from each other. The VLO is continuous with the vlPO in the rat and in the human inferior olive and with the dlPO in the rabbit and the cat. No such continuity appears to exist in the marmoset and the macaque monkey.

Afferent Connections of the Inferior Olive Four main categories of afferents of the inferior olive, each with their own distribution, can be distinguished. The inferior olive processes somatosensory input mostly in the MAOc and DAO, vestibular and optokinetic input in the DC/VLO/group beta, and visual information in the medial part of MAOc. The PO and MAOr process information relayed by nuclei at the mesodiencephalic border from the cerebral

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cortex. However, overlap between the various modalities within olivary subnuclei has been noted. Below, we provide a more detailed account of these projections.

Projections from Spinal Cord, Trigeminal Nuclei, and Dorsal Column Nuclei Ventral Spino-Olivary Pathways Spino-olivary fibers originate mainly from the contralateral cervical and lumbar gray matter, ascend in the ventral funiculus, and terminate in the caudal MAOc and, laterally, in caudal and rostral parts of the DAO (Fig. 4) (Boesten and Voogd 1975; Armstrong and Schild 1979; Armstrong et al. 1982). The system has been described in different mammalian species, but not in monkeys (Brodal et al. 1950; Brown et al. 1977; Martin et al. 1980; Mizuno 1966; Swenson and Castro 1983a, b; Whitworth and Haines 1983). Detailed information on the anatomy and the physiology of the Fig. 4 The ventral funiculus spino-olivary pathway in the cat. The origin of this system is illustrated in diagrams of the lumbosacral cord for cells retrogradely labeled from the entire DAO (L5-S3, Molinari 1984) and from the caudal MAO and DAO (L6-L7, Molinari 1985), the low cervical (Armstrong et al. 1982), and high cervical cord (Richmond et al. 1982). Projections from these levels to the contralateral MAOc and DAOc show much overlap, and a more distinct topical projection is present in the DAOr (Armstrong et al. 1982; Boesten and Voogd 1975). A projection from the contralateral spinal trigeminal nucleus (Trig) occupies the rostromedial MAOc and the medial DAOr (Courville et al. 1983b). (Redrawn from illustrations of the cited papers). For abbreviations, see Fig. 1

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ventral funiculus olivocerebellar pathway (vfSOCP) (Oscarsson and Sjölund 1977a, b, c) is available for the cat (Fig. 22a). Spino-olivary fibers originate from the medial ventral horn (Rexed’s (1952) lamina VIII), the nucleus proprius of the dorsal horn (laminae IV/V), cells in the lateral funiculus, and the intermediate gray (lamina VII). Except for lower cervical levels, all neurons giving rise to spino-olivary fibers are located contralaterally. The majority of the system takes its origin from the lumbar and sacral cord; the contribution of the thoracic cord is negligible and of the cervical cord rather small. The lateral cervical nucleus does not contribute to the projection (Armstrong and Schild 1979; Armstrong et al. 1982; Buisseret-Delmas 1982; Molinari 1984, 1985; Richmond et al. 1982). Lumbar and sacral spino-olivary fibers terminate ventrolaterally in the MAOc, overlapping with the projection from the cervical cord that extends more medially. A similar overlap of sacrolumbar and cervical afferents is present in the caudal DAO. In the rostral DAO, a distinct somatotopical organization is present, with lumbar and cervical fibers terminating in increasingly more medially located lamellae (Armstrong et al. 1982; Boesten and Voogd 1975; Richmond et al. 1982). A very similar somatotopical organization was found in the DAO of the cat for the distribution of evoked potentials on peripheral stimulation (Fig. 5) (Gellman et al. 1983). Evoked potentials from light cutaneous stimuli predominate over deep input from muscles Fig. 5 Somatotopical localization in the dorsal accessory olive of the cat. (Redrawn from Gellman et al. 1983)

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and fascia in DAOr, and the latter predominate in the DAOc. These recordings represent the combined projections from the ventral and the dorsal column spinoolivary pathways. Projections to the MAOc and the DAOc originate mainly from the medial ventral horn and projections to the DAOr from the dorsal horn. The intermediate gray projects to both accessory olives (Molinari 1984, 1985). Spino-olivary fibers terminate as boutons containing spherical vesicles, with asymmetrical synapses on dendritic shafts and spines, more inside than outside the glomeruli (King et al. 1975; Molinari and Starr 1989).

Projections from the Sensory Nuclei of the Trigeminal Nerve The sensory trigeminal nuclei project to the extreme medial part of the contralateral DAOr (Cook and Wiesendanger 1976) and, in addition, to the adjoining vlPO in the cat and the rabbit (Van Ham and Yeo 1992), to the dorsomedial group in the rat (Huerta et al. 1983), and to a separate region in the vlPO in the rabbit (Van Ham and Yeo 1992). No terminations are present in the dorsomedial cell column in any of these species (Fig. 6). In the MAOc, the trigeminal nuclei project to its rostromedial Fig. 6 Localization of projections of the contralateral spinal trigeminal nucleus illustrated in a rostral and a more caudal section through the inferior olive of the rat (Huerta et al. 1983), the cat (Berkley and Hand 1978), and in transverse sections and a diagram of the flattened inferior olive of the rabbit (Van Ham and Yeo 1992). For abbreviations, see Fig. 2

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region, next to the rostral pole of the group beta in all species where they overlap with the terminals from the cuneate nucleus (see section “Projections from the Dorsal Column Nuclei” and Fig. 6c). In the cat, the projection extends more caudally, overlapping with the terminals from the cervical cord (Fig. 6). Interestingly, terminations in the rat DAOr were identified as collateral projections of the trigemino-tectal pathway, but the projection of the trigeminal nuclei to the MAOc is an unbranched system (Huerta et al. 1983). No data on the trigemino-olivary projection are available for primates. Most authors agree that the main origin of the trigemino-olivary projection is located in the pars interpolaris of the spinal nucleus (Huerta et al. 1983; Huerta and Harting 1984; Swenson and Castro 1983a; Van Ham and Yeo 1992; Walberg 1982), although some also include the principal sensory nucleus and the pars caudalis.

Projections from the Dorsal Column Nuclei Two fiber systems occupy the dorsal columns: the ascending branches of the dorsal root fibers and the postsynaptic dorsal column pathway that contains an extra synapse in the dorsal horn (Fig. 7). Both pathways transmit somatosensory

Fig. 7 The dorsal funiculus spino-olivary pathway in the cat. (a) Both ascending collaterals from spinal root fibers and the postsynaptic dorsal column pathway participate in the projection to the dorsal column nuclei. Projections to the inferior olive take their origin from regions outside the cell clusters (cl) that give origin to the medial lemniscus. (b) Projections from the contralateral gracile nucleus (Boesten and Voogd 1975). (c) Projections from the contralateral gracile and internal cuneate nuclei (Boesten and Voogd 1975). (d) Projections from the contralateral cuneate nucleus (Groenewegen et al. 1975) (b–d redrawn from illustrations of the cited papers). Abbreviations: CE external cuneate nucleus, Cui internal cuneate nucleus, GR gracile nucleus. For other abbreviations, see Fig. 2

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information to the dorsal column nuclei, but the latter pathway has been shown to be responsible for the transmission of nociceptive input to the inferior olive in the cat (Ekerot et al. 1991). The connectivity in the dorsal funiculus spino-olivocerebellar pathway (df-SOCP) has been extensively studied by Ekerot and Larson (1979a, b) (Fig. 22b). In the dorsal column nuclei of the cat, the fusiform cells that project to the contralateral inferior olive are located outside the cell cluster regions of the internal and gracile nuclei, which give rise to the medial lemniscus (Fig. 8). Neurons of the gracile nucleus that project to the rostral and caudal DAO accumulate rostral to the cluster region in the transitional portion of the nucleus. The main projection is to the DAOr. The numbers of the cells labeled from injections of retrograde tracers in the DAOc and the MAOc are small (Molinari 1984, 1985). A wider distribution of neurons with projections to the inferior olive was found for the internal cuneate nucleus (Alonso et al. 1986; Buisseret-Delmas 1982) (Fig. 8). The projections from the gracile and internal cuneate nuclei occupy lateral and more medial bands in the DAOr and mostly spare the DAOc (Fig. 7b, d). A minor projection from the gracile nucleus is present in the MAOc (Figs. 7b and 8). Terminals from the internal cuneate nucleus are found in the rostromedial MAOc at its border with the MAOr (Fig. 7c), a region that also receives a projection from

Fig. 8 Localization of neurons of the dorsal column nuclei projecting to the contralateral inferior olive in the cat. Left panels (blue) show the location of neurons in the gracile nucleus and the rostrocaudal distribution of neurons projecting to the entire DAO, the MAOc and the DAOc, and the MAOc only (Molinari 1984, 1985). Right panel shows the distribution of neurons of the internal cuneate nucleus after large injections of a retrograde tracer in the inferior olive (Alonso et al. 1986). (Redrawn from illustrations of the cited papers). Abbreviations: AP area postrema, Cui internal cuneate nucleus, GR gracile nucleus

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the spinal trigeminal nucleus (Fig. 5). Projections to the ipsilateral inferior olive from the dorsal column nuclei, described by several authors, may originate from the adjoining reticular formation (Courville et al. 1983b). Few data are available for the projection of the dorsal column nuclei to the inferior olive in monkeys. Sections of cases from Kalil (1979) and Molinari et al. (1996), illustrated in Fig. 9, show terminations in the DAOr, the DMCC, and the rostromedial MAOc. These projections are in accordance with the findings in cats, with the exception of the DMCC that receives vestibular, rather than somatosensory input in this species. It may be that the monkey DMCC corresponds to the dorsomedial group, as identified in the rat, rather than with the DMCC of other species. Electron microscopic studies of the dorsal column-olivary projection documented its terminals as excitatory boutons with spherical vesicles and asymmetrical synaptic contacts (Molinari et al. 1991). GABAergic neurons in the cuneate and less in the gracile nucleus, with projections to the contralateral inferior olive, were observed by Nelson and Mugnaini in the rat (1989). Alternative routes for the transmission of peripheral input to the inferior olive are provided by ascending spinal, trigeminal, and dorsal column pathways terminating in the pretectum that innervates the DAOr (see below), in Darkschewitsch nucleus that innervates the DAOr, or in the parvocellular red nucleus that innervates the principal olive (Wiberg and Blomqvist 1984a, b; Wiberg et al. 1986, 1987).

Optokinetic and Vestibular Projections to the Inferior Olive The optokinetic system with its projections of the nuclei of the accessory optic system and the nucleus of the optic tract in the mesencephalon to the dorsal cap (DC) and the ventrolateral outgrowth (VLO) recently was reviewed by Giolli et al. (2006), Barmack (2006), and Voogd (Voogd and Barmack 2006; Voogd et al. 2011). Fig. 9 Projections from the internal cuneate nucleus of the macaque monkey. (a) is the most rostral section (a and d redrawn from Kalil (1979), c and d from Molinari et al. (1996)). Abbreviations see Fig. 2

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For complete references, we refer to these reviews. DC and VLO receive information on global movements of the visual surround from large field ganglion cells in the contralateral retina via the optic tract (Fig. 10a). These movements generate retinal slip signals, which can serve as an error signal in long-term adaptation of the vestibulo-ocular and optokinetic reflexes. The retinal slip signals around a vertical axis excite neurons of the nucleus of the optic tract and the dorsal nucleus of the accessory system. These nuclei project to the DC of the ipsilateral inferior olive. Global movements of the visual surround around an oblique horizontal axis at 45° azimuth, that is approximately colinear with the axis of the ipsilateral anterior semicircular canal, are transmitted bilaterally by the medial and lateral nuclei of the accessory optic system and contralaterally by the visual tegmental relay zone. These nuclei project to the VLO. The organization of the accessory optic system and the projections of its subnuclei to the inferior olive in primates are very similar to that in lower mammals. The border between the projections of vertical axis and horizontal axis neurons in the rabbit is located halfway within the dorsal cap. Consequently, the two functional subdivisions in this species correspond to the VLO and the rostral

Fig. 10 Optokinetic and vestibular afferents of the inferior olive. (a) Projection of the nuclei of the accessory optic system and the nucleus of the optic tract on to the dorsal cap and the ventrolateral outgrowth. (b) Map of the projection of the paramedian pontine reticular formation to the dorsal cap in the cat (Gerrits and Voogd 1986). Abbreviations: bc brachium conjunctivum, cp cerebral peduncle, D dorsal nucleus of the accessory optic system, DC dorsal cap, dlPO dorsal lamina of the principal olive, L lateral nucleus of the accessory optic system, LGB lateral geniculate body, ll lateral lemniscus, M medial nucleus of the accessory optic system, MGB medial geniculate body, NRTP nucleus reticularis tegmenti pontis, NTO nucleus of the optic tract, opt.tr optic tract, Pc posterior commissure, PPRF paramedian pontine reticular formation, transped.tr transpeduncular tract, V trigeminal nerve, VLO ventrolateral outgrowth, vlPO ventral lamina of the principal olive, VTRZ ventral tegmental reflex zone

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dorsal cap that relay information from horizontal axis neurons and the caudal dorsal cap that serves as the relay for the vertical axis neurons. The VLO merges with the vlPO, and the vertical axis subdivision may spill over in this lamina in species like the rat. The DC and the VLO receive additional input from the paramedian reticular formation (Fig. 10b), the dorsal group Y, and the nucleus prepositus hypoglossi (Fig. 11a). The paramedian reticular formation is involved in the generation of saccades. Its projection to the dorsal cap has been identified only in the cat (Gerrits and Voogd 1986). The dorsal group Y is located within the floccular peduncle and is the target of Purkinje cell zones influencing eye movements about a similar horizontal axis as the cells of the VLO. In the cat, it projects to the contralateral VLO (Gerrits et al. 1985), and in the rabbit, this projection also includes the rostral DC (De Zeeuw et al. 1994a). This projection is GABAergic. The nucleus prepositus hypoglossi has a role in gaze holding. Separate neuronal populations connect it with the horizontal gaze center in the paramedian reticular formation, the vestibular nuclei, the cerebellum, and the inferior olive (McCrea and Baker 1985). The projection of the nucleus prepositus hypoglossi to the dorsal cap is contralateral in

Fig. 11 (a) Injection sites of antegrade tracers in different parts of the vestibular nuclei, the group Y and the nucleus prepositus hypoglossi, and their projections to the inferior olive. (Redrawn from Gerrits et al. 1985). Additional projections of the group Y to the contralateral group beta (Barmack 2006) and of the nucleus prepositus hypoglossi to the ipsilateral dorsal cap (De Zeeuw et al. 1993) are hatched. (b) Projection of the parasolitary nucleus to the group beta in the rat. (Redrawn from Barmack et al. 1998). Abbreviations: F fastigial nucleus, IA anterior interposed nucleus, L lateral cerebellar nucleus, Y group Y, FlO flocculus, LV lateral vestibular nucleus, DV descending vestibular nucleus, MV medial vestibular nucleus, PrH nucleus prepositus hypoglossi, S nucleus of the solitary tract, CE external cuneate nucleus, CU internal cuneate nucleus, PO principal olive, vlo ventrolateral outgrowth, dc dorsal cap, dmcc dorsomedial cell column, MAO medial accessory olive, ß group beta

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the cat and rat (Barmack et al. 1993; Gerrits et al. 1985) but bilateral in the rabbit (De Zeeuw et al. 1993). This projection consists of a mixture of cholinergic and GABAergic afferents and of elements expressing both transmitters (Barmack et al. 1993; De Zeeuw et al. 1993). According to Barmack (2006), vestibular input to the group beta and the DMCC is organized as a simple push-pull system, with excitatory input from the group Y and inhibition from the parasolitary nucleus. A projection of the group Y to the contralateral DMCC (but not to the group beta) was traced in the cat (Gerrits et al. 1985) (Fig. 11a) but not in the rabbit (De Zeeuw et al. 1994a) where this system, moreover, was found to be GABAergic. The parasolitary nucleus is located lateral to the solitary nucleus, next to the caudal pole of the descending vestibular nucleus (Fig. 11b). It receives root fibers from branches of the vestibular nerve that innervate the ampullae of the vertical canals and the utriculus. Its small, compact neurons provide the ipsilateral group beta and the DMCC with inhibitory synapses (Barmack et al. 1998; Loewy and Burton 1978; Molinari and Starr 1989). Projections of the medial and descending vestibular nuclei to the ipsilateral group beta and the DMCC were found by several authors in cat, rat, and rabbit (Barmack et al. 1993; Brown et al. 1977; Gerrits et al. 1985; Nelson and Mugnaini 1989; SaintCyr and Courville 1979; Swenson and Castro 1983a) (Fig. 11a). Signals from the ipsilateral anterior semicircular canals, relayed through the parasolitary nucleus, are mapped upon the caudal group beta, signals from the posterior canal onto its rostral part. There are no projections from the horizontal canal. DMCC neurons respond preferentially to otolithic stimulation. The pattern of vestibularly modulated activity in DMCC neurons is consistent with an inhibitory vestibulo-olivary projection, supposedly from the parasolitary nucleus (Barmack 2006).

Afferents from Tectum and Pretectum A contralateral projection of the superior colliculus to the medial MAOc, located next to the group beta, was demonstrated in rat, cat, rabbit, and monkey (Frankfurter et al. 1976; Harting 1977; Hess and Voogd 1986; Holstege and Collewijn 1982; Saint-Cyr and Courville 1982; Weber et al. 1978) (Fig. 12c). It takes its origin from the fourth, intermediate gray lamina of the superior colliculus. When Weber’s et al. (1978) plot of the neurons that were labeled retrogradely from the inferior olive (Fig. 12b) is examined, these neurons appear to be located in layers or patches in the superficial and deep parts of the intermediate gray. Huerta and Harting (1984) found similar patches of neurons with projections to the inferior olive to be arranged in a grid in the intermediate gray layer that also contains neurons with projections to the trigeminal nuclei and those giving rise to the predorsal fascicle (Fig. 12a). The functional meaning of this organization is not known. In the rat MAOc, the tectoolivary projection remains separated from the more laterally and rostrally terminating trigemino-olivary pathway (Akaike 1989). The ventral anterior pretectal nucleus and scattered neurons in the pretectum, that may belong to the dorsal pretectal nucleus and the nucleus of the posterior

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Fig. 12 Projections to the inferior olive from the tectum and the pretectum. (a–c) The tecto-olivary projection. (a, b) Tecto-olivary neurons in the cat are located in the intermediate gray layer as part of a grid, where they alternate with tectospinal (green) and tectotrigeminal (yellow) neurons. (Redrawn from Huerta and Harting (1984) and Weber et al. (1978)). (c) Termination in the rat of tecto-olivary projection in medial MAOc (Akaike 1992). (d, e) The pretecto-olivary projection in the cat. (d) Origin from the anterior pretectal nucleus (Kitao et al. 1989). (e) Termination in the DAOr (Kawamura and Onodera 1984). Abbreviations: APN anterior pretectal nucleus, CG central gray, Cp posterior commissure, DAO dorsal accessory olive, GC central gray, II-V layers II-V of the superior colliculus, MAO medial accessory olive, MAO neurons projecting to MAOc, R red nucleus, THAL thalamus, tsp tectospinal neurons, ttr tectotrigeminal neurons

commissure, have been found to project to the ipsilateral DAOr in the rabbit and cat (Itoh et al. 1983; Kawamura and Onodera 1984; Kitao et al. 1989) (Fig. 12d, e). These nuclei receive afferents from the dorsal column nuclei. In the DAOr, the projections from the pretectum and the dorsal column nuclei overlap (Kawamura et al. 1982; Bull et al. 1990).

Nuclei at the Mesodiencephalic Border: The Central and Medial Tegmental Tracts The origin of the central tegmental tract, one of the main fiber systems of the human brain stem, from the parvocellular red nucleus and its termination in the principal olive, was established by Verhaart (1936).

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The medial tegmental tract was discovered by Ogawa (1939) in the cat. It arises from the region surrounding the fasciculus retroflexus, including Darkschewitsch nucleus in the rostral central gray, descends along the raphe in the ventral part of the medial longitudinal fascicle, and terminates in the MAOr and the vlPO. The presence of the two tegmental tracts, one arising from the parvocellular red nucleus, that innervate the principal olive and the other from different nuclei surrounding the fasciculus retroflexus, innervating MAOr, has been confirmed in different species, including humans (Voogd 2004). The mesodiencephalic projections were analyzed in great detail by Onodera (1984) in the cat (Fig. 13). This author distinguished a series of nuclei, surrounding the fasciculus retroflexus with projections to the ipsilateral inferior olive. Darkschewitsch nucleus projects to the MAOr and less intensely to the DMCC. Bechterew’s nucleus connects with the vlPO and the parvocellular red nucleus with the dlPO. A rather vague projection of Cajal’s interstitial nucleus and/or the prerubral Fig. 13 Connections of the parvocellular red nucleus and other nuclei at the mesodiencephalic border to the inferior olive in the cat. Projections of the cerebral cortex to these nuclei are indicated in the upper diagram of rostral view of the cerebral hemisphere. (Lower panels redrawn and modified from Onodera (1984)). Abbreviations: aq aqueduct, B Bechterew’s nucleus, D Darkschewitsch nucleus, DAOc/r caudal/rostral dorsal accessory olive, dc dorsal cap, dmcc dorsomedial cell column, FEF frontal eye fields, IC interstitial nucleus Cajal, MAOr/c rostral/caudal part of medial accessory olive, prf prerubral field, r fasciculus retroflexus, Rp parvocellular red nucleus, ß group beta, vl/ dlPO ventral/dorsal lamina of the principal olive, Vlo ventrolateral outgrowth

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field was found to the lateral MAOc and the VLO. A topographic arrangement was found for the parvocellular red nucleus, with its lateral portion projecting to rostral and its medial portion to caudal dlPO. Similarly, dorsolateral Darkschewitsch nucleus projects to caudal MAOr and its ventromedial portion to rostral MAOr (Porter et al. 1993). The connections of the parafascicular region with the inferior olive in the rat were reviewed by Ruigrok (2004). Although details on this system in the rat are not known, it seems likely that its organization is very similar to that of the cat. Strominger et al. (1979) found these connections to be very similar in monkey (Fig. 14), although they were not able to provide definite proof of the projection of Darkschewitsch nucleus to the MAOr; in Fig. 14, this projection is illustrated in analogy with the cat. The dorsomedial subnucleus of the parvocellular red nucleus, located medial to the fasciculus retroflexus, represents Bechterew’s nucleus and projects to the vlPO. The main lateral and caudal parts of the parvocellular red nucleus project topographically to dlPO and llPO, with lateral parts projecting medially in dlPO and medial parts more laterally. Thus, it transmits the somatotopical organization of this nucleus, imposed upon it by the cerebral cortex. The terminations in the PO are distributed in alternating bands of high and low density. The significance of this pattern is not known but may indicate a more precise topical organization of the system. The preolivary nuclei at the mesodiencephalic border receive afferents from the cerebellum and from the cerebral cortex. Direct cortico-olivary connections have been observed but appear to be rather scanty (see Saint-Cyr (1983) for a review and Borra et al. (2010) for a more recent observation). Darkschewitsch’s nucleus receives a cerebellar projection from the posterior interposed nucleus (Fig. 32a). The fastigial and dentate nuclei have been mentioned as possible afferent sources. In monkeys, the dentate nucleus projects to the parvocellular red nucleus, with a termination from its ventrocaudal part in the dorsomedial nucleus and of its dorsal and rostral parts in its main ventrocaudal portion (Stanton 1980b; Voogd 2004) (Fig. 32b, c). In the cat, cortical afferents to the nuclei of the mesodiencephalic border stem from the frontal eye fields and the areas 4, 6, and 3 (Miyashita and Tamai 1989; Nakamura et al. 1983; Saint-Cyr 1987). These areas project to Darkschewitsch’s nucleus and the parvocellular red nucleus (Fig. 13). Afferents from posterior parietal cortex terminate in the parvocellular red nucleus (Oka 1988). Bechterew’s nucleus was not considered as a separate nucleus in these studies. Through the topical projection of Darkschewitsch’s nucleus to the MAOr, the rostral pole of this nucleus receives oculomotor and its caudal part MAOr skeletomotor input (Porter et al. 1993). The corticorubral projection has been studied in greater detail in monkeys (Fig. 14). The total cortical area projecting to the parvocellular red nucleus was determined by Humphrey et al. (1984) (Fig. 14, stippled). It includes areas 4, 6, and 8 and the posterior parietal cortex area 7, extending into the dorsal bank of the intraparietal cortex. It originates from a specific set of pyramidal neurons in upper layer 4 (Catsman-Berrevoets et al. 1979). The projection of the motor cortex to the

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Fig. 14 Connections of the parvocellular red nucleus and other nuclei at the mesodiencephalic border to the inferior olive in the monkey. Origin of projections to these nuclei is indicated in the upper diagram of the cerebral hemisphere. Stippled pre- and postrolandic areas contain all neurons retrogradely labeled from the parvocellular red nucleus (Humphrey et al. 1984). Antegrade tracing was performed from frontal eye fields, primary ventral premotor, supplementary motor, and posterior parietal areas. Projections from primary motor and supplementary motor areas to the parvocellular red nucleus are somatotopically arranged. Projections to the inferior olive, illustrated in a transverse section at the bottom of the figure, were redrawn from Strominger et al. (1979). Abbreviations: aq aqueduct, D Darkschewitsch’s nucleus, dl/ll/vlPO dorsal/lateral/ventral lamina of the principal olive, DM dorsomedial subnucleus of the parvocellular red nucleus (Bechterew’s nucleus), FEF frontal eye field, M1 primary motor cortex, MAOr rostral medial accessory olive, SEF supplementary eye field, SMA supplementary motor area

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magnocellular red nucleus is differently organized: it stems from neurons in deep layer 4 and constitutes a collateral projection of the pyramidal tract. The frontal eye field projects to Darkschewitsch’s nucleus and the dorsomedial subnucleus of the parvocellular red nucleus and the supplementary eye field to the dorsomedial subnucleus only (Burman et al. 2000; von Hartmann-Monakow et al. 1979; Huerta and Kaas 1990; Huerta et al. 1986; Kuypers and Lawrence 1967; Leichnetz 1982; Leichnetz et al. 1984; Shook et al. 1990). The main lateral and caudal part of the parvocellular red nucleus receives overlapping, somatotopically arranged projections from the primary motor cortex, the supplementary motor area, and ventral and dorsal premotor area (Burman et al. 2000; von Hartmann-Monakow et al. 1979; Jürgens 1984; Kuypers and Lawrence 1967; Leichnetz et al. 1984; Orioli and Strick 1989; Tokuno et al. 1995; Wiesendanger and Wiesendanger 1985). Posterior parietal afferents mainly terminate in Darkschewitsch’s nucleus; the projection to the parvocellular red nucleus is sparse (Burman et al. 2000; Faugier-Grimaud and Ventre 1989; Leichnetz 2001). Prefrontal projections from the prearcuate cortex dorsal to the principal sulcus, specifically from area 9, were noticed by Leichnetz (Leichnetz and Gonzalo-Ruiz 1996; Leichnetz et al. 1984). Because direct connections of the cerebral cortex with the inferior olive are few, most are shunted through the nuclei of the mesodiencephalic border. Alternative pathways use other preolivary nuclei such as ventral regions of the dorsal column nuclei that may serve as a relay between the motor cortex and the DAO and the MAOc in cat and rat (Ackerley et al. 2006; Andersson 1984; McCurdy et al. 1992). This region also receives a projection from the contralateral magnocellular red nucleus. Reports on inhibition of transmission in the inferior olive by rubral or cortical stimulation (Gibson et al. 2002) may be related to the presence of GABAergic neurons in this region that project to the inferior olive (Nelson and Mugnaini 1989). Another alternative pathway for inhibition of the DAOr passes through the anterior interposed nucleus, which receives a collateral projection from the rubrospinal tract (Huisman et al. 1983) and the nucleo-olivary pathway from this nucleus.

The Corticonuclear and Olivocerebellar Projections The Corticonuclear Projection The concept of the longitudinal zonal organization of the corticonuclear projection resulted from a combination of Weidenreich’s subdivision of the cerebellar nuclei with observations on the presence of parasagittally oriented white matter compartments in the cerebellum of the ferret and the cat (Voogd 1964, 1969). With the Häggqvist myelin stain, bundles of medium-sized myelinated Purkinje cell axons could be distinguished in the cerebellar white matter separated by narrow slits that contain small myelinated fibers only (Fig. 15). Each compartment channels the Purkinje cell axons from a longitudinal Purkinje cell zone to a particular cerebellar nucleus. These Purkinje cell zones are illustrated for the ferret in Fig. 16. The A zone

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Fig. 15 Reconstruction of the white matter compartments in the anterior lobe of the cerebellum of the ferret. Each compartment contains the cerebellar target nucleus of the corresponding Purkinje cell zone, illustrated in the A compartment with the fastigial nucleus. Bottom photograph: border between compartments A and B. Häggqvist stain

is present in the entire vermis and projects to the fastigial nucleus. The B zone occupies the lateral vermis of the anterior and posterior lobes; Deiters’ lateral vestibular nucleus is its target nucleus. The C1 and C3 zones merge in the ventral anterior lobe. They extend into the simplex lobule. C3 reappears in the Crus II and terminates in the rostral paramedian lobule; C1 is present in the medial paramedian lobule. C1 and C3 project to the anterior interposed nucleus. The C2 zone extends over the entire cerebellum, from lobule II of the anterior lobe to the paraflocculus and the flocculus. It connects with the posterior interposed nucleus. The D zone occupies the lateral hemisphere. In the ansiform lobule and the paraflocculus, it is divided into the medial D1 and the lateral D2 zones that project to ventrocaudal and rotrodorsal parts of the dentate nucleus, respectively. This longitudinal pattern in the corticonuclear projection was confirmed with retrograde axonal transport from the cerebellar nuclei (Fig. 17) (Bigaré 1980; Voogd and Bigaré 1980) and by Trott et al., using antegrade axonal tracing methods (Trott and Armstrong 1987; Trott et al. 1998), both in the cat. The B zone now was found to be restricted to the anterior vermis. Moreover, an injection of the lateral vestibular nucleus also produced labeled Purkinje cells in the anterior A zone (Fig. 17b).

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Fig. 16 Reconstructions of the Purkinje cell zones of the cerebellum of the ferret. (Redrawn from Voogd 1969). Abbreviations: ANS ansiform lobule, ANT anterior lobe, PFL paraflocculus, PMD paramedian lobule, SI simplex lobule

Exclusive labeling of this subpopulation was obtained from injections of the medial vestibular nucleus (Fig. 17c). In the dorsal anterior lobe, a gap between the labeled Purkinje cells in the A and B zones contains the X zone (Fig. 17c, arrow). In the anterior lobe, D1 and D2 zones are restricted to its dorsal folia. A very similar pattern in the corticonuclear projection was described for the anterior lobe of the macaque, the squirrel monkey, and the bush baby and for the paramedian lobule and the paraflocculus of Tupaia glis using Nauta’s silver impregnation for degenerated axons (Haines et al. 1982). White matter compartments in the macaque monkey, delineated by the accumulation of acetylcholinesterase at the borders of the compartments, were found to be arranged like in the cat (Hess and Voogd 1986; Voogd et al. 1987a, b). The zonal organization of the corticonuclear projection was confirmed for the rat by Buisseret-Delmas with antegrade axonal transport of horseradish peroxidase (Buisseret-Delmas and Angaut 1993). In addition to the earlier identified set of zones, they described additional X, A2, and Y zones (Fig. 18). The X zone is located between the A and B zones in the dorsal anterior lobe; it was first identified in electrophysiological experiments on the olivocerebellar projection (see below). It projects to cell groups located between the fastigial and posterior interposed nucleus, known as the interstitial cell groups (Trott and Armstrong 1987; Trott et al. 1998). The A2 zone is located in the medial hemisphere of the simplex lobule and the Crus II (Akaike 1992). The dorsolateral protuberance of the fastigial nucleus is the target of its corticonuclear projection. The Y zone (Buisseret-Delmas’ D0 zone) projects to

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Fig. 17 Reconstructions of the anterior lobe (1), the dorsal aspect (2), and the posterior aspect (3) of the cerebellum of the cat, showing labeled Purkinje cells after injections of a retrograde tracer in a particular cerebellar nucleus. For each panel, the injected nucleus (MV medial vestibular nucleus) and the labeled Purkinje cell zone (A zone) is indicated. (Redrawn from Bigaré 1980; Voogd and Bigaré 1980). Abbreviations: AI anterior interposed nucleus, ANS ansiform lobule, ANT anterior lobe, Cr I/II Crus I/II, Dc caudal dentate nucleus, Dr rostral dentate nucleus, F fastigial nucleus, LV lateral vestibular nucleus, MV medial vestibular nucleus, PFL paraflocculus, PI posterior interposed nucleus, PMD paramedian lobule, SI simplex lobule

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Fig. 18 Diagram of the zonal organization of the cerebellum of the rat. (a) Diagram of the flattened cerebellar cortex, the Purkinje cell zones are shown in the right half of the diagram. (b) Cerebellar and vestibular target nuclei of the Purkinje cell zones. (c) Diagram of the flattened inferior olive, showing subnuclei with projections to the Purkinje cell zones and their target nuclei. (d) Diagram of the zebrin-positive and zebrin-negative bands. Abbreviations: A-D2 Purkinje cell zones A-D2, 1–7 zebrin-positive bands P + 17, AI anterior interposed nucleus, Beta cell group beta, c caudal (MAO or DAO), C subnucleus C of the caudal MAO, DAO dorsal accessory olive, Dc caudal subnucleus of the dentate nucleus, DC dorsal cap and ventrolateral outgrowth, DLP dorsolateral protuberance of the fastigial nucleus, DMCC dorsomedial cell column, DM dorsomedial group, Dr rostral subnucleus of the dentate nucleus, F fastigial nucleus, i intermediate MAO, ICG interstitial cell groups, LV lateral vestibular nucleus, MAO medial accessory olive, PI posterior interposed nucleus, PO principal olive, r rostral (MAO or DAO), vest vestibular nuclei

the dorsolateral hump of the anterior interposed nucleus. Buisseret-Delmas located the Y zone between C3 and D1. In studies of the olivocerebellar projection, it was found to occupy a more lateral position, between D1 and D2 (Fig. 18).

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Another aspect of the corticonuclear projection was highlighted by the application of immunohistochemical methods, that distinguished between two populations of zonally distributed Purkinje cells, one population immunoreactive for zebrin (zebrin II: aldolase C) and a second population that was zebrin-negative. Alternating zebrin-positive and zebrin-negative bands are arranged in a reproducible pattern (Fig. 23). Axons of zebrin-positive Purkinje cells converge upon ventrocaudal and lateral parts of the cerebellar nuclei, and axons from zebrin-negative Purkinje cells terminate more rostrally (Fig. 25b). The use of the zebrin pattern as a template for the study of the olivocerebellar projection is considered in section “The Olivocerebellar Projection.”

The Olivocerebellar Projection In early morphological studies of the olivocerebellar projection, the origin of the climbing fibers from the inferior olive was not known. Axonal tracing methods visualizing the climbing fibers only became available in 1974 (Desclin 1974). Their origin from the olive had been established by Eccles et al. (1966), and Oscarsson and his group in Lund, acting on this observation, started their studies on spinoolivocerebellar climbing fiber paths (SOCPs) in the same year (Oscarsson and Uddenberg 1966). The first attempt at a map of the topographical organization of the olivocerebellar projection was by Holmes and Steward (1908) (Fig. 19). It remains the only diagram of its sort for the human cerebellum. The diagram shares its lobular organization with the diagrams produced for the olivocerebellar projection in rabbit and cat by Brodal 30 years later (Brodal 1940) (Fig. 20). Different subdivisions of the olive project to different lobules. The anterior lobe is an exception. In the rabbit, the extreme lateral portion of the anterior lobe, the “hemisphere proper,” receives afferents from the rostral pole of the principal olive. The accessory olives project to the vermis and to a paravermal, intermediate zone. This tripartition was confirmed in later studies of Jansen and Brodal (1940, 1942) of the corticonuclear projection, where the vermis was found to project to the fastigial and the vestibular nuclei, the intermediate zone to the interposed nucleus, and the hemisphere to the lateral cerebellar nucleus. These observations lead these authors to the conclusion that olivocerebellar and corticonuclear projections are arranged according to the same zonal pattern. The three-zonal arrangement only applies to the anterior lobe and the simplex lobule. Attempts have been made to extrapolate it to the posterior lobe, but these attempts have not met with much success. The conclusions of Voogd (1969) and Groenewegen and Voogd (1977) and Groenewegen et al. (1979) on the longitudinal zonal organization of the olivocerebellar projection were based on the observation that olivocerebellar fibers from subnuclei of the inferior olive use the white matter compartments to terminate on Purkinje cells of the corresponding longitudinal zone and, as collaterals, on its target nucleus. The organization of the olivocerebellar system is not a lobular but a zonal one.

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Fig. 19 Diagram illustrating the topographical relations between the inferior olive and the human cerebellum. The dorsal accessory olive and the medial half of the dorsal leaf of the principal olive are connected with the cortex of the superior surface of the cerebellum. Olivocerebellar fibers from the ventral lamina of the principal olive and the ventral part of the medial accessory olive project to the tonsilla and the caudal vermis. (From Holmes and Steward 1908). Abbreviations: Bi biventral lobule, Ce central lobule, DAO dorsal accessory olive, Fl flocculus, Gr lobulus gracilis, Lg lingula, MAO medial accessory olive, PO principal olive, Qa anterior quadrangular lobule, Qp posterior quadrangular lobule, Si inferior semilunar lobule, Ss superior semilunar lobule, To tonsilla

Groenewegen and Voogd (1977) and Groenewegen et al. (1979) used autoradiography of [3H]leucine to map the olivocerebellar projection in the cat. Earlier, Courville and colleagues (Courville 1975; Courville and Faraco-Cantin 1978; Courville et al. 1974) had demonstrated the termination of olivocerebellar fibers in longitudinal climbing fiber zones with the same method. However, they concluded that these zones corresponded to Brodal’s lobular pattern of termination. Groenewegen (Groenewegen and Voogd 1977; Groenewegen et al. 1979) distinguished the same zones recognized earlier from their white matter compartments (Fig. 21). The A zone is innervated by the MAOc. It extends over the entire vermis, with the exception of lobule X that receives it climbing fibers, together with the flocculus, from the dorsal cap and the VLO. The DAOc projects to the B zone that is limited to the lateral vermis of the anterior lobe and the simplex lobule. C1 and C3

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Fig. 20 The olivocerebellar projection in the rabbit indicated in flattened maps of the cerebellum and the inferior olive. The construction of the map of the olive is indicated in the bottom figurine. Olivary subnuclei and their projections are indicated with the same color. (Redrawn from Brodal 1940). Abbreviations: ANS ansiform lobule, ANT anterior lobe, DAO dorsal accessory olive, dc dorsal cap, dl dorsal lamina principal olive, dmcc dorsomedial cell column, F fastigial nucleus, FLO flocculus, INT interposed nucleus, LAT lateral cerebellar nucleus, MAO medial accessory olive, PFL paraflocculus, PMD paramedian lobule, PO principal olive, SI simplex lobule, vl ventral lamina principal olive

zones are innervated by the DAOr. They are present in the anterior lobe with the simple lobule and in the Crus II of the ansiform lobule and the paramedian lobule. C3 is restricted to the rostral paramedian lobule. Both zones fuse in the rostral anterior lobe, around the rostral extremity of the C2 zone. This zone receives its climbing fibers from the MAOr and extends over the entire cerebellar cortex, including the paraflocculus. The lateral D zone, innervated by the principal olive, also extends over the entire rostrocaudal length of the cerebellar cortex. At the level of the ansiform lobule and the paraflocculus, it is divided into D1 and D2 zones, but a differential origin of these climbing fiber subzones from the principal olive could not be established. Climbing fibers always emit collaterals to the cerebellar or vestibular target nucleus of the Purkinje cell zone they innervate. Such a collateral projection could not be identified for the projections of the VLO and the DC. Oscarsson and his group defined their spino-olivocerebellar climbing fiber paths (SOCPs) by the spinal funiculus they use as their first link. They mapped the terminations of these paths by recording the positive climbing fiber potentials from the cerebellar surface and complex spikes from the underlying Purkinje cells from the anterior lobe and determined their laterality, somatotopical organization, and the

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Fig. 21 Diagram of the zonal organization of the olivocerebellar and corticonuclear projections in the cat shown as flattened maps of the cerebellar cortex, the cerebellar nuclei, and the inferior olive. (Redrawn from Groenewegen et al. 1979). Abbreviations: ANS ansiform lobule, ANT anterior lobe, DAO dorsal accessory olive, dc dorsal cap, Deiters’ Deiters’ lateral vestibular nucleus, dmcc dorsomedial cell column, FLO flocculus, MAO medial accessory olive, PFL paraflocculus, PMD paramedian lobule, PO principal olive, SI simplex lobule, vlo ventrolateral outgrowth

quality of their peripheral input. The ventral funiculus (vf)-SOCP takes its origin from the contralateral spinal gray, as illustrated in Fig. 4. It terminates in the vermis in the A zone, in the B zone, and in the C1 and C3 zones of the rostral anterior lobe (lobules I-IV). Input to the A, C1, and C3 zones stems from the hind limb and is ipsilateral; the B zone receives a bilateral input from all limbs, with the projection of the forelimb located more laterally, partially overlapping with the projection from the hind limb (Oscarsson and Sjölund 1977a, b; Oscarsson and Uddenberg 1966) (Fig. 22a). The A and B zones receive their input through the cell groups in the ventral horn and/or the intermediate gray and the MAOc and the DAOc, respectively. The hindlimb input to the C1 and C3 zones is relayed through the cell groups in the dorsal horn that are absent in the cervical enlargement. Because the ventral funiculus was isolated at the C3 segment, they missed the C1 projection to the DAOr (Fig. 4) and its contribution to the rostral C1 and C3 zones. Projections to the posterior lobe were rarely studied by the physiologists. The C1 zone in the paramedian lobule was found to share climbing fiber collateral input with the C1 and C3

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Fig. 22 Distribution and properties of spino-olivary climbing fiber paths (SOCPs) in the anterior lobe of the cat. (a) Ventral funiculus (vf)-SOCP. (Redrawn from Oscarsson and Sjölund 1977b). (b) Dorsal funiculus (df)-SOCP. (Redrawn from Ekerot and Larson 1979a). (c) Somatotopical organization of the forelimb segment of the C3 zone. Color-coded map illustrates partially overlapping, half-moon-shaped terminal fields, activated from subsequently more cranial cutaneous nerves 1–8, indicated in upper figurine. Broken line indicates border of mirrored representations in medial and lateral C3 zone. (Redrawn from Ekerot and Larson 1979b). (d) Transverse branching of climbing fibers innervating dual zones. (Redrawn from Ekerot and Larson 1982)

zones in the anterior lobe (Armstrong et al. 1973; Oscarsson and Sjölund 1977a). The presence of a C3 zone in the rostral paramedian lobule was never confirmed. The bilateral projection of the four limbs to the B zone was studied in more detail by Andersson and Oscarsson (1978). They described narrow, mediolaterally arranged longitudinal strips of Purkinje cells that receive the same climbing fiber input (i.e., mainly ipsilateral hind limb, bilateral hind limb, bilateral hind- and forelimb, etc., with a trigeminal microzone located most medially (Andersson and Eriksson 1981)). These “microzones” are narrow, with a width of a few Purkinje cells, but may extend for tens of millimeters in the rostrocaudal direction. The relationship of the microzones to the morphology of the climbing fiber system is discussed in ▶ Chap. 23, “Axonal Trajectories of Single Climbing and Mossy Fiber Neurons in the Cerebellar Cortex and Nucleus.” The dorsal funiculus (df)-SOCP was studied by Oscarsson (1969) and Ekerot and Larson (1979a, b). Its first link consists of spinal root fibers ascending in the dorsal columns. Its relay in the dorsal column nuclei and its projections to the inferior olive were discussed in section “Projections from the Dorsal Column Nuclei” and illustrated in Figs. 7, 8, and 9. The projection to the anterior lobe is ipsilateral for all the zones. Oscarsson (1969) documented ipsilateral hind- and forelimb projections to the B zone and an ipsilateral hindlimb projection to A. These projections presumably overlap with similar projections from the vfSOCP. The relay for the B zone in the DAOc only has been substantiated for the hind limb (Fig. 6). A substantial hindlimb

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projection from the gracile nucleus to MAOc would provide for the activation of the A zone. Ekerot and Larson (1979a, b) limited their study to the four short-latency zones, X, C1, C3, and D2, relayed monosynaptically by the dorsal column nuclei to the inferior olive, and two long-latency zones, C2 and D1, with an extra synapse, presumably in the mesencephalon (Fig. 22b). The C1, C3, and D2 (or Y) zones are innervated by the DAOr. Rostral hindlimb segments of the C1 and C3 zones overlap with the vf-SOCP, and their forelimb segments extend into lobule V. A projection of this subnucleus to the D2 zone was not noticed in earlier morphological studies. Originally, the D2 zone was defined by its lateral location, its projection to the rostral dentate, and its climbing fiber afferents from the dorsal lamina of the principal olive. Although Ekerot’s D2 zone is located in the most lateral part of the anterior lobe of the cat, its connections clearly differ from the original D2 zone. It should be considered as a third zone of the C1-C3 collective, innervated by the rostral DAO and projecting to the anterior interposed nucleus. The true D2 zone may have been inaccessible for the microelectrode, as it is hidden in the lateral pole of the anterior lobe of the cat. Garwicz (1997), in the ferret, proposed the neutral term Y zone for Ekerot’s D2 zone. In the rat, a D0 zone (Buisseret-Delmas 1989) was identified in the lateral anterior lobe and the paramedian lobule, located between the D1 and D2 zones (Voogd et al. 2003; Sugihara and Shinoda 2004). The D0 zone occupies a similar position as the Y zone in the cat. Its connections, however, are with subnuclei that have not been identified in carnivores, receiving climbing fibers from the dorsomedial group of the ventral lamina of the principal olive and projecting to the dorsolateral hump. Moreover, it gives rise to the uncrossed descending limb of the brachium conjunctivum (Mehler 1969) that has not been identified in carnivores either. The X zone is located between the A and B. It is a pure forelimb zone located in lobule V. It receives its climbing fibers from intermediate levels of the MAO (Campbell and Armstrong 1985) (illustrated in Fig. 18 for the rat). The forelimb projection from the cuneate nucleus to the intermediate MAO is illustrated in Fig. 6. A trigeminal input to this region is illustrated in Figs. 4 and 5. Alternative routes for the transmission of peripheral input to the inferior olive involve the crossed ascending projections of somatosensory relay nuclei to the nuclei of the mesodiencephalic junction, referred to before. For the long-latency projection to D1, the pathway probably involves Bechterew’s nucleus, a subsidiary of the parvocellular red nucleus, and the ventral lamina of the principal olive (Fig. 13). The pathway for the C2 zone includes Darkschewitsch’s nucleus (Fig. 13) and the MAOr. The D1 zone displays an indistinct somatotopical organization; C2 lacks a somatotopical arrangement. The somatotopical organization of the forelimb region of the C3 zone was studied in more detail. Climbing fibers transmitting information from cutaneous nerves terminate in partially overlapping half-moon-shaped fields in this zone. When stimulating thoracic, ulnar, radial, and neck nerves, the fields shift rostrally in this order (Fig. 22c). Apparently, the C3 zone contains two mirror-faced somatotopical maps in its medial and lateral halves. A similar, but single, somatotopical organization is present in the C1 and the Y (D2) zone.

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Transverse climbing fiber branching was found between medial C3 and C1 and between lateral C3 and Y (D2) (Armstrong et al. 1973; Ekerot and Larson 1982) (Fig. 22d). Moreover, climbing fibers branch between the X zone and a new CX zone, located between C2 and C1. The presence of zonal pairs sharing the same topically arranged peripheral climbing fiber input, enclosing a zone innervated by climbing fibers carrying information descending from the mesodiencephalic junction, is a remarkable but still unexplained feature of the anterior lobe. In rat and mouse, transverse branching in the anterior lobe among the C1, C3, and D0 zones in lobules VI and VI between A and A2 and in the copula pyramidis in the C1 zone was noticed with antegrade labeling of climbing fibers by Sugihara and Shinoda (2004) and Sugihara and Quy (2007). Apart from tactile input, the df-SOCP climbing fibers of the df-SOCP were found to relay nociceptive input. This quality is relayed by the postsynaptic dorsal column pathway, and not by the spinal root fibers of the dorsal funiculus (Ekerot et al. 1991; Uddenberg 1968). Nociceptive input is found for the X, C1, CX, and C3 zones (Garwicz et al. 1992). In the most recent chapter in the study of the olivocerebellar projection, the “zebrin pattern” was used as a template. Antibodies known as the zebrins exclusively stain a subpopulation of Purkinje cells in rodents that are arranged in parallel longitudinal bands, separated by bands of zebrin-negative Purkinje cells (Hawkes and Leclerc 1987) (Fig. 23). One of these antibodies, zebrin II, recognizes the enzyme aldolase C (Hawkes and Herrup 1995). Earlier, the same pattern was described by Scott (1964) for the enzyme 5-nucleotidase in the molecular layer of the cerebellum of the mouse. In the nomenclature devised by Hawkes, zebrin-positive bands are numbered from medial to lateral as P1+ to P7+, and the zebrin-negative bands P1- to P6- are located lateral to the zebrinpositive bands bearing the same number (Fig. 23). The “satellite bands” distinguished by these authors (red in Fig. 23) were not numbered. Later they were found to be a reproducible feature and indicated with lowercase characters (Figs. 18, 23, and 24). The main question that remained was whether the zebrin-positive and zebrinnegative bands were identical to the corticonuclear and olivocerebellar projection zones. The answer to this question was provided by Voogd et al. (2003), using a bidirectional axonal tracer, injected into identified zones of the cerebellar cortex of the rat and, in much greater detail, by Sugihara c.s who mapped the olivocerebellar projection from numerous small injections of an antegrade axonal tracer in subnuclei of the inferior olive in rat (Sugihara and Shinoda 2004) and mouse (Sugihara and Quy 2007) in material counterstained for aldolase C (zebrin II). Additional studies were published by Voogd and Ruigrok (2004) and Pijpers et al. (2005). Earlier, the olivocerebellar projection in the rat had been described by Buisseret-Delmas and Angaut (1993). Their findings largely confirmed the earlier studies in carnivores. Of the additional zones described by them, the X zone receives it climbing fibers from the lateral intermediate MAOc. The A2 zone is innervated by the medial MAOc, and the Y (Delmas’s D0 zone) by the dorsomedial group of the ventral lamina of the principal olive (Fig. 18a, c).

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Fig. 23 Diagram of zebrinpositive (black) and zebrinnegative (white) Purkinje cell bands in the cerebellum of the rat. Zebrin-positive (P+) bands are numbered according to Hawkes and Leclerc (1987). Non-numbered satellite bands are shown in red. Abbreviations: II-IX lobules II-IX, COP copula pyramidis, Cr I/II Crus I/II, PMD paramedian lobule, SI simplex lobule

In Voogd’s studies, the corticonuclear and olivocerebellar projection zones were found to be congruent with zebrin-positive and zebrin-negative bands. The C2, D1, and D2 zones consist of zebrin-positive Purkinje cells, and the X, B, C1, C3, and Y zones are zebrin-negative (Fig. 18.). Because these zebrin-negative zones are absent from the Crus I of the ansiform lobule and the paraflocculus, these lobules are entirely zebrin-positive, and the borders of the constituent C2, D1, and D2 zones cannot be distinguished. This is also the case for the X, B, and C1 zones that occupy the anterior zebrin-negative P2-band. It follows from the analysis of the olivocerebellar projection that Hawkes nomenclature for the zebrin bands in the anterior and posterior cerebellum is not consistent. Anterior bands P2+ to P6+ are continuous with posterior bands P3+ to P7+. The A2 zone occupies a region in the Crus II, containing the zebrin-positive and zebrin-negative P4b and P5a bands. Anteriorly, it corresponds to the c and d bands of the simplex lobule. In the following account, anterior and posterior bands that receive their climbing fibers from the same subdivision of the inferior olive will be indicated with their numbers separated by a dash (i.e., anterior band 2+ and posterior band 3+ are indicated as 2+/3+). Greater detail was obtained in Sugihara and Shinoda’s study (Sugihara and Shinoda 2004) of the olivocerebellar projection in the rat. They distinguished four

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Fig. 24 (a) Olivocerebellar projections to aldolase-C-positive and aldolase-C-negative Purkinje cell zones. The four groups in this projection, their origin from the olive and their termination in the cortex, are indicated in different colors. Group I (green) and group II (blue) project to aldolase-positive bands. Group III (yellow) and group IV (red) project to aldolase-negative bands. (b) Flattened reconstruction of the cerebellar cortex showing aldolase-C-positive and aldolase-C-

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groups in this projection (Fig. 24a, b). Group I (green) includes the lateral subnucleus a of the MAOc, the MAOr, and the principal olive. It projects to zebrinpositive bands P1, with the exception of lobule VII, 2+/3+ and to the 4+/5+, 5+/6+, and 6+/7+. With the exception of subnucleus a of the MAOc that receives somatosensory input, it receives its afferents from the nuclei at the mesodiencephalic junction. Group II (blue) comprises the projections of caudal subnucleus c of the MAOc, group beta, and the DMCC and the caudal part of the dorsomedial group to zebrin-positive bands a+/2+, 3+, and 4+ in the uvula and a complicated array of zebrin-positive bands in intermediate regions of lobule VI–VIII (2b+, c+, d+, 4b+, 5a+). Of this group, the beta nucleus and the DMCC receive vestibular input, and lateral MAOc shares the tecto-olivary projection with the group III and receives a spatially segregated somatosensory afferents. Group III (yellow) includes the projections of subnucleus c of the MAOc to zebrin-negative bands in the vermis and in intermediate regions of lobules VI-VIII. In group IV (red), the DAO and the rostral part of the dorsomedial group project to anterior bands 2 , b+ and , 3+ and , 3b+ and , 4 and 5 and posterior 4 , e1 and 2+ and , and 5 and 6 . This region includes both zebrin-negative and the weakly zebrin-positive bands 3+ and 3b+ in the anterior cerebellum and e1 and e2 in the posterior cerebellum. Group IV is purely somatosensory. The correspondence between the four groups of Sugihara and Shinoda (2004) and the nomenclature of Voogd (Fig. 18) and Buisseret-Delmas and Angaut (1993) is indicated in Fig. 24c. The localization of X, B, C1–3, Cx and the D1, Y, and D2 zones is immediately clear. The position of the D1 and D2 zones, flanking the Y (Buiseret-Delmas’s D0 zone), now was definitely established. The possibility still exists that D1 is discontinuous in the Crus I (lobule VIc) because no labeling was observed in this region with injections of the vlPO. The main difference with previous maps is the composition of the A and A2 zones of an array of interdigitating zebrin-positive and zebrin-negative bands. The principle, formulated by Groenewegen et al. (1979) that olivocerebellar fibers emit collaterals that terminate in the target nucleus of the Purkinje cells innervated by these fibers, has not been challenged. The collateral olivocerebellar projection to the cerebellar nuclei was studied in the rat by Ruigrok and Voogd (2000) and Sugihara and Shinoda (2007). The collateral projections of subnuclei of the inferior olive were found to overlap with the corticonuclear projections from the Purkinje cell zones that receive climbing fibers from these subnuclei, as reviewed in the previous paragraphs. Zebrin (aldolase C) immunochemistry cannot be used to map the corticonuclear projection of the individual zones. However, it may serve to visualize the overall

ä Fig. 24 (continued) negative bands. (c) Correspondence of aldolase-C banding pattern with A-D zones and their origin from the inferior olive. The A and A2 zones correspond with multiple aldolase-C-positive (dark blue and dark orange) and aldolase-C-negative (light blue and light orange) bands (a and b, Redrawn from Sugihara and Shinoda (2004))

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topography of the corticonuclear projection of zebrin-(aldolase C)-positive and negative Purkinje cell zones as labeling of fibers and terminals in the cerebellar nuclear neuropil (Hawkes and Leclerc 1986; Sugihara and Shinoda 2007). Zebrinpositive and zebrin-negative zones that interdigitate in the cerebellar cortex converge upon two separate homogeneously zebrin-positive or zebrin-negative regions of the cerebellar nuclei, that occupy caudoventral and lateral, and rostrodorsal parts of the nuclei, respectively (Fig. 25b). As a result, the medial (fastigial) nucleus is divided into the rostrodorsal, zebrin-negative and caudoventral, zebrin-positive parts, which may be related to some functional localization in this nucleus. In the interposed nucleus, this division between the rostrodorsal and caudoventral parts roughly corresponds to the division between the anterior and posterior interposed nuclei. The lateral (dentate) nucleus is entirely aldolase-C-positive, in accordance with its innervation by zebrin-positive bands only. Collateral projections to the fastigial nucleus from groups I and II that innervate zebrin-positive zones include those from subnucleus a of the MAOc (green in Fig. 25), group beta and DMCC (light blue), and subnucleus c (dark blue). These collateral projections occupy subsequently more dorsal and rostral laminae (Fig. 25a, b, g, h). The collateral projection of subnucleus c to lobules VI and VII, the so-called visual vermis, demarcates the visuomotor subdivision of the fastigial nucleus. Subnucleus b of the MAO that belongs to group III, which innervates zebrin-negative territory, supplies collateral projections to the rostral and dorsal fastigial nucleus. Olivocerebellar fibers from medial subnucleus b that innervate the zebrin-negative bands of the A2 zone emit collaterals to the dorsolateral protuberance and spill over in the adjacent posterior interposed nucleus (orange). Lateral subnucleus b innervates the base of the DLP and the interstitial cell groups (yellow). The latter represents the collateral projection of the X zone. Collateral projections from the MAOr and the ventral and dorsal laminae of the PO, that belong to group I (green), terminate in the zebrin-positive neuropil of the posterior interposed nucleus and in the caudal and rostral portions of the dentate nucleus, respectively. Collateral projections of group IV include those of the DAOr that innervate the anterior interposed nucleus (red) and the DAOc that provide collaterals to the lateral vestibular nucleus and to islands of gray matter between the anterior interposed and lateral nuclei, known as the anterior interstitial cell groups (AICG, pink). The neuropil of the target nuclei of group IV is devoid of zebrin-positive elements. Olivocerebellar projections to the flocculus and the nodulus and neighboring lobules have received much attention. In the flocculus of the rabbit, five Purkinje cell zones and corresponding white matter compartments could be distinguished (Tan et al. 1995a, b, c) (Fig. 26a). The caudal extension of the C2 zone is located along its lateral border. Actually, this lateral border corresponds to the inner, medial border of the folial chain of the hemisphere that is turned back upon itself as the flocculus. The f1 and f3 zones receive a projection from the rostral dorsal cap (DC) and the ventrolateral outgrowth (VLO), the f2 and f4 zones from the caudal DC. In the flocculus of the rat, the C2 zone and the four floccular zones, with the same dual projection from the DC and the VLO, could be distinguished

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Fig. 25 (a) Collateral projections of olivocerebellar fibers to the cerebellar nuclei in the rat illustrated in diagrams of parasagittal (a–f ) and transverse sections (g, h). Projections from the four groups in the olivocerebellar projection, distinguished in Fig. 24a, are shown in the same colors. Within group II, the projection to lobules VI and VII (the “visual vermis”: dark blue) is distinguished from other lobules (light blue). Within group III, the projections of the dorsolateral protuberance and medial posterior interposed nucleus (orange) are distinguished from those to rostral fastigial nucleus and interstitial cell groups (yellow). (b) Caudal view of a 3-D reconstruction of the caudoventral and lateral aldolase-C (zebrin-positive) and rostral aldolase-C-negative compartments of the cerebellar nuclei of the rat. (Redrawn from Sugihara and Shinoda 2007). Abbreviations: AI anterior interposed nucleus, AICG anterior interstitial cell groups, C caudal, CVP caudal pole, D dorsal, DLH dorsolateral hump, DLP dorsolateral protuberance, DMC dorsomedial crest, ICG interstitial cell groups, L lateral cerebellar nucleus, LV lateral vestibular nucleus, M medial cerebellar nucleus, PI posterior interposed nucleus

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Fig. 26 Afferent climbing fiber and efferent projections of the flocculus and the nodulus and adjacent lobules. (a) Zonal organization of the olivocerebellar projection to the flocculus and the adjacent ventral paraflocculus and to the nodulus and the uvula in the rat and their origin from the inferior olive, shown in flattened diagrams of these structures. (b) Efferent connections of the flocculus and the nodulus in rabbits. Note different localization of group beta-innervated zone in the nodulus of rat and rabbit. Abbreviations: DC dorsal cap, DM dorsomedial group, f0-f4 floccular zones f0-f4, Fast, fastigial nucleus, MAOc/r caudal/rostral medial accessory olive, MV medial vestibular nucleus, n1-n5 nodular zones 1–5, PI posterior interposed nucleus, PO principal olive, ß group beta, SV superior vestibular nucleus, VLO ventrolateral outgrowth, Y group Y

(Ruigrok et al. 1992). A fifth DC-innervated f0 zone was identified by Sugihara et al. (2004) (Fig. 26a). A differential projection of caudal and rostral parts of the VLO was found by these authors, confirming earlier observations by Gerrits (1982) in the cat. A similar zonal organization is present in the flocculus of the mouse (Schonewille et al. 2006). In monkeys, the f4 zone appears to be absent (Voogd et al. 1987a, b). In all species, the floccular zones extend for some distance on the ventral paraflocculus. In

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the rabbit, this extension is known as folium P (Yamamoto 1978, 1979), in the cat as the medial extension of the ventral paraflocculus (ME: Gerrits and Voogd 1982), and in monkeys, the floccular zones occupy the entire ventral paraflocculus (Voogd et al. 1987b). Collateral projections from the DC terminate in the rostrolateral ventral dentate nucleus, from the VLO in its medial part and in the dorsal group Y (Sugihara et al. 2004). Climbing fibers from the VLO also terminate in the extreme lateral part of the ansiform lobule (Fig. 24). Olivocerebellar fibers from DC and VLO do not collateralize to the vestibular nuclei (Ruigrok and Voogd 2000; Sugihara et al. 2004). Collateral projections from the group beta and a lateral part of subnucleus b of the MAOc to parts of the vestibular nuclei were identified by Ruigrok (unpublished) and Sugihara and Shinoda (2007), respectively. The zonal organization of the nodulus and the uvula is fairly complicated. In the uvula, four zebrin-positive bands are present, separated by narrow zebrinnegative slits. These zebrin-negative slits disappear in the ventral uvula. Purkinje cells in the ventral uvula and the nodulus are all zebrin-positive (Fig. 26) (Voogd et al. 1996). In the medial and lateral uvula, the n1 and n5 zones are innervated by the DC, and an intermediate N3 band receives climbing fibers from the VLO. Of these zones, only n3 continues into the ventral uvula. In the uvula, the caudal group beta innervates zebrin-positive band P1+ and medial P2+, rostral group beta innervates lateral P2+ and medial P3+, and climbing fibers terminating in lateral P3+ and in P4+ are derived from the DMCC. The narrow P1 , P2 , and P3 bands receive climbing fibers from subnucleus b of the MAOc. According to Sugihara and Shinoda (2004), climbing fibers terminating in P4+ are derived from the caudal part of the dorsomedial group, and the most caudal and medial part of the vlPO and the dorsomedial group is an alternative source for the P3 projection. The localization of the DC and VLO-innervated zones was confirmed for the rat by Ruigrok (2003), who also demonstrated collateralization of climbing fibers between the projections from the DC to the rostral DC-innervated zone in the ventral paraflocculus and the n1 and n5 zones in the nodulus and for the VLO between f1 and f3 and n3. The efferent connections of the Purkinje cell zones of the flocculus and the nodulus have been studied in rabbits (Fig. 26b). The DC-innervated f2 and f4 zones project to oculomotor relay cells in the medial vestibular nucleus, the VLO-innervated f1 and f3 zones project to oculomotor relay cells in the group Y and the superior vestibular nucleus (De Zeeuw et al. 1994b; Tan et al. 1995a). The zonal organization of the rabbit nodulus differs from the rat in the presence of a medial beta-innervated zone, but DC and VLO-innervated N1, N3, and n4 zones are present in the same configuration as in the rat. All the zones project to the medial vestibular nucleus; additional projections to the superior vestibular nucleus and group Y take their origin from n3 and n4 (Wylie et al. 1994). Terminations in the superior and medial vestibular nuclei are complementary to those from the flocculus (Angaut and Brodal 1967; Haines 1977; Voogd 1964). All or most of the Purkinje cell zones of the flocculus and the nodulus project to the basal interstitial nucleus.

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The Nucleo-Olivary Pathway The pathway from the cerebellar nuclei to the contralateral inferior olive was discovered by Graybiel et al. (1973) in the cat. It takes its origin from the small, GABAergic neurons in all cerebellar nuclei (Mugnaini and Oertel 1985). The projection is reciprocal with respect to the collateral projections of the subnuclei of the inferior olive to the cerebellar nuclei and has been described in the rat (Ruigrok and Voogd 1990), the cat (Courville et al. 1983a; Legendre and Courville 1986; Tolbert et al. 1976), and the monkey (Beitz 1976; Chan-Palay 1977; Kalil 1979). Nucleo-olivary fibers from the dentate and interposed nuclei ascend in a separate bundle, ventral to the brachium conjunctivum, decussate caudal to the brachium, and descend in the tegmentum to the olive. Nucleo-olivary fibers from the fastigial nucleus take a more diffuse route to the olive (Legendre and Courville 1986). GABAergic projections from the vestibular nuclei and the group Y to the DC, VLO, the group beta, and the DMCC were considered in section “Optokinetic and Vestibular Projections to the Inferior Olive.” In the rat, small numbers of fibers recross at the level of the olive. Recrossing fibers mainly terminate in MAOr, vlPO, and in the dorsomedial group (Ruigrok and Voogd 1990). In all species, a projection from the ventrocaudal dentate to the vlPO, and from the rostral dentate to the dlPO, was found.

Olivocerebellar and Corticonuclear Projections in Primates The presence of corticonuclear projection zones A-D in prosimians, macaques, and squirrel monkeys was demonstrated by Haines and his colleagues for the anterior lobe of these species (Haines et al. 1982). A division of the D zone into D1 and D2 zones was not observed by these authors. The parasagittal organization of white matter compartments in the macaque cerebellum, visualized by the accumulation of acetylcholinesterase at their borders, was found to be very similar to earlier observations in carnivores (Voogd et al. 1987a) (Fig. 27). An X compartment was recognized in the anterior cerebellum; D1 and D2 compartments that issue at the caudal and more rostral portions of the dentate nucleus were recognized in the dorsal paraflocculus and the paramedian lobule. In experiments using autoradiography of antegradely transported tritiated leucine, the A, X, B, and C2 compartments were shown to channel the olivocerebellar fibers to their respective Purkinje cell zones. Knowledge of the corticonuclear and olivocerebellar projections in subhuman primates remains fragmentary, particularly with respect to the connections of the dentate nucleus. A major advance was the publication of a complete map of the aldolase-C (zebrin II)-positive and negative bands in the marmoset, a small primate (Fujita et al. 2010) (Fig. 28). For the vermis, the zebrin pattern in primates was analyzed by Sillitoe et al. (2005), but the hemisphere remained unexplored. The banding pattern of the marmoset cerebellum is very similar to the rat (Fig. 24). A, C1, C2, C3, D1, and D2 zones could be recognized using small injections of bidirectional tracers in specific aldolase-C-positive or aldolase-C-negative bands.

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Fig. 27 White matter compartments in the anterior lobe of Macaca fascicularis. Processed for acetylcholine esterase. Abbreviations: IntA anterior interposed nucleus; bc brachium conjunctivum; cr restiform body

D1 receives a projection from the vlPO and D2 from the dlPO. In the posterior lobe, the P5a bands appear to be absent. In the rat, these bands are part of the A2 zone. The target of the P5a- band, the dorsolateral protuberance of the fastigial nucleus, is not present in the marmoset either. A reduction of the A2 zone in this species, therefore, appears likely.

The Cerebellar Nuclei: Efferent Connections and Recurrent Climbing Fiber Paths The Fastigial Nucleus The fastigial nucleus receives projections from the anterior vermis and lobule VIII in its rostral portion, from the oculomotor vermis (lobule VII) in a caudal subdivision, and from lobules IX and X in its ventrocaudal part (Fig. 29). In rodents, a dorsolateral protuberance is present that receives Purkinje cell axons from the A2 zone (Buisseret-Delmas 1988) (Fig. 18). The rostral fastigial nucleus projects bilaterally and symmetrically to the vestibular nuclei (magnocellular medial and descending

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Fig. 28 Aldolase-C-positive and aldolase-C-negative bands in a flattened reconstruction of the cerebellar cortex of the marmoset (left). The correspondence with the A, C1, C2, C3, D1, and D2 zones, based on the afferent climbing fiber and efferent nuclear connections of the aldolase-Cpositive and aldolase-C-negative bands, is indicated in the right hand panel. The symmetry axis for the numbering of the bands and the areas without cortex in the center of the ansiform loop are shown in red. (Redrawn from Fujita et al. 2010). Abbreviations: ANT anterior lobe, FLO flocculus, PFL paraflocculus, PMD paramedian lobule, SI simplex lobule, I-X lobules I-X

vestibular nuclei, nucleus parasolitarius) and the medial bulbar and pontine reticular formation (Batton et al. 1977; Homma et al. 1995; Teune et al. 2000). The entire contralateral projection uses the uncinate tract (Thomas 1897) that decussates in the cerebellar commissure and hooks over the brachium conjunctivum to enter the vestibular nuclear complex from laterally. It emits an ascending branch (Probst 1901) consisting of scattered fibers around the medial pole of the brachium, which does not join it in its decussation. The direct fastigiobulbar tract enters the vestibular nuclei from medially. In the mouse, the ipsilateral pathway was found to originate from glycinergic neurons (Bagnall et al. 2009). The distribution of these glycinergic cells in the ventral and rostral fastigial nucleus in the mouse corresponds closely to the neurons with ipsilateral projections in the rat (Fig. 30). The projections of the caudal fastigial nucleus and the dorsolateral protuberance are entirely crossed. The connections of the caudal, oculomotor division of the fastigial nucleus have been studied mainly in monkeys (Noda et al. 1990) (Fig. 29). This subdivision appears to be the main source of the crossed ascending branch of the uncinate tract.

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Fig. 29 Diagram of the projections of the fastigial nucleus. Projections of the rostral and ventrocaudal fastigial nucleus are indicated in yellow and those from its visuomotor division in green. The recurrent climbing fiber pathway from the superior colliculus is shown in red. Abbreviations: coll.sup superior colliculus, Fr rostral division fastigial nucleus, Fvc ventrocaudal division fastigial nucleus, I-X vermal lobules I-X, MAOc caudal medial accessory olive, med.s.ret medial reticular formation, no nucleo-olivary pathway, PPRF pontine paramedian reticular formation, riMLF rostral interstitial nucleus of the medial longitudinal fascicle, vest.nu vestibular nuclei, vis. fast visuomotor division fastigial nucleus

Its bilateral projection to the vestibular nuclei and the bulbar reticular formation overlaps with the rostral fastigial nucleus. Specific contralateral projections of the oculomotor division include the pontine paramedian reticular formation (PPRF) that contains the excitatory and inhibitory burst cells for horizontal eye movements, the rostral interstitial nucleus of the medial longitudinal fascicle (riMLF) with similar neurons for vertical eye movements, the rostral intermediate layer of the superior colliculus, where fibers cross in the tectal commissure to innervate the contralateral side (May et al. 1990), and parts of the suprageniculate, ventral intermediate, ventral lateral, and intralaminar thalamic nuclei. A recurrent tecto-olivary pathway takes its origin from the intermediate layer of the superior colliculus to terminate in the contralateral medial MAOc (Figs. 12 and 30). In all species, this subnucleus projects to the oculomotor vermis. In rodents, the tecto-olivary pathway also innervates a separate neuronal population in subnucleus b of the MAOc that projects to the A2 zone and its target nucleus, the dorsolateral protuberance (Akaike 1992; Ruigrok and Voogd 2000). The contralateral projection of the dorsolateral protuberance to the brain stem is mainly directed at the lateral, parvocellular reticular formation and the adjoining spinal nucleus of the trigeminal

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Fig. 30 Labeled neurons in the rat fastigial nucleus from an injection of a retrograde tracer affecting the entire leftsided output of the nucleus. Abbreviations: DLP dorsolateral protuberance, Fr rostral fastigial nucleus, Fvc ventrocaudal fastigial nucleus, PI posterior interposed nucleus

nerve, the parabrachial nuclei, the nucleus pedunculopontinus, and the deep mesencephalic nucleus. This system appears to absent or rudimentary in primates and carnivores.

Anterior Interposed Nucleus Projections from the anterior and posterior C1, C3, and Y zones converge on to the anterior interposed nucleus, where they are arranged into a single somatotopical map (Garwicz and Ekerot 1994). The main projections of the anterior interposed nucleus include the magnocellular red nucleus, the nucleus reticularis tegmenti pontis, and, through the ventral intermediate and ventral lateral thalamic nuclei, the primary motor cortex (Fig. 31). A recurrent pretecto-olivary pathway arises from the anterior pretectal nucleus and relays in the DAOr (Kawamura and Onodera 1984; Kawamura

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Fig. 31 Diagram of the projections of the anterior interposed nucleus. The recurrent climbing fiber pathway from the pretectum is indicated in red. Abbreviations: AI anterior interposed nucleus, Ant.pret. nu anterior pretectal nucleus, DAOr rostral dorsal accessory olive, M primary motor area, no nucleo-olivary pathway, Rmc magnocellular red nucleus, Thal thalamus, VIM ventral intermediate thalamic nucleus

et al. 1982; Sugimoto et al. 1982) (see also section “Afferents from Tectum and Pretectum” and Figs. 12 and 31). In rodents, the dorsolateral hump (Goodman et al. 1963) (Fig. 1) may be considered as a subnucleus of the anterior interposed nucleus. It receives a projection of the D0 zone, the presumed equivalent of the Y zone in the cat (Sugihara et al. 2009) (Fig. 18). The D0 zone and the dorsolateral hump are innervated by the dorsomedial group of the ventral lamina of the principal olive. The dorsolateral hump gives origin to the uncrossed descending branch of the superior cerebellar peduncle (Cajal 1972; Mehler 1969). It terminates in the lateral parvocellular reticular formation and the adjoining spinal nucleus of the trigeminal nerve (Teune et al. 2000), where it overlaps with terminals of the contralateral dorsolateral protuberance. Both of these systems appear to be absent in non-rodent species.

Posterior Interposed Nucleus and Interstitial Cell Groups The posterior interposed nucleus is the recipient of Purkinje cell axons of the C2 zone that extends over the entire rostrocaudal length of the cerebellar cortex from lobule III into the flocculus. The MAOr provides the C2 zone with its climbing fibers and the posterior interposed nucleus with a collateral projection. The MAOr receives its descending input through the medial tegmental tract from Darkschewitsch nucleus located at the mesodiencephalic junction (Ogawa 1939). This nucleus is a relay in the projection from frontal eye fields to the rostral pole of the MAOr and motor and posterior parietal cortices to its caudal parts (see section “Nuclei at the Mesodiencephalic Border: The Central and Medial Tegmental Tracts” and Fig. 13). The rostral pole of the MAOr projects to the flocculus and the adjacent ventral paraflocculus. The dorsal paraflocculus and the ansiform lobule receive their climbing fibers from successively more caudal parts of the MAOr. The caudal

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portion of the MAOr, which receives motor and parietal input, projects to the C2 zone of the anterior lobe and the paramedian lobule (Brodal and Kawamura 1980). Laterocaudal visuomotor and rostromedial skeletomotor divisions also have been recognized in the posterior interposed nucleus (van Kan et al. 1993). The laterocaudal visuomotor division receives a corticonuclear projection from the paraflocculus (Xiong and Nagao 2002). The topical projections of the more rostral segments of the C2 zone to the posterior interposed nucleus have not yet been studied. Efferent connections of the posterior interposed nucleus (Fig. 32a) include the contralateral magnocellular red nucleus, Darkschewitsch’s nucleus, the nearresponse region located dorsal to the oculomotor nuclei which is required for vergence eye movements (May et al. 1992), the superior colliculus, and, as thalamocortical projections, the primary motor and premotor cortex and the frontal eye fields and posterior parietal areas (Kievit 1979; Lynch and Tian 2006; Matelli and Luppino 1996; Matelli et al. 1989). Another link with the frontal eye field and, possibly, parietal areas is provided by the superior colliculus (Lynch et al. 1994; Tian and Lynch 1997). Extensive projections to the medial intraparietal area MIP, from the anterior and paramedian C2 zone, through the laterocaudal half of the posterior interposed nucleus and a more restricted projection of its laterocaudal pole to the ventral lateral intraparietal area LIP, were documented by Prevosto et al. (2009). Efferents of the posterior interposed nucleus largely overlap with those from the anterior interposed and dentate nuclei. Darkschewitsch nucleus constitutes the link in the direct and indirect reciprocal climbing fiber paths (Fig. 32a). The interstitial cell groups share projections to the vestibular nuclei, the reticular formation, the red nucleus, and the thalamus with neighboring nuclei (BuisseretDelmas et al. 1998; Teune et al. 2000). A specific feature of this cell group is its collateral projection to the spinal cord with the caudal medial reticular formation and to the thalamus with the superior colliculus (Bentivoglio and Kuypers 1982).

Dentate Nucleus The dentate nucleus can be divided into rostrodorsal and caudoventral parts that receive corticonuclear projections of the D1 and D2 zones, respectively, and collaterals from the olivocerebellar fibers that innervate these two zones (Fig. 18). Rostral motor and ventrocaudal non-motor divisions were distinguished by Strick in the cebus monkey (Strick et al. 2009). A visuomotor division was identified in the ventrocaudal pole of the monkey dentate (van Kan et al. 1993). It is not known whether these different modes that partition the dentate nucleus define the same rostrocaudal subdivisions. The caudal visuomotor division of the dentate nucleus gives rise to a component of the brachium conjunctivum that terminates contralaterally in the dorsomedial parvocellular red nucleus, the superior colliculus, and medially in the ventrolateral thalamic nucleus including area X, with minor extensions in the adjoining mediodorsal and anterior nuclei (Fig. 32b). The rostral dentate projects to the lateral

544 Fig. 32 Diagrams of the projections of the posterior interposed nucleus (a), the caudal dentate nucleus (b), and the rostral dentate nucleus (c). Recurrent climbing fiber pathways are indicated in red. Abbreviations: ctt central tegmental tract, coll.sup superior colliculus, D Darkschewitsch’s nucleus, Dc caudal dentate nucleus, Dr rostral dentate nucleus, FA supplementary eye field, FE frontal eye field, MAOr rostral medial accessory olive, mt medial tegmental tract, no nucleo-olivary pathway, Par parietal cortex, PI posterior interposed nucleus, POdl dorsal lamina principal olive, POvl ventral lamina principal olive, Rpc DM dorsomedial subdivision parvocellular red nucleus (Bechterew’s nucleus), Rpc lat lateral subdivision parvocellular red nucleus, Thal thalamus, VIM ventral intermediate thalamic nucleus, VLO ventral lateral thalamic nucleus oral part, VL-X ventral lateral thalamic nucleus, nucleus X

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and caudal parvocellular red nucleus and the ventral intermediate and lateral portions of the ventral lateral thalamic nucleus (Chan-Palay 1977; Kievit 1979) (Fig. 29c). Nucleo-olivary pathways connect the rostral dentate with the dorsal lamina and the lateral bend of the inferior olive and the caudal dentate with the ventral lamina (see section “The Nucleo-olivary Pathway”). Strick’s distinction in the monkey dentate of rostrodorsal motor and ventrocaudal non-motor divisions is based on retrograde transneuronal labeling experiments. Neurons in the motor division can be labeled from the primary and premotor cortex including the supplementary motor area (SMA). Neurons in the caudal non-motor division are connected with the preSMA and the prefrontal areas 9d and 46 (Fig. 33). A projection to the frontal eye field was located in the extreme caudal pole of the nucleus (Strick et al. 2009) (Fig. 32b, c). Neurons projecting to the anterior intraparietal area (AIP; Clower et al. 2005) are located in both the motor and non-motor divisions, and those projecting to the medial intraparietal (MIP) mainly occupy the rostral dentate (Prevosto et al. 2009). Projections to parietal area 7b (Clower et al. 2001) and the lateral intraparietal area (LIP; Prevosto et al. 2009) are derived from its non-motor division. The dorsomedial parvocellular red nucleus, the medial tegmental tract, and the ventral lamina of the principal olive are links in direct and indirect recurrent projections from the frontal eye fields and parietal areas to the caudal dentate and the D1 zone. The lateral and caudal parvocellular red nucleus, the central tegmental tract, and the dorsal lamina of the principal olive are links in the recurrent pathway from motor and premotor cortical areas to the rostral dentate and the D2 zone (Figs. 14 and 32b, c). The zonal organization of the connections of the inferior olive and the cerebellar nuclei, as described in this chapter, adequately covers the anatomy of the cerebellum of lower mammals. However, our knowledge of the connections of the hemisphere of the great apes and the human cerebellum, which accounts for the bulk of the cerebellar cortex in these species, remains incomplete. The demonstration by Fujita et al. (2010) of the presence of D1 and D2 zones in the marmoset hemisphere does support the idea that the construction of the primate hemisphere is similar to that in rodents and carnivores, but the relative proportions of the marmoset hemisphere are not very different from rodents. The source of the climbing fiber projection to the D1 zone in rodents and primates is the ventral, non-convoluted lamina of the principal olive (see section “The Corticonuclear and Olivocerebellar Projections”). If this subdivision of the principal olive is represented in the human inferior olive by its medial lamina (Fig. 3), the contribution of the human D1 zone to the hemisphere would be small indeed. Its major output would be represented by the D2 zone, with its projection to the convoluted dentate nucleus. In this case, the subdivision of the human dentate in rostrodorsal microgyric and caudolateral macrogyric portions would correspond with two major subdivisions of the D2 zone. There is no evidence on the corticonuclear projection of the human cerebellar hemisphere. The only observations on the connections of the two parts of the human dentate stem from

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Fig. 33 Diagram illustrating transneuronal retrograde labeling from injection sites in different cortical areas in the cebus monkey. (a) Localization of injection sites resulting in labeling within the dentate nucleus (red) and in cases without labeling of this nucleus (blue). (b) Diagram of the unfolded dentate nucleus of the cebus monkey, showing approximate position of the labeling from injections of different cortical areas. Broken line indicates border between motor and non-motor divisions of the dentate nucleus. Question mark indicated the non-explored medial lamina of the dentate nucleus. Red ellipse indicates extent of the labeling from an injection of the anterior intraparietal area that includes both the motor and non-motor divisions of the nucleus (Reproduced and modified from Strick et al. (2009)). Abbreviations: IP anterior intraparietal area, AS arcuate sulcus, CgS cingulate sulcus, CS central sulcus, FEF frontal eye field, PS principal sulcus, IP intraparietal sulcus, LS lateral sulcus, Lu lunate sulcus, M1 primary motor cortex, PMv ventral premotor area, PreSMA rostral division of the supplementary motor area, SMA supplementary motor area (SMA proper), ST superior, TE temporal lobe, ST temporal sulcus

papers on crossed cerebro-cerebellar atrophy by Demolé (1927a, b) and Verhaart and Wieringen-Rauws (1950). Demolé concluded that degeneration of the rostrodorsal, microgyric dentate occurred with large, chronic lesions involving the pre- and postcentral gyri. Lesions of more posterior parts of the hemisphere, involving parietal, occipital, and temporal areas, resulted in atrophy of the ventrocaudal macrogyric dentate. Prefrontal lesions would spare the dentate nucleus. These observations still need to be confirmed but, at least, emphasize the possibility that the increase in size of the cerebellar hemisphere is also related to the elaboration of its connections with postrolandic areas, in addition to the expansion of the cerebello-

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prefrontal connectivity, as advocated by many cognitive neuroscientists. Interestingly, Masao Ito (2012) in his recent book The cerebellum. Brain for an Implicit Self proposes a neural control system for mental activities that includes both prefrontal and postrolandic areas and the cerebellar hemispheres. In this system, the prefrontal cortex serves as the controller, the representation of the controlled subjects is found in the temporoparietal cortex, and the cerebellar hemispheres provide the internal models of the controlled objects represented in the temporoparietal cortex.

Cross-References ▶ Development of Cerebellar Nuclei ▶ Proneural Genes and Cerebellar Neurogenesis in the Ventricular Zone and Upper Rhombic Lip ▶ Purkinje Cell Migration and Differentiation ▶ Specification of Cerebellar and Precerebellar Neurons ▶ Zones and Stripes: Development of Cerebellar Topography

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Axonal Trajectories of Single Climbing and Mossy Fiber Neurons in the Cerebellar Cortex and Nucleus

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Yoshikazu Shinoda and Izumi Sugihara

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Axonal Trajectories of Single Olivocerebellar Axons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Distribution of CFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thin Collaterals of OC Axons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Relationship Between the Longitudinal Distribution of CFs of Single OC Axons and Aldolase C Bands in the Cx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Compartmentation of the CN and Its Relationship to the Cortical Compartments . . . . . . . . . . . . Morphology of Single Mossy Fibers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lateral Reticular Nucleus Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Features of Axonal Trajectories of Single LRN Neurons . . . . . . . . . . . . . . . . . . . . . . . . . Distribution of Terminals of Single LRN Axons in the Cx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Morphology of Collaterals Terminating in the Cerebellar and Vestibular Nuclei . . . . . . . . . . . . . Dorsal Column Nucleus Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pontine Nucleus Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spinal Cord Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Features of Axonal Projection Patterns of Single CF and MF Neurons . . . . . . . . . . . . . . Functional considerations: Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

A major factor in determining the function of a particular cerebellar cortical region depends upon its afferent and efferent connections. Two distinct afferent pathways convey information to the cerebellar cortex: climbing fibers and mossy fibers. A large amount of fundamental knowledge about afferent projections to the cerebellum from various precerebellar nuclei has been accumulated using new anatomical methods, including knowledge about the axonal trajectories of single Y. Shinoda (*) · I. Sugihara Department of Systems Neurophysiology, Graduate School of Medicine, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_20

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climbing fiber neurons in the inferior olive and single mossy fiber neurons of multiple sources. Knowledge about the morphologies of single mossy fiber neurons and climbing fiber neurons in the cerebellum is essential for understanding the function of the cerebellum. This chapter describes and compares the entire axonal trajectories of single olivocerebellar (OC) neurons, and single mossy fiber neurons in the lateral reticular nucleus, pontine nucleus, dorsal column nucleus and spinal cord in the cerebellar cortex and nucleus. Furthermore, this chapter will deal with the relationship between the longitudinal cortical and nuclear compartmentations revealed by aldolase C expression and the longitudinal bands of cortical and nuclear axonal terminals of single climbing fiber neurons and single mossy fiber neurons. We discuss the functional significance of these arrangements for the generation of the final output from the cerebellar nuclei which target extracerebellar structures for control of movement and other functions. Keywords

Mossy fiber · Climbing fiber · Purkinje cell · Aldolase C · Lateral nucleus · Pontine nucleus · Inferior olive · Zebrin

Introduction The Purkinje cell is the only output neuron of the cerebellar cortex (Cx), and the cortical neuronal circuitry in which Purkinje cells (PCs) are embedded remains remarkably constant in different cerebellar regions. Therefore, a major factor in determining the function of a local cerebellar area depends upon its afferent and efferent connections and the relationship between the two (Eccles et al. 1967; Ito 1984; Voogd 1969). Two distinct afferent pathways which arise from many different origins (vestibular, spinal, and cerebral cortical) convey information to the Cx. The afferents that project to the cerebellum via precerebellar nuclei with the exception of the inferior olive (IO) take the form of mossy fibers (MFs) in the Cx, while the afferents to the Cx via the IO (olivocerebellar axons) take the form of climbing fibers (CFs). CFs originate from the contralateral IO, and each PC is directly innervated by a single CF (Cajal 1911; Szenthágothai and Rajkovits 1959). On the other hand, MF axons originate from multiple sources and project often bilaterally by crossing the midline in the cerebellar commissure. The cerebellar nuclei (CN) comprise the fastigial (medial) (FN), interposed (IP), and dentate (lateral) nuclei (DN), and three subdivisions of the corticonuclear projection are identified, medial (vermis), intermediate, and lateral zones, projecting to the FN, IP, and DN, respectively (Jansen and Brodal 1940). In the Cx, longitudinal compartmentation beyond these three subdivisions was revealed by the demonstration of zones A–D based on cholinesterase staining in the cerebellar white matter and the topography of the corticonuclear and olivocortical projections (Voogd 1964, 1969; Groenewegen and Voogd 1977; Kawamura and Hashikawa 1979; Buisseret-

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Delmas and Angaut 1993). These longitudinal zones extend across one or more lobules, even across the entire rostrocaudal length of the Cx (Voogd and Bigaré 1980; Voogd et al. 1987). The olivocerebellar (OC) projection is also arranged according to the same principle (Voogd 1969; Oscarsson 1969). Details of the topographic relationship of cerebellar zones are described in a separate chapter. For a proper understanding of cerebellar function, it is essential to know how MF and CF afferent systems interact with these cortical longitudinal zones defined both anatomically and electrophysiologically and emit output signals to the CN via PCs and how these PC output signals interact with nuclear collateral inputs from MF and CF afferents in nuclear neurons and generate final cerebellar output signals to their targets outside the cerebellum. Since the late twentieth century, neuroanatomists have tried to reveal the unknown neural connections in the mammalian central nervous system (CNS). Along with the development of new anatomical techniques, a large amount of fundamental knowledge about afferent systems to the cerebellum has been accumulated. However, the conclusions reached by the earlier neuroanatomists are not always correct, because of the following methodological advantages and disadvantages of the different anatomical techniques: 1. The degeneration method was widely used early on for its ability to identify fiber connections, was applied to the analysis of cerebellar afferent projections, and was greatly enhanced with the advent of the Nauta method. But this method is capricious, and its most serious drawback is that it is very difficult to distinguish degenerated passing fibers from degenerated terminals. 2. Great technical development in neuroanatomy was achieved in 1970–1990 by the introduction of new retrograde tracers such as horseradish peroxidase (HRP), wheat germ agglutinin-horseradish peroxidase (WGA-HRP), and cholera toxin B subunit. These methods appreciably expanded our knowledge about fiber connections in the CNS. However, one serious problem in these retrograde-labeling methods is that these tracers are taken up not only by nerve terminals but also by fibers of passage. The projections from the precerebellar nuclei to the CN was investigated by injecting retrograde traces into the CN, but many studies reported false-positive data about collateral projections to the CN. As pointed out by Dietrichs et al. (1983), injection tracks to deliver a tracer solution into the CN inevitably pass through the Cx, or tracers might be taken up by passing fibers in and around the CN. 3. Injection of an orthograde tracer into a certain nucleus is generally useful for detecting projections from the injected nucleus to multiple target regions, although this method cannot differentiate whether single neurons in the nucleus project to two different targets via collaterals or neurons that project to individual targets coexist in the nucleus. New orthograde tracers were introduced, first WGA-HRP and later Phaseolus vulgaris-leucoagglutinin (PHA-L) and biotinylated dextran amine (BDA). As described for retrograde labeling, tracer uptake by passing fibers may occur for orthograde labeling. For example, in the case of an injection into the pontine nucleus, a tracer is often taken up by passing

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fibers from the nucleus reticularis tegmenti pontis or contralateral pontine nucleus (Mihailoff 1993). PHA-L and BDA were reported to be taken up by passing fibers especially when injected in a large amount, but it does not occur significantly when injected in a small amount. Afferent projections were also investigated by means of anterograde transport of tritiated amino acids such as leucine, since these amino acids are considered to be taken up only by cell bodies. However, termination or fine passing fibers could not be confirmed with certainty from the light microscopical material, and, in addition, this method could not determine whether labeled materials are either axon collaterals from stem axons of MFs or CFs projecting to the Cx or axon terminals of axons that specifically project to the CN without any projection to the Cx. 4. Despite abundant anatomical studies on the CF and MF systems, there is little information available on the organization of CF and MF projection at the level of single neurons. The Golgi method was the only staining method for observing single-cell morphology, but this method could not adequately delineate axonal morphology because it is difficult to impregnate myelinated axons in adult tissue and the neural processes pass out of the plane of section. Therefore, most of the neurons in the mammalian CNS remain terra incognita as far as their axonal trajectories are concerned. A new intracellular staining method with fluorescent dyes made it possible to study the morphology of physiologically identified neurons (Stretton and Kravitz 1968), but fluorescent dyes were not suitable for staining thin axon collaterals in the mammalian CNS. For visualization of the entire axonal morphology of a single neuron with a long axon, HRP was successfully used for intracellular staining (Jankowska et al. 1976; Snow et al. 1976; Kitai et al. 1976), and Kitai et al. (1976) succeeded in staining single electrophysiologically identified PCs with this method. Although all of the processes of a single neuron labeled with a tracer are not contained in a single section, the reconstruction of the axonal trajectory using serial sections makes it possible to reveal the entire axonal trajectory of a single labeled neuron, and, at present, neurons with long axons such as corticospinal and vestibulospinal axons can be visualized with this method over a distance of 10–30 mm (Shinoda et al. 1981, 1986). The single cerebellar afferent fibers first stained with this method were functionally identified MFs that responded to muscle stretch (Krieger et al. 1985). Since then, the branching patterns of cerebellar afferent and efferent systems were investigated with this method (Shinoda et al. 1992). However, intracellular iontophoretic injection of HRP into a cell or an axon requires highly proficient skills, and the same result can be achieved by the extracellular injection of BDA. Extracellularly injected BDA is taken up by dendrites and cell bodies in the vicinity of an injection site and carried to terminals arising from stained neurons. By controlling the amount of injection, it is possible to label a limited number of neurons or even a single neuron, which makes it possible to reconstruct the entire trajectories of single cerebellar afferent neurons from serial sections (Sugihara et al. 1999; Wu et al. 1999). This review will summarize and compare the characteristic features of the axonal projection patterns of single CF and MF neurons in the Cx. In addition, the projections of

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single CF and MF neurons will be correlated to cerebellar cortical longitudinal zones and nuclear zones classified by aldolase C expression. Besides the projection to the Cx, CF and MF projections to the CN have not been fully investigated. The CN gives rise to cerebellar outputs to target structures outside the cerebellum (Toyama et al. 1968; Uno et al. 1970; Allen and Tsukahara 1974; Shinoda et al. 1985a, b; Futami et al. 1986; Sato et al. 1996, 1997), and efferent CN neurons receive inhibitory input from PCs (Eccles et al. 1967; Ito et al. 1970). The presence or absence of excitatory inputs to the CN from the precerebellar nuclei is important for understanding cerebellar function (Shinoda et al. 1993, 1997). It had commonly been assumed that neurons in the precerebellar nuclei project to the Cx and that all have axon collaterals to the CN. This view has been echoed in textbooks, reviews, and even research articles without experimental evidence. However, cerebellar anatomists could not definitely confirm the existence of afferent axons to the CN with the classical degeneration method. The existence of axon collaterals of OC axons to the CN was first demonstrated by Gerrits and Voogd (1987), using a modern reliable anatomical staining method. The existence of the projections of MFs to the CN had been more controversial (Dietrichs et al. 1983; Chan-Palay 1977; Ito 1984). By introducing an intraaxonal staining method with HRP, electrophysiologically identified MFs were visualized using serial sections, and the existence of nuclear axon collaterals of single MF axons terminating in the Cx was definitely demonstrated (Shinoda et al. 1992). However, in spite of a wealth of anatomical reports on the afferent projections to the Cx, there have been far fewer studies on afferent projections to the CN. Therefore, this review also deals with the presence or absence of cerebellar afferent projections to the CN and discusses the functional significance of these projections for output generation in the cerebellum for motor control.

Axonal Trajectories of Single Olivocerebellar Axons The entire axonal trajectories of OC neurons were completely reconstructed on serial sections in the rat (Sugihara et al. 1999). For clarification in the following description, the entire axon of an IO neuron is called an OC axon, while a thick branch of the OC axon in the Cx that terminates on dendrites of a PC in the molecular layer is called a CF (Cajal 1911). Stem axons left the IO toward the contralateral side, crossed the midline, and ran transversely above or through the contralateral IO (Fig. 1b). After entering the white matter of the inferior cerebellar peduncle (ICP), they ran longitudinally through the dorsolateral ICP and in the white matter rostral and dorsal to the CNs (Voogd 1995), but sometimes they ran through or beneath the CNs (Fig. 2c). Axons projecting to the vermis through the rostral ICP entered the deep cerebellar white matter rostral to the FN, whereas those projecting to the lateral and intermediate hemisphere through the caudal ICP entered the cerebellar white matter rostral to the DN. OC stem axons successively ramified into many branches in the deep cerebellar white matter, when the stem axons reached the semi-parasagittal plane in which axonal branches terminated as CFs. These axonal branches entered the folial white matter and while ramifying ran together in the semi-parasagittal

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Fig. 1 Frontal view of the trajectory and the distribution of climbing fibers (CFs) of a single olivocerebellar (OC) axon innervating crus Ia. Biotinylated dextran amine (BDA) was injected into the dorsal lamella in the principal olive of the inferior olive (IO). A filled arrowhead indicates a thin collateral in the inferior cerebellar peduncle (ICP), an arrow the first bifurcation into two thick branches, and open arrowheads the first two branching points of thin collaterals that terminated in the granular layer. All collaterals of this axon could be traced to their terminals. Abbreviation: FL flocculus, FN fastigial nucleus, PFL paraflocculus, PIN posterior interpositus nucleus, Sim b lobule simplex b, D, V, L, and M dorsal, ventral, lateral, and medial. (From Sugihara et al. 1999)

plane to reach their sites of termination in the Cx contralateral to the IO of their origin (Fig. 2a). The branches of OC axons were grouped into thick branches (0.7– 1.4 μm in diameter) and thin collaterals (0.2–0.5 μm), and the diameter of stem axons was within the range of that of thick branches (Fig. 1a). A single OC axon generated

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Fig. 2 Reconstruction of the entire trajectories of six OC axons originating from a centromedial portion of the medial accessory olive (MAO). (a, c) Lateral view of six OC axons. CF terminals of each axon are distributed widely in a rostrocaudal direction through lobules VI and VII, but all of the terminals are distributed in a limited mediolateral width of about 0.3 mm. CFs in gray do not belong to the six reconstructed OC axons represented by different colors. Dotted lines, borders of the granular layers. V–VIII and X, lobules V–VIII and X. (b) Longitudinal band of CFs of the six OC axons in the cerebellar cortex (Cx). CFs of individual OC axons are plotted on the unfolded parasagittal strip of the cerebellar cortical surface of lobules VI and VII (stippled area in the inset in a). Colors used for CFs in (b) correspond to those used for the OC axons in (a) and (c). Light and dark gray areas in the unfolded scheme represent the Cx exposed on the cerebellar surface and hidden in the sulci, respectively. Note that thin axon collaterals of the OC axons terminate in the FN. (From Sugihara et al. 2001)

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2–17 final thick branches (CFs) (6.1
3.7, mean
S.D., n ¼ 16), each of which innervated a single PC as a CF. The number of CFs of a single OC axon is consistent with the average number of CFs per OC axon (about seven in the rat) inferred by counting the total numbers of PCs and IO neurons (Schild 1970).

Distribution of CFs The most distal portion of each thick branch of an OC axon reached a target PC usually at its soma, and a terminal arborization on a single PC was always formed by a single CF. The number of swellings on the terminal arborization of a single CF was 154–321 (249.8
42.2, n ¼ 32). The diameter of swellings ranged from 0.5 to 2.0 μm, mostly 1.2–1.6 μm. Assuming 6.1 CFs per OC axon, 249.8 swellings per CF corresponded to 1,524 swellings on CF terminal arborizations per OC axon, on average. The cortical distribution of CFs of a single OC axon conformed to the pattern predicted from previous mass labeling studies of the OC projection; namely, all CFs of a single OC axon terminated in a single strip-shaped longitudinal band in the Cx. This band spread widely in a rostrocaudal direction, covering single or multiple lobules, but only narrowly in a mediolateral direction (usually about 200–300 μm) (Fig. 2). In the example shown in Fig. 2, six labeled OC axons in the medial accessory olive (MAO) ran close to each other in the brain stem and the most rostral ICP (Fig. 2c). Stem axons curved caudally and ran closely together rostral and dorsal to the FN and started ramifying in the deep white matter in a rostrocaudal direction. The branched main axons ascended in the white matter in the same parasagittal plane toward the vermal cortex of lobules VI and VII and, ramifying in a rostrocaudal direction in the folial white matter of individual lobules, terminated as CFs in the molecular layers of single (brown axon), multiple separate (light blue axon), or adjacent lobules (pink, green, orange, and purple axons) (Fig. 2a). As in this example, IO neurons in a very restricted area of the IO have common features in axonal coursing and terminal distribution in a particular lobule or lobules. Increasing volumes of BDA injected into a particular portion of the IO subnucleus resulted in the rostrocaudal extension of the projection area in a single longitudinal band, but with only slight extension in the mediolateral width. This finding indicates that adjacent IO neurons project to a set of segments in the same longitudinal band rather than to multiple segments in separate longitudinal bands (Sugihara et al. 2001) and that individual longitudinal compartments of single OC axons are much narrower than classical longitudinal zones of A, B, C, and D (Voogd 1969). The width of a longitudinal compartment innervated by a single OC axon almost corresponded to the width of the mediolateral distribution of PCs that show synchronous firing of complex spikes (Sugihara et al. 1995).

Thin Collaterals of OC Axons Thin collaterals, which were given off from stem axons and thick branches of OC axons, were more abundant in terms of the number per OC axon than thick branches. For convenience of description, they were classified into three types according to

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their main termination sites: (1) white matter in the ICP, (2) the CNs, and (3) the cerebellar granular layer. All of the thin axon collaterals and their terminals in the ICP, the CNs, and the granular layer were derived from OC axons terminating as CFs in the Cx, and none of the OC axons terminated specifically in the CNs without projecting to the Cx. Thin collaterals to the CNs were observed in 20 out of 22 OC axons, and each of these 20 axons had one (n ¼ 15), two (n ¼ 3), three (n ¼ 1), or six (n ¼ 1) collaterals (1.4
1.2 collaterals per OC axon) that innervated only a single CN (Sugihara et al. 1999). In the example in Fig. 2, all OC axons projected to lobules VI and VII of the vermis, and their nuclear collaterals were given off only to the FN. The diameters of nuclear collaterals were very thin, ranging from 0.2 to 0.3 μm, and their terminal branches bore several swellings of en passant and terminal types. The average number of swellings per nuclear OC collateral was 54.0
66.0 (n ¼ 22). Thin collaterals terminating mainly in the granular layer were given off from stem or thick branches of OC axons in the deep and folial white matter (Fig. 1a). Swellings were densest in the upper portion of the granular layer but were seen at all depths in that layer. Some swellings in the granular layer seemed to make contact with the soma of a presumed Golgi cell, and other swellings were located among a dense aggregation of granule cells. Thin collaterals usually terminated in the same lobule and the same parasagittal zone as CFs of the same OC axons. The number of thin collaterals in the granular layer ranged from 3 to 16 (average, 8.5) per OC axon (see details of thin collaterals in Sugihara et al. 1999).

Relationship Between the Longitudinal Distribution of CFs of Single OC Axons and Aldolase C Bands in the Cx The cortical longitudinal zones are classically divided into A, B, C1, C2, C3, D1, and D2 (Voogd 1969). An electrophysiological study showed that the Cx is composed of fine longitudinal strips with a width of 0.3 mm and length of around 3 mm, and this functional unit is called a “microzone” (Oscarsson 1979). Even finer longitudinal compartmentation in the Cx was defined based on the expression pattern of aldolase C (zebrin II). Hawkes and Leclerc (1987) showed that a subset of PCs and their axons that were stained with antizebrins were arranged in longitudinal zones alternating with strips of non-zebrin-immunoreactive PCs and that most zebrin-positive bands continued uninterruptedly from the anterior to the posterior lobe. Recently, a correspondence between the OC projection pattern and aldolase C compartments of some parts of the Cx has been examined using a combined orthograde labeling of OC axon terminals and aldolase C immunohistochemistry in mass labeling materials (Voogd et al. 2003; Voogd and Ruigrok 2004; Pijpers et al. 2005, 2006). Figure 3 shows an example of the relationship between CFs of single OC axons and aldolase C expression pattern in the Cx in a systematic study of the entire Cx and IO (Sugihara and Shinoda 2004). A comprehensive two- dimensional map of the aldolase C compartments was first formed in the entire unfolded Cx from serial sections. CFs labeled by a small injection of BDA into the IO were then mapped onto this aldolase C map generated from the same rat. Labeled CFs following injection

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Fig. 3 Reconstruction of aldolase C compartments throughout the Cx and the relationship of CF longitudinal bands to aldolase C (zebrin II) pattern. Continuity of the compartments in the rostrocaudal direction was determined by precise reconstruction of individual compartments on serial sections and then plotted on a map of the unfolded Cx (see Sugihara and Shinoda 2004). The nomenclatures of compartments were adopted according to Hawkes and Leclerc (1987), Voogd et al. (2003), and Voogd and Ruigrok (2004). An aldolase C-positive compartment and its laterally neighboring negative compartment usually have the same name with different suffixes (+, positive compartment; , negative compartment). I–X, lobules I–X; a–c, sublobules a–c. Distribution of CFs labeled following injection of BDA into the MAO in the four experiments is superimposed on the aldolase C map. The colored dots plotted on an unfolded representation of the Cx indicate locations of individual CFs labeled by injection into four different parts of the MAO. Narrow longitudinal band-shaped OC projection from a single injection site connects corresponding rostral and caudal aldolase C compartments. (From Sugihara and Shinoda 2004)

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into the caudolateral MAO (red) were distributed in a longitudinal band of aldolase C-negative band (1-) and spread widely even in the anterior and posterior vermis. Similar distributions of labeled CFs following injections into different parts of the MAO were observed in aldolase C-negative longitudinal bands (green and light blue) and aldolase C-positive band (purple) (Fig. 3). However, even though CFs shown in the same color seemed to be located in a single continuous longitudinal band in the anterior and posterior lobes, they belonged to bands of different names in the anterior and posterior lobes (e.g., green CFs in the anterior lobe are located in the (1-) compartment, whereas green CFs in the posterior lobe are located in the (2-) compartment). Single OC axons often innervate the rostral and caudal cerebellum by their axon collaterals (Sugihara et al. 2001). Taking advantage of this property, a specific pair of rostral and caudal aldolase C compartments was correctly linked based on the common projection of single OC axons. Whereas previous studies presumed that rostral and caudal compartments with the same nomenclature corresponded to each other (Hawkes and Leclerc 1987; Brochu et al. 1990), it turned out that this relationship did not always hold (see the links between rostral and caudal aldolase C compartments in Table I in Sugihara and Shinoda (2004)). Individual longitudinal bands of CFs in different colors (Fig. 3) were aligned in the new pairs of the linked rostral and caudal compartments determined in relation to the common topographic OC projection to the pair of compartments in the anterior and posterior lobes.

Compartmentation of the CN and Its Relationship to the Cortical Compartments The compartmentation of OC projection in the Cx suggests that an equivalent compartmentation may exist in the CNs, because PCs project topographically onto the CNs (Buisseret-Delmas and Angaut 1993) and topographically projecting OC axons gives rise to collaterals to the CN (Sugihara et al. 1999, 2001). Most single OC axons have axon collaterals to the CN on their way to the main cortical projection area (Sugihara et al. 1999). In the example in Fig. 2, OC axons originating from the MAO projected to lobules VI and VII in the vermis and to the FN by their axon collaterals. Taking advantage of this innervation property of single OC axons, the functional relationship between the OC compartments of the CN and the Cx was systematically investigated (Sugihara and Shinoda 2007). First, aldolase C expression of PC axon terminals was used to map the compartments of the CNs. The localization of PC terminals with or without aldolase C classified the CNs into aldolase C-positive and C-negative groups, respectively (Fig. 4c). The DN and the posterior interpositus (PIN) were aldolase C-positive, whereas the anterior interpositus (AIN) was aldolase C-negative. The FN was divided into rostral aldolase C-negative and caudal aldolase C-positive compartments (Fig. 4d). Then, a pair of cortical and nuclear aldolase C compartments innervated by single OC axons was

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Fig. 4 Clustering of termination areas of nuclear collaterals of OC axons in the cerebellar nuclei (CNs) classified into five groups based on their cortical projection patterns. (a) Mapping of 123 injection sites on the dorsal view of individual subnuclei of the right IO. (b) Mapping of labeled CF terminals in aldolase C compartments on the unfolded cortical scheme. Each injection site was classified into one of the five groups based on its projection pattern to aldolase C compartment by referring to the classification of OC projection (Sugihara and Shinoda 2004, their Fig. 8a). The injection sites in the IO (a) and their corresponding labeled CFs (b) and olivonuclear termination areas (c) are indicated by different colors, depending on which group they belong to (green, group I; blue, group II; yellow, group III; red, group IV; gray, group V). (c): Rostral (a), dorsal (b), and caudal (c) views of the left CNs showing three-dimensional distribution of nuclear termination areas of 123 olivary injections shown in (a). (d) Three-dimensional reconstruction of the aldolase C-positive (gray) and C-negative area in the left CNs shown in a dorsocaudal view for comparison. The wire frames are coronal contours of the cerebellar nuclei. Gray and darker gray areas indicate aldolase C-negative and C-positive compartments, respectively. PO and DAO principal and dorsal accessory olive, CP copula pyramidis in (b), Cr I and Cr II crus I and II of ansiform lobule, Par paramedian lobule, pf primary fissure, VPFL ventral paraflocculus, DC dorsal cap of Kooy, VLO ventrolateral outgrowth, ICG interstitial cell group, DMC dorsomedial crest, CP caudal pole in (c) and (d), DLH dorsolateral hump, DLP dorsolateral protuberance, AIN anterior interpositus nucleus, d-Y dorsal group Y nucleus. (From Sugihara and Shinoda 2007)

systematically mapped following injections of a small amount of BDA into various parts of subnuclei of the IO (Fig. 4a). In each IO injection case, CFs of labeled OC axons were mapped within cortical aldolase C compartments (Fig. 4b), and then

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terminals of nuclear collaterals of the same OC axons were mapped in aldolase C compartments of the CN (Fig. 4c). Based on the results of this analysis, the olivocorticonuclear projection was classified into five “groups” of functional compartments (represented by five different colors in Fig. 4a–c) (Sugihara and Shinoda 2007). Each group originated from a subarea within the IO (Fig. 4a) and projected to multiple cortical strips of PCs, all of which were either aldolase C-positive (groups I–II and V) or aldolase C-negative (groups III and IV). As mentioned above, the CNs were divided into caudoventral aldolase C-positive (DN, PIN, and caudal FN) and rostrodorsal aldolase C-negative parts (AIN and rostral FN) (Fig. 4c, d). The olivonuclear terminations of the five groups projected topographically to five separate compartments within the CNs with the same aldolase C expression (either positive or negative). A PC axon formed a terminal arbor in a specific small area in the CN, and rostrocaudal PCs in a single longitudinal band of aldolase C-positive or C-negative cortical compartment converged upon the aldolase C-positive or C-negative nuclear compartment, respectively (Sugihara et al. 2009). Therefore, whether PCs were located in the anterior or posterior lobe, aldolase C-positive PCs projected to the caudoventral aldolase C-positive nuclear compartments, and aldolase C-negative PCs projected to the rostrodorsal aldolase C-negative nuclear compartments. These findings suggest that each nuclear compartment and its corresponding cortical longitudinal strip innervated by the common OC axons are connected to each other by PCs with the same properties in aldolase C expression, and these three form a functional unit in the cerebellum. This structure may be a morphological correlate for a functional unit of a “corticonuclear microcomplex” proposed by Ito (1984).

Morphology of Single Mossy Fibers Quantitatively important sources of MFs are the spinal cord, the pontine nuclei (PNs), the vestibular nuclei, the lateral reticular nucleus (LRN), and the dorsal column nuclei (DCNs). However, our knowledge about the precise terminations of most afferent MF systems, especially their single axonal projection patterns in the Cx and CN, is far from complete. Since the cerebellar MF projection from the LRN has been investigated well in the rat, this section will describe single axonal morphologies of LRN neurons first and the similarity and difference of the projection pattern between the LRN and other MF systems later.

Lateral Reticular Nucleus Neurons General Features of Axonal Trajectories of Single LRN Neurons Mass labeling studies using autoradiography (Künzle 1975; Chan-Palay et al. 1977) and PHA-L (Ruigrok and Cella 1995) clearly showed that MFs of the LRN terminate in longitudinal strips in the granular layer. Data obtained from complete

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reconstruction of the entire trajectories of single LRN axons confirmed their findings and further extended the information about the projection pattern (Wu et al. 1999). A majority of LRN axons passed through the ipsilateral ICP to the cerebellum (n ¼ 25 out of 29) (Fig. 5), but some axons (n 4) ran through or under the contralateral IO and entered the cerebellum through the contralateral ICP. Generally, an arbor of an LRN axon within the cerebellum could be regarded as consisting of a thick stem axon (2.5–3.5 μm in diameter) running transversely, cortical branches of various diameters (around 2 μm), and very thin nuclear branches (0.4–1.0 μm). Most stem axons crossed the midline within the cerebellum to make bilateral projections with ipsilateral preponderance. While running transversely in the cerebellar white matter rostral and dorsal to the CNs toward the contralateral side, stem axons gave rise to several primary collaterals to the Cx and CN. These cortical collaterals arose almost perpendicularly from the stem axons and ran almost in the parasagittal plane. On their way, individual collaterals ramified widely mainly in a dorsoventral direction, but did not spread so much in a mediolateral direction, so that each collateral

Fig. 5 Reconstruction of the entire trajectory of an MF axon originating from a lateral reticular nucleus (LRN) neuron in the cerebellum and brain stem. The reconstruction of the axon labeled with extracellular iontophoretic application of BDA was made from 158 serial sections of 50 μm thickness. IP posterior interpositus nucleus, sct spinocerebellar tract, sptV spinal trigeminal tract, SPVI nucleus interpolaris. (From Shinoda 1999)

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terminated as an MF rosette in the granular layer in a relatively narrow longitudinal zone covering one to four lobules (Fig. 5). The number of cortical primary collaterals given off from a transverse stem axon was five to nine (7.0
1.0, n ¼ 29). In each bilaterally projecting neuron, the number of ipsilateral and contralateral primary collaterals was three to five (3.8
0.8, n ¼ 25) and two to six (3.7
1.4, n ¼ 25), respectively. In each ipsilaterally projecting neuron, the number of primary collaterals was five to eight (6.0
1.2, n ¼ 4).

Distribution of Terminals of Single LRN Axons in the Cx Each terminal branch of a single LRN axon always terminated as a rosette terminal of terminal type or en passant type in the granular layer. The number of rosettes per axon ranged from 84 to 219 (154.0
37.0, n ¼ 11). In each bilaterally projecting axon, the ratio of axon terminals in the ipsilateral Cx to those in the contralateral Cx ranged from 1.3 to 2.3 (1.7
0.4, n ¼ 7). Axon terminals were mainly seen in lobules III–VI; occasionally in lobules II, VII, and VIII in the vermis and paravermal area of the anterior lobe; and sometimes in the hemisphere. Cortical primary collaterals sent terminal branches sometimes to a single lobule but usually to multiple (one to four) lobules and spread rather widely in the semi-parasagittal plane (width, 400–2,000 μm, usually more than 1,000 μm) (lower drawings in Fig. 6). In contrast, the spread of the terminal branches of a single primary collateral was relatively restricted in the transverse plane (mediolateral width, usually 300– 650 μm), and the terminal distribution of a single LRN axon roughly showed a pattern of multiple longitudinal bands arranged mediolaterally (upper drawings in Fig. 6). Figure 7 shows an example of the longitudinal terminal distribution of individual primary collaterals, in which the distances from the midline to individual terminals were plotted on unfolded longitudinal strips of the vermal lobules. In Fig. 7a, two adjacent primary collaterals terminate in a longitudinal zone which is labeled zone c in Fig. 6. In this zone, terminals of one collateral were distributed in lobule V, and those of the other in lobule VI with two clusters of terminals were slightly separated in lobules VIa and VId. The longitudinal spread of the terminal clusters extended over 6.5 mm (see legend in Fig. 7), whereas the mediolateral spread of the clusters was limited between 230 and 400 μm. Even as a whole, these terminals were well aligned in a single longitudinal strip less than 400 μm wide in the transverse plane. Similarly, Fig. 7b shows the distribution of terminals of another primary collateral of the same axon (labeled zone e in Fig. 6) on the unfolded cortical parasagittal strip. This collateral bifurcated into two main branches, one in lobule III and the other in lobules IV and V. Terminals were distributed widely in a parasagittal longitudinal strip (11.6 mm long), but the mediolateral spread was restricted within 600 μm as a whole. As shown in this example, the general feature of the cortical distribution of terminals of a single LRN axon could be summarized as follows. Terminals that belong to one or sometimes two primary collaterals spreading in a few lobules make a longitudinal zone in the parasagittal plane that is usually less than

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Fig. 6 Frontal (top) and lateral views (bottom) of a completely reconstructed single LRN axon originating from the caudal part of the right LRN. This axon enters the cerebellum through the right ICP, projects to the vermis bilaterally (lobules II through VII) and the FN (see the bottom drawing e), and forms a multiple longitudinal zonal projection pattern by its cortical arborescent collaterals. Bottom drawings show lateral views of individual collaterals as indicated in the topdrawing with lowercase letters (a–g). (Modified from Wu et al. 1999)

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Fig. 7 Longitudinal band distribution of terminals of single primary collaterals of an LRN axon in the unfolded Cx. Primary collaterals in (a) and (b) are the same as shown in Fig. 6c and e, respectively. (a) Terminals of two primary collaterals plotted on the unfolded Cx (left). Two terminals in lobule VII that were far away from the other terminals in lobules V and VI are not included in the unfolded strip, but they were located in the same parasagittal strip. (b) Terminals borne on a primary collateral plotted on unfolded lobules III–V (right). The rostrocaudal distance

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500 μm wide in a mediolateral direction, and several such longitudinal zones of terminals are arranged almost in parallel mediolaterally.

Morphology of Collaterals Terminating in the Cerebellar and Vestibular Nuclei All reconstructed LRN axons supplied collaterals to the CN. Nuclear collaterals were given off from transversely running stem axons or proximal parts of cortical primary branches and ran in a caudal direction. A single axon had two to three (2.5
0.5, n ¼ 11) primary collaterals to the cerebellar (and/or vestibular) nuclei. Each of these nuclear collaterals was much thinner (diameter, 0.4–1.0 μm) than stem axons (diameter 1.5–2.0 mm) and cortical branches and had a localized termination area in the CN or CNs. A nuclear collateral ran toward the target nucleus in a relatively straight path without any branching when the branching point was far from the CN. Within the CN, a nuclear collateral bore several en passant swellings and had only one or two ramifications to end in several (usually one to four) terminal branches. Each terminal branch was usually about 200–500 μm long and bore frequent en passant swellings and sometimes short branchlets bearing a terminal swelling. Usually, a single axon innervated only one target nucleus, but sometimes two CNs, or both the cerebellar and vestibular nuclei (most often the FN and IP and occasionally the DN and IP). There seemed to be a rough correspondence in the cortical and nuclear projections of single LRN axons, which is compatible with the zonal arrangement in corticonuclear projection (Voogd et al. 1996). For example, when an axon had a collateral in the FN, the same axon always had terminations in the vermis on the same side as the FN. An axon with collaterals in the IP and the DN often innervated the intermediate part including the most lateral vermis and the hemisphere.

Dorsal Column Nucleus Neurons The connections of the DCNs with the cerebellum have been extensively investigated both anatomically and electrophysiologically. Sagittal organization of MFs from the cuneocerebellar tract was reported by Voogd (1964, 1969) and definitely confirmed by Gerrits et al. (1985) with autoradiography. The axonal trajectories of ä Fig. 7 (continued) regarding distribution of terminals was measured along the surface of the molecular layer on a reconstructed parasagittal section, and the locations of axon terminals in the granular layer were projected to the corresponding sites on the surface of the unfolded Cx. Arabic numbers attached to the portions of the folia correspond to those on the unfolded cortical parasagittal strips. Roman numbers indicate names of lobules. Note the narrow mediolateral and wide longitudinal distributions of terminals belonging to individual primary collaterals. (Reproduced from Wu et al. 1999)

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single dorsal column nucleus (DCN) (gracile (GN), cuneate (CuN), and external cuneate nucleus (ECuN)) neurons were analyzed only recently (Quy et al. 2011). Almost all axons projected only to the ipsilateral cerebellum (Fig. 8d), although some axons in the ECuN projected bilaterally (Fig. 8a). This finding is consistent with previous reports that the DCN-cerebellar projection is predominantly ipsilateral (Somana and Walberg 1980; Gerrits et al. 1985) with a small but definite projection to the contralateral anterior vermis (Voogd 1964). Stem axons originating from the DCN ran rostrolaterally in the dorsolateral superficial white matter of the medulla without any collaterals and entered the ipsilateral ICP. While running medially, the stem axons gave rise to several primary collaterals mostly in the ipsilateral (Fig. 8d) and occasionally in the bilateral deep white matter (Fig. 8a). These collaterals entered the folial white matter of several lobules which were either adjacent or separate from each other and further branched before entering the granular layer.

Fig. 8 Morphologies of reconstructed single MF axons of an external cuneate nucleus (ECuN) neuron (a, b) and a gracile nucleus (GN) neuron (d). (a) Frontal view of the axonal trajectory of an ECuN neuron, which projects bilaterally to the Cx, drawn on the montage of rostral and central cerebellar sections and a section of the caudal medulla. (b) Distribution of all the rosette terminals of this axon mapped on the unfolded cortical scheme. (c) Injection site in the ECuN mapped on the horizontal scheme of the dorsal column nucleus. The injection site in the GN applies to the neuron in (d). (d) Lateral view of the axonal trajectory of a single GN neuron on the montage of the cerebellum and the brain stem. Note a nuclear collateral of this neuron in the AIN (arrowhead). (From Quy et al. 2011)

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Each branch formed a cluster of MF rosettes in a band-shaped small area in a lobule. DCN axons showed trajectories and ramification patterns that were essentially similar to those described above, but the cortical lobules of their termination varied, depending on the locations of their cell bodies in the DCN. In the example in Fig. 8a, an ECuN axon projected bilaterally by way of its transcortical transverse stem axon in the deep cerebellar white matter. Several lobular branches were given off perpendicularly from the traversing stem axon, and axon terminals of individual primary collaterals were localized in a mediolaterally narrow strip zones. This branching pattern is very similar to that of LRN axons (Wu et al. 1999). The number of rosette terminals per axon ranged from 57 to 202 with an average of 123. Nuclear collaterals were relatively unusual in DCN-cerebellar axons (1/15 single neurons examined), in contrast to abundant collaterals in the CN of spinocerebellar MF axons (Matsushita and Yaginuma 1995). To examine the relationship between terminal distribution of single DCN axons and the aldolase C expression pattern in the Cx, all terminals of a single DCN axon were mapped on the aldolase C expression map of the same animal (Fig. 8b). The GN mainly projected to the copula pyramidis and lobules III–V, the CuN to the paramedian and simple lobules, and the ECuN to lobules I–VI and VIII–IX, although there was some overlap. The majority of terminals of the GN and CuN axons were located within aldolase C-negative or lightly C-positive compartments in different lobules, even though many single DCN axons projected to the anterior and posterior lobes with their axon collaterals. However, terminals of single neurons in the ECuN were located not only in aldolase C-negative but also in aldolase C-positive compartments, since single ECuN neurons often projected to lobule IX, which is mostly aldolase C-positive. One GN neuron that had an axon collateral to the AIP had rosette terminals in aldolase C-negative compartments in the anterior lobe (lobules III–V) and the posterior lobe (lobule VIII) (Fig. 8d).

Pontine Nucleus Neurons Inputs from the cerebral cortex to the CN were investigated by stimulating areas 6 and 4 and recording intracellular potentials from CN neurons in the cat (Shinoda et al. 1987). Stimulation of the precruciate cortex (area 6) produced small excitatory postsynaptic potentials (EPSPs) followed by large inhibitory postsynaptic potentials (IPSPs), and these EPSPs were considered to be mediated by the PN and the nucleus reticularis tegmenti pontis (NRTP), since stimulation of the PN and the NRTP produced monosynaptic EPSPs followed by IPSPs in the same DN neurons. To confirm these pathways anatomically, single MF axons originating from the PN were stained with intraaxonal injection of HRP after electrophysiological identification (Fig. 9b), and thin tiny axon collaterals of MF axons projecting to the Cx were identified in the DN (Fig. 9a) (Shinoda et al. 1992). However, nuclear collaterals were found only in about 20% of the PN axons well stained. Since the entire axonal trajectories of single PN axons could not be stained well in the cat, the axonal morphologies of single PN neurons were recently analyzed in the rat (Fig. 9c) (Na, Sugihara, and Shinoda unpublished). Typically, single pontocerebellar axons crossed

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Fig. 9 Photomicrographs of a nuclear collateral (a) and MF rosettes (b) of an intraaxonally stained pontocerebellar axon in the cat. Scale in B, 50 μm. (c) Axonal trajectory of a reconstructed single pontocerebellar axon superimposed on a montage of several coronal sections of the rat in which many terminals were located. A nuclear collateral was not found in this axon. All MF terminals of this axon are mapped on the scheme of aldolase C compartments of the Cx. BPN basilar pontine nucleus. (Reproduced from Shinoda et al. 1992)

the midline in the pons, and after entering the cerebellum through the contralateral middle cerebellar peduncle, ran transversely in the deep cerebellar white matter toward, and often across the midline. From the transversely running stem axons, multiple primary collaterals were successively given off almost perpendicularly in the Cx only contralaterally or bilaterally with a contralateral predominance. Each primary collateral further branched in a parasagittal plane to form a strip-shaped termination area with rosette-type swellings in the granular layer. Terminals were distributed mainly in the apex of the target lobules. Rosette terminals of PN axons were clustered almost exclusively in aldolase C-positive compartments in a single or multiple lobules (Biswas et al. 2019; Na et al. 2019). This projection pattern of single pontocerebellar axons with axon collaterals to multiple longitudinal compartments is very similar to that of single LRN and DCN neurons and may represent a general feature of the cortical projection of single axons in the MF systems. Axons originating from the central, rostral, and lateral part of the PN projected mainly to specific lobules with multiple branches to the simple lobule, crus II, and paramedian lobule, to crus I and dorsal paraflocculus, and to the ventral paraflocculus and lobule IXc, respectively. These findings indicated that the projection of single pontocerebellar axons was closely related to both lobular and longitudinal organizations of the cerebellum.

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Spinal Cord Neurons We recently reconstructed 22 single mossy fiber axons originating from the thoracic spinal cord in the mouse (Luo et al. 2017). They were classified into three groups in relation to their origins identified in retrograde labeling studies (Matsushita and Hosoya 1982): (1) non-crossed axons of Clarke’s column neurons (NCC), (2) noncrossed axons of marginal Clarke’s column neurons (NMCC), and (3) crossed axons of neurons in the medial ventral horn (CMVH). “Non-crossed” and “crossed” mean the pattern of the initial path of an axon in the spinal cord segment to enter the ascending path in the lateral funiculus of the spinal cord. Among these groups, NCC axons and NMCC axons retain similar characteristics in their overall projection pattern. They project to the cerebellar cortex with as many as about 100 mossy fiber terminals (99.4
49.8 terminals in 8 NCC axons, average and standard deviation, 91.0
30.0 terminals in 7 NMCC axons), which are distributed in multiple lobules as well as in multiple aldolase C stripes. They also innervated the cerebellar nuclei and additionally some parts of the vestibular nuclei which can be regarded akin to the cerebellar nuclei. In contrast, they give rise to no collaterals in other areas of the medulla or in the spinal cord. These characteristics, including many (about 100) mossy fiber terminals per axon and collateral termination to the cerebellar nuclei accompanied often or sometimes but no collateral termination in other areas in the axonal pathway, are also shared by mossy fiber axons originating from the LRN, PN, and DCN (above). This type of mossy fiber morphology is designated as “precerebellar type” (Luo et al. 2017). In contrast, CMVH axons show different branching patterns (below). The projection pattern of NCC and NMCC axons in the cerebellar cortex and nuclei appears tightly related to their functional significance. Originating from the thoracic spinal cord, these axons convey somatic sensory and integrative signals mainly for the hind limb and nearby trunk areas. Cortical and nuclear projection of these NCC axons project to the bilateral vermal lobules I–V and VIII–IX and mainly ipsilateral medial cerebellar nucleus and nucleus X (example shown in Fig. 10), whereas NMCC axons project to the ipsilateral paravermal lobules II–V and VIII/ copula pyramidis and medial anterior interposed nucleus. These areas, which overlap with the target areas of LRN and DCN axons (Wu et al. 1999; Quy et al. 2011), fit with the general definition of “spinocerebellum” (Brodal 1981; Nieuwenhuys et al. 2008). In comparison to LRN and DCN axons, projection areas of thoracic spinocerebellar axons are located in more medial and more rostral (in the anterior lobules) or caudal (in the posterior lobules) areas in the cerebellum than those of LRN and DCN axons, which fit with general somatotopy of the cerebellar cortex (hind limb-related activity is located in more medial and more rostral (in the anterior lobules) or caudal (in the posterior lobules) areas in the cerebellum) (Snyder et al. 1978; Brodal 1981). Concerning functional relationships between NCC and NMCC axons, the paravermal cerebellar cortex and anterior interposed nucleus are involved more in the control of specific limb parts by projecting to the thalamus and red nucleus, while the vermal (anterior and posterior) lobules and medial nucleus (rostrodorsal parts) are involved more in the control of trunk movement, locomotion,

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Fig. 10 Reconstruction of a single mossy fiber axon originating from the spinal cord (NCC axon). This axon terminated in the ipsilateral nucleus X and bilateral lobules II, III, VIII/copula pyramidis, and IX. (a, b) Caudal (a) and lateral (b) views of the reconstructed axonal trajectory. The axonal trajectory was drawn on a montage of drawings of multiple sections on which major axonal termination or a major axonal path was observed. (c) Mapping of all mossy fiber terminals of this axon on the scheme of aldolase C stripes in the unfolded cerebellar cortex of the mouse (Fujita et al. 2014). (d) Lateral view of the entire axonal trajectory in the brain and spinal cord. (e) Reconstruction of the BDA injection site in the thoracic segment T8. (f) Drawing of two collaterals that terminated in the nucleus X. Arrowheads indicate the trunk of the stem axon in (a) and (b) and branching points of collaterals in (f). Abbreviation: 1+, 1-, and so on, aldolase C compartment 1+, 1- and so on; I–V, VIII, IX, lobules I–V, VIII, IX; a–c, sublobules a–c (as in IXa–b); C, caudal; Cop, copula pyramidis; D, dorsal; ICP, inferior cerebellar peduncle; IVN, inferior vestibular nucleus; L, lateral (with orientation bars); Lt, left; M, medial; NX, nucleus X; R, rostral; Rt, right; sp5, spinal trigeminal tract; T, thoracic segment; V, ventral. (From Luo et al. 2017)

and posture by their projection to the vestibular nucleus and reticular formation (module C1–C3 versus module A (Teune et al. 2000; Brodal 1981; Nieuwenhuys et al. 2008)). Therefore, the difference in the projection patterns of single NMCC and NCC axons indicates a functional distinction between these projections; the NCC and NMCC axons seem to be involved in trunk- and extremity-related (or proximal and distal) sensorimotor control, respectively. CMVH axons show morphological characteristics remarkably different from other mossy fiber axons (Fig. 11). They give rise to multiple collaterals in the spinal

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Fig. 11 Scheme of three groups (NCC, blue; NMCC, red; and CMVH, green) of the spinocerebellar projection originating from the thoracic segments. (a) Termination areas in the cerebellar cortex. Superimposition of terminal mapping of 22 reconstructed axons. (b–e) Collateral termination areas with a sample of collaterals in the cerebellar nuclei (b) in the rostral and caudal medulla (c and d, respectively) and in the spinal cord (e). (f) Origins of these groups in a thoracic segment. Abbreviation: I–V, VIII, IX, lobules I–V, VIII, IX; a–c, sublobules a–c (as in IXa–b); AIN, anterior interposed nucleus; C, caudal (with orientation bars), cervical segment; CMVH, crossing medial ventral horn neurons; Cop, copula pyramidis; D, dorsal; Gi, gigantocellular reticular nucleus; IVN, inferior vestibular nucleus; L, lateral (with orientation bars); LRN, lateral reticular nucleus; M, medial; MdD, dorsal part of the medullary reticular nucleus; MN, medial nucleus; MVNmc, magnocellular part of the medial vestibular nucleus; NCC, non-crossing Clarke’s column neurons; NMCC, non-crossing marginal Clarke’s column neurons; NX, nucleus X; PnC, pontine reticular nucleus, caudal part; R, rostral; Rt, right; sp5, spinal trigeminal tract; T, thoracic segment; V, ventral. (From Luo et al. 2017)

cord and medulla which terminate in the ventral horn and commissural gray matter of the spinal cord and in several areas in the reticular formation in the medulla and pons (medullary reticular nucleus, gigantocellular reticular nucleus, lateral reticular nucleus, nucleus X, inferior vestibular nucleus, magnocellular and parvocellular parts of the medial vestibular nucleus, intermediate reticular nucleus, pontine reticular nucleus) with dense terminal arbor. On the contrary, CMVH axons have relatively small numbers of mossy fiber terminals (n ¼ 27.7
14.0 in 7 CMVH

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axons) in the cerebellar cortex, which were distributed in bilateral lobules I–V. Because of their axonal termination pattern, CMVH axons are postulated to serve primarily as the propriospinal and spinoreticular projection and secondarily as the spinocerebellar projection. This non-precerebellar type of mossy fiber projection has also been demonstrated in the primary afferent axons of the vestibular nerve, which originate from the semicircular canal or the otolith organ and terminate primarily in the vestibular nuclei and additionally, in the cerebellum as mossy fibers (Sato et al. 1989). The weak cerebellar projection of these axons suggests that these terminals were created to provide an increase in axonal arbor into the cerebellum as it developed in the dorsal pons in phylogenetically old vertebrates.

General Features of Axonal Projection Patterns of Single CF and MF Neurons One of the common features of the branching patterns of single MF axons is that multiple longitudinal zones innervated by single MF axons are arranged mediolaterally in one to a few lobules of the Cx. In general, stem axons of MFs give rise to several primary collaterals successively to the Cx while running medially toward the midline in the deep white matter rostral and dorsal to the CN (Fig. 12a). These primary collaterals arise perpendicularly from the stem axons and ramify widely mainly in the parasagittal plane of the folium, so that each MF collateral terminates in a relatively narrow longitudinal zone covering one to a few lobules. It is generally assumed that transverse, lobular subdivisions of the Cx are mainly based on the distribution of the MF input, whereas longitudinal divisions represent the output systems of the Cx in which both the PC zones and their target CNs are innervated by the common CF axons of adjacent neurons in a subnucleus of the IO (Fig. 12b). However, the main discontinuities of terminals of single MF axons are mediolateral rather than lobular and concern the clustering of MF terminals in sagittal strips. This clustering of terminals of a single MF axon into sagittal strips may be a common feature of MF projections in general. These branching patterns of single MF axons may account for the “patchy mosaic” or “fractured somatotopy” of granule cell cutaneous receptive fields in which skin surfaces are represented discontinuously in adjacent granule cells (multiple representations of the same receptive fields) (Welker 1987). Even though the distribution of cutaneous receptive fields looks patchy, the basic organization of the projection of single MF axons in the Cx should be regarded as multiple sagittal strips along longitudinal compartments of aldolase C expression and OC projection. The relationship between MF multiple zones and aldolase C-defined longitudinal zones was examined in several MF systems. MF projection zones of the LRN were aldolase C-negative in the paramedian lobule (Ruigrok and Cella 1995). Pontocerebellar MF terminals are located in aldolase C-positive bands, whereas most MF terminals originating from the GN and CuN are located in aldolase C-negative bands. Thus, the functional significance of cerebellar compartmentation defined from the viewpoint of aldolase C expression seems to be well correlated with

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Fig. 12 Schematic summary diagrams showing characteristic features of the axonal projection patterns of a single MF neuron (a) and a single CF neuron (b) in the Cx and CN and the relationship between MF and CF longitudinal zones innervated by single MF and CF neurons, respectively (c). (a) A single MF neuron terminates in multiple small longitudinal strip-like zones that are arranged successively in a mediolateral direction, often bilaterally. Nuclear collateral may or may not exist in different MF systems. Individual small longitudinal zones may correspond to “microcomplexes.” MF Nucl, nucleus from which a MF arises. (b) A single CF terminates in a longitudinal zone across one or more lobules, even the entire rostrocaudal length of the cerebellum. PCs within the zone project to the corresponding target nucleus that the same CF neuron innervates, and both the PCs and the target nucleus have the same aldolase C expression pattern (either aldolase C-positive or C-negative). (c) The relationship between longitudinal band-like zones of MF terminals of a single neuron and longitudinal bands of the OC projection and PCs within the aldolase C-negative bands

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the zones defined from the viewpoint of olivocerebellar, corticonuclear, and MF projections. However, there are some exceptions to this relationship. In lobules VIII and IX, spinocerebellar and trigeminocerebellar MFs terminate in patches, which are topographically related to the zebrin-negative zones, but the borders of some of the efferent modules or CF zones are located in the middle of a zebrin-positive or zebrinnegative zone, and some modules include both zebrin-positive and zebrin-negative PCs (Gravel and Hawkws 1990). Some MF axons of the ECuN send axon collaterals to aldolase C-negative and aldolase C-positive bands (Quy et al. 2011). Therefore, the relationship between terminal zones of single MF axons and bands defined by aldolase C expression will require further investigation for each MF system. One of the important questions for understanding cerebellar function based on morphology is how multiple longitudinal zones of terminals of an MF neuron are functionally related to the longitudinal zones identified with OC and corticonuclear projections and the aldolase C expression. Concerning the nuclear projection, it is evident that the cortical and nuclear projections of a single MF axon does not exactly follow the so-called corticonuclear topographical relationship, since the cortical projection of a single MF neuron is generally more widely spread in the transverse direction than its nuclear projection, and the MF nuclear projection does not exist in all MF systems. Therefore, this situation does not exactly fit the classical microcomplex scheme of Ito (1984), in which collaterals of MF axons and PCs that receive input from the same MF axons converge onto common target nuclear output neurons. However, the concept of the microcomplex as a functional unit is still applicable by classifying microcomplexes into microcomplexes with and without nuclear MF collateral input. In this basic structure of the microcomplexes, a single MF neuron may innervate multiple microcomplexes in a single longitudinal compartment of the OC and olivonuclear projection and multiple microcomplexes which are arranged in the transverse plane and belong to separate longitudinal compartments with the same aldolase C expression (Fig. 12c). Cerebellar granular cells have three to five dendrites, each of which receives one excitatory MF synapse (Palay and Chan-Palay 1974). Parallel fibers are 4–7 mm long end to end (Brand et al. 1976; Pichitpornchai et al. 1994). Therefore, the transverse arrangement of the MFs is further enhanced by the transverse orientation of the parallel fibers that link the MF input via granule cells with PCs, suggesting that the MF granule cell-parallel fiber system may distribute information to many PCs along a folial axis. However, granule cells within a microzone are mainly reached by MFs with the same receptive fields that have little convergence from MFs with different types of input, and their activation patterns primarily reflect the synchronized activity in presynaptic MFs driven by similar input (Jorntell and Ekerot 2006). MFs of the cuneocerebellar tract with specific receptive fields are distributed approximately along the longitudinal microzonal organization determined by CFs with specific cutaneous receptive fields, and the cutaneous parallel fiber receptive fields in PCs and interneurons are similar to those of MFs (Garwicz et al. 1998).

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Ekerot and Larson (1980) demonstrated a close correlation between the sagittal projection zones in the hemisphere of the anterior lobe activated by the MF of the cuneocerebellar path and the CF of the dorsal funiculus spino-olivocerebellar paths. This finding clearly provides electrophysiological evidence correlating the MF sagittal strips with the CF longitudinal band in a single longitudinal compartment defined by aldolase C expression. Since aldolase C-positive and C-negative bands alternate mediolaterally within lobules, the question remains as to how parallel fibers of granule cells innervated by single MF axons influence PCs in these two longitudinal bands. Whether a single MF axon innervates only adjacent or separate lobules depends on the MF axon and the MF system to which it belongs. Some cutaneous tactile MF projections are highly localized, while the LRN projection that conveys flexor reflex afferent inputs is rather widespread in a rostrocaudal direction. These physiological findings are consistent with the projection patterns of single MF axons in these MF systems. Single MF axons of the LRN tend to innervate adjacent or separate lobules, whereas those of the DCN tend to innervate only one lobule. This difference in the rostrocaudal extent of the sagittal bands of a single MF axon is probably related to the functional aspect of the single MF axon that reflects the somatotopy and the degree of independence or coordination of movements of limbs and axial muscles. The same may hold true for single CFs, since cortical segments that are separate in a rostrocaudal direction but within a single longitudinal band are often innervated by axon collaterals of a single IO neuron (Fig. 2) (Ekerot and Larson 1982). To understand the functional interaction between widely distributed PCs innervated by a group of adjacent single MF neurons and those innervated by single OC axons, more detailed information is needed as to how terminals of single PCs in separate cortical longitudinal zones are organized in the CN and how the two afferent inputs are integrated as a final output at the PCs. Furthermore, for understanding the basic functional mechanism of MF systems in general, it will be necessary to specify the similarity and the difference of axonal projection patterns of single MFs in other MF systems such as the spinocerebellar and vestibular systems.

Functional considerations: Conclusions From the studies on single axonal morphologies, it is clear that some MF systems emit axon collaterals to the CN, but others do not, or only a small portion of neurons in an MF system emit nuclear collaterals. In contrast, almost all of OC axons emit nuclear collaterals to the corresponding target CN. Eccles et al. (1974) showed that early excitation in the FN was not evoked from the dorsal spinocerebellar tract by hind limb inputs, but was evoked by spinocerebellar inputs via the LRN and the IO. The present anatomical findings are consistent with these electrophysiological findings. Therefore, it is important to identify the presence or absence of excitatory input to the CN by a nuclear collateral in each MF system, although it is still tacitly assumed that all afferent neurons in the MF systems have nuclear axon collaterals. During slow tracking movements of wrist flexion and extension, both PCs (Mano

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and Yamamoto 1980) and nuclear neurons in the DN and IP (Schieber and Thach 1985) were found to show a bidirectional increase of spike activity rather than a reciprocal pattern. In rapid alternating movements of a forelimb, CN cells showed reciprocal changes of activity above and below a resting mean frequency (Thach 1968; Wetts et al. 1985), whereas PCs had a bidirectional discharge pattern (predominantly bidirectional increase) (Mano and Yamamoto 1980). As exemplified in these cases, CN cells either increase or decrease their activity at the onset of and during movement. The neural mechanism of this increase or decrease of discharge frequency in cerebellar nuclear cells is an unsolved important question of cerebellar physiology (Shinoda et al. 1987, 1992, 1993, 1997). There are two possible pathways to produce this increase in spike firing in nuclear neurons (Fig. 13). If there is an excitatory input via axon collaterals of MF neurons to the CN (Fig. 13a), this excitatory input may cause an initial increase of nuclear cell discharge. In this case, PCs may either increase or decrease their firing, although most PCs are known to increase their activity at the onset of movement (Thach 1968; Mano and Yamamoto 1980). Only a few intracellular recording studies were performed in in vivo preparations to examine synaptic inputs to nuclear neurons from the precerebellar nuclei (Ito et al. 1970; Kitai et al. 1977; Shinoda et al. 1987). EPSPs were evoked by stimulation of the IO, the PN, and the NRTP (Ito et al. 1970; Shinoda et al. 1987). Accordingly, excitatory inputs of extracerebellar origin may exist to increase nuclear cell discharge at the onset of or during movement. However, contrary to the common assumption that precerebellar neurons that project to the Cx emit axon collaterals to the corresponding CN, some MF neurons have no axon collateral to the CN (Fig. 13b). In this case, changes in nuclear cell firing rates will be caused solely by changes in PC firing rates; an increase in nuclear cell discharge will be caused by disinhibition through PCs that decrease their firing, since PCs are inhibitory (Fig. 13Ba). Physiologists have searched for PCs that show an increase of activity in response to sensory stimuli or movements, but they have paid less attention to the possible existence of PCs that show a decrease in activity. PCs have high spontaneous or background activity (60–80/s) (Thach 1968; Mano and Yamamoto 1980), and CN neurons have also spontaneous activity (30–40/s). Spontaneous simple spikes occur in isolated PCs in the absence of any parallel fiber input (Llinás and Sugimori 1980; Raman and Bean 1999). The relatively high frequencies of simple spikes may establish optimal carrier frequencies necessary for effective modulation of PCs and enable bidirectional responses in PCs and their target CN and VN, namely, an increase in firing due to either excitation or disinhibition and a decrease in firing due to either inhibition or disfacilitation. Interneurons in the molecular layer, basket and stellate cells, exert inhibitory control on PCs (Andersen et al. 1964; Eccles et al. 1967; Midtgaard 1992). Golgi cells in the granule cell layer indirectly influence simple spike discharge by inhibiting the discharge of granule cells (Eccles et al. 1967). Therefore, even excitatory inputs of MFs may suppress activity of PCs via these inhibitory interneurons. On the other hand, a decrease of activity in nuclear neurons was observed in alternating arm movements (Thach 1968; Wetts et al. 1985) and also in horizontal saccadic eye movements (Ohtsuka and Noda 1991) at the onset of and during movement. This decrease in activity in nuclear cells may be

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Fig. 13 Two possible operational modes of cerebellar corticonuclear interaction in the CN in relation to MF input from the cerebral cortex. (a) A pathway with an MF collateral terminating on the CN. Nuclear output neurons increase or decrease their activity at the onset of and during movement, depending on the strength of PC inhibition. (b) A pathway without an axon collateral projecting to the CN. Nuclear output neurons increase their activity (Ba) or decrease their activity (Bb) at the onset of and during movement. Mx motor cortex, Ass Cx association cortex, IN inhibitory interneuron (basket and stellate cell), Gr cell granular cell, PT pyramidal tract. (Modified from Shinoda et al. 1993)

caused by an increase in activity of PCs, even though nuclear axon collaterals of MFs are either present (Fig. 13a) or absent (Fig. 13Bb). It has been suggested that the background discharge of CN neurons is due to continuous excitatory input or the membrane properties of CN neurons (Thach 1968). A study in a slice preparation

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supports the latter mechanism because the electroresponsive membrane properties of CN neurons contribute to the background discharge (Jahnsen 1986). Furthermore, Llinás and Mühlethaler (1988) demonstrated the existence of a powerful low-threshold Ca2+-dependent spike which triggered a burst of fast Na+-dependent spikes in CN neurons. Therefore, changes of spike activity in CN neurons can be easily caused by slight modulation of the membrane potential by excitatory or inhibitory inputs superimposed on the underlying spontaneous activity. It is still unknown in the case of voluntary limb and eye movements whether nuclear output is generated only by PC input or by the interaction of MF or CF input and PC input. From the perspective of the function of target cells outside the cerebellum, information is not yet available as to which is more important – an increase or a decrease in firing rates of CN neurons. Further analysis is required of the axonal projection patterns of single MF neurons with different origins, such as the NRTP and spinocerebellar neurons, to understand the neural mechanisms of interaction of MF inputs in the Cx and CN for proper generation of cerebellar outputs to targets outside the cerebellum for control of movement and other functions.

Cross-References ▶ Cerebellar Motor Disorders ▶ Cerebellar Nuclei and the Inferior Olivary Nuclei: Organization and Connections ▶ Cerebellum and Internal Models ▶ Cerebro-cerebellar Connections ▶ Inferior Olive: All Ins and Outs ▶ Neurons of the Deep Cerebellar Nuclei ▶ Zones and Stripes: Development of Cerebellar Topography Acknowledgments This research was supported by Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (KAKENHI 16 K070025).

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Visual Circuits from Cerebral Cortex to Cerebellum; The Link Through Pons

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Contents Which Cells in the Cerebral Cortex Have an Axon that Projects to the Pons? . . . . . . . . . . . . . . . . Which Areas of Cortex Project to the Pons? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is the Pathway of the Cortical Projection to the Pons? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Where Do Corticopontine and Collicular Fibers Terminate in the Pons? . . . . . . . . . . . . . . . . . . . . . . Demagnification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fibers from the Cerebral Cortex and Colliculus Give off Collaterals . . . . . . . . . . . . . . . . . . . . . . . . . . What Are the Receptive Field Properties of Pontine Visual Cells? . . . . . . . . . . . . . . . . . . . . . . . . . . . . Where and how Do the Axons of Pontine Cells Terminate on the Cerebellum? . . . . . . . . . . . . . . Some Further Speculations on the Role of the Cortico-Ponto-Cerebellar System . . . . . . . . . . . . . Behavioral Evidence of the Function of the Corticopontine Link . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Collateral Fibers and the Corollary Discharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Receptive Fields and Visual Guidance; the Appearance of the Ground to a Walking Cat . . . . Cerebellum and Kinesie Paradoxale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Localization and Current Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

This chapter reviews some anatomical, behavioral, and physiological studies that bear on the role of the sensory input to the cerebellum via the pons in general and the visual input in particular. The core of the argument is that in monkeys, the visual input comes from those extrastriate visual areas that are involved in motion detection and visual control of movement. Studies of other inputs and other species are cited when they are relevant to the more general issue of the nature of sensory input to the cerebellum.

M. Glickstein (*) Cell and Developmental Biology, University College London, London, UK e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_21

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Keywords

Receptive field · Superior colliculus · Cerebellar cortex · Visual input · Pontine nucleus

The pons occupies a prominent place at the base of the brain, extending from the caudal end of the midbrain to the rostral border of the medulla. Costanzo Varolio (aka Varolius) (1591) dissected the human brain from its ventral surface, thus giving him a clear view of the origin of the cranial nerves and the shape of the lower brainstem. It was Varolius who gave the pons its name, based on its resemblance to a bridge over a canal. Importantly subdivided into a dorsal and a ventral division, it is the ventral division that contains the pontine nuclei. One of the largest circuits through the human brain originates in the cerebral cortex and projects to the cerebellum by way of the pontine nuclei. The input to the pons arises from both sensory and motor areas of the cerebral cortex. Pontine inputs also originate from the superior colliculus and other brainstem structures, but it is the cortical input to the pons that is by far the largest. Anatomical, recording, and lesion-based studies help to understand the functions of these pathways. In this chapter, I will emphasize the visual input in relation to some of the more general principles about the nature of the cortico-ponto-cerebellar circuit. In addition to a purely visual input, visual information is also a constituent element of visuomotor signals. My discussion is based mostly on vision and the work of my own lab. A much broader view is well summarized in a recent review by Thier and Möck (2006).

Which Cells in the Cerebral Cortex Have an Axon that Projects to the Pons? There are two related questions about the nature of the link between cerebral cortex and the pons. Which cells are the origin of the corticopontine fibers? Which areas of cortex provide an input to the pons? The first question is easily answered. The input to the pontine nuclei comes only from Lamina V pyramidal cells. Injection of horseradish peroxidase (HRP) into the pontine nuclei allows identification of the cells of origin of the axons that project to the pons. Often in such preparations, there is a single line within lamina V composed of corticopontine cells. In all cases that have been studied, it is only lamina V pyramidal cells that are labeled. Figure 1 shows a cross section through the frontal cortex of a tree shrew in which HRP had been injected into the pontine nuclei several days prior to the brain being prepared to identify labeled cortical cells. In some cases, cortical Lamina V may be divisible into a superficial layer Va and a deeper Vb. In the rat, all corticopontine fibers originate in Vb. Cells in lamina Va are labeled after an injection confined to the basal ganglia (Mercier et al. 1990).

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Fig. 1 Cross section through the frontal lobe of a tree shrew (Tupaia glis) showing the location of retrogradely labeled cells after HRP injection in the pons. The gray line in lamina V of cortex is a continuous band of labeled pyramidal cells

Which Areas of Cortex Project to the Pons? Although all corticopontine cells are located in lamina V, the distribution and extent of such cells across the cortex varies greatly among mammals. In rats, all of the cerebral cortex projects to the pons (Legg et al. 1989). In monkeys, some cortical areas are without a pontine projection, and for some areas the projection is sparse (Glickstein et al. 1985). The great majority of corticopontine connections arise from a contiguous area of cortex that extends from the superior temporal sulcus caudally to the arcuate sulcus rostrally and from the corpus callosum medially to the superior temporal sulcus laterally (Fig. 2). Differences in the source of the projection from cortical visual areas help to interpret the functions of the cortico-ponto-cerebellar pathway. The extrastriate visual areas can be subdivided into two major groups: a dorsal-medial group that extends into in the parietal lobe, and a ventral-lateral group that extends into in the temporal lobe (Ungerleider and Mishkin 1982; Glickstein and May 1982). The dorsal-medial visual areas project heavily to the pons, the lateral-ventral areas do not. Differences between the two groups in the extent of their corticopontine projections reflect their differences in function. Lesions of the dorsal areas in monkeys produce a profound deficit in visual guidance of the wrist and fingers without impairing the animal’s ability to learn a visual discrimination task. Ventral lesions are without effect on visual guidance of movement, but severely impair visual discrimination learning (Glickstein et al. 1997).

What Is the Pathway of the Cortical Projection to the Pons? Corticopontine fibers descend in the internal capsule and collect ventrally at the base of the midbrain in the cerebral peduncles. In the human and monkey, corticopontine fibers constitute the great majority of the fibers in the cerebral peduncles. The cerebral peduncles also contain the axons of the pyramidal tract. One way to

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appreciate the relative importance of the cortico-cerebellar link is to compare the ratio of cross-sectional area of the peduncle to that of the pyramidal tract. Figure 3 illustrates the point. The section on the left is through the midbrain showing the fibers in the cerebral peduncle of a fiber-stained human brain. The section on the right is through the pyramidal tract in the same brain.

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Fig. 3 Fiber-stained human brain. Compare the volume of fibers in the cerebral peduncles with that of the pyramidal tract

Interruption of the pathway from cortex to the pons at the level of the caudal limb of the internal capsule in a stroke patient produced a profound impairment in skilled visuomotor performance by the contralateral hand, and a moderate impairment on the ipsilateral hand (Classen et al. 1995). The interpretation of the loss in this case was that the fiber lesion had interrupted an input to the pons from extrastriate cortical visual areas.

Where Do Corticopontine and Collicular Fibers Terminate in the Pons? In monkeys, the major targets of extrastriate visual areas are the dorsolateral and dorsal regions of the pontine nuclei (Glickstein et al. 1980). The location of functional borders within the pontine nuclei is relatively arbitrary. There are hints that the true organization is probably based on a central-peripheral axis within the pontine nuclei. In an elegant study of pontine termination from the cerebral cortex of rats, Leergaard et al. (2000) showed that the pattern of termination is based on a circular arrangement around the pyramidal tracts as they course through the pontine nuclei. The same principle may be present for terminations of fibers originating in cortical visual areas. There are other, noncortical sources of visual input to the pontine nuclei. In all animals studied, there is an input from both the deep “motor” laminae of the superior colliculus as well as from lamina III, the stratum opticum (Mower et al. 1979; Schwarz et al. 2005). In monkeys, the cortical and collicular projections to the pons terminate in adjacent, partially overlapping regions of the dorsolateral and dorsal regions of the pontine nuclei. In cats, the projections are to different areas. Fibers that project to the pons from the superior colliculus terminates in the dorsolateral pons, whereas fibers from the cerebral cortex terminate in ventromedial pons.

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The fact that the two inputs do not overlap allows for a comparison of their cerebellar targets and offers some insights into the difference in the functions of the two pathways. Cortically activated visual cells have as their major target the dorsal paraflocculus of the cerebellar hemispheres and adjacent uvula. The axons of cells that receive an input from the superior colliculus terminate principally in lobule VII, the oculomotor vermis.

Demagnification The receptive field properties of visual cells in the cat pons resemble those of the cortical cells that provide their input (Gibson et al. 1978). Both corticopontine and pontine receptive fields are powerfully influenced by the speed and direction of visual targets. They are relatively insensitive to differences in target shape. In both cases, the major difference between cortical and pontine receptive fields is in their size. Corticopontine cells in cat Area 18 have receptive fields that are up to a degree or two in cross section, while pontine receptive fields may encompass an entire visual hemifield. In the cerebral cortex of both monkeys and cats, the central portion of the visual field is represented in a much greater area than the periphery. The large size of some pontine receptive fields poses a challenge. Consider an object traveling across the cortical representation of the visual field. Because of the great difference in magnification from center to periphery, it would travel slowly across the cortical representation of the central visual field, and then more rapidly in the periphery. If cortex were represented uniformly in its projection to the pons, then optimal target speed would be different in the center and periphery of a large receptive field. The corticopontine pathway corrects by de-magnifying the visual input in cats (Cohen et al. 1981). In monkeys, there is a very small corticopontine projection from the peripheral field representation in Area 17. There is an orderly increase in the number of corticopontine cells as you go from the representation of the center of gaze to the periphery.

Fibers from the Cerebral Cortex and Colliculus Give off Collaterals In his Textura del Systema Nervioso (1899), Cajal illustrates a Golgi-stained section through the pontine nuclei. Each of the fibers gives off a collateral to the pons. Ugolini and Kuypers injected fast blue, a retrograde tracer into the pyramidal tract at the level of the medulla. In addition to the expected retrograde filling of pyramidal tract fibers, she described extensive collaterals of pyramidal tract fibers as they traversed through the pontine nuclei (Ugolini and Kuypers 1986). The same principle of collaterals may be present for corticopontine fibers. Corticopontine visual fibers in the cat give off collaterals to the superior colliculus (Baker et al. 1983). Many cortical visual cells that can be activated antidromically from the pontine nuclei are also activated antidromically by electrical stimulation in

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the superior colliculus. By analyzing the pattern of collision between responses activated from the two sites, it is possible to calculate the point at which the bifurcation occurs. One branch of these axons may play a direct role in motor control, the other branch in the corollary discharge.

What Are the Receptive Field Properties of Pontine Visual Cells? In cats, pontine visual cells appear to be activated solely by the magnocellular visual system. They are strongly influenced by the direction and velocity of moving targets, but relatively unaffected by their shape. These properties resemble closely those of the cortical cells which activate them (Gibson et al. 1978). Similarly, in monkeys, the extrastriate cortical visual areas that project to the pons are dominated by their magnocellular inputs.

Where and how Do the Axons of Pontine Cells Terminate on the Cerebellum? The distribution of pontocerebellar fibers can help to interpret the function of the corticopontine system. Anna Rosina and her colleagues (1980) studied the pattern of termination of pontine cells on the cerebellar cortex. While the majority of the pontocerebellar fibers terminate in the contralateral cerebellum, there is a definite ipsilateral projection. Following Bolk (Glickstein and Voogd 1995), we might speculate that the ipsilateral fibers are particularly involved in the coordination of movements that require cooperation between the two sides of the body, such as rotation of the neck or conjugate movement of the eyes.

Some Further Speculations on the Role of the Cortico-PontoCerebellar System In cats, there are inputs to the pontine nuclei from two distinct cortical visual areas: Area 18 (Visual II) and the lateral suprasylvian area. The pontine targets of the two cortical areas do not overlap extensively. Fibers originating in Area 18 terminate centrally within the pontine nuclei, close to the pyramidal tract fibers as they course through the pons. Fibers from lateral suprasylvian cortex terminate more peripherally within the pontine nuclei. This pattern of input is related to the distribution of axons from these two areas on the cerebellar cortex (Mower et al. 1979; Robinson et al. 1984). The axons of cells that receive an input from Area 18 terminate medially on the vermis-paravermal area of the cerebellar cortex. Pontine cells that relay the input from the lateral suprasylvian area terminate more laterally in the cerebellar hemispheres. Both classes of visual input are probably involved in the visual guidance of movement. The input from Area 18 may be involved in regulating

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whole body movements; the lateral suprasylvian area in independent use of the limbs.

Behavioral Evidence of the Function of the Corticopontine Link The corticopontine pathway is involved in the sensory control of movement. One example of that principle comes from a study of rats jumping. Rats can be readily trained to jump across a gap to reach a bit of food at the end of a runway. In the dark, rats use their whiskers to gauge the distance which must be crossed (Hutson and Masterton 1986). The somatosensory areas of the rat cerebral cortex, including the whisker barrel field sends a powerful input to the pontine nuclei. If this pathway is cut, rats will refuse to jump the gap in the dark, although jumping in the light is unaffected (Jenkinson and Glickstein 2000).

Collateral Fibers and the Corollary Discharge When a movement is executed, there is a corollary discharge which signals that movement. As Helmholtz pointed out, such a system would serve to maintain the perceptual stability of the world around us despite movement of the eyes or head. The pattern of branching by corticopontine fibers may well contribute to that function. Collateral branching of the fibers as they traversed the pons would provide an anatomical basis for the corollary discharge.

Receptive Fields and Visual Guidance; the Appearance of the Ground to a Walking Cat Occasionally a receptive field will seem uniquely appropriate for guiding a specific movement. Some pontine receptive fields are maximally activated by a large, textured target moving downward and outward in the visual field. A target of this sort resembles the appearance of the ground to a walking or running cat. Following David Lee (1980), the cell could be part of a circuit that calculates time to contact with an object in the visual field of a moving cat.

Cerebellum and Kinesie Paradoxale Kinesie paradoxale refers to the fact that patients suffering from Parkinson’s disease are often capable of skilled and coordinated movement. They may catch a ball, walk, or run if aided by an appropriate visual input. The corticopontine system could provide an appropriate visual input allowing for cerebellar control of those movements. The properties of pontine visual cells are similar to the visual inputs that promote such movements. The suggestion is that an intact cerebellar pathway may

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serve to control movement in a patient with nonfunctional basal ganglia (Glickstein and Stein 1991).

Cerebellar Localization and Current Problems One basic problem which is still poorly addressed is that of localization in the cerebellum. Except for lateralization, Luciani (1891) denied any localization in the cerebellar cortex. This chapter has presented some of the evidence for the role of one or another part of the cerebellum in sensory guided movement. There is good evidence, for example, for a the role of Vermis Lobule VII and caudal VI in saccadic adaptation (Barash et al. 1999) and Pavlovian conditioning (Thompson 1983; Yeo et al. 1984) showed that the critical area is hemispheric Lobule VI. The control of these functions is localized in definite and restricted regions of the cerebellum. The challenge is to understand the functions of the great mass of the cerebellar cortex, especially that of the hemispheres. One current view is that they are involved in some forms of cognition. But anatomical evidence leads me to question such a role. The visual input is from motion sensitive areas of the prestriate and adjacent cortex. There is virtually no input to the pons from the lateral-ventral extrastriate visual areas. There is a modest projection from prefrontal cortex, but the areas that project to the pons are mostly those related to eye movements. The situation of the cerebellar hemispheres is reminiscent of that of the corpus callosum in 1936 when Walter Dandy (1936) cut the callosum in a surgical patient without causing any obvious deficits. He wrote “This simple experiment at once disposes of the extravagant claims to function of the corpus callosum.” It didn’t.

References Baker J, Gibson A, Mower G et al (1983) Cat visual corticopontine cells project to the superior colliculus. Brain Res 265:222–232 Barash S, Melikyan A et al (1999) Saccadic dysmetria and adaptation after lesions of the cerebellar cortex. J Neurosci 19:1031–1039 Cajal SR (1899) Textura del Sistema Nervioso. Moya, Madrid Classen J, Kunesch F et al (1995) Subcortical origin of visuo-motor apraxia. Brain 118:1365–1374 Cohen J, Robinson F et al (1981) Cortico-pontine projections of the lateral suprasylvian cortex: De-emphasis of the central visual field. Brain Res 219:239–248 Dandy W (1936) Operative experience in cases of pineal tumor. Arch Surg 33:19–46 Gibson A, Baker J, Mower G, Glickstein M (1978) Corticopontine visual cells in area 18 of the cat. J Neurophysiol 41:484–495 Glickstein M, May J (1982) Visual control of movement: the visual input to the pons and cerebellum. In: Neff WD (ed) Contributions to sensory physiology. Academic, New York Glickstein M, Stein J (1991) Paradoxical movement in parkinson’s disease. Trends Neurosci 11: 480–482 Glickstein M, Voogd J (1995) Lodewijk bolk and the comparative anatomy of the cerebellum. Trends Neurosci 18:206–210 Glickstein M, Cohen JL et al (1980) Corticopontine visual projections in macaque monkeys. J Comp Neurol 190:209–229

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Glickstein M, May J, Mercier B (1985) Corticopontine projection in the macaque: the distribution of labelled cortical cells after large injections of horseradish peroxidase in the pontine nuclei. J Comp Neurol 235:343–359 Glickstein M, May J, Buchbinder S (1997) Visual control of the arm, the wrist, and the fingers; pathways through the brain. Neuropsychologia 36:981–1001 Hutson K, Masterton R (1986) The sensory contribution of a single vibrissa’s cortical barrel. Neurophysiology 56:1196–1223 Jenkinson E, Glickstein M (2000) Whiskers, barrels, and cortical efferent pathways in gap-crossing by rats. J Neurophysiol 84:1781–1789 Lee D (1980) The optic flow-field: the foundation of vision. Philos Trans R Soc 290:169–179 Leergaard TB et al (2000) Rat somatosensory cerebropontocerebellar pathways: spatial relationships of the somatotopic map of the primary somatosensory cortex are preserved in a threedimensional clustered pontine map. J Comp Neurol 422:246–266 Legg C, Mercier B, Glickstein M (1989) Corticopontine projection in the rat: the distribution of labelled cortical cells after large injections of horseradish peroxidase in the pontine nuclei. J Comp Neurol 286:427–441 Luciani L (1891) Il Cerveletto. Le Monnier, Florence Mercier B, Legg C, Glickstein M (1990) Basal ganglia and cerebellum receive different somatosensory information in the rat. Proc Natl Acad Sci U S A 87:4388–4392 Mower G, Gibson A, Glickstein M (1979) Tectopontine pathway in the cat: laminar distribution of cells of origin and visual properties of target cells in dorsolateral pontine nucleus. J Neurophysiol 42:1–15 Robinson F, Cohen J et al (1984) Cerebellar targets of visual pontine cells in the cat. J Comp Neurol 223:471–482 Rosina A, Provini L et al (1980) Ponto-neocerebellar axonal branching as revealed by double fluorescent retrograde labelling technique. Brain Res 195:461–466 Schwarz C, Horowski A, Möck M, Thier P (2005) Organization of tectopontine terminals within the pontine nuclei of the rat and their spatial relationship to terminals from the visual and somatosensory cortex. J Comp Neurol 484:283–298 Thier P, Möck M (2006) The oculomotor role of the pontine nuclei and the nucleus reticularis tegmenti pontis. Prog Brain Res 151:293–320 Thompson R (1983) Neuronal substrates of simple associative learning; classical conditioning. Trends Neurosci 6:270–275 Ugolini G, Kuypers HG (1986) Collaterals of corticospinal and pyramidal fibres to the pontine grey demonstrated by a new application of the fluorescent fibre labelling technique. Brain Res 365: 211–227 Ungerleider L, Mishkin M (1982) Two cortical visual systems. In: Ingle DJ et al (eds) Analysis of visual behavior. MIT Press, Cambridge Varolio C (1591) De nervis opticis. Wechel and Fischer, Frankfurt Yeo C, Hardiman M, Glickstein M (1984) Discrete lesions of the cerebellar cortex abolish the classically conditioned nictitating membrane response of the rabbit. Behav Brain Res 60:99–113

Cerebellar Connections with Limbic Circuits: Anatomy and Functional Implications

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Jeremy D. Schmahmann, Adrian L. Oblak, and Gene J. Blatt

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Defining the Limbic System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Connections with the Limbic System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar-Hypothalamic Circuits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Connections with Paralimbic and Neocortical Association Areas . . . . . . . . . . . . . . . . . Observations from Neuroimaging Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional Topography in the Cerebellum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellum and Pain Modulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Autonomic Influences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Indirect Limbic Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cerebellum Is Implicated in Autism Spectrum Disorders (ASD) . . . . . . . . . . . . . . . . . . . . . . . . . Implications of a Cerebellar Role in Emotional Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Therapeutic Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The affective component of the cerebellar cognitive affective syndrome provides empirical evidence for cerebellar participation in limbic-related functions including emotion and affect. The underlying connectivity of the cerebellar cortex and J. D. Schmahmann (*) Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA e-mail: [email protected] A. L. Oblak Department of Radiology and Imaging Sciences, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA e-mail: [email protected] G. J. Blatt Program in Neuroscience, Hussman Institute for Autism, Baltimore, MD, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_22

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nuclei with limbic-related brain areas and with associative and paralimbic cortices suggests widespread cerebellar influence on behaviors including the experience and expression of emotion, sadness and grief, integrative hypothalamic visceral/ sensory functions, pain perception, modulation, and intensity due to noxious stimuli, as well as other non-motor behaviors. The key anatomical relationships are the fastigial nucleus projections to the ventral tegmental area, cerebellar interconnections with the septum, hippocampus and amygdala, direct cerebellar connections with hypothalamic circuits that integrate somatic-, visceral-, and limbic-related activity, and indirect connections with the nucleus accumbens, a mesolimbic dopaminergic structure that predicts activity in a reward paradigm in limbic-related structures. Additionally, the cerebellum is interconnected with cingulate cortices that play a role in motivation and emotional drive, and with associative and paralimbic regions of prefrontal, posterior parietal, superior temporal polymodal, and parahippocampal regions heavily implicated in high order processing important for the integration of cognition and emotion. These connections between cerebral cortical and subcortical areas of the limbic system with the cerebellum (vermis and fastigial nucleus in particular) are the likely anatomical underpinning of the demonstrated cerebellar influence on limbicrelated behaviors in the clinical setting and in earlier behavioral and physiological studies. These cerebellar connections with cerebral limbic areas are also implicated in neurodevelopmental disorders such as autism which demonstrate neuropathology and aberrant neurochemistry in the cerebellar cortex and nuclei. Defining the vermis and fastigial nuclei as the core cerebellar limbic regions has relevance for studies of cerebrocerebellar interconnections and functional coupling, and for therapeutic strategies that attempt to enhance cerebellar modulation of limbic-related structures to treat neuropsychiatric disorders. Keywords

Limbic system · Paralimbic · Association areas · Emotion · Affect · Cognition · Pain · Visceral functions · Vermis · Fastigial nucleus · Pontine nuclei · Hypothalamus · Autonomic · Cingulate cortex · Cerebellar lobules · Autism spectrum disorders · Depression · Schizophrenia · Ventral tegmental area · Cerebellar cognitive affective syndrome

Introduction Converging lines of evidence reveal that the cerebellum is incorporated into the distributed neural circuits subserving cognition and emotion as well as motor control (Schmahmann 1991, 1997, 2010; Schmahmann et al. 2019). Unlike the cerebral cortex which can be parcellated on the basis of its architectonic heterogeneity (Brodmann 1909), the main components of the cerebellar cortex are essentially uniform throughout (Eccles et al. 1967; Ito 1984) with the exception of selected neuronal elements such as unipolar brush cells in the vestibulocerebellum (Mugnaini

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and Floris 1994), molecular identities of cerebellar cortical neurons (Schilling et al. 2008), and variations in physiology of the parasagittal zebrin positive and negative bands. In contrast to the repeating and paracrystalline structure of the cerebellar cortex, the anatomical connections of the cerebellum with extracerebellar areas are remarkably heterogeneous. Defining these connections of the cerebellum with brain areas involved in higher function is integral to the evolving understanding of cerebellar function. Advances in clinical structure-function correlation, neurophysiology, neuroanatomy, and functional imaging have made it clear that there are cerebellar regions devoted to topographically organized sensorimotor, vestibular, and autonomic functions, as well as to cognitive processing and emotional modulation. This chapter reviews evidence demonstrating links between the cerebellum and cerebral areas concerned with the experience and expression of emotion, affect, and personality. Intellect and emotion are tightly interrelated (LeDoux 1996; Barbas 2007) and so the areas of cerebellum involved in neuropsychiatric phenomena likely extend beyond the cerebellar areas linked only with regions traditionally regarded as limbic.

Defining the Limbic System Paul Broca (1824–1880) drew attention to the cingulate gyrus, hippocampus, and parahippocampal gyrus at the medial surface of the mammalian brain (Broca 1878), introducing the term limbic lobe (derived from the Latin word limbus or edge), because it formed the hem or edge of the medial part of the cerebral hemisphere. These structures, along with the olfactory bulb, were initially considered to be important for the sense of smell. James Papez (1883–1958) introduced the notion that a number of interconnected brain areas subserve the experience and expression of emotions. He proposed “that the hypothalamus, the anterior thalamic nuclei, the gyrus cinguli, the hippocampus, and their interconnections constitute a harmonious mechanism which may elaborate the functions of central emotion, as well as participate in emotional expression” (Papez 1937). Regions now considered integral parts of what Paul MacLean (1954) called the limbic system include the amygdala, cingulate cortex, fornix, hippocampus, hypothalamus, olfactory cortex, thalamus, brainstem, ventral tegmental area, and parts of the prefrontal cortex (MacLean 1949, 1954, 1969; Nauta 1958, 1986; Heimer et al. 2008). Subcortical areas such as the ventral striatum and the extended amygdala were not initially conceptualized as part of the limbic circuit but are now recognized as brain substrates essential for the experience and expression of emotion (Schreiner and Kling 1953; Bucy and Kluver 1955; Nauta and Domesick 1976). Similarly, converging evidence indicates that regions within the cerebellum are recruited into the distributed neural circuits subserving emotion. Competing theories of the neurobiology of emotion have existed for some time, including the James-Lange (Lange and James 1922) view that feelings arise from physiological responses to the environment and the Cannon-Bard theory (Cannon 1927) which holds that physiological responses and feeling states arise simultaneously. Whichever theory is correct, interactions between mood state and physical

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experience are dependent upon the anatomical interactions between regions concerned with feelings and those concerned with physiologically defined phenomena, and on the way these brain areas regulate, or react to, the internal and external environment. The experience of feeling is also fundamentally influenced by one’s conscious awareness and interpretation of one’s own mood (Damasio 1999). Emotion and cognition are thus interdependent, as reflected in the extensive interconnections between the limbic system and cortical association areas (see Pandya and Yeterian 1985; Barbas et al. 2003). It is therefore pertinent to the present discussion of the anatomic systems underlying cerebellar connections with the limbic system to briefly consider the cerebellar incorporation into the distributed neural circuits that support cognitive operations.

Cerebellar Connections with the Limbic System Anatomical tract tracing and physiological studies demonstrate that the cerebellum is interconnected with the limbic system. The fornix, mammillothalamic tract, median forebrain bundle, and cingulum bundle are closely related to classic limbic system structures including the anterior thalamic nucleus, hypothalamus, cingulate cortex, and hippocampus. The mammillary bodies, critical subcortical nodes of the memory circuit, are closely linked with the anterior thalamic nuclei through the mammillothalamic tract and are connected with the cerebellum through projections to the nuclei of the basilar pons (Haines and Dietrichs 1984; Aas and Brodal 1988). The limbic regions are connected with the ventral tegmental area (VTA), periaqueductal gray, and interpeduncular nucleus. In the cat, the fastigial nucleus projects to the VTA, interpeduncular nucleus, periaqueductal gray, and locus coeruleus; the interpositus and dentate nuclei project to the interpeduncular nucleus and VTA (Snider and Maiti 1975). Optogenetic studies in the mouse confirm the direct cerebellar projections to the VTA (Carta et al. 2019). They show that the cerebellar-VTA pathway is necessary for the expression of social behavior, likely via VTA connections with the nucleus accumbens, suggesting that the cerebellum dynamically encodes social signals, relaying them to the VTA for the specific purpose of modulating behavior. The cingulate cortex is important for the introspective feeling of emotions and supports other behaviors including initiation, motivation, and goal-directed behaviors (Devinsky et al. 1995). The anterior cingulate cortex modulates autonomic activity and internal emotional responses as well as a cognitive domain that is involved in skeletomotor activity and responds to noxious stimuli. Vilensky and Van Hoesen (1981) demonstrated in the monkey that the cingulate gyrus projects to the cerebellum through the nuclei of the basis pontis: the rostral cingulate cortex projects to the medial pontine nuclei and the caudal cingulate zone to more lateral pontine regions. Brodal et al. (1991) studied the organization of the connections of the cingulate cortex and cerebellum using the retrograde tracer, wheat germ agglutininhorseradish peroxidase (WGA-HRP). Following injections of tracer into the nuclei

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of the basis pontis, retrogradely labeled cells were found in layer V throughout the cingulate cortex. Topographic organization within the pons of fibers originating in different parts of the cingulate gyrus was also demonstrated. Cingulopontine fibers were distributed in a patchy mosaic within a narrow band along the ventromedial aspect of the pontine nuclei. With the combined use of lesions in the cingulate gyrus and injections of WGA-HRP in the ventral paraflocculus, there was considerable overlap between terminal fibers originating in the cingulate gyrus, and cells retrogradely labeled from the ventral paraflocculus. Physiological mapping studies show that cerebellar stimulation produces changes in limbic structures. In cats and rats, stimulation of the rostral vermis, fastigial nucleus, and intervening midline folia of the cerebellum result in facilitation of units in the septal region, inhibition of units in the hippocampus, and a mixed pattern of physiological responses in the amygdala (Babb et al. 1974). However, stimulating the lateral hemispheres of the cerebellum or the dentate nucleus produces no change in activity in these areas, and stimulation of the posterior vermis leads to inconsistent facilitation of the septal nuclei with no change in the hippocampus. These findings supported the notion of Heath (1977) and Heath et al. (1978) and Schmahmann (1991, 2000, 2010) that the fastigial nucleus is an integral part of the network for emotion, and they have been bolstered in recent years by studies using contemporary techniques. Using two-photon calcium imaging in behaving mice, Wagner et al. (2017) reported that granule cells convey information about the expectation of reward. In mice initiating voluntary forelimb movements for a delayed sugar-water reward, some granule cells responded preferentially to reward or reward omission, whereas others selectively encoded reward anticipation. The existence of predictive, non-sensorimotor encoding in granule cells enriches the contextual information available to postsynaptic Purkinje cells, and provides physiological-behavioral evidence in the mouse model that the cerebellum is engaged in the processing of emotionally salient information. Single-cell gene expression profiling and anatomical circuit analyses of vermis output neurons in the medial cerebellar nucleus of the mouse (equivalent to the fastigial nucleus) by Fujita et al. (2020) identified five different classes of glutamatergic projection neurons. Each of these is differentially linked with a specific set of inferior olivary neurons, Purkinje cells, and functionally related downstream targets in motor, cognitive, and affective forebrain circuits. This includes posturomotor, oromotor, and positional-autonomic circuits, as well as orienting circuits relevant to behaviors such as awareness of threat, salience, and behavioral switching, and arousal circuits engaged in vigilance, arousal, motivation, cortical arousal, and working memory.

Cerebellar-Hypothalamic Circuits Bidirectional pathways link all four intracerebellar nuclei with the hypothalamus that is engaged in somatic-visceral integration (see Zhu et al. 2006 for review). These connections may play a role in feeding, cardiovascular, osmotic, respiratory,

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micturition, immune, emotion, and other nonsomatic regulations. It has been proposed that these cerebellar-hypothalamic pathways are essential modulators and coordinators that integrate visceral and behavioral responses (Zhu et al. 2006). This role may explain, in part, why many studies that investigate visceral functions also implicate the cerebellum. These direct cerebellar-hypothalamic circuits have been confirmed both anatomically (see Dietrichs et al. 1994; Haines et al. 1997 for reviews) and physiologically (Bratus and Ioltukhovskiĭ 1986; Supple 1993; Wang et al. 1994). Horseradish peroxidase (HRP) labeling studies of cerebellarhypothalamic circuits reveal that the posterior part of the dorsomedial hypothalamic nucleus receives direct projections from the cerebellum, with somewhat lighter projections from the posterior hypothalamic nucleus (Onat and Cavdar 2003). In addition to these direct projections, there are also indirect projections from the hypothalamus via the basilar pontine nuclei to the cerebellum. Liu and Mihailoff (1999) demonstrated hypothalamopontine projections in rat to the rostral medial and dorsomedial portions of the pons which in turn project to the paraflocculus and vermis of the cerebellum. These authors hypothesize that since cerebral cortical inputs including limbic cortical inputs target similar pontine nuclei, the hypothalamopontine system might integrate autonomic and/or limbic-related functions with movement or somatic-related activity or, more likely, that the cerebellum uses both the direct and indirect hypothalamic inputs to perform integrative somatic, limbic, and visceral functions.

Cerebellar Connections with Paralimbic and Neocortical Association Areas The cerebellum is connected to the cerebral cortex through a two-step process with the pontine nuclei serving as the conduit between the corticopontine pathway and the mossy fiber-mediated pontocerebellar pathway. The two-step pathway from the cerebellum back to the cerebral cortex has the thalamus as the intermediate step between the cerebellothalamic pathway and the thalamocortical pathway. Schmahmann and Pandya (1992) examined the associative and paralimbic pathways in rhesus monkey and described a particular ordering of corticopontine projections. Each cerebral cortical area commits fibers that course with a predictable trajectory in the cerebral white matter, and that end in a unique patch of terminations in the nuclei of the basis pontis. Prefrontal cortical projections arise in the dorsolateral prefrontal cortex (DLPFC) and dorsomedial prefrontal cortex and terminate in the rostral third of the medial pons. Posterior parietal projections arise from both gyral and sulcal cortices including the multimodal caudal regions and terminate throughout the rostrocaudal extent of the pons. Projections from the temporal lobe arise from multimodal regions of the cortex of the upper bank of the superior temporal sulcus and the superior temporal gyrus and terminate in the lateral and dorsal pontine regions. Paralimbic cortices in the cingulate gyrus concerned with motivation, emotion, and drive (Devinsky et al. 1995; Paus 2001) communicate with the cerebellum via their projections to the pontine nuclei (Brodal et al. 1991; Vilensky

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and van Hoesen 1981). The caudal inferior parietal lobule, multimodal regions of the superior temporal gyrus, and the posterior parahippocampal formation that are interconnected with paralimbic structures also contribute to the corticopontine projection (Schmahmann 1996; Schmahmann and Pandya 1997). The cortico-ponto-cerebellar projections in the nonhuman primate are extensive (Glickstein et al. 1985; Schmahmann and Pandya 1991, 1993, 1997; Schmahmann 1996). There is a notable topographic arrangement of corticopontine projections in the monkey. The DLPFC and medial prefrontal cortex project to the medial pons, a finding confirmed also by electrophysiological recordings in the rat (Watson et al. 2009); parietal cortex to the lateral pons; superior temporal lobe (including language and auditory areas) to the lateral and dorsolateral pons; and the parahippocampal gyrus (spatial memory) and parastriate areas project to the dorsolateral pons (Schmahmann and Pandya 1989, 1991, 1992, 1993, 1995, 1997; Schmahmann 1996). Cerebellar efferents from the intracerebellar nuclei, including the dentate, are known to largely target the ventrolateral thalamic nucleus (VL), a structure which has been known for many years to perform sensorimotor transformations and in turn projects to primary motor cortex (M1). The VL thalamic nucleus, along with other traditionally motor cerebellar-recipient thalamic nucleus (the ventral posterolateral nucleus and nucleus X of Olszewski [1952]), project not only to the motor and premotor cortex, but in varying degrees of strength, they are also connected with the supplementary motor area (SMA), and the prefrontal (areas 8 and 46), posterior parietal (superior and inferior parietal lobules), and multimodal temporal regions (area TPO in the upper bank of the superior temporal sulcus) as well. The intralaminar thalamic nuclei (central lateral, paracentral, centromedianparafascicular) and medial dorsal thalamic nucleus also receive projections from the deep cerebellar nuclei and project in varying combinations to the association and limbic cortices (see Schmahmann 1996). Transsynaptic viral tract-tracing studies in monkey identified cerebrocerebellar links across the intervening obligatory synapses in the pons and thalamus, and confirmed and extended these physiological observations. Strick and colleagues demonstrated that whereas the primary motor cortex, M1, is linked with cerebellar lobules IV, V, and VI, the prefrontal and posterior parietal cortices are reciprocally interconnected with cerebellar lobules Crus I and Crus II (the hemispheric extensions of lobule VIIA), and they also have connections with cerebellar lobules VIIB and X (Hoover and Strick 1999; Middleton and Strick 2001; Kelly and Strick 2003; Strick et al. 2009 for review). The cerebral association areas are considerably expanded in human compared to monkey. This is reflected in the composition of the cerebral peduncle that conveys the corticopontine fibers. Using diffusion tensor magnetic resonance imaging, it appears that whereas in the monkey cortico-pontine fibers are derived largely from the motor system, the bulk of the corticopontine fibers in the human are derived from prefrontal regions (Ramnani 2006). Supplementing these anatomical investigations, physiological studies showed that, in contrast to arm and leg sensorimotor representations in cerebellar anterior lobe and lobule VIII, with face representation additionally in lobule VI (Snider and

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Eldred 1951), the anterior cingulate region projects to medial parts of Crus I and II. Association cortices project to the posterior lateral cerebellar hemispheres (Allen and Tsukahara 1974), and in particular, the parietal lobe is linked with lobule VII, including Crus I, Crus II, and paramedian lobule VIIB (Sasaki et al. 1975). The widespread cerebellar connectivity with the cerebral cortex allows cerebellar regions to modulate non-motor functions including attentional processes, multiple cognitive domains, and emotion (Ito 1993; Schmahmann 1996; Schmahmann and Sherman 1998; Schmahmann 2001, 2004; Strick et al. 2009 for review).

Observations from Neuroimaging Studies Functional Topography in the Cerebellum A comprehensive discussion of functional topography in the human cerebellum revealed by task-based and resting state functional connectivity studies can be found in the chapter in this volume by Stoodley et al. (▶ Chap. 33, “Functional Topography of the Human Cerebellum Revealed by Functional Neuroimaging Studies”). The early positron emission tomography (PET) and task-based functional magnetic resonance imaging (fMRI) studies revealed activation of the cerebellum by tasks within multiple cognitive domains including executive, linguistic, mnemonic, attentional, and visuospatial. Meta-analysis using an activation likelihood estimation approach confirmed the conclusion derived from clinical and anatomical studies that there is a functional topography within the cerebellum (Stoodley and Schmahmann 2009). The sensorimotor cerebellum is located in the anterior lobe, parts of lobule VI, and lobule VIII; and the cognitive cerebellum is located in lobule VI and VII at the vermis, and in the hemispheric extensions into lobule VI as well as Crus I and II of lobule VIIA, and lobule VIIB. Functional MRI of a range of cognitive and motor paradigms shed further light on the topographic arrangement of these different processes in the cerebellum (Stoodley et al. 2010, 2012). Five tasks investigating sensorimotor (finger tapping), language (verb generation), spatial (mental rotation), working memory (N-back), and emotional processing (viewing images from the International Affective Picture System [IAPS]) were conducted in nine healthy subjects. Finger tapping activated the ipsilateral anterior lobe (lobules IV-V) as well as lobules VI and VIII. Activation during verb generation was found in right lobules VII and VIIIA. Mental rotation activated left-lateralized clusters in lobules VII-VIIIA, VI, Crus I, and midline VIIAt. The N-back task showed bilateral activation in right lobules VI, Crus I, and left lobules VIIB-VIIIA. Cerebellar activation was evident bilaterally in lobule VI while viewing arousing versus neutral images. This fMRI study was the first to evaluate multiple cognitive paradigms within single individuals, and it provided the first evidence for topographic organization of motor execution versus cognitive/emotional domains within the cerebellum of single individuals. It also revealed activation by emotion-inducing images of the IAPS task in the cerebellar vermis and lateral hemispheres. Recent studies of task-

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based fMRI performed many times in the same individuals reveals a comprehensive map of multiple higher-order cognitive functions represented in the cerebellar posterior lobe (King et al. 2019). Subsequent task-based and resting state functional connectivity MRI studies provide comprehensive detail regarding the primary and secondary sensory motor representations in the anterior lobe, adjacent part of lobule VI, and lobule VIII, as well as the primary (lobule VI/crus I), secondary (crus II/lobule VIIB), and tertiary (lobule IX) cognitive representations in the posterior lobe (Buckner et al. 2011; Guell et al. 2018, 2019), and the reflection of intrinsic connectivity networks of the cerebral hemispheres into the cerebellum, with interindividual variability identified as well (Xue et al. 2021). Activation of the cerebellum in studies of the neural correlates of pain anticipation, thirst, hunger, and smell provide additional fMRI evidence for a limbic cerebellum consisting of the fastigial nucleus, vermis, and flocculonodular lobe. Cerebellar vermis activation is seen in neuroimaging studies investigating panic (e.g., Reiman et al. 1989), sadness, and grief (Beauregard et al. 1998; Gündel et al. 2003). Autonomic processing (Parsons et al. 2000), including the autonomic cardiovascular arousal that occurs during both exercise and mental arithmetic stressor tasks (Critchley et al. 2000), and air hunger (Evans et al. 2002) result in activation of posterior cerebellar regions in both the midline and lateral hemispheres.

Cerebellum and Pain Modulation Nociception is a complex behavior that recruits autonomic, sensorimotor, affective, and cognitive systems. Human pain imaging studies regularly demonstrate activation in the cerebellum, and investigations directed specifically at the role of the cerebellum in pain appreciation have been performed. Anterior regions of the cerebellum are activated by the experience of pain (Becerra et al. 1999), whereas posterior regions are active during the anticipation of pain (Ploghaus et al. 1999). Different cerebellar regions are involved when processing one’s own painful experience (posterior vermis) as opposed to experiencing empathy for another’s pain (lobule VI; Singer et al. 2004). The activation of hemispheral lobule VI and vermal lobule VII is quite consistent across these studies of emotionally salient stimuli (Stoodley and Schmahmann 2009), and like the activation patterns seen within the cerebellum for cognitive tasks, the focus of the cerebellar activation varies according to the demands of the task. It is possible that hemispheric lobule VI and VII activation reflects more cognitive components of task performance (e.g., empathy), due to the connections of these regions with association cortices, and more limbic tasks (including autonomic processing) may particularly involve the posterior vermis, the putative limbic cerebellum. Helmchen et al. (2003) examined perceived pain intensity to a noxious and non-noxious thermal stimulus. In contrast to innocuous stimuli, painful stimuli revealed activation in the intracerebellar nuclei, anterior vermis, and bilaterally in cerebellar hemispheric lobule VI. With the same noxious stimulus, there was

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differential cerebellar activation depending on the perceived pain intensity: high pain intensity ratings were associated with activation in ipsilateral hemispheric lobule III-VI, deep cerebellar nuclei, and in the anterior vermis (lobule III). This differential cerebellar activation pattern reflects a cerebellar role not only in somatosensory processing but also in perceived intensity of a painful stimulus, indicating a role for the cerebellum in the modulation of nociceptive circuits. Borsook et al. (2008) studied the effects of noxious thermal heat and brush applied to the face in a group of healthy subjects and patients with neuropathic pain, and defined areas of activation in the cerebellum. The data indicate that different regions of the cerebellum are involved in acute and chronic pain processing. Heat produces greater contralateral activation compared with brush stimulation, whereas brushing resulted in more ipsilateral/bilateral cerebellar activation. Further, innocuous brush stimuli in healthy subjects produced decreased cerebellar activation in lobules concerned with somatosensory processing. These data provided support for a dichotomy of innocuous stimuli/sensorimotor cerebellum activation versus noxious experience/cognitive/limbic cerebellum activation. These authors (Moulton et al. 2011) later demonstrated that the cerebellum may contain specific regions involved in encoding generalized aversive processing. In their study, aversive stimuli in the form of noxious heat and unpleasant pictures (as tested using the IAPS) were shown to activate overlapping areas in cerebellar lobules VI, Crus I, and VIIB. Further, functional connectivity MRI (fcMRI) mapping indicated that cerebellar areas showing functional overlap with pain and viewing unpleasant pictures are interconnected with limbic system structures including the anterior hypothalamus, subgenual anterior cingulate cortex, and the parahippocampal gyrus.

Autonomic Influences The earlier physiological literature (Martner 1975) as well as clinical (Heath et al. 1979; Schmahmann and Sherman 1998; Levisohn et al. 2000; Schmahmann et al. 2007; Tavano et al. 2007) and behavioral studies in animals (Berman et al. 1978) suggest that the cerebellar vermis is involved in the regulation of a range of nonsomatic functions including cardiovascular control, thirst, and feeding behavior. Cerebello-hypothalamic circuits have been postulated to be a potential neuroanatomical substrate underlying this modulation. Demirtas-Tatlidede et al. (2011) tested the relationship between the cerebellar vermis and nonsomatic functions by stimulating the cerebellum noninvasively using transcranial magnetic stimulation. Theta burst stimulation (TBS) was applied to the vermis (identified with neuronavigation software), the right cerebellar hemisphere, and the left cerebellar hemisphere in 12 healthy human subjects with the aim of modulating cerebellar activity. Following stimulation of the vermis, but not the cerebellar hemispheres, there was a mild but significant decrease in heart rate, and subjective ratings by subjects indicated a significant increase in thirst as well as a trend toward increased appetite. These observations are consistent with physiological and imaging data indicating a role for the cerebellum in the regulation of visceral responses, and suggest a role for the

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vermis in somatovisceral integration, likely through cerebello-hypothalamic pathways.

Indirect Limbic Inputs Resting state functional connectivity magnetic resonance imaging (fcMRI) studies have provided novel insights into the interactions of the cerebellum with the cerebral hemispheres in the human brain (Habas et al. 2009; Krienen and Buckner 2009; O’Reilly et al. 2010). These investigations demonstrate network connectivity of limbic and paralimbic areas of the cerebral hemispheres with the cerebellar vermis and with crus I and II of lobule VIIA. The cerebellum receives most of its inputs from the cerebral hemispheres by way of the pontine nuclei. Associative and limbic inputs to the cerebellum may be more widespread than originally conceptualized, however. Functional connectivity MRI reveals that spontaneous activity in the nucleus accumbens (NAcc), a major structure in the dopaminergic mesolimbic system, predicts activity from a reward paradigm in limbic structures including the orbital medial prefrontal cortex, amygdala, insula, and posterior parietal cortex as well as the cerebellum, despite an absence of direct connections between cerebellum and the NAcc (Cauda et al. 2011). This relationship may be explained by the finding that the ventral tegmental area, the origin of the dopaminergic mesolimbic system, projects to the nucleus accumbens; however, the ventral tegmental area receives strong, behaviorally relevant projections from the deep cerebellar nuclei (Carta et al. 2019).

The Cerebellum Is Implicated in Autism Spectrum Disorders (ASD) There is evidence that autism is associated with structural brain abnormalities that include the cerebellum. Postmortem studies of early infantile autism reveal decreased neurons in deep cerebellar nuclei and reduced numbers of Purkinje cells especially in posterolateral cerebellar cortex (e.g., Bauman and Kemper 1985). Using MRI to compare the brains of normal subjects with those of individuals with autism, Courchesne et al. (2001) reported that cerebellar vermal lobules VI and VII are significantly smaller in autistic individuals. These regions of the cerebellum are connected to brain areas that govern attention, arousal, and the assimilation of sensory stimulation. Certain characteristic features of autism, including sensitivity to sensory stimuli and repetitive behavior, may therefore be explained in part by these cerebellar structural abnormalities. In addition to neuropathology in the cerebellum in autism, there are GABAergic differences in the posterolateral cerebellar cortex in the Crus II region (Yip et al. 2007, 2008, 2009). In adult postmortem subjects with autism, the remaining Purkinje cells and larger sized interneurons in the dentate nuclei contain decreased glutamic acid decarboxylase type 65 or 67 (GAD 65/67) whereas molecular layer interneurons such as basket cells contain increased GAD 67 compared to age-matched controls.

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Since the Crus II region is a major recipient area for frontal lobe afferents via the pons, dysfunction of this portion of the lateral posterior hemisphere and dentate may influence autistic behaviors including social interactions, executive function, and affect. An fMRI study of young adults with autism found increased cerebellar activation by motor tasks but decreased cerebellar activation in an attention paradigm (Allen and Courchesne 2003). These findings were thought to be related to deficient sensory tracking when stimuli appeared at a rapid rate, reflecting decreased cerebellar volumes in individuals with autism. Kates et al. (1998) studied a pair of monozygous twins, one of whom met criteria for strictly defined autism while the other showed restrictions in social interaction and play but did not meet these criteria. Both boys had smaller frontal lobes and superior temporal gyri compared to healthy controls, but the more affected twin had smaller cerebellar vermis lobules VI and VII as well as smaller caudate, amygdaloid, and hippocampal volumes. Children with attention-deficit/hyperactivity disorder have reduced volumes of the posterior inferior lobe of the cerebellum compared to age-matched control subjects, even adjusting for brain volume and IQ (Berquin et al. 1998). Adults with Down’s syndrome also have smaller cerebellar volumes than age-matched controls after controlling for total intracranial volume and total brain volume, a difference that did not appear to change over time in a small subset of patients followed serially (Aylward et al. 1997). Neuropathology in the hippocampus and cerebellum was reported in three postmortem cases of fragile-X syndrome, one of the autism spectrum disorders that results from a single gene defect, the fragile-X mental retardation 1 (FMR1) gene with the FMR1 protein being absent or deficient in affected individuals (Greco et al. 2011). The size of the vermis was decreased preferentially in posterior lobules VI and VII, and there were decreased numbers of Purkinje cells throughout the cerebellum. Additionally, altered neuronal migration was evident both in the hippocampus and cerebellum, indicating the vulnerability of the two structures to a single gene defect. Children with autism spectrum disorder have been shown to have reduced gray matter in cerebellar lobule VII (crus I and crus II) and lobule IX (Stoodley 2014; D’Mello et al. 2015) with atypical connectivity on rsfcMRI between right crus I and the left inferior parietal lobule (Stoodley et al. 2017). Animal models of autism add further insights into cerebellar pathology in this disease. Atypical structural connectivity between right crus I and the left inferior parietal lobule has been identified in the tuberous sclerosis complex mouse model of autism (Tsc1 ASD; Stoodley et al. 2017). Loss of the Tsc1 gene in Purkinje cells in this model results in decreased Purkinje cell function and autistic-like behaviors including abnormal social interaction, repetitive behavior, and vocalizations (Tsai et al. 2012). Kelly et al. (2020) further highlighted interactions between the right cerebellum and the medial prefrontal cortex in this mouse model. They concluded that through polysynaptic connections from cerebellum via ventromedial thalamus to the left medial prefrontal cortex, right crus I regulates social preference in autism spectrum disorder whereas the posterior vermis regulates behavioral flexibility.

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Implications of a Cerebellar Role in Emotional Processing In the original description of the cerebellar cognitive affective syndrome (Schmahmann and Sherman 1997, 1998; Levisohn et al. 2000), patients whose pathology included the cerebellar vermis and midline regions containing the fastigial nucleus experienced personality changes characterized by either flattening of affect or disinhibition with inappropriate behavior. These behavioral phenomena following midline lesions are in accord with earlier physiological experiments demonstrating a relationship between the fastigial nucleus and complex behaviors such as sham rage, grooming repertoires, and predatory attack (Berntson et al. 1973; Reis et al. 1973; Ball et al. 1974). Changes in mood are reported in patients with what was previously known as dominantly inherited olivopontocerebellar atrophy (Kish et al. 1988), now recognized as one of many spinocerebellar ataxias (SCAs). Patients experience higher depression scores compared to controls, and the depression scores correlate weakly with cognitive testing. In 300 participants with SCA types 1, 2, 3, and 6 followed by the Clinical Research Consortium for Spinocerebellar Ataxias (Lo et al. 2016), depression was present in 26%. Suicidal ideation was reported in 65% of patients with SCA 3. Depression had a consistently negative and significant impact on functional status and quality of life in all the SCAs, even after accounting for progression of the motor ataxia syndrome. In multiple system atrophy of the cerebellar type (MSA-C), 36% of patients experience pathological laughing and crying (PLC; Parvizi et al. 2007) at some point in the course, reflecting incongruity between the experience and expression of emotion. When the MSA is predominantly of the parkinsonian form (MSA-P), the incidence of PLC is substantially lower, on the order of 3%. Both MSA-C and MSA-P are synucleinopathies, with the principal difference between them lying in the degree of pathology in the cerebellum and brainstem. Imaging studies link the cerebellum to depression. Increased cerebral blood flow was noted in the cerebellar vermis in the study by Mayberg et al. (1999) who induced transient sadness in healthy volunteers and in patients with depression. An MRI voxel-based morphometric study (Peng et al. 2010) investigating gray matter density in patients with major depressive disorder (MDD) found volumetric reductions in the left cerebellar hemisphere along with lower volumes of gray matter of the frontallimbic cortical areas including orbital frontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC). Resting-state fcMRI in patients with depression reveals that connectivity between the cerebellar vermis and the posterior cingulate cortex correlates with severity of the depression (Alalade et al. 2011). These results are supported by postmortem studies in MDD patients, which show reduced glial fibrillary acidic protein in the cerebellum (Fatemi et al. 2004). Deficits in behavior and emotions are apparent when the cerebellar vermis is involved, as occurs in patients with congenital malformations and/or tumors (Pollack et al. 1995; Schmahmann et al. 2007; Tavano et al. 2007). The posterior vermis has been conceptualized as the limbic cerebellum (Schmahmann 1991, 2000), and vermal abnormalities appear to account in large part for the emotional disturbances,

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inappropriate behavior and changes in affect that characterize the cerebellar cognitive affective syndrome both in adults and children (Schmahmann and Sherman 1998; Levisohn et al. 2000; Schmahmann et al. 2007). The postoperative pediatric cerebellar mutism syndrome is characterized by mutism that comes on within 1–2 days after surgery in children for cerebellar and/or fourth ventricular tumors. The mutism is associated with the cerebellar cognitive affective syndrome, and to varying degrees, the cerebellar motor syndrome with or without brainstem and corticospinal tract dysfunction (Gudrunardottir et al. 2016). The surgical approach is frequently directed through the vermis, and morphometric and lesion network analyses have identified the posterior vermis (particularly lobules IX, VIII, and X in decreasing order of severity), the fastigial nucleus, and the superior cerebellar peduncles as most relevant in the pathophysiology of this condition (Albazron et al. 2019). The anatomical circuits reviewed in this chapter have relevance for a wide repertoire of behaviors that intersect with affect, personality, and theory of mind necessary for social cognition (see ▶ Chap. 86, “The Cerebellar Cognitive Affective Syndrome and the Neuropsychiatry of the Cerebellum,” this volume). The neuropsychiatric impairments have been conceptualized as consisting of hypermetric and hypometric behaviors that fall within five domains: emotional control, attentional control, autism spectrum, psychosis spectrum, and social skill set (Schmahmann et al. 2007). Coordination of behavior, both motor and nonmotor, appears to be a central theme in the role of the cerebellum in nervous system function, as encapsulated in the theories of dysmetria of thought and the universal cerebellar transform (Schmahmann 1991, 2000; Schmahmann et al. 2019) discussed elsewhere in this volume.

Therapeutic Implications There are important therapeutic implications that arise out of this new appreciation that the cerebellum is engaged in the modulation of affect and emotion, and that the posterior vermis and fastigial nucleus are the putative sites of the limbic cerebellum. In the first proof of principal study of its kind, theta burst transcranial magnetic stimulation was applied to the cerebellar vermis in patients with refractory schizophrenia (Demirtas-Tatlidede et al. 2010). This approach was shown to be safe and well-tolerated. There was significant improvement in the negative features of schizophrenia as measured by the positive and negative syndrome scale of schizophrenia. Visual analog scale assessments showed improvement in happiness, sadness, alertness, and depression, and patients also improved on a continuous performance task of attention. These findings have subsequently been replicated (Garg et al. 2016; Brady Jr et al. 2019).

Conclusions and Future Directions The paradigm shift in thinking about the cerebellar role in movement, cognition, and emotion has been advanced by the theories of dysmetria of thought and the universal cerebellar transform, harmonizing the dual anatomic realities of homogeneously

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repeating cerebellar cortical microcircuitry set against the heterogeneous and topographically arranged cerebellar connections with extracerebellar structures. The cerebellar posterior vermis and fastigial nuclei are regarded here as the core of the limbic cerebellum, with evidence in support of this notion derived from clinical evaluation of patients, neuroanatomical tract tracing studies, physiological experiments, behavioral observations in experimental animals, and task-based and functional connectivity MRI in healthy subjects and in patients with cerebellar damage. Intellectual function and emotional processing are inexplicably intertwined, and the cognitive regions of the cerebellar posterior lobes complement the limbic cerebellum by virtue of their connections with the cerebral association areas critical for higherorder function. Acknowledgments Supported in part by the National Ataxia Foundation, the MINDlink Foundation, and Mrs. Mary Jo Reston.

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cerebellar Nuclei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medial and Lateral Descending Motor Systems from the Brainstem . . . . . . . . . . . . . . . . . . . . . . . . . . Reticulospinal Tracts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medial Cerebellar Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Posterior Interposed Nucleus and the Interstitial Cell Groups . . . . . . . . . . . . . . . . . . . . . . . . . The Anterior Interposed Nucleus and the Dorsolateral Hump . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Lateral Cerebellar Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vestibulospinal Tracts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Corticovestibular Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Nucleo-Vestibular Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rubrospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Projections to the Red Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tectospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Nucleo-Tectal Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Interstitiospinal Tract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Projections to the Interstitial Nucleus of Cajal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Projections to Other Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Divergence of Cerebellar Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Convergence of Cerebellar Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Clinical Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hypotonia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ataxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Intention Tremor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The cerebellar nuclei, and to some extent the vestibular nuclei, mediate the ultimate result of cerebellar processing to the rest of the brain. Cerebellar output is directed to the diencephalon and to a score of brainstem regions. This chapter reviews the cerebellar nuclear projections to the brainstem areas that give rise to descending connections that can influence motor programming at spinal cord level, i.e., the reticulospinal, vestibulospinal, rubrospinal, tectospinal, and interstitiospinal pathways. In addition, cerebellar projections to other areas will be briefly considered. Although cerebellar output is structured by the modular internal organization of cerebellar circuitry and related olivocerebellar connections, it is concluded that the modular output, i.e., output of individual cerebellar nuclei or parts thereof, still reaches many areas in the brainstem and diencephalon. In addition, multiple modules may converge their outputs indirectly to the same muscles. This suggests that multiple modules may each take part in different aspects of control of the same muscle or muscle group. Conversely, individual modules, due to the distributed nature of their outputs, may simultaneously affect several descending motor systems with the same ensuing goal. Tools for detailed anatomical and physiological studies are now available and are expected to enhance our knowledge on the effects of the cerebellum on descending motor pathways. Keywords

Cerebellar nuclei · Reticulospinal tracts · Rubrospinal tract · Vestibulospinal tracts · Tectospinal tract List of Abbreviations

12 3V 4/5 Cb 4V 7 AIN Amb AP Aq BIN BPN Cbl CG CN cp D DLH

Hypoglossal nucleus 3rd ventricle Cerebellar lobule 4/5 4th ventricle Facial nucleus Anterior interposed nucleus Ambiguus nucleus Anterior pretectal nucleus Aquaduct Basal interstitial nucleus Basilar pontine nuclei Cerebellum Central gray Cerebellar nuclei Cerebral peduncle Nucleus of Darkschewitsch Dorsolateral hump

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Ecu FF fr Gi IC ICG icp INC IO IV LCN LG LRN LV MCN mcp Md MG ml mlf Mo5 MV n7 NRTP PAG PCRt PF Pfl PIN PnC PnO py RN RNm RNp SC scp Sim SN SO Sp5 SpV SuV VTh ZI

External cuneate nucleus Fields of Forel Retroflex fascicle Gigantocellular reticular nucleus Inferior colliculus Interstitial cell groups Inferior cerebellar peduncle Interstitial nucleus of Cajal Inferior olive Fourth ventricle Lateral cerebellar nucleus Lateral geniculate nucleus Lateral reticular nucleus Lateral vestibular nucleus Medial cerebellar nucleus Middle cerebellar peduncle Medullary reticular nucleus Medial geniculate nucleus Medial lemniscus Medial longitudinal fascicle Motor trigeminal nucleus Medial vestibular nucleus Facial nerve Nucleus reticularis tegmenti pontis Periaqueductal gray Parvicellular reticular formation Parafascicular thalamic nucleus Paraflocculus Posterior interposed nucleus Caudal pontine reticular formation Oral pontine reticular formation Pyramidal tract Red nucleus Magnocellular red nucleus Parvicellular red nucleus Superior colliculus Superior cerebellar peduncle Simple lobule Substantia nigra Superior olive Spinal trigeminal nucleus Spinal vestibular nucleus Superior vestibular nucleus Ventral group thalamic nuclei Zona incerta

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Introduction The cerebellum, which is dominantly involved in the coordination, adaptation, and learning of motor behavior and, most likely, also participates in visceral, affective, and cognitive functions, exerts its influence on these functions by way of the cerebellar nuclei. In addition, selected sets of Purkinje cells provide a direct input to specific regions of the vestibular nuclei. The specific connections of virtually all regions of the cerebellar nuclei with those parts of the thalamus that are connected to the primary and premotor cortices were already recognized and stressed in the early literature (Allen and Tsukahara 1974). However, the cerebellar nuclei also have a prominent direct impact on a number of premotor centers with connections to the spinal cord or lower brainstem. Here, a brief overview of the cerebellar nuclei will be provided followed by a review of their connections to these descending motor systems. Finally, these connections will be briefly assessed in relation to other regions that receive cerebellar output and their joint impact on cerebellar functioning and dysfunctioning.

The Cerebellar Nuclei The cerebellar nuclei are divided into four main nuclei: the medial, posterior interposed, anterior interposed, and lateral cerebellar nuclei (Fig. 1). These divisions are essentially based on cytoarchitectonic grounds but also agree with organizational features of the cerebellum. Purkinje cells projecting to each nuclear subdivision are organized into longitudinal strips. Jan Voogd, in his historic work (Voogd 1964, 2011), proposed that the medial cerebellar nucleus (MCN) receives its cortical afferents from the A zone, both interposed nuclei from the C zone, and the lateral cerebellar nucleus (LCN) from the D zone. The B zone, intercalated between A and C zones, targets the lateral vestibular nucleus. Presently, this basic scheme still holds true although the description of multiple subdivisions of the various zones has been refined considerably and has been shown to correspond with the description of several nuclear subdivisions (Apps and Hawkes 2009; Voogd and Glickstein 1998; Sugihara and Shinoda 2007; Cerminara et al. 2013; Ruigrok 2011). The remarkable reciprocal relation between the inferior olive and cerebellar nuclei has been noted by several authors and has been suggested to form the basis of the olivocerebellar organization (Ruigrok 1997; Ruigrok and Voogd 1990, 2000). Here, a short general description of the cerebellar nuclei of the rat, cat, macaque, and man will be presented before detailing the projections from these nuclei to the rest of the brain (see Fig. 1). The MCN, in cat, macaque, and human often referred to as the fastigial nucleus as it is positioned directly adjacent to the fastigium (apex, roof) of the fourth ventricle, is the most medially located nucleus. Its rostral half is found directly dorsomedial to the rostral half of the fourth ventricle. Caudally, it is found dorsal to the lateral part of the nodulus. In the rat, as in mice, the MCN is characterized by a prominent outgrowth that reaches up into the white matter, consists of generally large cells,

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Rostral view Rat

629

Dorsorostral view MCN

PIN

AIN

LCN DLH

DLP ICG 1 mm

Cat

1 mm

Macaque

1 mm

Human

Fast.

Globose

Embolif.

Dentate microgyra

5 mm

macrogyra

Fig. 1 Three-dimensional reconstructions of the left cerebellar nuclear complex of the rat, cat, macaque, and human (from top to bottom). Left hand panels show the nuclear complex from a rostral view. Right-hand panels show the individual nuclei from a dorsorostral view. Note that the

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and is known as the dorsolateral protuberance (DLP; Korneliussen 1968). The rostral tip of the MCN is in ventrolateral direction continuous with the medial aspect of the superior vestibular nucleus. Caudally, the MCN is separated from both parts of the interposed nuclei by passing corticovestibular fibers. Located within these fibers are small groups of nuclear cells which are collectively known as the interstitial cell groups (ICG; Buisseret-Delmas et al. 1998). The ICG, based on their cortical and efferent connections, seem to be mostly associated with the posterior interposed nucleus (PIN; Buisseret-Delmas et al. 1993; Pijpers et al. 2005). Although the ICG are not mentioned in the description of the cerebellar nuclei of other mammals, they can also be recognized in the cat. In man, the fastigial nucleus also displays a dorsally extending protuberance; however, it is not known to what extent this is homologous to the DLP of rodents. The PIN is found directly lateral to the caudal half of the MCN where it rests on the roof of the fourth ventricle. More rostrally and laterally, its borders with the anterior interposed and lateral cerebellar nuclei, respectively, are not always clear, especially in transverse sections. The rostromedial extension of the PIN continues as the interstitial cell groups (Buisseret-Delmas et al. 1993, 1998). In cat, the PIN carries a medial and lateral dorsal-ward protrusion. The human equivalent of the PIN is designated globose nucleus (Voogd and Ruigrok 2012). The anterior interposed nucleus (AIN) of rat and cat has a mediolaterally elongated shape, whereas the macaque AIN is elongated mostly in the anteroposterior direction. The human equivalent, the emboliform nucleus, has a caudodorsal extension that reaches toward the dorsomedial part of the dentate nucleus (Fig. 1). In rat, the AIN displays a clear somatotopic pattern with representation of the hind limb located mediorostrally and the head region in its caudolateral aspect (e.g., see Lu et al. 2007; Pijpers et al. 2005). In the rat, a conspicuous bulge is noted at the border region between the AIN and the LCN. This dorsolateral hump (DLH) has been associated with either the AIN or the LCN (Voogd 2004; Korneliussen 1968). It has been shown to receive cortical afferents from a strip of Purkinje cells located between the D1 and D2 zones, which has been termed D0, and to receive climbing fiber collaterals that are derived from the dorsomedial group that is associated with the principal olive (Pijpers et al. 2005; Sugihara and Shinoda 2004, 2007). It is remarkable that the DLH provides a prominent ipsilateral descending projection to the lateral medullary reticular formation and adjacent spinal trigeminal nucleus (Fig. 2f; Bentivoglio and Kuypers 1982; Teune et al. 2000). Although, in the cat, the existence of an ipsilaterally descending tract originating from the cerebellar nuclei has been described by Ramon y Cajal (1903) and was also reported in monkey by Chan-Palay (1977), it has not been verified by others. Also, as far as we know, ä Fig. 1 (continued) general organization of the nuclei in all four species is virtually similar, but especially the size of the human dentate has increased formidably. For abbreviations see “List of Abbreviations.” Reconstructions were made with Neurolucida (MicroBrightfield, Inc., Williston, VT, USA) using serial microscopic sections (rat, cat, human) or sections from the macaque atlas by Paxinos et al. (2000). Segmentation of the human nuclear complex was performed by Jan Voogd

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Fig. 2 Serial plots (b–g) of microscopical sections depicting patterns of labeled varicosities (i.e., terminal arborizations) in the caudal brainstem after various injections (shown in a) with an anterograde tracer in the cerebellar nuclei of the rat. The boundaries of several nuclei and fiber tracts are indicated. Note the generally widespread distribution of projections in every case. For abbreviations, see “List of Abbreviations.” (Adapted from Teune et al. 2000)

in man using diffusion tensor imaging, an ipsilateral descending tract originating from the cerebellar nuclei has not been reported (Ye et al. 2013). The LCN, also referred to as dentate nucleus in cat and primates, is rostrally separated from the AIN by traversing fibers from the inferior cerebellar peduncle. In the rat, the LCN consists of the dorsolateral magnocellular part and a ventromedial parvicellular part. In the rhesus monkey, these areas actually form a dentated area, with the medial sheath consisting of mostly small neurons, whereas the lateral sheath is made up of mostly large cells. Only in the human, a multiple dentated nucleus is present, which is considerably larger than the other cerebellar nuclei. Within its

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dentated form, a dorsal microgyric part and a ventral macrogyric part are recognized (Voogd and Ruigrok 2012). Throughout the neuropil of all cerebellar nuclei, small cells are located that have been demonstrated to supply GABAergic input to the inferior olive (De Zeeuw et al. 1989; Fredette and Mugnaini 1991; Teune et al. 1995). In primates, including man, a loosely packed group of neurons, the basal interstitial nucleus (BIN), is found ventral to the LCN that is continuous in a rostrolateral direction toward the floccular peduncle and which maintains reciprocal connections with the vestibulocerebellum (Langer 1985; Ding et al. 2016). In the cat and rat, neurons in a similar position are found but form an even less homogeneous nuclear contour (Ruigrok 2003). The BIN has not been indicated in the reconstructions of Fig. 1.

Medial and Lateral Descending Motor Systems from the Brainstem Hans Kuypers divided the pathways descending to the spinal cord into three groups (Kuypers 1981, 1985). The first group consists of the corticospinal tract, which is subdivided into the crossed lateral and uncrossed medial descending tracts. A second group of descending tracts originates from the brainstem and is also divided into a medial and a lateral descending system based on the funicular course of the fibers and the termination pattern of the participating fibers within either the medial or lateral part of the intermediate region (i.e., layers V–VIII) of the spinal cord. A third group originates from the locus coeruleus and subcoeruleus as well as from the raphe nuclei and terminates diffusely throughout the gray matter of the spinal cord. This review will focus on the cerebellar influence of the second group of descending connections, i.e., the reticulospinal, vestibulospinal, tectospinal, rubrospinal, and interstitiospinal tracts.

Reticulospinal Tracts The medial and medioventral pontomedullary reticular formation are the origin of several long descending tract systems (Torvik and Brodal 1957). Delineation and identification of various subregions has proven to be difficult and may be different in different species. For example, in the rat, over 25 reticular regions have been shown to contain neurons with descending fibers (Newman 1985a, b). Many of these areas have recently been shown to contain neurons that are presynaptic to motoneurons or to spinal interneurons (Arber 2017; Esposito et al. 2014). Here, we will describe the cerebellar influence on the reticulospinal tracts in a general sense. It is well established that reticulospinal connections may follow several routes to the spinal cord (Nyberg-Hansen 1965; Peterson et al. 1975). Reticulospinal neurons located in the pontine and rostral medullary reticular formation mostly, but certainly not exclusively, follow a course by way of the ventral funiculus where they are found adjacent to the fibers of the medial longitudinal fascicle (mlf). They terminate

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throughout the length of the spinal cord predominantly in the medial and central parts of the intermediate zone (i.e., in laminae VII–VIII). Additional reticulospinal tracts are found in the ipsilateral and contralateral ventrolateral funiculus. Both tracts are followed by the axons of reticulospinal neurons from more caudal regions. Projections from these tracts are found throughout all laminae of the spinal cord. Individual reticulospinal axons can collateralize over considerable distances, thereby affecting different regions of the body (Peterson et al. 1975). To further exemplify the heterogeneous nature of the reticulospinal tracts, it has been shown that the individual fibers may be excitatory (glutamatergic), inhibitory (containing GABA, glycine, or both), or modulatory (e.g., serotonin) (Holstege and Kuypers 1987). At least part of the reticulospinal axons can have monosynaptic excitatory effects on motoneurons located throughout the length of the spinal cord (Shapovalov and Gurevitch 1970; Shapovalov 1972) as was also recently elegantly verified in mice using selective, monosynaptic, and conditional viral tracing techniques (Capelli et al. 2017; Esposito et al. 2014). From the above, it follows that the actions of the reticulospinal system are extremely diverse (for review, see Arshavsky et al. 1986). Indeed, reticulospinal systems have been suggested to be involved in maintaining and controlling ongoing motor activity such as locomotion, in the gating of somatosensory information to segmental as well as supraspinal levels and in the control of autonomic activity including pain modulatory systems (Fields 2004; Saper 2004; Arber 2017). The cerebellar nuclei are known to project prominently to the reticular formation (see Fig. 2), thereby involving the regions that give rise to the reticulospinal tracts. In fact the only nuclear region that does not seem to contribute significantly to pontomedullary reticular projections is the posterior interposed nucleus (PIN; Fig. 2, Table 1). Major inputs have been described to arise from specific areas of the MCN and LCN. In addition, in the rat, the nuclear region intercalated between the MCN and the interposed nuclei, i.e., the ICG, and the transition area between the interposed nuclei and the LCN, i.e., the DLH, also display projections to the pontomedullary reticular formation. Several of these cerebellar nuclear areas were recently shown to provide excitatory monosynaptic contacts to premotor neurons in the ventral part of the medullary reticular formation (Esposito et al. 2014). The organization of cerebellar nuclear projections to areas with reticulospinal input is further reviewed below.

Medial Cerebellar Nucleus Projections from especially the caudal aspect of the MCN have been shown to terminate in the dorsal aspect of the contralateral medial pontomedullary reticular formation by way of the uncinate tract in rat (Fig. 2d), cat, and monkey (Asanuma et al. 1983; Batton et al. 1977; Teune et al. 2000; Voogd 1964). In the monkey, the caudal region of the fastigial nucleus has been implicated in oculomotor functions subserving saccades (Noda 1991; Gonzalo-Ruiz et al. 1988). This area not only projects to the contralateral medial pontine reticular formation, known to be involved

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Table 1 Overview of brainstem and diencephalic regions of the rat where labeled varicosities were found after injection with an anterograde tracer in the part of the cerebellar nuclei indicated and, at least partly, depicted in Figs. 2 and 3. Large dots denote dense labeling, intermediate dots indicate fair labeling, and small dots indicate sparse labeling. Question mark indicates that the area was not available for analysis; i indicates that the labeling was found ipsilateral to the injection side. (Based on Teune et al. 2000) MCN

PIN

Rostral

DLP

Caudal

ICG

Medial

(T195)

(R127)

(R100)

(T82)

Inferior olive







Lateral reticular nucl.

− −

− −



−

Parasolitary nucl.

/i





− −

Medullary reticular nucl.

/i







− −

−

− −



AIN

LCN

Lateral Medial

Lateral

DLH

Rostral Ventral

(T79)

(T108)

(R89)

(R98)

(R138)

(T77)











/i





− − − − −

i

− − − − − −

(R178)

Caudal (T94)

Medulla oblongata

Nucl. of the solitary tract

Paramedian nucl. Parvocell. retic. nucl. Gigantocell. retic. nucl. Lat. paragigantocell. nucl.

/i 

Spinal trigem. nucl., oral part

−

Spinal trigem. nucl., interpolar part

− −

Spinal trigem. nucl., caudal part Superior vestibular nucl. Lateral vestibular nucl. Medial vestibular nucl., rostral Medial vestibular nucl., caudal Spinal vestibular nucl. Nucl. prepositus hypoglossi

/i /i  / i  / i / i 

−



−



− − −

− − − − − − − − −

−

− − − − − − − −

− − − − − − − − − − − − − − − − −







− −

− −





− −

− −

 

/i − 

i

− 

−

−

/i / i / i / i / i /i  



i



i



i



i

i



i





i

− −

− − −

i

i

− − −



i

i

− −

− −



−

− 

/i − −

/i 



i



i

i

−



i

i

i

/i

i

i

i

−

− − − −

− − 

i

− − 

i

−





i

− − − −



i

−



i

− − − − −

/i /i − − − − − − − − − − − − − − − − −

− − − − − − i

/i /i 

i



i



i

− − − − −

Metencephalon Basal pontine nuclei Nucl. retic. tegm. pontis A5 noradrenergic group (?) Principal sens. trig. nucl.

− − − −

−



−

−

















−

−

− − − −

Caud. pont retic. nucl.









Oral pont. retic. nucl.









Central gray pons

− − −





/i

− − −

Pedunculopontine tegm. nucl. Parabrachial nucl.

/ i



/

 

i

 

−











−













i

i

i

− − − − − −



−

− −

− − − −







− − 



− 

−





i



i

−

/i /i

−

/i 



i







i

−

−





Mesencephalon Red nucl., parvicellular



Red nucl., magnocellular



Pararubral area

− − − − − − − − − − − − −

Deep mesenceph. nucl. Superior colliculus, superficial Superior colliculus, intermediate Superior colliculus, deep Ventral tegmental area Dorsal raphe nucleus Ventral tegm. relay zone Deep mesenceph. nucl. Superior colliculus, superficial Superior colliculus, intermediate Superior colliculus, deep Ventral tegmental area













/i





−

−

− − −

−

−

−

−



















− − − − −

−

−

−

− − − − −

− − − −



−





/i





− − − − − − 

−

− − − −

− − − −

− −







−













−

− −

− 





− − −



 − −

 







−







−

 









− − −

− − −

− − −

























−

−

−

− − − −

− − − −



−





/i



−

−











−

−

−



i

− −

− 

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Table 1 (continued)

Nucl. of Darkschewitsch

−

−



−

−

−

− − − − −

Nucl. parafascicularis prerubr.















Periaqueductal gray

− − − −









−



− − − −



− − −

− − −



−



− −













−



− − − −

− − − −

−

− − −

− − −

− − −





− − − −

− − − −

− − −



− − − −

Dorsal raphe nucleus Ventral tegm. relay zone Medial access. oculomot. nucl. Interstitial nucl. of Cajal

Nucl. of post. commissure Anterior pretectal nucl. Posterior pretectal nucl.

− − − 

− − 







− − −

−

− − −









 



−

−

− − − − −

−







− − −

− − −







− −

− −

i

−







/i /i  /i 





/i  /i 



 /i /i



Diencephalon Mammillary nuclei Lateral hypothal. area Dorsal hypothal. area Zona incerta

 





Nucl. fields of Forel





















Ventral lat. geniculate nucl.

− − − − − −

−

−

−



−

− −

− − −

− −











−

− − − −

















Parafascicular thalam. nucl. Central medial thalam. nucl. Laterodorsal thalam. nucl. Posterior thalamic nucl.







− − − −

− − −

− − − − − −

− 









−

/i



/i



/i /i /i /i 



/i



−





 

−

− −





 / i



?



Ventromedial thalam. nucl.

















Ventrolateral thalam. nucl.



?

?



?







− − −

Total number of areas

19

31

40

26

15

16

27

28

21

25

31

41

With fair or dense labeling

10

14

21

10

4

9

7

10

13

15

26

25

Ventroposterior thalam. group





in saccade control (Enderle 2002), but also to the contralateral dorsomedial medullary reticular formation (Noda et al. 1990). This latter area would overlap the region from where neck muscles can be directly activated or inhibited (Peterson et al. 1975). Ipsilateral reticular projections that originate from the MCN are conspicuously less dense. They enter the brainstem by way of the direct fastigiobulbar tract located directly medial to the superior cerebellar peduncle (Teune et al. 2000; Voogd 1964; Ruigrok et al. 1990). The dorsolateral protuberance (DLP) of the MCN, which is prominent in rodents, has been shown to more specifically reach intermediate and lateral (i.e., parvicellular) parts of the contralateral reticular formation (Fig. 2c; Rubertone et al. 1990; Teune et al. 2000). The rostral MCN seems to preferentially target the vestibular nuclei (see below) and only sends moderate projections to the intermediate (mediolateral) levels of the reticular formation and to the lateral paragigantocellular nucleus (Fig. 2b). Bagnall et al. (2009) provided evidence that the ipsilateral connections of the MCN are glycinergic whereas glutamatergic MCN neurons project contralaterally. Glutamatergic but not glycinergic projections from the medial cerebellar nucleus control reticulospinal neurons involved in controlling manipulatory actions of the forelimbs (Esposito et al. 2014). By definition, the Purkinje cells that innervate the MCN belong to the A zone (Voogd 1964; Voogd and Glickstein 1998), which has been subdivided into

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Fig. 3 (continued)

a number of subzones, each of which relate to a specific region of the MCN (Apps and Hawkes 2009; Voogd and Ruigrok 2004). Sugihara and Shinoda (2007) have suggested that three regions may be recognized in the MCN dealing with spinal (DLP and rostral MCN), eye movement (centrodorsocaudal MCN), and head orientation (centrocaudal MCN) aspects of motor control. The A zone has also been implicated in the control of emotional behavior, such as fear learning, affective state, cardiovascular control, and freezing behavior (Apps and Strata 2015; Bradley et al. 1991; Koutsikou et al. 2014), but it is not known to what extent this involvement is mediated by way of MCN projections to the reticular formation.

The Posterior Interposed Nucleus and the Interstitial Cell Groups The ICG of the rat, which are intercalated between the MCN and both interposed nuclei, are the target of the Purkinje cells of the X and CX zone (Buisseret-Delmas

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Fig. 3 Serial plots (b–k) of coronal sections depicting patterns of labeled varicosities (i.e., terminal arborizations) in the rostral brainstem and mesodiencephalic junction after various injections (shown in a) with an anterograde tracer in the cerebellar nuclei of the rat. (Adapted from Teune et al. 2000)

et al. 1993, 1998; Voogd and Ruigrok 2004). They have been shown to have projections to the contralateral pontomedullary reticular formation, where they mostly terminate in the gigantocellular reticular nucleus (Fig. 2e; Teune et al. 2000). In the rat, apart from the nucleo-olivary projections, virtually no pontomedullary projections have been described that originate from the main body of the PIN.

The Anterior Interposed Nucleus and the Dorsolateral Hump The dorsolateral hump (DLH) is sometimes also incorporated as part of the LCN (Angaut and Cicirata 1990), because it maintains reciprocal connections with the dorsomedial group of the principal olive (Ruigrok and Voogd 2000; Ruigrok et al. 2015). Nevertheless, it was originally described as part of the AIN (Goodman et al. 1963; Korneliussen 1968), and the DLH and lateral part of the AIN are the origin of the ipsilateral descending tract of the cerebellum (Bentivoglio and Kuypers 1982; Bentivoglio and Molinari 1985; Mehler 1967). They terminate mostly in the

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parvicellular regions of the ipsilateral pontomedullary reticular formation but also invade the deeper layers of the spinal trigeminal nucleus (Fig. 2f; Teune et al. 2000). Stimulation of the DLH induces movement of the lips, neck, and forelimbs (Cicirata et al. 1992; Angaut and Cicirata 1990). As such it has been suggested to be specifically involved in food manipulation. Indeed, the lateral and intermediate medullary reticular formation of the rat have been demonstrated to contain preoromotor neurons (Travers et al. 2000) and are involved with mastication and swallowing (Luo et al. 2001). More rostral regions of the lateral reticular region have been shown to be involved in vocalization in the squirrel monkey (Hannig and Jurgens 2006). The ventral part of the medullary reticular formation, on the other hand, has been shown to be critically involved in grasping (Esposito et al. 2014). Transneuronal transport of viral tracers suggests that the DLH may also be involved with eye blink as well as hind limb muscles (Morcuende et al. 2002; Ruigrok et al. 2008). The DLH receives its Purkinje fiber input from the D0 zone, which is intercalated between the D1 and D2 zones of lobules V–VII (Pijpers et al. 2005; Sugihara and Shinoda 2004).

The Lateral Cerebellar Nucleus The connections of the LCN with the pontomedullary reticular formation are well documented for rat, cat, and monkey (Chan-Palay 1977; Teune et al. 2000; Tolbert et al. 1980). Particularly dense projections are noted in the contralateral gigantocellular reticular nuclei (Fig. 2g). The projection originates mostly from the magnocellular dorsal aspects of the nucleus suggesting that region receives its Purkinje cell projections mostly from the D2 zone. Projections also reach the ipsilateral reticular formation and have been shown to activate monosynaptically reticulospinal neurons to the lumbar cord in cat (Bantli and Bloedel 1975; Tolbert et al. 1980) and to the cervical cord in mice (Esposito et al. 2014). Especially, the recent work in mice suggests that the disynaptic dentate-reticulo-spinal may be used to control skilled motor behavior.

Vestibulospinal Tracts Classically, the vestibular nuclear complex is divided into a medial (MV), spinal (SpV), lateral (LV), and superior vestibular nucleus (SuV). In addition, several subgroups have been recognized in various animals (i.e., groups F, L, X, Y, and Z) (Brodal 1974; Highstein and Holstein 2006). Vestibulospinal tracts are divided into a medial vestibulospinal tract, which descends by way of the mlf, originates mainly from the MV, and reaches to cervical levels where its fibers terminate bilaterally, and into a lateral vestibulospinal tract, which runs lateral to the mlf, originates from the LV, and descends and terminates mostly ipsilaterally throughout the length of the spinal cord (Brodal 1974; Holstege and Kuypers 1982; Nyberg-Hansen 1964b; Highstein and Holstein 2006; Kasumacic et al. 2015; Lambert et al. 2016; Voogd

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2016). Apart from their termination in the ventromedial part of the intermediate zone of the spinal cord, projections to the dorsal horn have been described (Bankoul and Neuhuber 1992). Moreover, the medial vestibulospinal tract may carry both inhibitory and excitatory fibers, whereas the LV neurons that contribute to the lateral vestibulospinal tract are excitatory. In addition to the vestibulospinal tracts, projections from especially the MV and SV are directed to the oculomotor centers where they can have excitatory or inhibitory influences. Some neurons, mostly located in the rostral, magnocellular part of the MV, collateralize to both the oculomotor centers as well as the cervical cord (Highstein and Holstein 2006; Ruigrok et al. 1995; Voogd and Barmack 2006). Finally, vestibular connections to autonomic brainstem systems are known that may regulate cardiovascular responses (Balaban and Porter 1998; Highstein and Holstein 2006). The vestibular nuclei are intimately connected with the cerebellum (Voogd 2016; Voogd et al. 1996). Not only is a large part of its output directed to the cerebellar cortex and nuclei, but it also receives a main input from the cerebellum (e.g., see Fig. 2b). The cerebellar input to the vestibular complex is special because it is the only brainstem system that receives afferents from the cerebellar nuclei as well as directly from the cerebellar cortex.

Cerebellar Corticovestibular Projections Direct projections from the cerebellar cortex to the vestibular nuclei arise from the vermis (lateral A and B zones), from the caudal vermis (ventral uvula and nodulus), and from the flocculus and adjacent ventral paraflocculus (Voogd et al. 1996). The projections from the Purkinje cells of the B zone, which is mostly located in lobules I–VIa but also has a small component in lobule VIII (Ruigrok et al. 2008; Sugihara and Shinoda 2004), to the neurons of the LV constitute the most direct influence of the cerebellar cortex on a descending pathway (Ito and Yoshida 1966; Voogd 2016). The B-zone-lateral vestibulospinal connection is mostly involved in the control of extensor or anti-gravity musculature (Arshavsky et al. 1986). Purkinje cell projections from the nodulus and ventral uvula can be found throughout most of the vestibular complex with the exception of the LV (Bernard 1987; Wylie et al. 1994). This region is implicated in the control of head movement. Floccular projections to the vestibular nuclei seem to terminate in a more orderly fashion. Purkinje cells that show modulation in their firing frequency upon visual stimulation around a vertical axis project predominantly to the magnocellular part of the MV, whereas Purkinje cells modulated by visual stimulation around a horizontal axis project to SV and the Y-group (De Zeeuw et al. 1994; Schonewille et al. 2006; Tan et al. 1995; Balaban et al. 2000). Floccular function is predominantly attributed to the control of the vestibulo-ocular reflex and its coordination with pursuit movements (Ilg and Thier 2008; Voogd and Barmack 2006). The Purkinje cells of the flocculus target a specific population of the MV, termed floccular target neurons, which have physiological characteristics resembling cerebellar projections neurons (Sekirnjak et al. 2003).

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Cerebellar Nucleo-Vestibular Connections More indirect control of vestibular function is also induced by the Purkinje cells of the A zone by way of the MCN. Apart from the reticular connections mentioned above, prominent, usually bilateral, projections to virtually all components of the vestibular nuclei are found (Teune et al. 2000), which mostly, but not exclusively, originate from the rostral part of the MCN (Fig. 2, Table 1). In the mouse ipsilateral MCN projections, like the projections to the reticular formation, have been shown to be glycinergic, whereas contralateral vestibular projections are glutamatergic (Bagnall et al. 2009). It is not known if cortical and MCN projections converge upon the same vestibular regions or neurons. Sparse vestibular projections from the other cerebellar nuclei arise from ICG, AIN, DLH, and LCN and are mostly ipsilateral (Delfini et al. 2000; Teune et al. 2000). They suggest that cerebellar processes are widely integrated with vestibular functions.

Rubrospinal Tract In most mammals the red nucleus (RN) can be recognized as a prominent round structure located centrally in the rostral part of the mesencephalic tegmentum. Usually, a distinction is made between a caudal magnocellular part (RNm) and a rostral parvicellular part (RNp). It should be recognized that this distinction to some extent relates to the difference in projections of both regions. The magnocellular part is the origin of the crossed rubrospinal tract. This part can be identified in the mesencephalon of most limb-carrying terrestrial vertebrates (ten Donkelaar 1988). In primates and carnivores, the parvicellular part is mostly associated with the uncrossed projection to the inferior olive by way of the central tegmental tract. Miller and Gibson (2009) have proposed the additional term of parvicellular contralateral red nucleus (RNpc) to identify small- and medium-sized neurons that also project to the contralateral spinal cord or the contralateral brainstem (Pong et al. 2008; Esposito et al. 2014). Thus, the axons of RNm and RNpc neurons cross at the level of the red nucleus, project mostly contralaterally, and basically only differ from each other with respect to the distance they have to travel to their respective main projection region, i.e., caudal cord versus rostral cord or brainstem. On the other hand, RNp neurons, by definition, project to the ipsilateral olive by way of the central tegmental tract. As such, the rodent red nucleus, as defined by the atlas of Paxinos and Watson (1998), essentially only consists of RNm and RNpc neurons (Ruigrok 2004; Rutherford et al. 1984). In many other species, such as cat, macaque, and human, a “real” RNp has been identified (for review see Onodera and Hicks 2009). In addition, in these animals, as well as in the rodent, immediately rostral, medial, and dorsal to the RN, several areas are located that basically surround the retroflex fascicle and carry names such as the nucleus of Bechterew, nucleus of Darkschewitsch, interstitial and rostral interstitial nucleus of the medial longitudinal fascicle, subparafascicular nucleus, and prerubral field. Homologies between various names that are presently in use are difficult to establish (e.g., see Onodera and Hicks

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2009; Ruigrok 2004), but these nuclei mostly have in common the fact that they contain small neurons, which project massively to the inferior olive. For this reason they have been collectively named as nucleus parafascicularis prerubralis in the rat (Carlton et al. 1982; Ruigrok 2004). Onodera and Hicks (2009) have provided evidence that the projection from this mesodiencephalic area to the inferior olive is topographically organized and that some species differences may exist in whether these projections course by way of either the medial or central tegmental tracts. Rubrospinal fibers terminate mostly within the intermediate zone of the spinal cord; however terminals are also found at cervical levels in lamina IX of monkey, cat, and rat (Miller and Gibson 2009) where they may sparsely terminate on motoneurons that innervate distal muscles (Al-Izki et al. 2008; Kuchler et al. 2002). Rubrospinal fibers also collateralize to the lateral reticular nucleus and to the anterior interposed nucleus (Beitzel et al. 2017; Huisman et al. 1983; Rajakumar et al. 1992; Shokunbi et al. 1986). The function of the rubrospinal tract is still under debate. Selective lesion of this system produces only mild deficits in motor control. In cat and monkey, this affects grasping behavior and causes dragging of the dorsum of the paw during locomotion (Horn et al. 2002; Miller and Gibson 2009). In rat, mild changes in locomotion pattern have been described (Muir and Whishaw 2000; Whishaw et al. 1998). RNm stimulation mostly seems to affect distal extensor muscles in cat (Horn et al. 2002), whereas most RNm units display up-modulation during the swing phase in stepping decerebrate cats (Arshavsky et al. 1986, 1988). Many authors have mentioned that the rubrospinal tract diminishes with the expansion of the corticospinal tract. In man, it is questioned if the rubrospinal tract, which may consist of only several hundreds of fibers, descends beyond the cervical level (for review see Onodera and Hicks 2009). The decrease in size of the rubrospinal tract is countered by an increase in the importance of the RNp and adjacent regions to the inferior olive. It has been speculated that the relative increase in the projection from the mesodiencephalic junction nuclei to the inferior olive or to specific parts thereof mimics the increased control of cerebellar and cortical structures over specific motor functions and, in man, may have enabled the advent of bipedalism and speech (Onodera and Hicks 1999, 2009; Hicks and Onodera 2012).

Cerebellar Projections to the Red Nucleus Rubrospinal neurons are heavily targeted by the AIN (Fig. 3a, f–h, Table 1), fibers of which terminate in a somatotopic fashion (Daniel et al. 1987; Ruigrok 2004; Teune et al. 2000) on their somata and proximal dendrites (Ralston 1994). Although small changes may exist between different mammalian species, it appears that the medial or mediorostral part of the AIN projects to the RN part that sends projections to the lumbar cord whereas the (caudo-)lateral-most part of the AIN targets RN regions that terminate within the contralateral brainstem and upper cervical cord (Conde 1988; Daniel et al. 1987; Stanton 1980).

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The medial aspect of the PIN projects to the medial margin of the RNm in rat (Fig. 3a, e; Daniel et al. 1987) and cat (Robinson et al. 1987). This projection is less dense compared to the input derived from the AIN. RNm projections originating from the MCN and LCN are sparse or non-existent, the latter mostly targeting regions immediately lateral and rostral to the RNm (Fig. 3). The PIN and LCN projections to the primate and cat RNp and the rodent area of the nucleus parafascicularis prerubralis function in a cerebellar nucleo-midbrain-olivary loop (De Zeeuw and Ruigrok 1994; Onodera and Hicks 2009; Ruigrok and Voogd 1995; Guillain et al. 1933).

Tectospinal Tract The superior colliculus is mostly associated with visual input and is involved in directing gaze to objects of interest. This is performed by saccades, head movements, or a combination of both. The control of the superior colliculus over the paramedian pontine reticular formation from where saccades are initiated is well established in most mammals (Enderle 2002). However, in addition, arm or even whole body movements may be evoked by stimulation of the superior colliculus. These body movements are triggered by tectoreticular and tectospinal pathways (Harting 1977; Nyberg-Hansen 1964a; Rose and Abrahams 1978). The tectospinal component seems to be small in most mammals with the largest component to be found in carnivores (Meredith et al. 2001; Murray and Coulter 1982; Nudo and Masterton 1989). Most tectospinal neurons do not project beyond the cervical segments from where the neck muscles are innervated (Nudo and Masterton 1989). Most axons arise from the caudolateral quadrant and, after decussating in the dorsal tegmental decussation, descend contralaterally close to the mlf where they form the predorsal bundle. In cat, a small ipsilateral projecting group of tectospinal fibers has been described (Olivier et al. 1994). Although tectospinal cells may terminate directly on cervical motoneurons (Olivier et al. 1995), conclusive anatomical proof has not yet been obtained (Muto et al. 1996; Shinoda et al. 2006). Therefore, the most direct impact of superior colliculus on cervical neck motoneurons seems to involve at least a segmental or reticular relay (Kakei et al. 1994; Shinoda et al. 2006).

Cerebellar Nucleo-Tectal Connections The cerebellar nuclei have a profound and often neglected impact on the mesencephalic tectum. Cerebellar projections to this region mostly terminate in the intermediate and deep layers of the contralateral superior colliculus (Fig. 3, Table 1). In various animals they have consistently been shown to originate predominantly from two areas of the cerebellar nuclei. The lateral aspect of the PIN and adjacent area of the LCN supply the bulk of cerebellotectal projections (Hirai et al. 1982; Kurimoto et al. 1995; May and Hall 1986; May et al. 1990; Uchida et al. 1983). Both regions mediate information from the paraflocculus, which is known to receive

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mostly extrastriate visual information by way of the dorsolateral basal pons in rat, cat, and monkey (Gayer and Faull 1988; Glickstein et al. 1994; Robinson et al. 1984; Kralj-Hans et al. 2007). In the macaque, neurons in the lateral PIN and LCN have been shown to connect disynaptically to visually related regions in the posterior parietal cortex (Prevosto et al. 2010). Projections to the superior colliculus also arise from the caudal, oculomotor, half of the MCN (Fig. 3a, b). This part mostly receives cortical input from the oculomotor vermis (caudal lobule VI and lobule VII) and has been suggested to be specifically involved with the control and adaptation of saccades (Thier et al. 2002; Noda and Fujikado 1987; Fujikado and Noda 1987; Takagi et al. 1998). Interestingly, the MCN of the rabbit, and hardly that of the gray squirrel, do not project to the superior colliculus (Uchida et al. 1983; May and Hall 1986), a finding that seems to correlate well with the observation that the rabbit superior colliculus does not seem to be essential for generating either saccades or optokinetic nystagmus (Collewijn 1975). The lateral aspect of the AIN has also been reported to provide input to the superior colliculus in the rat and rabbit (Kurimoto et al. 1995; Uchida et al. 1983). In the cat and monkey, the MCN has been shown to terminate bilaterally, generally located somewhat more superficial compared to the PIN projections which terminate strictly contralateral and deeper in the intermediate layer (Kawamura et al. 1982; May et al. 1990). Both types of projections seem to make use of a different type of synapse as judged from their respective degeneration characteristics (Warton et al. 1983) and have been suggested to play different roles in the control of saccades. A clear topographic pattern, however, has not been described in a variety of mammals (Hirai et al. 1982; Kawamura et al. 1982; Kurimoto et al. 1995; May and Hall 1986; May et al. 1990; Noda et al. 1990; Uchida et al. 1983; Teune et al. 2000). The ventrolateral aspect of the caudal superior colliculus reportedly receives the densest cerebellar input (Fig. 3). However, cerebellar terminals are also found in tectal areas that contain large tectospinal neurons. Presently, no specific anatomical information seems to be available that positively identifies the collicular targets of the cerebellar output (Warton et al. 1983). Although GABAergic projections to the pretectum have been reported to arise from the lateral PIN and ventral LCN in the cat (Nakamura et al. 2006), no evidence for cerebellar inhibitory synapses in the superior colliculus has been found (Warton et al. 1983).

Interstitiospinal Tract The interstitiospinal tract originates from scattered large neurons located dorsomedially to the red nucleus and lateral to the oculomotor nuclei and periaqueductal gray within and surrounding the mlf. This poorly defined region is known as the interstitial nucleus of Cajal (INC). Fibers descend ipsilaterally by way of the mlf to the spinal cord where they terminate in laminae VII and VIII of the spinal gray. The interstitiospinal tract has excitatory monosynaptic contacts with neck musculature but also provides di- and polysynaptic mostly excitatory activation of back, forelimb, and hind limb muscles (Fukushima et al. 1978; Holstege and

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Cowie 1989). The INC, apart from acting as origin of the interstitiospinal tract, is also involved in the control of eye movements. Neurons participating in this function appear to form a different population from the cells that give rise to the interstitiospinal tract (Bianchi and Gioia 1995; Zuk et al. 1983). Projections from the INC also reach the oculomotor nuclei, the pontine reticular formation, and the vestibular nuclei. As such it plays an important role in coordinating eye and head movements. The area directly rostral the INC, known as the rostral interstitial nucleus of the mlf and containing many parvalbumin-containing neurons, provides input to the INC and is specifically involved in the control of vertical eye movements (Buttner-Ennever 2006; Fukushima-Kudo et al. 1987; Fukushima 1991; Horn and Buttner-Ennever 1998; Tolbert et al. 1978b).

Cerebellar Projections to the Interstitial Nucleus of Cajal Most prominent cerebellar projections to the INC arise from the oculomotor part of the MCN in rat (Fig. 3b), cat, and monkey (Noda et al. 1990; Teune et al. 2000; Sugimoto et al. 1982). However, it also receives an afferent contribution from other parts of the cerebellar nuclei (Table 1) (Chan-Palay 1977; Teune et al. 2000).

Cerebellar Projections to Other Areas Apart from the cerebellar projections to the five classic descending premotor tracts, all cerebellar nuclei also provide input to various regions of thalamus (Aumann et al. 1994; Chan-Palay 1977; Teune et al. 2000), which will not be reviewed here (but see Table 1). Also, many cerebellar nuclear neurons have been shown to provide input to the cerebellar cortex (Provini et al. 1998; Batini et al. 1992; Buisseret-Delmas and Angaut 1988; Tolbert et al. 1978b; Gao et al. 2016; Houck and Person 2015; Ankri et al. 2015), some of which may be inhibitory (Uusisaari and Knopfel 2010; Batini et al. 1989; Ankri et al. 2015). In addition, the cerebellar nuclei provide input to a number of precerebellar nuclei in the brainstem. Cerebellar nuclear inputs to the reticulotegmental nucleus of the pons and the basal pontine nuclei are well-known and have been shown to participate in potential functionally important reverberating circuitry involving cerebello-bulbocerebellar loops (Mock et al. 2006; Tsukahara et al. 1983). However, projections to nuclei that give rise to the descending motor tracts may also provide feedback to the cerebellum, i.e., the vestibular nuclei and reticular formation form an important source of mossy fiber input to the cerebellum. In addition, many rubrospinal fibers have been demonstrated to collateralize specifically to the AIN (Huisman et al. 1983; Beitzel et al. 2017). A more prominent connection to a precerebellar nucleus, be it of a very different category, is formed by the cerebellar nuclear projections to the inferior olive. This connection has been shown to precisely match the collateral projection of the cerebellar climbing fibers to the cerebellar nuclei (Ruigrok and Voogd 1990, 2000) and to consist exclusively of GABAergic fibers (De Zeeuw et al.

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1989; Fredette and Mugnaini 1991) that originate from a population of small neurons intermingled with the larger and generally excitatory projection neurons and to possess their own physiological characteristics (Fredette and Mugnaini 1991; Uusisaari et al. 2007; Najac and Raman 2015). The population of small GABAergic neurons in the cerebellar nuclei most likely exclusively targets the inferior olive (Teune et al. 1995; De Zeeuw and Ruigrok 1994). Another major target of cerebellar nuclear projections is formed by nuclei that themselves supply a major input to the inferior olive. Especially the nuclei in the mesodiencephalic junction participate in this cerebellar nucleo-mesodiencephaloolivo-cerebellar loop (De Zeeuw and Ruigrok 1994; Ruigrok and Voogd 1995). In man, the main circuit is formed by the projections from the dentate nucleus to the parvicellular RN, which, by way of the central tegmental tract, targets the principal olive. Although the function of this circuit is far from clear (Ruigrok 1997; Ruigrok and Voogd 1995; Hoebeek et al. 2010; Kennedy 1990), this so-called triangle of Guillain-Mollaret (Guillain et al. 1933) has received attention as lesions of this circuit may be instrumental to inducing myoclonus, or rhythmic tremor, of the palatal muscles (sometimes also involving pharyngeal, laryngeal, diaphragm, or extraocular muscles) but also of conspicuous enlargement of particular parts of the inferior olive (Gautier and Blackwood 1961; Boesten and Voogd 1985; Ruigrok et al. 1990; Shaikh et al. 2010). Finally, cerebellar nuclear connections have been described that do not fall within any of the categories mentioned above (Table 1). Examples include the cerebellar projections to hypothalamic areas, zona incerta, parvicellular reticular formation, parabrachial nuclei, and periaqueductal gray (Teune et al. 2000; Zhu and Wang 2008; Haines et al. 1997). These connections suggest a wide impact of cerebellar processing involving various autonomic as well as pain functions.

Divergence of Cerebellar Projections The wide array of cerebellar targets described with anterograde techniques, even after small injections, suggests that individual nucleo-bulbar fibers may collateralize to multiple brainstem and diencephalic areas (Chan-Palay 1977; Teune et al. 2000). A survey of cerebellar nuclear targets based on a study with anterograde tracers in the rat is provided in Table 1 and was, partly, shown in Fig. 3 (both based on Teune et al. 2000). A systematic survey of collateralization based on reconstructions of individual fibers has not yet been performed, but two examples of completely reconstructed axons originating from the posterior interposed nuclei are shown in Fig. 4 (Ruigrok, unpublished data). Information on the wide collateralization of cerebellar nuclear axons is further based on available partial reconstructions (Shinoda et al. 1988), double retrograde tracing (Bentivoglio and Kuypers 1982; Lee et al. 1989; Gonzalo-Ruiz and Leichnetz 1987; Ruigrok and Teune 2014), and electrophysiological data (Tolbert et al. 1978a; Bharos et al. 1981). From these studies it is evident that, as a rule, individual nucleo-bulbar neurons, with the exception of the nucleo-olivary neurons, influence multiple areas simultaneously.

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Fig. 4 (a, b) Reconstructions of bulbar course and terminations of two axons originating in the interposed nuclei. Axons were labeled from a small injection with biotinylated dextran amine in the interposed nucleus. Individual axons were isolated and followed in consecutive coronal sections (80 μ) using Neurolucida (MicroBrightfield, Inc., Williston, VT, USA). Axonal varicosities are indicated with red dots; contours of CN, BPN, RN, and VTh are indicated in green; ventricular system is indicated in gray. Left-hand panels depict lateral view; right-hand panels depict dorsal view. Axon shown in (a) has main branches in deep layers of SC, BPN, ZI, and intralaminar and ventrolateral thalamic nuclei. Axon in (b) has main branches in parabrachial nuclei, PAG, ZI, and ventrolateral thalamus. For abbreviations see “List of Abbreviations.” (Based on Ruigrok, unpublished data)

Indeed, from Table 1 (also see Figs. 2 and 3), it can be seen that relatively small injections result in labeled varicosities within at least ten different areas (and usually considerably more). From the available anterograde and retrograde tracing data, it can be deduced that individual projection neurons in the cerebellar nuclei are likely to be involved in the control of several motor pathways. For example, a neuron in the AIN projecting to the magnocellular red nucleus may also influence, by way of ongoing projections to the ventrolateral and ventro-anterior region of the thalamus, motor output by way of the corticospinal tract. Simultaneously, activity may be fed back to the cerebellar cortex directly by way of nucleocortical collaterals (Gao et al. 2016; Houck and Person 2015; Tolbert et al. 1978b), by way of direct nuclear projections to the basal pontine nuclei (Tsukahara et al. 1983), by way of rubrocerebellar collaterals of the rubrospinal tract (Beitzel et al. 2017), or by way of longer circuits such as the cortico-ponto-cerebellar route. It is evident that a more

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elaborate knowledge on the circuitry involving individual neurons will be necessary in order to be able to evaluate the functional processing within these multiple circuits.

Convergence of Cerebellar Projections In contrast to the apparent divergence of cerebellar nuclear connections, a considerable convergence of cerebellar output to specific muscles has also been noted. Injections with the retrogradely and transneuronally transported rabies virus into several muscles have resulted in viral labeling of several locations within the cerebellar nuclei and cerebellar cortex (Graf et al. 2002; Morcuende et al. 2002; Ruigrok et al. 2008; Tang et al. 1999). Ruigrok et al. (2008) showed that viral injections in antagonistic muscles of hind limb and forelimb result in infection of several longitudinal strips of Purkinje cells which were partly overlapping (Fig. 5). Initial strips were observed only in the vermis, but, with only slightly longer survival times, additional strips were found in paravermal and hemispheral parts of the cerebellum (Fig. 5). This suggests that multiple cerebellar modules, by way of their individual nuclear output, ultimately can converge to control the activity of the same muscle. Simultaneously however, the overlap of labeled strips suggests that a single module, by way of its nuclear output, can influence the activity of several, and even antagonistic, muscles or muscle groups. It is clear that the latter characteristic, at least partly, is also based on the distributed nature of the termination of individual fibers of the, e.g., reticulospinal and rubrospinal tracts (Shinoda et al. 1977, 2006).

Functional Implications The modular characteristics of the cerebellar circuitry, where strips of Purkinje cells converge upon an entity of the cerebellar nuclei and that is matched by the organization of the olivocerebellar climbing fiber system, have been suggested to lie at the basis of the functional working blocks of the cerebellum (Apps and Garwicz 2005; Ruigrok 2011). However, from the account sketched above, it will be obvious that as yet it is by no means clear how individual cerebellar modules interact with brainstem structures to result in functionally meaningful signals. For example, individual modules, by way of their collateralizing output, are capable of influencing numerous brainstem structures simultaneously, which may include several nuclei that have descending connections to the spinal cord. On the other hand, as shown with viral tracing techniques, multiple modules may participate in the control of the same muscle. This particular organization suggests that each cerebellar module may serve a specific function in the control of muscles. The interaction of multiple strips of Purkinje cells with several targets areas has most clearly been demonstrated in the relatively simple system of floccular control on reflexive eye movements (van der Steen et al. 1994; Voogd and Wylie 2004; Ruigrok et al. 1992; Sugihara et al. 2004; Wylie et al. 2017). However, studies that

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Fig. 5 Demonstration of involvement of multiple cerebellar modules in the control of single muscles using transneuronal retrograde transport of rabies virus in rat. (a1) Pattern of Purkinje cell labeling in the lateral vermis 5 days after rabies injection in the ipsilateral gastrocnemius muscle. (a2) 3-D reconstruction of the anterior lobe of this case indicating rabies-labeled Purkinje cells (red) together with zebrin II-labeled Purkinje cells (yellow). Note that the zebrin II-labeled bands identified as p1–p6 can all be recognized. The position of the rabies-labeled Purkinje cells between p2 and p3 (left-hand white arrowhead) is identical to that of the B zone. In addition, a contralateral strip of labeled Purkinje cells is noted just medial to the p2 zebrin II band (right-hand white arrowhead), which corresponds to the location of the lateral A1 zone. (b1, 2) Similar to (a1, 2) after injection of rabies virus in the ipsilateral anterior tibial muscle. This time both the B and lateral A1 zone (arrowhead) are noted ipsilateral to the injection. (c) Pattern of infection 6 days after injection of the gastrocnemius muscle. Note that the original zones can still be recognized but also have a mirror representation in the other cerebellar hemisphere. However, several additional zones are also recognized (arrowhead) in paravermis and hemisphere (not shown). (d) Similar to (c) for injection of the anterior tibial muscle. (Modified from Ruigrok et al. 2008 and Ruigrok 2011)

attempted to study the contribution of individual modules to skeletomotor function also suggest that a single module may affect a particular type of muscle control (Horn et al. 2010; Cerminara and Apps 2010; Pijpers et al. 2008). For example, impairment

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of the C1 hind limb module has been shown to affect the phase-locked modulation of reflexes during locomotion (Pijpers et al. 2008). Inactivation or lesion of various olivary regions, resulting in inactivation or severe functional impairment of related cerebellar nuclear areas, also results in highly specific deficits in motor control (Horn et al. 2010; Cerminara and Apps 2010). Hence, different cerebellar modules seem to be able to participate in the control of potentially the same muscles that are being used in different functional contexts.

Clinical Implications From this account it will be obvious that the impacts of cerebellar malfunctioning are diverse and not infrequently difficult to fully understand. Due to the distributed connectivity, specific damage of the vestibulocerebellar, vermal, paravermal, and hemispheral components of the cerebellum results in various combinations of specific cerebellar disorders (Thach and Bastian 2004). Conversely, due to the nature of ongoing spinocerebellar degenerative disease, this may differentially influence a multitude of cerebellar modules. Likewise, cerebellar tumors or lesions will almost invariably involve several adjacent modules in an incomplete way (i.e., the modules are organized in longitudinal cortical arrays which can be discontinuous and may be found in both the anterior and posterior lobes (Pijpers et al. 2006; Ruigrok 2011). The resulting clinical syndrome, therefore, is hard to predict or explain. Nevertheless, and despite the recent recognition that the cerebellum may be involved in a large array of non-motor brain functions, cerebellar disorders can lead to very clear motor deficits. Obviously, due to the double decussation of most cerebellofugal projections (i.e., the decussation of the superior cerebellar peduncle in the caudal mesencephalon, followed by the decussation of corticospinal and rubrospinal tracts), unilateral cerebellar deficits usually involve affected movements of the ipsilateral side of the body. Cerebellar-based handicaps in motor control commonly involve three symptoms: muscle weakness (hypotonia), ataxia, and tremor (Thach and Bastian 2004).

Hypotonia Sudden removal of cerebellar nuclear output in cases of, e.g., trauma, will diminish the tonic excitatory drive to premotor regions. This is likely to result in a general reduction of activation of the related motoneuron pools, which will be reflected in reduced muscle tone (hypotonia). Similarly, however, cerebellar lesions that do not involve the nuclei are likely to diminish the inhibitory drive of the cortical Purkinje cells on the cerebellar nuclei, thereby increasing nuclear output resulting in hypertonic responses. Hypotonia and hypertonia may (partly) disappear after a period of weeks or months, probably by adjustment of the tonic drive to premotor regions by other, unaffected, cerebellar or extracerebellar brain regions.

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Ataxia Although ataxia is typical for cerebellar disorders, it is not easily characterized. It usually reflects the inability of a patient to execute voluntary movements in a “normal” way. Movements, or parts thereof, are not initiated at the correct moment, are not terminated at the appropriate time, and are not corrected adequately. This results in improperly conducted and dysmetric movements. To some extent hypoand hypertonia of muscles or muscle groups form the foundation of these motor deficits. Because antagonistic and correcting activity is inadequately timed, oscillations will easily occur around the intended target or result in pendular reflexes. Due to dysmetria and failure to time movements, cerebellar patients also encounter problems with the execution of fast rhythmic movements (dysdiadochokinesis). When these disorders concern the mouth, pharynx, or larynx musculature, it results in cerebellar dysarthria that typically involves changes in rhythm and amplitude in combination with a careless or “slurred” pronunciation.

Intention Tremor This form of tremor is also very characteristic in cerebellar disorders and may be related to dysfunction of properly timed components of movements, resulting in a disturbance in the beat and rhythm of movements with tremor as a consequence. Increased pendular reflexes are clearly related to this phenomenon. Cerebellar nystagmus may be seen as a form of intention tremor reflecting dysfunction of the vestibulocerebellum.

Conclusions and Future Directions The cerebellum is usually appreciated as a structure with a uniform internal structure that will perform a particular type of information processing. Within this internal structure, based on the organization of corticonuclear and olivocerebellar connections, a number of parallel, longitudinally organized, modules can be recognized which form functional entities. The organization of the input to these modules and in particular the organization of their output channels, therefore, will determine the type of information processed within a module and which structures will be informed of its result. The above account shows that the output of a particular module is directed to many regions in brainstem and diencephalon and may affect multiple centers with descending connections to the spinal cord. In addition, several modules may ultimately affect activity patterns of the same muscle or muscle group. In order to fully understand the cerebellar involvement in motor control and learning (and in other functions), it will be imperative to understand to what extent individual modules or micromodules control different aspects of controlling muscles. In addition, a precise description of the often di- and polysynaptic pathways involved will be necessary. The advent of new neuroanatomical and physiological techniques such as selective

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(modular) lesioning, conditional transneuronal tracing, single-axon reconstructions, and optogenetics is expected to greatly aid in fulfilling these requirements for further understanding cerebellar function and dysfunction.

Cross-References ▶ Cerebellar Connections with Limbic Circuits: Anatomy and Functional Implications ▶ Cerebellar Control of Eye Movements ▶ Cerebellar Control of Posture ▶ Cerebellar Nuclei and the Inferior Olivary Nuclei: Organization and Connections ▶ Cerebellar Outputs in Non-human Primates: An Anatomical Perspective Using Transsynaptic Tracers ▶ Cerebellar Thalamic and Thalamocortical Projections ▶ Cerebellum and Eyeblink Conditioning Acknowledgments This work was supported by the Dutch Ministry of Health, Welfare and Sports (T.R.).

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Tang Y, Rampin O, Giuliano F, Ugolini G (1999) Spinal and brain circuits to motoneurons of the bulbospongiosus muscle: retrograde transneuronal tracing with rabies virus. J Comp Neurol 414(2):167–192 ten Donkelaar HJ (1988) Evolution of the red nucleus and rubrospinal tract. Behav Brain Res 28(1–2):9–20 Teune TM, Van der Burg J, Ruigrok TJH (1995) Cerebellar projections to the red nucleus and inferior olive originate from separate populations of neurons in the rat. A non-fluorescent double labeling study. Brain Res 673:313–319 Teune TM, van der Burg J, van der Moer J, Voogd J, Ruigrok TJ (2000) Topography of cerebellar nuclear projections to the brain stem in the rat. Prog Brain Res 124:141–172 Thach WT, Bastian AJ (2004) Role of the cerebellum in the control and adaptation of gait in health and disease. Prog Brain Res 143:353–366 Thier P, Dicke PW, Haas R, Thielert CD, Catz N (2002) The role of the oculomotor vermis in the control of saccadic eye movements. Ann N Y Acad Sci 978:50–62 Tolbert DL, Bantli H, Bloedel JR (1978a) Multiple branching of cerebellar efferent projections in cats. Exp Brain Res 31:305–316 Tolbert DL, Bantli H, Bloedel JR (1978b) Organizational features of the cat and monkey cerebellar nucleocortical projection. J Comp Neurol 182:39–56 Tolbert DL, Bantli H, Hames EG, Ebner TJ, McMullen TA, Bloedel JR (1980) A demonstration of the dentato-reticulospinal projection in the cat. Neuroscience 5(8):1479–1488 Torvik A, Brodal A (1957) The origin of reticulospinal fibers in the cat; an experimental study. Anat Rec 128(1):113–137 Travers JB, DiNardo LA, Karimnamazi H (2000) Medullary reticular formation activity during ingestion and rejection in the awake rat. Exp Brain Res 130(1):78–92 Tsukahara N, Bando T, Murakami F, Oda Y (1983) Properties of cerebello-precerebellar reverberating circuits. Brain Res 274:249–259 Uchida K, Mizuno N, Sugimoto T, Itoh K, Kudo M (1983) Direct projections from the cerebellar nuclei to the superior colliculus in the rabbit: an HRP study. J Comp Neurol 216(3):319–326 Uusisaari M, Knopfel T (2010) GlyT2+ neurons in the lateral cerebellar nucleus. Cerebellum 9(1):42–55. https://doi.org/10.1007/s12311-009-0137-1 Uusisaari M, Obata K, Knopfel T (2007) Morphological and electrophysiological properties of GABAergic and non-GABAergic cells in the deep cerebellar nuclei. J Neurophysiol 97(1): 901–911 van der Steen J, Simpson JI, Tan J (1994) Functional and anatomic organization of threedimensional eye movements in rabbit cerebellar flocculus. J Neurophysiol 72(31–46):31–46 Voogd J (1964) The cerebellum of the cat: structure and fiber connections. Van Gorcum, Assen Voogd J (2004) Cerebellum. In: Paxinos G (ed) The rat nervous system, 3rd edn. Elsevier Academic, San Diego, pp 205–242 Voogd J (2011) Cerebellar zones: a personal history. Cerebellum 10(3):334–350. https://doi.org/ 10.1007/s12311-010-0221-6 Voogd J (2016) Deiters’ nucleus. Its role in cerebellar ideogenesis: the Ferdinando Rossi memorial lecture. Cerebellum 15(1):54–66. https://doi.org/10.1007/s12311-015-0681-9 Voogd J, Barmack NH (2006) Oculomotor cerebellum. Prog Brain Res 151:231–268 Voogd J, Glickstein M (1998) The anatomy of the cerebellum. Trends Neurosci 2:305–371 Voogd J, Ruigrok TJ (2004) The organization of the corticonuclear and olivocerebellar climbing fiber projections to the rat cerebellar vermis: the congruence of projection zones and the zebrin pattern. J Neurocytol 33(1):5–21 Voogd J, Ruigrok TJH (2012) Cerebellum and precerebellar nuclei. In: Mai JK, Paxinos G (eds) The human nervous system, 3rd edn. Elsevier, Amsterdam, pp 471–545 Voogd J, Wylie DR (2004) Functional and anatomical organization of floccular zones: a preserved feature in vertebrates. J Comp Neurol 470(2):107–112. https://doi.org/10.1002/cne.11022 Voogd J, Gerrits NM, Ruigrok TJH (1996) Organization of the vestibulocerebellum. Ann N Y Acad Sci 781:553–579

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cyto- and Chemoarchitecture of the Motor Thalamus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Afferents of the Motor Thalamus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Motor Thalamic Projections to Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Although it is well known that the major output of the cerebellum is directed to the thalamus and ultimately to the cerebral cortex, the anatomical details and functional organization of this system remains unclear. Here, the current status of the cytoarchitecture of the motor thalamus, its afferents and efferent cortical projections are reviewed. The distribution of the cerebellothalamic and pallidothalamic projections to motor cortical areas is also discussed and the functional importance of these motor systems is highlighted. Keywords

Globus pallidus · Supplementary motor area · Cerebellar nucleus · Fastigial nucleus · Interpositus nucleus Abbreviations

BDA CL CM

Biotinylated dextran amine Central lateral nucleus Centromedian nucleus

S. T. Sakai (*) Department of Psychology and Neuroscience Program, Michigan State University, East Lansing, MI, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_24

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CS GPi MD MI PMd PMv Pre-SMA R SMA VA VApc VLa VLc VLm VLo VLp VLx VPI VPLo WGA-HRP

S. T. Sakai

Central sulcus Globus pallidus internal segment Mediodorsal nucleus Primary motor cortex Premotor cortex dorsal Premotor cortex ventral Presupplementary motor area Reticular nucleus Supplementary motor area Ventral anterior nucleus Ventral anterior nucleus pars principalis Ventral lateral nucleus anterior division Ventral lateral nucleus pars caudalis Ventral lateral nucleus pars medialis Ventral lateral nucleus pars oralis Ventral lateral nucleus posterior division Ventral lateral nucleus, nucleus X Ventral posterior inferior division Ventral posterolateral nucleus pars oralis Wheat germ agglutinin conjugated horseradish peroxidase

Introduction Thalamus as the gateway to the cerebral cortex occupies a pivotal place in the processing of incoming and outgoing signals. Over the past 20 years, interest in the organization of the motor thalamus increased due to its role in the amelioration of tremor and rigidity following either thalamotomy (Ohye and Narabayashi 1979; Tasker et al. 1982; Ohye 1997) or deep brain stimulation (Benabid et al. 1996; Hubble et al. 1997; Starr et al. 1998). Despite the importance of the motor thalamus in motor control functions, details of its anatomical organization including its afferent and efferent connections still remain to be addressed. Thalamic studies are often stymied by the difficulty in defining and clearly delineating its constituent nuclei and their borders. The lack of agreement on thalamic terminology and nomenclature has also contributed to the confusion (for review, see Percheron et al. 1996, Ilinsky and Kultas-Ilinsky 2002; Jones 2007). Thalamic nuclei can be defined based on cytoarchitecture and chemoarchitecture but the term motor thalamus refers to the projection territory of the basal ganglia (efferent projections of the substantia nigra and globus pallidus) and the deep cerebellar nuclei. Since these projections may not strictly adhere to nuclear boundaries, comparisons made from different experiments and based on different species are problematic. This is due, in part, to the difficulty in reliably delineating the boundaries of the motor thalamus across mammalian species since both the number and cytoarchitectural details of the constituent subnuclei vary across species (Jones 1985, 2007). Many studies compared results across different experiments and animals in concluding that the cerebellum and basal ganglia projections distributed to separate thalamic nuclei and that

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the thalamocortical projections to different motor cortical areas arose from separate thalamic nuclei (Schell and Strick 1984; Alexander et al. 1986; Jones 1985, 2007; Percheron et al. 1996). The primary problem with such comparisons is the uncertainty of applying the same thalamic nuclear boundaries across experiments. One way to address this uncertainty is to eliminate the need to delineate thalamic nuclear boundaries by directly evaluating overlap of the cerebellar and basal ganglia projections with thalamocortical projection neurons using multiple neuroanatomical tracers in the same animal. Here, a review of the afferent and efferent connections based on anatomical studies utilizing axonal transport techniques in primates with a particular emphasis on the comparison of the cerebellothalamic and pallidothalamic projections is presented. Results from experiments using transneuronal labeling are presented elsewhere in this volume and will not be reviewed here.

Cyto- and Chemoarchitecture of the Motor Thalamus According to the terminology of Olszewski (1952), the motor thalamus typically consists of the ventral anterior nucleus (VA), ventral lateral nucleus pars oralis (VLo), ventral posterior lateral nucleus pars oralis (VPLo), ventral lateral nucleus pars caudalis (VLc), ventral lateral nucleus pars medialis (VLm), and area X (X) in the macaque monkey. The cytoarchitectonic distinctions between these nuclei are somewhat vague and not readily agreed to by others who have proposed either more or less thalamic subnuclei (Walker 1938; Hassler 1982; Percheron et al. 1996; Ilinsky and Kultas-Ilinsky 2002; Jones 2007). An alternative approach to defining and naming thalamic nuclei was based on the distribution of afferent connections. Jones (2007) employed this criterion in proposing a terminology that might be applicable to both primate and non-primate species in his simpler nomenclature of the motor thalamus: VA and two subdivisions of VL: anterior and posterior where VLa primarily refers to the pallidothalamic territory and VLp, the cerebellothalamic territory. Some researchers have argued that a single VL should not contain both pallidal and cerebellar territories and that the nigral and pallidal thalamic projections to its primary targets should be subdivisions of a single basal ganglia–related entity such as VA (Percheron et al. 1996; Ilinsky and Kultas-Ilinsky 2002). The nomenclatures of Olszewski, Jones, and Ilinsky are compared in Table 1. Based on these differences, it is clear that thalamic parcellation and nomenclatures remain far from standardized. In the following, the distinctive cyto- and chemoarchitectonic features of the motor thalamus using Olszewski’s (1952) nomenclature and where directly applicable, the terminology of Jones (1985, 2007) is described. The ventral lateral nucleus pars oralis (VLo) of Olszewski (1952) in the macaque monkey primarily occupies the region caudal to the VA, rostral to the ventral posterior Table 1 Motor thalamic nomenclature Olszewski (1952) Jones (2007) Ilinsky and Kultas-Ilinsky (2002)

VApc VApc VApc

VLo VLa VAdc

VPLo VLp VL

X(VLx) VLp VL

VLc VLp VL

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lateral thalamus (VPL), and lateral to the internal medullary lamina. Its cytoarchitecture is diverse consisting of multiple subnuclei depending on the author (Walker 1938; Hassler 1982; Percheron et al. 1996). The VLo corresponds to the ventral lateral nucleus anterior division (VLa) of Jones (1985) and consists of small-to-medium-sized, darkly stained cells packed irregularly as seen in Nissl preparations. Cells of VLo can be distinguished from the more posterior ventral posterior lateralis nucleus pars oralis (VPLo) because the latter contains larger cells with a sparser and more homogeneous distribution. Cells of VLo are also distinct from the ventral lateral nucleus pars caudalis (VLc) in that the VLc cells are darkly stained for Nissl and smaller. A medial division of VPL (area X) was also identified by Olszewski (1952) and is characterized by the presence of small, homogeneously distributed, lightly Nissl stained cells. These subnuclei, VPLo, VLx, VLc, described by Olszewski together form the single VLp nucleus of Jones. Since the differences between these subnuclei are variants on a common theme and together these nuclei form a cerebellar projection to the motor cortex, Jones (1985) suggested the single designation VLp. The subnuclei of the motor thalamus are difficult to distinguish based on Nissl cytoarchitecture alone but differential staining within the motor thalamus has been found using a variety of histochemical and immunocytochemical stains. Acetylcholinesterase (AChE) staining greatly facilitates the comparison between VLo and VPLo (Fig. 1). The VLo (VLa) stains dark for AChE contrasting sharply with the lighter AChE staining in VA rostrally and moderately stained VPLo (VLp) caudally. The differential AChE staining is most apparent in the owl monkey thalamus (Stepniewska et al. 1994; Sakai et al. 2000) in comparison to the macaque monkey thalamus (Sakai et al. 2003; Jones 2007). Differential immunocytochemical reactivity to the monoclonal antibody, CAT 301, is also found where high immunoreactivity is found in VPLo (VLp) and low in VLo (VLa) in the macaque monkey thalamus (Fig. 1) (Hendry et al. 1988; Stepniewska et al. 2003). Subnuclei of the motor thalamus are also immunoreactive for calcium-binding proteins. Low calbindin immunoreactivity is found in VPLo and VLx whereas VLo and VLc were moderately to strongly immunoreactive (Percheron et al. 1996; Stepniewska et al. 2003; Calzavara et al. 2005; Jones 2007). Jones reported high parvalbumin immunoreactivity in VLp and moderate to weak immunoreactivity in VLa whereas Calzavara et al. (2005) found that parvalbumin immunoreactivity in VLo with dense and patchy immunoreactivity was found in VLx, VPLo, and VLc. The patchy immunoreactivity of dense and light staining, particularly in medial VLx, VLc and along the VLo and VPLo border lead Calzavara et al. (2005) to suggest that parvalbumin immunoreactivity is of limited value in delineating the motor thalamic subnuclei. In summary, cytoarchitectonic criteria combined with either AChE, CAT 301 or calbindin immunoreactivity enhance delineation of the motor thalamus, particularly the distinction between VLo and VPLo.

Afferents of the Motor Thalamus The motor thalamus can be defined based on its afferent projections from the cerebellum and globus pallidus. Many studies have examined the cerebellothalamic distribution in the macaque monkeys using silver degeneration methods following

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Fig. 1 Low power photomicrographs of a series of coronal sections through the macaque motor thalamus. (a) Brightfield photomicrograph of a section showing cerebellothalamic wheat germ agglutinin conjugated horseradish peroxidase (WGA-HRP) labeling in VPLo and the patches of pallidal biotinylated dextran amine (BDA) labeling in VLc. Asterisks denote the same blood vessel in A-E. (b) Major cytoarchitectonic features of the motor thalamus at this thalamic level in a cresyl violet stained section. (c) Darkfield photomicrograph of the same section shown in A. Patchy cerebellar and pallidal labeling in VLc interdigitate. (d) Acetylthiochoinesterase (AChE) chemoarchitecture stained section. (e) The adjacent section immunoreacted for CAT 301. Note that VPLo is immunopositive for CAT 301 (Modified from Sakai et al. (2003). Ascending inputs to the pre-supplementary motor area in the macaque monkey: cerebello- and pallido-thalamocortical projections. Thalamus Related Syst 2: 175–187 with permission)

cerebellar lesions and anterograde axonal transport techniques (Kusama et al. 1971; Mehler 1971; Chan-Palay 1977; Stanton 1980; Kalil 1981; Asanuma et al. 1983a, b; Ilinsky and Kultas-Ilinsky 1987). There is general agreement that the cerebellothalamic projections distribute in a lamella-like arrangement composed of rod-like zones of axonal terminations from the dentate nucleus and more diffuse and

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focal terminations from interpositus and fastigial nuclei (Kalil 1981; Asanuma et al. 1983b; Mason et al. 2000). These terminal projections arise from the contralateral dentate and interpositus nuclei and the fastigial nuclei bilaterally (Stanton 1980; Kalil 1981; Asanuma et al. 1983a, b; Rouiller et al. 1994; Sakai et al. 1996). Both the dentate and interpositus nuclei densely project to contralateral thalamus while the projections from fastigial nucleus are sparser in comparison (Kalil 1981; Asanuma et al. 1983a, b). The cerebellar nuclei project to the motor thalamus in a topographic manner whereby anterior regions of the cerebellar nuclei primarily project to lateral motor thalamus and posterior parts of the cerebellar nuclei preferentially project to medial motor thalamus (Stanton 1980; Kalil 1981; Asanuma et al. 1983a). The dentate and interpositus nuclei give rise to fibers that project to overlapping thalamic domains but it is not currently known if these inputs converge onto the same thalamic neurons in the monkey. Although a dorsoventral topography from the dentate nucleus has been described (Middleton and Strick 1997), an analysis of the fibers from the ventral dentate has shown that they distribute throughout the VL region (VLp of Jones) (Mason et al. 2000). It has been suggested that each cerebellar nucleus contains a somatotopic body representation (Asanuma et al. 1983a; Middleton and Strick 1997; Jones 2007). Recent evidence suggests that a point to point somatotopy arising from each cerebellar nucleus to the motor thalamus may not completely characterize these projections. Based on small injections of retrograde tracers into the motor thalamus of the macaque monkey following electrophysiological identification of the face, forelimb, or hind limb representation, Evrard and Craig (2008) suggest that the cerebellar projections can be more aptly described as somatotopographic reflecting their finding that these projections both diverge and converge within the thalamus in a pattern that includes limited foci as well as broadly dispersed patches. This pattern of focal and widely distributed axonal fields was also reported using biotinylated dextran amine (BDA) labeling of the cerebellothalamic axons (Mason et al. 2000). These data suggest that the afferent information arising from the cerebellar nuclei include both detailed somatotopically organized information as well as more generalized topographical information. Taken together, this anatomical distribution may best reflect the information processing required in order to produce coordinated multi-joint movements (Evrard and Craig 2008). The majority of cerebellothalamic fibers cross midline at the brachium conjunctivum and travel anteriorly to the diencephalon. Dense bundles of cerebellar fibers turn dorsally coursing through the fields of Fórel in approaching caudal thalamus. At this level, a contingent of fibers continues dorsally through the zona incerta, traversing the ventral posterior inferior nucleus (VPI) and traveling on to caudal intralaminar nuclei and the mediodorsal (MD) nucleus. The main bundle of cerebellar fibers courses rostrally to the external medullary laminae to successively disperse at multiple caudorostral levels to the motor thalamus including VPLo, VLx, and VLc (Stanton 1980; Kalil 1981; Asanuma et al. 1983a; Mason et al. 2000). As noted earlier, analysis of cerebellothalamic terminals reveal two primary types of fibers: fibers with focal terminal fields and those with dispersed terminal fields

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(Mason et al. 2000). A single cerebellothalamic axon may emit several long branches with individual terminal fields consisting of clusters of elongated discs (Kalil 1981; Mason et al. 2000). An axon could give rise to as many as 29 terminal fields and close to 300 terminal boutons are associated with a single cerebellothalamic axon (Mason et al. 1996, 2000). Cerebellothalamic terminals are large, filled with round vesicles, and make asymmetrical contacts onto dendrites of thalamocortical projection neurons or interneurons (Harding and Powell 1977; Kultas-Ilinsky and Ilinsky 1991; Mason et al. 1996; Ilinsky and Kultas-Ilinsky 2002). The putative neurotransmitter is glutamate. Although no direct evidence is available in primates, a recent study reported VGlut2 immunoreactivity associated with the cerebellothalamic projections in the rat (Kuramoto et al. 2011). There is some disagreement as to the extent of cerebellar projections to VLo with some investigators reporting this projection (Kusama et al. 1971; Mehler 1971; Chan-Palay 1977; Stanton 1980; Kalil 1981) and others denying it (Percheron 1996; Asanuma et al. 1983a; Ilinsky and Kultas-Ilinsky 1987; Jones 2007). If cerebellothalamic projections distribute to rostral motor thalamus including VLo as suggested by single tracing studies, then the possibility remains that thalamus receives overlapping and possibly converging inputs from the globus pallidus and cerebellum. A direct assessment of this question was made by using two anterograde tracers, one injected into the globus pallidus and the other injected into the deep cerebellar nuclei. The distribution of the axonal labeling emanating from each source is then directly compared (Rouiller et al. 1994; Sakai et al. 1996) (Fig. 2). In general, the pallidothalamic projections distribute broadly throughout VLo with small patchy foci found rostrally in the ventral anterior nucleus pars principalis (VApc) and VLc. Cerebellothalamic territory extends anteriorly beyond the cell-sparse zones of VPLo, VLx, and VLc. The double labeling method revealed some interdigitation of pallidothalamic and cerebellothalamic labeling in VLo, VLc, VLx, and VPLo (Rouiller et al. 1994; Sakai et al. 1996). These small interdigitating patches of pallidal and cerebellar projections are limited and occur preferentially along border zones between nuclei. Although zones of interdigitating inputs were observed in close apposition to the proximal dendrites and soma of the same neuron, this was very rare. Based on electrophysiological evidence, it is unlikely that single thalamic neurons receive converging inputs from the cerebellum and globus pallidus (Yamamoto et al. 1984; Nambu et al. 1988, 1991; Anderson and Turner 1991; Jinnai et al. 1993). While it seems clear that the projections arising from the globus pallidus and those arising from the cerebellar nuclei primarily distribute to separate thalamic territories, individual thalamic nuclei receive differentially weighted inputs from these sources (Rouiller et al. 1994; Sakai et al. 1996). One explanation of these findings is that finger-like cell groupings characteristic of VPLo extend rostrally and irregularly into VLo (Asanuma et al. 1983a; Calzavara et al. 2005; Jones 2007) and may account for some of the discrepancies in the reports of the cerebellothalamic distribution. At the same time, the small foci of cerebellar labeling observed in the most rostral motor thalamus seem unlikely to be rostral extensions of VPLo (Rouiller et al. 1994; Sakai et al. 1996). Nonetheless, areas of overlapping pallidal and

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VLc VLc

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CI X VPLo VPLo CM

ZI R VLc

VLc

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CI

VLo

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X VPLo

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WGA-HRP CM

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MD

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Pc VLo ZI

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VPI ZI

BDA

Fig. 2 Line drawings of coronal sections showing the distribution of cerebellothalamic (black) and pallidothalamic projections(red) in motor thalamus. Cerebellar labeling is a result of WGA-HRP injections into the contralateral cerebellar nuclei and BDA injections were made into the internal segment of the globus pallidus (GPi). Major cytoarchitectonic delineations are shown for each thalamic level in the corner insets. In sect. 63, the cerebellar labeling is dense and patchy in VPLo and VLx and pallidal labeling is present in VLo and VLc. More posteriorly in thalamus as seen in section 87, the cerebellothalamic projections are prominent in VPLo, VLx and VLc while pallidal projections decline in VLc (From Sakai et al. (1996) Comparison of cerebellothalamic and pallidothalamic projections in the monkey (M. fuscata): a double anterograde labeling study. J Comp Neurol 368: 215–228 with permission)

cerebellar projections were rare (Sakai et al. 1996). Finally, it should be noted that VLc is a nucleus that receives a patchy and complementary pattern of labeling (Rouiller et al. 1994; Sakai et al. 1996). In this regard, it is of interest that a direct correspondence between the cerebellothalamic territory and negative calbindin immunoreactivity is found in VPLo and much of VLx (Calzavara et al. 2005). These authors found a complementary pattern of patchy cerebellar projections and areas of calbindin-poor immunoreactivity in VLc. These results suggest that calbindin immunohistochemistry may be helpful in delineating the cerebellar territory without regard to the constraints imposed by cytoarchitectonic analysis (Calzavara et al. 2005). Although the bulk of the cerebellothalamic projections target the motor thalamus, cerebellar axons also distribute to MD and the intralaminar nuclei. Dense bundles of cerebellar fibers ascend through the fields of Forel, pass through the centrum medianum (CM), and distribute to the central lateral (CL) and to the paralamellar portion of MD (Asanuma et al. 1983a, b; Rouiller et al. 1994; Percheron et al. 1996; Sakai et al. 1996; Mason et al. 2000). The distribution of cerebellothalamic fibers

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arising specifically from the ventral dentate nucleus to MD is quite limited, and very little labeling is noted in MD other than its most lateral paralamellar portion (Mason et al. 2000).

Motor Thalamic Projections to Cortex The primary target of the motor thalamus is cortex lying anterior to the central sulcus. The general topography of the thalamocortical projections has been known for some years (Kievit and Kuypers 1977), but the extent of divergence and convergence of the thalamocortical projections as well as whether cerebellum or globus pallidus is a source of afferents to those projections is not completely known. The following will review the source of thalamocortical projections to the motor and premotor areas in nonhuman primates.

Projections to MI It has long been known that the primary cortical projection of the cerebellothalamic projections is to the primary motor cortex (MI) (for review, see Jones 2007) (Fig. 3). Typically, studies use microstimulation to map the body representation within MI (cytoarchitectonic area 4) in order to identify the sites for retrograde axonal tracer injections. These studies report that thalamic projections from VPLo, VLx, and VLc project to the primary motor cortex (Schell and Strick 1984; Wiesendanger and Wiesendanger 1985; Matelli et al. 1989; Darian-Smith et al. 1990; Tokuno and Tanji 1993; Rouiller et al. 1994; Morel et al. 2005). Moreover, when these experiments are combined with anterograde tracer injections into the cerebellar nuclei, the cerebellothalamic pathway is directly demonstrated revealing that the cerebellothalamic projections coincide with MI thalamocortical projections primarily in VPLo, but with decreasing coincidence of labeling in VLx, VLc, and VLo (Rouiller et al. 1994; Sakai et al. 2002; Stepniewska et al. 2003) (Fig. 4). In addition, a generalized somatotopic organization is observed with the face represented medially and the leg laterally. The idea that cortical areas receive mixed inputs derived from multiple thalamic nuclei was first proposed by Kievit and Kuypers (1977) and later by Darian-Smith et al. (1990). However, it was also proposed that ascending information from the cerebellum and globus pallidus project via parallel and separate pathways to the thalamic nuclei which in turn project to separate motor cortical fields including MI and the supplementary motor area (SMA) (Jones 1985; Ilinsky and Kultas-Ilinsky 1987; Alexander and Crutcher 1990). These results and other similar studies used retrograde tracers to label the thalamocortical neurons and then compared the distribution of labeling with reports of pallido- and cerebellothalamic projections (Schell and Strick 1984; Darian-Smith et al. 1990; Shindo et al. 1995). However, overlapping projections arising from the cerebellar territory and pallidal territory to a single cortical field had been proposed based on single labeling (Nambu et al. 1988, 1991; Matelli et al. 1989; Darian-Smith et al. 1990; Holsapple et al. 1991; Inase and Tanji 1995; Shindo et al. 1995) and multiple labeling experiments (Rouiller et al.

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SMA Pre-SMA M1

PMdc

PMdr

PMvc PMvr

Fig. 3 Schematic drawing of the motor cortical areas shown on a dorsal view of the macaque monkey brain. The motor cortical areas include: the primary motor cortex (MI), rostral and caudal subregions of the dorsal (PMd) and ventral premotor areas (PMv), and the pre-supplementary motor (pre-SMA) and supplementary motor areas (SMA) located on the mesial surface of the hemisphere

1994; Sakai et al. 1999, 2002). These latter studies showed that MI thalamocortical and cerebellothalamic projections overlap extensively, but regions of overlapping MI thalamocortical cells with pallidothalamic projections are also noted. The regions of overlapping cerebellar and pallidal thalamocortical projections tend to occur within the border areas particularly between VPLo and VLo (Fig. 4). As noted earlier, this labeling may be due to the difficulty in distinguishing the cell sparse interdigitating fingers of VPLo (Jones 2007), but the extent to which pallidothalamic projections reach MI remains controversial. Earlier studies noted that rostral MI, including the proximal forelimb representation, primarily receives thalamic projections from VLo whereas caudal MI, lying within the rostral bank of the central sulcus and containing the distal forelimb representation, primarily receives thalamic projections from VPLo (Matelli et al. 1989; Darian-Smith et al. 1990; Tokuno and Tanji 1993). In contrast, Holsapple et al. (1991) proposed that the caudal MI within the rostral bank of the central sulcus receives input predominantly derived from the globus pallidus via VLo. A preponderance of pallidothalamocortical projections to MI sulcal cortex has not been reported elsewhere, perhaps because few studies have systematically injected the sulcal cortex. However, coincidence of pallidothalamic projections with the digit representation of MI sulcal cortex was noted in VLo using multiple labeling techniques (Stepniewska et al. 2003).

Projections to SMA and Pre-SMA Cerebellothalamic projections extend beyond MI to project to other motor cortical fields including premotor cortex and supplementary motor areas. The supplementary

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Pre-SMA VApc SMA VLo

PMdr

GPi

PMdc VLc

PMv VLx

MI

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Fig. 4 Schematic summary diagram showing the distribution of cerebellothalamic and pallidothalamic projections to motor thalamus and the thalamocortical projections to the motor cortical areas in the macaque monkey. The major input from the dentate and interpositus nuclei is to the contralateral VPLo, VLx, VLc while the major input from the internal segment of the globus pallidus (GPi) is the VLo and VApc. The motor thalamus provides primary input to the motor cortical areas: MI receives dense projections from VPLo, and also VLx and VLc, SMA receives dense input from VLo, pre-SMA receives primary input from both VApc and VLx, PMdr receives primary input from VApc and VLc while PMdc receives primary input from VApc and VLo, and PMv receives primary input from VLo and VPL. Motor cortical areas largely receive mixed and weighted input derived from GPi and cerebellum. The gradient in the projection densities is roughly indicated by the thickness of the arrows (Data from Morel et al. 2005 Divergence and convergence of thalamocortical projections to premotor and supplementary motor cortex: a multiple tracing study in the macaque monkey. Eur J Neurosci 21: 1007–1029; Sakai et al. 2002 The relationship between MI and SMA afferents and cerebellar and pallidal efferents in the macaque monkey. Somatosens Mot Res 19: 139–148; Sakai et al. 2003 Ascending inputs to the pre-supplementary motor area in the macaque monkey: cerebello- and pallido-thalamocortical projections. Thalamus Related Syst 2: 175–187 with permission)

motor area was originally thought to reside within the mesial cortex anterior to MI and posterior to the frontal granular cortex (Penfield and Welch 1949; Woolsey et al. 1952). However, the traditional SMA has been further subdivided into the rostral pre-supplementary motor area (pre-SMA) and caudal SMA based on distinctive functional and anatomical features (Matsuzaka et al. 1992; Tanji 1994; Matsuzaka and Tanji 1996; Picard and Strick 1996; Sakai et al. 2003) (Fig. 3). The SMA is microexcitable cortex but at higher current thresholds than those effective in MI. In contrast, pre-SMA is less responsive to even higher microstimulation currents. Although previous work suggested that the SMA was primarily influenced by the basal ganglia outflow (Schell and Strick 1984), other studies reported thalamic afferents arising from multiple nuclei, including those nuclei that receive cerebellar

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input (Yamamoto et al. 1984; Wiesendanger and Wiesendanger 1985; Nambu et al. 1988, 1991; Darian-Smith et al. 1990; Matelli et al. 1989, 1996; Tokuno et al. 1992). The afferent distribution of the SMA thalamocortical cells was determined using a triple labeling paradigm whereby the pallidal and cerebellar afferents were labeled using two different anterograde tracers, and the SMA thalamocortical cells were labeled using a retrograde tracer following physiological identification of the hand/ arm representation in SMA (Sakai et al. 1999). The interrelationship between the afferent sources and the retrogradely labeled neurons could be directly assessed using this paradigm. The SMA receives primarily afferents arising from VLo coincident with pallidal projections but it also receives some afferents from VLc, VLx, and VPLo, coincident with cerebellar projections (Fig. 4). Similar results were reported by Rouiller et al. (1994) based on multiple labeling methods. Because the thalamic projections to MI and SMA arise from overlapping regions, the possibility that these projections might originate from the same neuron required further study. The direct comparison of the ascending projections from the pallidal and cerebellar sources to MI and the supplementary motor area (SMA) using multiple labeling methods revealed that MI and SMA receive predominant thalamic input originating from the cerebellum and globus pallidus, respectively (Rouiller et al. 1994; Sakai et al. 2002) (Fig. 4). MI and SMA also received secondary afferent input but evidence of collateralized projections from thalamus to MI and SMA was rare (Darian-Smith et al. 1990; Rouiller et al. 1994; Shindo et al. 1995; Sakai et al. 2002; Morel et al. 2005). The projections to the pre-SMA have also been evaluated using multiple labeling techniques. The pre-SMA occupies the mesial cortex rostral to the SMA and is functionally distinct from SMA in that its neurons are responsive during movement preparation (Tanji 1994; Matsuzaka and Tanji 1996; Picard and Strick 1996) and in updating the temporal order of movement events (Shima and Tanji 1998, 2000). Using multiple labeling techniques, the pre-SMA receives ascending inputs from both the cerebellum and globus pallidus by way of the motor thalamus in both the owl monkey (Sakai et al. 2000) and macaque monkey (Sakai et al. 2003) (Fig. 4). These results were similar to those reported by Matelli and Luppino (1996) who used fluorescent tracers to retrogradely label these thalamocortical neurons. The pre-SMA inputs primarily arose from caudal VA in the pallidothalamic territory and VLx in cerebellothalamic territory.

Projections to the Premotor Cortex The premotor cortex consists of the cortex lying rostral to MI and is coincident with cytoarchitectonic area 6. The spur of the arcuate sulcus roughly divides the premotor cortex into dorsal and ventral subdivisions (Fig. 3). The dorsal premotor cortex (PMd) lies medial to the spur of the arcuate sulcus and extends as far medially as SMA while the ventral premotor cortex (PMv) lies lateral to the spur. In addition, the PMd and PMv can be further subdivided into rostral and caudal divisions. These subdivisions differ anatomically based on cytoarchitectonic and histochemical differences (Barbas and Pandya 1987; Matelli et al. 1985, 1989; Matelli and Luppino 1996; Kurata 1994; Stepniewska et al. 2007) and functionally (Kurata and Tanji

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1986; Rizzolatti et al. 1988; Preuss et al. 1996). Recently, the distribution of thalamic afferents to the premotor subdivisions has been re-evaluated using multiple labeling techniques in conjunction with quantitative methods. These analyses reveal that each premotor subdivision receives a predominant thalamic input and secondary, less dense afferents derived from multiple thalamic nuclei. The PMd receives afferents from motor thalamus including VLo, VLx, and VLc (Morel et al. 2005; Stepniewska et al. 2007) as well as VApc (Kurata 1994; Matelli and Luppino 1996; Rouiller et al. 1999; Morel et al. 2005; Stepniewska et al. 2007). A topographic shift in the distribution of thalamocortical projections is noted in comparison of the rostral and caudal PMd afferents (Fig. 4). Rostral PMd preferentially receives projections from VApc, VLc, and MD whereas caudal PMd preferentially receives projections arising from VLo (VLa in Morel et al. 2005) in the macaque monkey and VLa and VLx in the owl monkey (Stepniewska et al. 2007). Rostral and caudal sectors of PMv also receive differentially distributed afferents: rostral PMv receives predominant input from MD with less dense input from VApc, and VLo and caudal PMv receive predominant afferents from VLo and VLc (Morel et al. 2005). Others have noted significant input arising from VLx to PMv (Matelli et al. 1989; Rouiller et al. 1999; Stepniewska et al. 2007). Taken together, these data demonstrate that sectors of PM receive differentially weighted thalamic inputs. Morel and others (2005) speculated on the extent of divergence and convergence in the cortex by analyzing the degree of overlap and segregation in the thalamocortical projections. They suggest that the degree of thalamic overlap varies in the PM subdivisions with gradients of increasing projections from MD to rostral PM and from VLo and VPLo to caudal PM. To some extent, the degree of overlap in thalamus is related to the proximity of the cortical area. For example, greater overlap in thalamus was noted from adjacent cortical areas such as between rostral and caudal PMv (Morel et al. 2005), caudal PMd and SMA (Rouiller et al. 1999), and pre-SMA and rostral PMd (Rouiller et al. 1999). The thalamic inputs to the PM subdivisions cross cytoarchitectonic boundaries and arise from nuclei receiving afferent inputs from the cerebellum and the globus pallidus. The information from these sources is likely to overlap in the cortex. Since the predominant input to both VLx and VPLo originates from the cerebellum and these nuclei, in turn, provide afferents to PM subdivisions, these cortical subdivisions receive cerebellar inputs, albeit of differing strengths (Morel et al. 2005; Stepniewska et al. 2007). Similarly, since the nuclei, VApc, VLo, and VLc, all receive pallidal input and in turn, project to PM, these cortical regions also receive inputs derived from the globus pallidus. In this manner, the PM subdivisions receive mixed inputs from these sources.

Projections to Other Cortical Areas The cerebellar thalamic territory also projects to other cortical areas. The VLx gives rise to a small percentage of cells projecting to the frontal eye field (area 8) and even fewer to area 45 (Contini et al. 2010). The VLc projects to the posterior parietal

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cortex, in particular, the superior parietal lobule (Miyata and Sasaki 1983; Schmahmann and Pandya 1990). A small number of labeled cells in VLx and VLc were noted projecting to prefrontal cortical areas 9 and 46 using conventional neuroanatomical tracers (Middleton and Strick 2001). As described earlier, cerebellar afferents also distribute to the central lateral nucleus (CL) and the lateral part of MD (Fig. 2). Cells of the central lateral nucleus of the intralaminar group project to all of the motor areas and cells in lateral or paralamellar MD project to more rostral cortical areas including motor, frontal eye fields, and prefrontal cortex (Matelli et al. 1989; Darian-Smith et al. 1990; Schmahmann and Pandya 1990; Shindo et al. 1995; Matelli and Luppino 1996; Morel et al. 2005; Stepniewska et al. 2007; Contini et al. 2010).

General Topography of Projections Each motor cortical area receives differentially weighted inputs arising from the thalamic territories receiving cerebellar and pallidal afferents (Fig. 4). These inputs represent a unique mixture of afferents arising from multiple thalamic nuclei. However, there is considerable overlap in the afferent distribution to adjacent cortical areas, especially from border zones between cortical areas. A general topography corresponding to functional gradients within the motor areas has been previously noted (Matelli et al. 1989; Matelli and Luppino 1996; Rouiller et al. 1999; Morel et al. 2005). Traditional views of the motor cortical areas propose that these areas are hierarchically organized with MI involved in movement execution and the remaining motor cortical areas engaged in higher order aspects of motor control. The PMd and PMv have been associated with different roles in the selection and planning of movement (Wise et al. 1997; Hoshi and Tanji 2007), while the SMA is involved with internally generated movement sequences (Mushiake et al. 1991; Tanji 1994; Shima and Tanji 1998). The pre-SMA is hypothesized to participate in movement preparation and in updating the temporal order of movement events (Matsuzaka et al. 1992; Matsuzaka and Tanji 1996; Shima and Tanji 1998, 2000). Despite the distinctly hierarchical functions attributed to each of these areas, recent accounts suggest a modification of this view. Functional analyses of the results obtained from varying microstimulation parameters suggest that the motor cortex processes information required for activating multiple muscles and movements (Schieber 2001; Graziano 2006; Graziano and Afalo 2007). Rather than a focal somatotopic organization of hierarchically organized areas, the motor cortex contains multiple, overlapping, and fractured representations that are suggested to provide the substrate for the production of coordinated synergistic movements within a broad topography (Sanes and Donoghue 2000; Schieber 2001, 2002; Graziano 2006; Graziano and Afalo 2007). Anatomically, a distributed network of diverging and converging connections may well provide the necessary substrate (Schieber 2001; Graziano 2006; Graziano and Afalo 2007; Evrard and Craig 2008). The existence of widespread cortico-cortical projections, diverging corticospinal projections, and converging spinothalamic and cerebellothalamic afferents all have been proposed as links in

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a larger distributed network subserving flexibility in motor responses (Schieber 2001; Graziano 2006; Graziano and Afalo 2007; Evrard and Craig 2008). In addition, the differentially weighted ascending input originating from cerebellum and globus pallidus would be an important link in such a distributed network. The basal ganglia plays an important role in the acquisition of motor skills, the maintenance of motor routines, and procedural learning (Yin et al. 2009, for review, see Doyon et al. 2003). Both the cerebellum and the basal ganglia output nucleus, the globus pallidus, contribute to motor skill learning (Hikosaka 2002; Groenewegen 2003), but the mechanisms of how these structures interact is largely unknown. The differentially weighted thalamic output to the motor cortical areas may provide an important substrate for motor skill learning. Additional studies comparing the distributions of these projections to the motor cortical areas will help elucidate these mechanisms. For over a decade now, the cerebellum has been increasingly implicated in cognitive processing (Schmahmann 1996; Middleton and Strick 2001; Thach 2007; Ito 2008; Strick et al. 2009). While there is wealth of neuroimaging data in humans demonstrating a role for the cerebellum in higher order cognitive processing, the precise anatomical pathways subserving such functions remain elusive based on direct anatomical tracing methods. Cerebellar inputs largely project to MI, PM subdivisions, and pre-SMA via VPLo, VLx, and VLc. Cerebellothalamic projections distribute less densely to the VA, CL and MD, nuclei that in turn project to more rostral cortical regions including eye movement related areas such as supplementary eye field, frontal eye field, and rostral part of PMd (Shook et al. 1991; Rouiller et al. 1999; Morel et al. 2005). The cerebellar input to MD is largely confined to its lateral or paralamellar portion and projections to other parts of MD are quite sparse (Stanton 1980; Kalil 1981; Asanuma et al. 1983a; Sakai et al. 1996; Stepniewska et al. 2003). Paralamellar MD and CL project diffusely to sensorimotor cortex (for review, see Jones 2007). Since the preponderance of the cerebellar projections ultimately target premotor and motor cortical areas, it is likely that the main role of the cerebellothalamic projection system is to facilitate motor responses or action plans (see Glickstein 2007). At the same time, recent evidence suggests that prefrontal cortex may influence the motor thalamus by way of corticothalamic projections (Xiao et al. 2009), thus, providing a route for the cognitive mediation of motor plans.

Conclusions and Future Directions Tremendous progress has been made in detailing the cerebellothalamic and thalamocortical projections in nonhuman primates. The motor thalamus has been defined on the basis of newer chemoarchitectonic methods and correlated with the distribution and topography of these projections using a multitude of neuroanatomical tracing methods. Cerebellothalamic projections arise primarily from the contralateral dentate and interpositus nuclei and the fastigial nucleus bilaterally. These projections heavily distribute to VPLo with less dense projections to adjacent

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subnuclei including VLx, VLc, VLo, CL, and lateral MD. In turn, these nuclei give rise to projections to the motor cortical areas. Overall, the density of the thalamic projections to these areas varies, giving the impression that each cortical area receives differentially weighted afferents derived from the cerebellum and the globus pallidus, the second source of primary afferents of the motor thalamus. Converging input derived from the cerebellum and the globus pallidus to the motor cortical areas may provide crucial information for movement execution including motor skill learning. The thalamus occupies a pivotal position influencing cerebellar and pallidal access to the cerebral cortex but still little is known regarding the relative contributions of these structures to the overall motor network. Future studies combining multiple neuroanatomical tracers will help elucidate the details of the cortical processing of these inputs. These studies are crucial to our understanding of how motor output is influenced by ascending cerebellar and pallidal information.

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Tokuno H, Tanji J (1993) Input organization of distal and proximal forelimb areas in the monkey primary motor cortex: a retrograde double labeling study. J Comp Neurol 333:199–209 Tokuno H, Kimura M, Tanji J (1992) Pallidal inputs to thalamocortical neurons projecting to the supplementary motor area: an anterograde and retrograde double labeling study in the macaque monkey. Exp Brain Res 90:635–638 Walker AE (1938) The primate thalamus. Chicago University Press, Chicago Wiesendanger R, Wiesendanger M (1985) Cerebello-cortical linkage in the monkey as revealed by transcellular labeling with the lectin wheat germ agglutinin conjugated to the marker horseradish peroxidase. Exp Brain Res 59:105–117 Wise SP, Boussaoud D, Johnson PB, Caminiti R (1997) Premotor and parietal cortex: corticocortical connectivity and combinatorial computations. Annu Rev Neurosci 20:25–42 Woolsey CN, Settlage PH, Meyer DR, Spencer W, Pinto Hamuy T, Travis AM (1952) Patterns of localization in precentral and “supplementary” motor areas and their relation to the concept of a premotor area. Res Publ Assoc Nerv Ment Dis 30:238–264 Xiao D, Zikopoulos B, Barbas H (2009) Laminar and modular organization of prefrontal projections to multiple thalamic nuclei. Neurosci 161:1067–1081 Yamamoto T, Noda T, Miyata M, Nishimura Y (1984) Electrophysiological and morphological studies on thalamic neurons receivng entopedunculo- and cerebellothalamic projections in the cat. Brain Res 301:231–242 Yin HH, Mulcare SP, Hilário MRF, Clouse E, Holloway T, Davis MI, Hansson AC, Lovinger DM, Costa RM (2009) Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill. Nat Neurosci 12:333–341

Cerebellar Outputs in Non-human Primates: An Anatomical Perspective Using Transsynaptic Tracers

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Andreea C. Bostan and Peter L. Strick

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Output Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Macro-Architecture of Cerebro-Cerebellar Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Cerebellum Is Interconnected with the Basal Ganglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Important insights into cerebellar function can be gained from an anatomical analysis of cerebellar output. Recent studies using transsynaptic tracers in nonhuman primates demonstrate that the output of the cerebellum targets multiple nonmotor areas in the prefrontal and posterior parietal cortex, as well as the motor areas of the cerebral cortex. The projections to different neocortical areas originate from distinct output channels within the cerebellar nuclei. The neocortical area that is the main target of each output channel is a major source of input to the channel. Thus, a closed-loop circuit represents the fundamental macroarchitectural unit of cerebro-cerebellar interactions. The outputs of these circuits provide the cerebellum with the anatomical substrate to influence the control of movement and cognition. Similarly, it has been shown that discrete multisynaptic loops connect the basal ganglia with motor and nonmotor areas of the cerebral cortex. Interactions between cerebro-cerebellar and cerebro-basal ganglia loops have been thought to occur mainly at the level of the neocortex. More recently, A. C. Bostan (*) Department of Neurobiology, Center for the Neural Basis of Cognition, Systems Neuroscience Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA e-mail: [email protected] P. L. Strick Pittsburgh Veterans Affairs Medical Center, Pittsburgh, PA, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_25

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neuroanatomical studies demonstrate that the anatomical substrate exists for substantial interactions between the cerebellum and the basal ganglia in both the motor and nonmotor domains. These data, along with the revelations about cerebro-cerebellar circuitry, provide a new framework for exploring the contribution of the cerebellum to diverse aspects of behavior. Keywords

Cerebellar cortex · Rabies virus · Posterior parietal cortex · Cerebellar nucleus · Output channel

Introduction The neocortical areas that provide inputs to the cerebellum have been well established (Fig. 1) (Glickstein et al. 1985; Schmahmann 1996). On the other hand, the targets of cerebellar output are still in the process of being fully identified (Strick et al. 2009). Recent results from neuroanatomical studies using transsynaptic tracers in nonhuman primates indicate that cerebellar output targets both motor and nonmotor areas of the cerebral cortex. This feature of cerebellar output provides part of the neural substrate for the involvement of cerebellum not only in the generation and control of movement but also in nonmotor aspects of behavior. This chapter reviews new evidence about the areas of the cerebral cortex that are the target of cerebellar output. It describes the functional map that has recently been discovered within one of the major output nuclei of the cerebellum, the dentate nucleus. Furthermore, the chapter presents evidence that the fundamental unit of cerebro-cerebellar operations is a closed-loop circuit. Finally, it discusses the new anatomical evidence that the cerebellum and basal ganglia are interconnected. The classical view of cerebro-cerebellar interconnections is that the cerebellum receives information from widespread neocortical areas, including portions of the frontal, parietal, temporal, and occipital lobes (Fig. 1) (Glickstein et al. 1985; Schmahmann 1996). This information was then thought to be funneled through cerebellar circuits where it ultimately converged on the ventrolateral nucleus of the thalamus (e.g., Allen and Tsukahara 1974; Brooks and Thach 1981). The ventrolateral nucleus was believed to project to a single neocortical area, the primary motor cortex (M1). Thus, cerebellar connections with the cerebral cortex were viewed as means of collecting information from widespread regions of the cerebral cortex. The cerebellum was thought to perform a sensorimotor transformation on its inputs and convey the results to M1 for the generation and control of movement. According to this view, cerebellar output was entirely within the domain of motor control, and abnormal activity in this circuit would lead to purely motor deficits. Recent analysis of cerebellar output and function has challenged this view (e.g., Schell and Strick 1984; Middleton and Strick 1994, 1996a, b, 2000, 2001; Hoover and Strick 1999; Clower et al. 2001, 2005; Dum and Strick 2003; Kelly and Strick 2003; Akkal et al. 2007; Strick et al. 2009). It is now clear that efferents from the

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Fig. 1 Origin of projections from the cerebral cortex to the cerebellum. Top: The relative density of corticopontine neurons is indicated by the dots on the lateral and medial views of the macaque brain. Bottom: Histogram of relative density of corticopontine cells in different cytoarchitectonic areas of the monkey. Ai, As inferior and superior limbs of arcuate sulcus, respectively, CA calcarine fissure, CgS cingulate sulcus, CS central sulcus, IP intraparietal sulcus, LS lateral sulcus, Lu luneate sulcus, IO inferior occipital sulcus, PO parietal-occipital sulcus, PS principal sulcus, STS superior temporal sulcus (Adapted from Strick et al. (2009))

cerebellar nuclei project to multiple subdivisions of the ventrolateral thalamus (for a review, see Percheron et al. 1996), which, in turn, project to a myriad of neocortical areas, including regions of frontal, prefrontal, and posterior parietal cortex (Jones 1985). Thus, the outputs from the cerebellum influence more widespread regions of the cerebral cortex than previously recognized. This change in perspective is important because it provides the anatomical substrate for the output of the cerebellum to influence nonmotor as well as motor areas of the cerebral cortex. As a consequence, abnormal activity in cerebro-cerebellar circuits could lead not only to motor deficits but also to cognitive, attentional, and affective impairments. Prior neuroanatomical approaches for examining cerebro-cerebellar circuits have been hindered by a number of technical limitations. Chief among these limitations is the multisynaptic nature of these pathways and the general inability of conventional

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tracers to label more than the direct inputs and outputs of an area. To overcome these and other problems, neurotropic viruses have been used as transneuronal tracers in the central nervous system of primates (for references and a review, see Strick and Card 1992; Kelly and Strick 2000, 2003). Selected strains of virus move transneuronally in either the retrograde or anterograde direction (Zemanick et al. 1991; Kelly and Strick 2003). Thus, one can examine either the inputs to or the outputs from a site. The viruses used as tracers move from neuron to neuron exclusively at synapses, and the transneuronal transport occurs in a time-dependent fashion. Careful adjustment of the survival time after a virus injection allows for the study of neural circuits composed of two or even three synaptically connected neurons. Virus tracing has been used to examine cerebello-thalamocortical pathways to a wide variety of neocortical areas (Middleton and Strick 1994, 1996a, b, 2001; Lynch et al. 1994; Hoover and Strick 1999; Clower et al. 2001, 2005; Kelly and Strick 2003; Akkal et al. 2007) (Fig. 2).

Cerebellar Output Channels In an initial series of studies, virus was injected into physiologically defined portions of M1 and the survival time was set to label second-order neurons in the deep cerebellar nuclei (Hoover and Strick 1999). In general, cerebellar projections to M1 originate largely from neurons in the dentate nucleus (75%), although a smaller component also originates from the interpositus (25%). Several studies have focused on the organization of the dentate nucleus. The dentate nucleus is a complex threedimensional structure (Fig. 3). Results from different experiments can be displayed in a common framework on an unfolded map of the nucleus (Fig. 4) (Dum and Strick 2003). Virus transport following injections into the arm representation of M1 labeled a compact cluster of neurons in the dorsal portion of the dentate at mid-rostro-caudal levels (Figs. 2 and 3, far right panel, Fig. 4, top center panel). Virus transport from the leg representation of M1 labeled neurons in the rostral pole of the dorsal dentate (Figs. 2 and 4, top left panel), whereas virus transport from the face representation labeled neurons at caudal levels of the dorsal dentate (Figs. 2 and 4, top right panel). Clearly, each neocortical area receives input from a spatially separate set of neurons in the dentate, which has been termed an output channel (Middleton and Strick 1997). The rostral to caudal sequence of output channels to the leg, arm, and face representations in M1 (Fig. 4, top panels, Fig. 5) corresponds well with the somatotopic organization of the dentate previously proposed on the basis of physiological studies (e.g., Allen et al. 1978; Stanton 1980; Rispal-Padel et al. 1982; Asanuma et al. 1983; Thach et al. 1993). The region of the dentate that contains neurons that project to M1 occupies only 30% of the nucleus (Hoover and Strick 1999; Dum and Strick 2003). This implies that a substantial portion of the dentate projects to neocortical targets other than M1. To test this proposal and define the neocortical targets of the unlabeled regions of the

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Fig. 2 Targets of cerebellar output. Red labels indicate areas of the cerebral cortex that are the target of cerebellar output. Blue labels indicate areas that are not the target of cerebellar output. These areas are indicated on lateral and medial views of the cebus monkey brain. The numbers refer to cytoarchitectonic areas. AIP anterior intraparietal area, AS arcuate sulcus, CgS cingulate sulcus, FEF frontal eye field, IP intraparietal sulcus, LS lateral sulcus, Lu lunate sulcus, M1 face, arm, and leg areas of the primary motor cortex, PMd arm arm area of the dorsal premotor area, PMv arm arm area of the ventral premotor area, PrePMd predorsal premotor area, PreSMA presupplementary motor area, PS principal sulcus, SMA arm arm area of the supplementary motor area, ST superior temporal sulcus, TE area of inferotemporal cortex (Adapted from Strick et al. (2009))

dentate, virus was injected into selected premotor, prefrontal, and posterior parietal areas of the cortex (Fig. 2). Virus transport from the arm representations of the ventral premotor area (PMv) and the supplementary motor area (SMA) provided evidence that both neocortical areas are the targets of cerebellar output (Fig. 2) (Middleton and Strick 1997; Akkal et al. 2007). The output channels to these premotor areas are located in the same region of the dentate that contains the output channel to arm M1 (Figs. 3 and 5). It has been hypothesized that the clustering of output channels to M1 and the premotor areas in the dorsal region of the dentate creates a motor domain within the nucleus (Fig. 5) (Dum and Strick 2003). It has been shown that the dorsal premotor cortex (PMd) also receives inputs from the motor territory of the dentate (Hashimoto et al. 2010). Interestingly, the output channels to the arm representations

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Fig. 3 Output channels in the dentate. The dots on representative coronal sections show the location of dentate neurons that project to a specific area of the cerebral cortex in the cebus monkey. The neocortical target is indicated above each section. Abbreviations are according to Fig. 2 (M1 primary motor cortex, PMv ventral premotor area). D dorsal, M medial (Adapted from Middleton and Strick (1996b))

of M1, PMv, PMd, and SMA appear to be in register within the dentate. This raises the possibility that the nucleus contains a single integrated map of the body within the motor domain. Virus transport following injections into prefrontal cortex revealed that some subfields are the target of dentate output, whereas others are not (Middleton and Strick 1994, 2001). Dentate output channels project to areas 9 m, 9 l, and 46d, but not to areas 12 and 46v (Figs. 2–5). Importantly, the extent of the dentate that is occupied by an output channel to a specific area of prefrontal cortex is comparable to that occupied by an output channel to a neocortical motor area (Fig. 4). Thus, it is likely that the signal from the dentate to prefrontal cortex is as important as its signal to one of the neocortical motor areas. In addition, dentate output channels to areas of prefrontal cortex are located in a different region of the nucleus than the output channels to the neocortical motor areas. The output channels to prefrontal cortex are clustered together in a ventral region of the nucleus that is entirely outside the motor domain. The output channels to prefrontal cortex are also rostral to the output channel that targets the frontal eye field (Lynch et al. 1994). Although the presupplementary motor area (PreSMA) has traditionally been included with the motor areas of the frontal lobe, evidence indicates that it should be considered a region of prefrontal cortex (for reviews, see Picard and Strick 2001; Akkal et al. 2007). In support of this proposal, virus transport from the PreSMA labeled an output channel in the ventral dentate where the output channels to areas 9 and 46 are located (Figs. 2 and 4, bottom, Fig. 5). This result illustrates that the topographic arrangement of output channels in the dentate does not mirror the arrangement of their targets in the cerebral cortex. For example, the PreSMA is adjacent to the SMA on the medial surface of the hemisphere (Fig. 2), but the output channels to the two neocortical areas are spatially separated from one another in the dentate (Fig. 5). Thus, the topographic arrangement of output channels in the dentate appears to reflect functional relationships between neocortical areas rather than the spatial relationships among them.

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Fig. 4 Unfolded maps of the dentate: output channels to different areas of the cerebral cortex in the cebus monkey. Top panels: Somatotopic organization of output channels to leg, arm, and face M1 in the dorsal dentate. Bottom panels: Ventral location of output channels to prefrontal cortex. The key below each diagram indicates the density of neurons in bins through the nucleus. Rostral is to the left. Abbreviations are according to Fig. 1 (M1 primary motor cortex, PreSMA presupplementary motor area) (Adapted from Dum and Strick (2003) (which includes a detailed description of the unfolding method))

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Fig. 5 Summary map of dentate topography. The lettering on the unfolded map indicates the neocortical target of different output channels in the cebus monkey. The location of different output channels divides the dentate into motor and nonmotor domains. Staining for monoclonal antibody 8B3 is most intense in the nonmotor domain. The dashed line marks the limits of intense staining for this antibody. The designation of the region marked by “?” is unclear. Abbreviations as in Fig. 2 (FEF frontal eye field, M1 primary motor cortex, PMv ventral premotor area, PreSMA presupplementary motor area, SMA supplementary motor area) (Adapted from Dum and Strick (2003) and Akkal et al. (2007))

Virus transport from regions of posterior parietal cortex demonstrated that some of its subfields are also the target of output channels located in the dentate (Figs. 2 and 5) (Clower et al. 2001, 2005). For example, area 7b, which in the cebus monkey is located laterally in the intraparietal sulcus, is the target of an output channel located ventrally in the caudal pole of the dentate (Fig. 5). A second region of posterior parietal cortex, the anterior intraparietal area (AIP), receives a focal projection from a small cluster of neurons that is located dorsally in the dentate at mid-rostro-caudal levels. In addition, the AIP receives a broadly distributed projection from neurons that are scattered in dentate regions that contain output channels to M1, the PMv, and perhaps other premotor areas. This creates a unique situation in which AIP may receive a sample of the dentate output that is streaming to motor areas in the frontal lobe, as well as input from its own separate output channel. However, area 7a, which is located on the inferior parietal lobule (Fig. 2), does not receive substantial input from the dentate or other cerebellar nuclei (Clower et al. 2001). There also is evidence that the medial intraparietal area (MIP) and ventral lateral intraparietal area (LIPv) are the targets of cerebellar output from the deep cerebellar nuclei (Prevosto et al. 2010). Currently, the information about cerebellar

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projections to other areas in the posterior parietal cortex is complex and incomplete. It is clear, however, that multiple areas of the posterior parietal cortex are the targets of output channels from the ventral dentate. Maps from individual experiments have been coalesced into a single summary diagram where the average location of each output channel is indicated (Fig. 5). This summary diagram emphasizes several notable features about the topographic organization of the dentate. A sizeable portion of the nucleus projects to parts of the prefrontal and posterior parietal cortex. The output channels to prefrontal and posterior parietal areas are clustered in a ventral and caudal region of the nucleus. Consequently, these output channels are spatially segregated from those in the dorsal dentate that target motor areas of the cortex. Thus, the dentate appears to be spatially subdivided into separate motor and nonmotor domains that focus on functionally distinct neocortical systems. Another feature emphasized by the summary diagram is that the neocortical targets for large portions of the dentate remain to be determined. The division of the dentate into separate motor and nonmotor domains is reinforced by underlying molecular gradients within the nucleus (Fortin et al. 1998; Pimenta et al. 2001; Dum et al. 2002; Akkal et al. 2007). Fortin et al. (1998) reported that immuno-staining for two calcium-binding proteins, calretinin and parvalbumin, is greatest in ventral regions of the squirrel monkey dentate. A monoclonal antibody, 8B3, which recognizes a chondroitin sulfate proteoglycan on subpopulations of neurons, also differentially stains the dentate in cebus monkeys and macaques (Pimenta et al. 2001; Dum et al. 2002; Akkal et al. 2007). Immunoreactivity for 8B3 is most intense in ventral regions of the dentate that project to prefrontal and posterior parietal areas of cortex. In contrast, antibody staining is least intense in the dorsal regions of the nucleus that project to the neocortical motor areas. These observations suggest that 8B3 recognizes a significant portion of the nonmotor domain within the dentate. Measurements indicate that approximately 40% of the nucleus is intensely stained by 8B3. This analysis does not include the caudal portion of the dentate (marked by a “?” in Fig. 5) because this region does not stain intensely for 8B3 and its neocortical target remains to be determined. However, based on its location, it is likely that this caudal region projects to a nonmotor area of the cerebral cortex. If this is the case, then the nonmotor domain of the dentate may represent as much as 50% of the nucleus in the cebus monkey. In the human, it has long been recognized that the dentate is composed of a dorsal, microgyric portion and a ventral, macrogyric portion (for references and illustration, see Voogd 2003). Compared with the microgyric dentate, the macrogyric dentate is reported to (a) develop later, (b) have smaller cells, (c) display a selective vulnerability in cases of neocerebellar atrophy, and (d) have a higher iron content. This last observation suggests that molecular gradients may exist within the human dentate as they do in the monkey dentate; however, this possibility remains to be tested. Comparative studies suggest that the dentate has expanded in great apes and humans relative to the other cerebellar nuclei (Matano et al. 1985). Furthermore, most of this increase appears to be due to an expansion in the relative size of the ventral half of the dentate (Matano 2001). This observation implies that the nonmotor functions of the dentate grow in importance in great apes and humans.

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Macro-Architecture of Cerebro-Cerebellar Loops The neocortical areas that are the target of cerebellar output also project via the pons to the cerebellar cortex (Glickstein et al. 1985; Schmahmann 1996). This observation suggests that cerebro-cerebellar connections may form a closed-loop circuit. This concept has been tested for a representative motor area (the arm area of M1) and a nonmotor area (area 46 in the prefrontal cortex) (Kelly and Strick 2003). The anatomical evidence indicates that a specific region of the cerebellar cortex both receives input from and projects to the same area of the cerebral cortex. Retrograde transneuronal transport of rabies virus was used to define the Purkinje cells in cerebellar cortex that project to M1 or to area 46. The arm area of M1

Fig. 6 Regions of cerebellar cortex that project to areas of cerebral cortex. The black dots on the flattened surface maps of the cerebellar cortex indicate the location of Purkinje cells that project to the arm area of M1 (left panel) or to area 46 (right panel) in the cebus monkey. The Purkinje cells that project to M1 are located in lobules that are separate from those that project to area 46. Nomenclature and abbreviations are according to Larsell (1970) (Adapted from Kelly and Strick (2003))

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receives input from Purkinje cells located mainly in lobules IV–VI of the cerebellar cortex (Fig. 6, left panel). In contrast, area 46 receives input from Purkinje cells located mainly in Crus II of the ansiform lobule (Fig. 6, right panel). There is no evidence of overlap between the two systems. Thus, the two areas of the cerebral cortex are the targets of output from Purkinje cells that are located in separate regions of the cerebellar cortex. Clearly, the separation of motor and nonmotor functions seen in the dentate nucleus extends to the level of the cerebellar cortex. In separate experiments, anterograde transneuronal transport of herpes virus was used to define the granule cells in cerebellar cortex that receive input from M1 or from area 46. The arm area of M1 projects to granule cells located mainly in lobules IV–VI, whereas area 46 projects to granule cells mainly in Crus II. Again, each cerebral cortical area projects to granule cells that are located in a separate region of the cerebellar cortex. Moreover, these findings indicate that the regions of the cerebellar cortex that receive input from M1 are the same as those that project to M1. Similarly, the regions of the cerebellar cortex that receive input from area 46 are the same as those that project to area 46. Thus, M1 and area 46 form separate, closedloop circuits with different regions of the cerebellar cortex (Fig. 7). Altogether, these observations suggest that multiple closed loop circuits represent a fundamental macro-architectural feature of cerebro-cerebellar interactions. There are a number of important functional implications to these results. They suggest that the cerebellar cortex is not functionally homogeneous. Instead, the results imply that cerebellar cortex contains localized regions that are interconnected with specific motor or nonmotor areas of the cerebral cortex. In fact, it has been hypothesized that the map of function in the cerebellar cortex is likely to be as rich and complex as that in the cerebral cortex (Kelly and Strick 2003). As a consequence, global dysfunction of the cerebellar cortex can cause wide-ranging effects on behavior (e.g., Schmahmann 2004). However, localized dysfunction of a portion of the cerebellar cortex can lead to more limited deficits, which may be motor or nonmotor depending on the specific site of the cerebellar abnormality (e.g., Fiez et al. 1992; Schmahmann and Sherman 1998; Allen and Courchesne 2003; Gottwald et al. 2004). Thus, precisely defining the location of a lesion, a site of activation, or a recording site is as important for studies of the cerebellum as it is for studies of the cerebral cortex. As noted above, the neocortical targets for substantial portions of the dentate remain unidentified. In addition, fastigial and interpositus nuclei send efferents to the thalamus (Batton et al. 1977; Stanton 1980; Kalil 1981; Asanuma et al. 1983), and the neocortical targets of these deep nuclei remain to be fully determined. The closed-loop architecture described above enables us to make some predictions about additional neocortical targets of cerebellar output (Middleton and Strick 1998; Dum and Strick 2003; Kelly and Strick 2003). If closed-loop circuits reflect a general rule, then all of the areas of cerebral cortex that project to the cerebellum are the targets of cerebellar output. In addition to the neocortical areas that have already been investigated, the cerebellum receives input from a wide variety of higher-order, nonmotor areas. This includes areas of extrastriate cortex, posterior parietal cortex, cingulate cortex, and the parahippocampal gyrus on the medial

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Fig. 7 Closed-loop circuits link the cerebellum with the cerebral cortex. Two topographically separate closed-loop circuits are illustrated. One interconnects the cerebellum with M1 and the other interconnects the cerebellum with area 46. In each loop, the neocortical area projects to a specific site in the pontine nuclei (PN), which then innervates a distinct region of the cerebellar cortex (CBM). Similarly, a portion of the dentate nucleus (DN) projects to a distinct region of the thalamus, which then innervates a specific neocortical area. Note that the neocortical area, which is the major source of input to a circuit, is the major target of output from the circuit. CBM cerebellar cortex, DN dentate, PN pontine nuclei, TH subdivisions of the thalamus (Adapted from Strick et al. (2009))

surface of the hemisphere (Fig. 1) (Brodal 1978; Wiesendanger et al. 1979; Vilensky and van Hoesen 1981; Leichnetz et al. 1984; Glickstein et al. 1985; Schmahmann and Pandya 1991, 1993, 1997). If some or all of these areas turn out to be cerebellar targets, then the full extent of cerebellar influence over nonmotor areas of the cerebral cortex is remarkable and much larger than previously suspected. In discussing the neural substrate for a cerebellar influence over nonmotor functions, it is important to note the longstanding notion that the cerebellum is interconnected with the limbic system. Cerebellar stimulation can alter limbic function and elicit behaviors like sham rage, predatory attack, grooming, and eating (e.g., Zanchetti and Zoccolini 1954; Berntson et al. 1973; Reis et al. 1973). Cerebellar lesions can tame aggressive monkeys without creating gross motor abnormalities (Peters and Monjan 1971; Berman 1997). Classic electrophysiological evidence suggests that cerebellar stimulation, especially in portions of the fastigial nucleus and associated regions of vermal cortex, can evoke responses at limbic sites, including the cingulate cortex and amygdala (e.g., Anand et al. 1959; Snider and Maiti 1976). The major weakness in the cerebello-limbic hypothesis is the absence of a clear anatomical substrate that links the output of the cerebellum, and especially the fastigial nucleus, with limbic sites such as the amygdala. Although neuroanatomical evidence indicates that the deep cerebellar nuclei are interconnected with the hypothalamus (Haines et al. 1990), these connections do not appear sufficient to mediate all of the behavioral effects evoked by cerebellar stimulation. Thus, the circuits that link the output of the cerebellar nuclei with regions of the limbic system need to be explored using modern neuroanatomical methods.

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The Cerebellum Is Interconnected with the Basal Ganglia The loops that link the cerebellum with the cerebral cortex have traditionally been considered to be anatomically and functionally distinct from those that link the basal ganglia with the cerebral cortex (Doya 2000; Graybiel 2005). As the projections from the cerebellum and basal ganglia to the cerebral cortex are relayed through distinct thalamic nuclei (Percheron et al. 1996; Sakai et al. 1996), any interactions between cortico-cerebellar and cortico-basal ganglia loops were thought to occur primarily at the neocortical level. Results from recent anatomical experiments challenge this perspective and provide evidence for disynaptic pathways that link the cerebellum with the basal ganglia more directly. To explore whether the cerebellum projects to the basal ganglia, rabies virus was injected into a region of the putamen. The injection sites were localized largely to the sensorimotor territory of the striatum (Parent and Hazrati 1995a). The virus went through two stages of transport: retrograde transport to first-order neurons in the thalamus that innervate the injection site and then, retrograde transneuronal transport to second-order neurons in the deep cerebellar nuclei that innervate the first-order neurons (Fig. 8). The neurons in the cerebellar nuclei that were labeled by virus transport were located largely in the dentate nucleus. Thus, a major output of cerebellar processing, the dentate, projects via the thalamus to an input stage of basal ganglia processing, the putamen. In another series of experiments, rabies virus was injected into the external segment of the globus pallidus (GPe). The virus went through three stages of transport: retrograde transport of the virus from the injection site to first-order neurons in the striatum, retrograde transneuronal transport from these first-order neurons to second-order neurons in the thalamus, and retrograde transneuronal transport from the second-order neurons in the thalamus to third-order neurons in the deep cerebellar nuclei. Most of the labeled neurons in the cerebellar nuclei were confined to the dentate (Fig. 8). Thus, not only does the output from the cerebellum influence the striatum, but the target of this influence includes striatal neurons in the so-called indirect pathway which projects to GPe (e.g., DeLong and Wichmann 2007). The injections of rabies virus into GPe involved two different regions of the nucleus. The injection in one animal labeled neurons primarily in ventral and caudal regions of dentate. The injection site in the other animal was placed approximately 1 mm caudally in GPe and labeled neurons in more dorsal regions of dentate. These observations suggest that the projection from the dentate to the basal ganglia is topographically organized. Virus transport from the basal ganglia labeled neurons in both the motor and nonmotor domains of the dentate (Hoshi et al. 2005). These observations suggest that the cerebellar projection to the input stage of basal ganglia processing influences motor and nonmotor aspects of basal ganglia function. To explore whether the basal ganglia project to the cerebellum, rabies virus was injected into selected sites within the cerebellar cortex. The virus went through two stages of transport: retrograde transport of the virus from the injection site to firstorder neurons in the pontine nuclei, and then, retrograde transneuronal transport

Fig. 8 Experimental paradigms and circuits interconnecting the cerebellum and basal ganglia: The left panel depicts the experimental paradigm and results from Hoshi et al. (2005), describing cerebellar output to the basal ganglia (orange circuit). Rabies virus was injected into the striatum. The virus went through two stages of transport: retrograde transport to first-order neurons in the thalamus that innervate the injection site and then, retrograde transneuronal transport to second-order neurons in the dentate nucleus (DN) that innervate the first-order neurons. Striatal neurons that receive cerebellar inputs include neurons in the “indirect” pathway that send projections to the external globus pallidum (GPe). The right panel of the figure depicts the experimental paradigm and results from Bostan et al. (2010), describing basal ganglia output to the cerebellum (purple circuit). Rabies virus was injected into the cerebellar cortex. The virus went through two stages of transport: retrograde transport to first-order neurons in the pontine nuclei (PN) that innervate the injection site and then, retrograde transneuronal transport to second-order neurons in the subthalamic nucleus (STN) that innervate the first-order neurons. These interconnections enable two-way communication between the basal ganglia and the cerebellum. Each of these subcortical structures has separate parallel interconnections with the cerebral cortex (up and down large black arrows). The small black arrows in both panels indicate the direction of virus transport. DN dentate nucleus, GPe external segment of the globus pallidus, GPi internal segment of the globus pallidus, PN pontine nuclei, STN subthalamic nucleus (Adapted from Bostan and Strick (2010))

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from these first-order neurons to second-order neurons in the subthalamic nucleus (STN) of the basal ganglia (Figs. 8 and 9). Rabies virus injections were placed in two areas within the hemispheric expansion of cerebellar lobule VII: the posterior aspects of Crus II (Crus IIp) and the hemispheric lobule VIIB (HVIIB). In all of these experiments, virus transport labeled substantial number of second-order neurons in the STN (Fig. 9). The second-order neurons labeled from virus injections into Crus IIp and HVIIB differed in their rostro-caudal and dorso-ventral distributions within the STN. The Crus IIp injections labeled larger numbers of neurons in ventromedial portions of rostral STN, whereas the HVIIB injections labeled larger numbers of neurons in the dorsal aspects of caudal STN (Fig. 9). Thus, a disynaptic connection links the STN with cerebellar cortex and this connection is topographically organized. The STN can be subdivided into sensorimotor, associative, and limbic territories based on its interconnections with regions of the globus pallidus and the ventral pallidum (Fig. 9) (Parent and Hazrati 1995b; Joel and Weiner 1997; Hamani et al. 2004). The results from rabies virus injections into cerebellar cortex provide evidence that the projections from the STN to the cerebellar cortex originate from all three of its functional subdivisions. Specifically, most of the STN neurons that project to Crus IIp were found in the associative territory, in regions that receive substantial inputs from the frontal eye fields and regions of the prefrontal cortex (Fig. 9) (Monakow et al. 1978; Stanton et al. 1988; Inase et al. 1999; Kelly and Strick 2004). In contrast, most of the STN neurons that project to HVIIB were found in the sensorimotor territory, in regions that receive substantial inputs from the primary motor cortex and premotor areas of the frontal lobe (Fig. 9) (Monakow et al. 1978; Nambu et al. 1996, 1997; Inase et al. 1999; Kelly and Strick 2004). Therefore, the anatomical substrate exists for both motor and nonmotor aspects of basal ganglia processing to influence cerebellar function. The results from the transsynaptic tracer studies reveal the anatomical substrate for two-way communication between the cerebellum and the basal ganglia in both the motor and nonmotor domains. One prediction from these findings is that activity in one of these major subcortical systems may directly affect the function of the other. Similarly, the interconnections between the two structures may enable abnormal activity at one site to propagate to the other. Such interactions between the cerebellum and the basal ganglia are likely to have important implications for motor and nonmotor functions. They supply a framework for understanding cerebellar contributions to disorders such as Parkinson’s disease and dystonia that have traditionally been considered “basal ganglia disorders” (for a review, see Bostan and Strick 2010). Furthermore, the anatomical connections between the cerebellum and the basal ganglia provide a potential explanation for the presence of cerebellar involvement in studies that were explicitly designed to study the normal functions of the basal ganglia. For example, several imaging studies have examined whether regions of the basal ganglia and related neocortical areas display functional activation consistent with their involvement in temporal difference models of reward-related learning (O’Doherty et al. 2003; Seymour et al. 2004). It is noteworthy that robust cerebellar activation was present in these

696 Fig. 9 STN projection to the cerebellar hemisphere: (a) Histogram of the rostrocaudal distribution of secondorder neurons labeled in the STN by retrograde transport of virus from Crus IIp (red bars) and HVIIB (blue bars). Missing bars correspond to missing sections. (b) Charts of labeled neurons in STN after rabies virus injections into Crus IIp (red dots) and HVIIB (blue dots) are overlapped to illustrate the topographic differences in distribution of STN second-order neurons in the two cases. (c) Schematic representation of STN organization, according to the tripartite functional subdivisions of the basal ganglia (Parent and Hazrati 1995b; Joel and Weiner 1997; Hamani et al. 2004). (d) Schematic summary of the known connections between STN and areas of the cerebral cortex. C caudal, D dorsal, M medial, STN subthalamic nucleus (Adapted from Bostan et al. (2010))

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experiments along with activation in the dorsal and ventral striatum. The disynaptic connection between the cerebellum and the basal ganglia provide an anatomical substrate for reward-related signals in the basal ganglia to influence cerebellar function during learning, and vice versa. Thus, the two subcortical structures may be linked together to form an integrated network. Future work is needed to elucidate the functional characteristics of this network.

Summary and Conclusions The dominant view of cerebellar function over the past century has been that it is concerned with the coordination and control of motor activity through its connections with M1 (Brooks and Thach 1981). It is now apparent that a significant portion of the output of the cerebellum projects to nonmotor areas of the cerebral cortex, including regions of prefrontal and posterior parietal cortex. Thus, the anatomical substrate exists for cerebellar output to influence the cognitive and visuospatial computations performed in prefrontal and posterior parietal cortex (Clower et al. 2001, 2005; Middleton and Strick 2001). Furthermore, it has been shown that there are significant interconnections between the cerebellum and the basal ganglia in both the motor and nonmotor domains. Thus, the anatomical substrate exists for cerebellar output to influence the basal ganglia, and vice versa. As a corollary, abnormalities in cerebellar structure and function have the potential to produce multiple motor and nonmotor deficits by affecting various neocortical areas and subregions of the basal ganglia. The output to nonmotor areas of the cerebral cortex and basal ganglia originates specifically from a ventral portion of the dentate. This nonmotor region of the dentate is recognized by several molecular markers. Several authors have argued that ventral dentate and related regions of the cerebellar hemispheres are selectively enlarged in great apes and humans (Leiner et al. 1991; Matano 2001). Indeed, the enlargement of the ventral dentate in humans is thought to parallel the enlargement of prefrontal cortex. These observations have led to the proposal that the dentate participation in nonmotor functions may be especially prominent in humans (e.g., Leiner et al. 1991; Schmahmann and Sherman 1998). In recent years, concepts about cerebellar structure and function have changed radically. Not only is the cerebellum informed by neocortical information from multiple domains, but cerebellar output is directed at a variety of neocortical regions. As a consequence the output from the cerebellum can impact not only the generation and control of movement, but also cognition and affect. The anatomical evidence that the cerebellum exerts an influence over nonmotor function is complemented by results from neuroimaging studies and by the analysis of the deficits that accompany cerebellar lesions. Thus, it has become clear that the adaptive plasticity that the cerebellum provides for the generation and control of movement is also available for cognition and affect.

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Delineation of Cerebrocerebellar Networks with MRI Measures of Functional and Structural Connectivity

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Christophe Habas, William R. Shirer, and Michael D. Greicius

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional Connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ROI-Based fcMRI of the Dentate Nucleus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ROI-Based fcMRI of the Cerebellar Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ROI-Based fcMRI of the Cerebral Cortex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ICA fcMRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tractography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In humans, resting-state functional connectivity MRI (fcMRI) allows precise in vivo delineation of the neocerebellum’s participation in well-segregated, nonmotor intrinsic connectivity networks (ICNs). These data reveal that the neocerebellum participates in several ICNs, including the default mode network (lobule IX), the salience network (lobule VI), and the right and left executive networks (crus I and II). Additionally, fcMRI permits an anatomical parcellation of the neocerebellum based on its specific functional links with the associative cortex. Lobules V, VII, IX, and especially crus I and II constitute a supramodal cognitive zone specifically interconnected with prefrontal, parietal, and cingulate

C. Habas (*) Service de NeuroImagerie, CHNO des XV–XX, Université Pierre et Marie Curie, Paris, France e-mail: [email protected] W. R. Shirer · M. D. Greicius Department of Neurology and Neurological Sciences, Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Stanford University School of Medicine, Stanford, CA, USA e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_26

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neocortices. Structural connectivity using DTI-based tractography complements fcMRI data and confirms anatomical connections between the dentate nucleus, thalamus, and associative cortices. Taken together, these results support the theory that specific neocerebellar subregions are key nodes in parallel, multisynaptic, closed-loop circuits involved in executive, mnemonic, and affective functions. Keywords

Cerebellum · Cerebral cortex · Thalamus · Dentate nucleus · Tractography · fMRI · Resting-state · Functional connectivity · Closed-loop circuits · Intrinsically connected network

Introduction In primates, the cerebrocerebellar system is organized into discrete, parallel, multisynaptic, closed-loop circuits (Strick et al. 2009). A common gross anatomical connectivity pattern is shared by all these circuits. The cerebral cortex selectively projects via the pontine nuclei (PN) to the contralateral deep cerebellar nuclei, mainly the dentate nuclei (DN), and to the associated cerebellar cortex. The DN, in turn, send projections to the cerebral cortex via the contralateral thalamus (Vincent et al. 2003; Nieuwenhuys et al. 2007). These cerebro-ponto-cerebello-thalamocerebral networks specifically and differentially influence motor, premotor, and association cortices (Middleton and Strick 1997; Schmahmann and Pandya 1997). For instance, tracing methods demonstrate that dorsal, lateral, and ventral parts of the DN are specifically connected with frontal motor, premotor, and prefrontal cognitive regions, respectively (Middleton and Strick 2001; Dum and Strick 2003; Akkal et al. 2007) (Fig. 1). Moreover, motor areas preferentially connect with the anterior cerebellar lobe (lobules I–V) and lobule VIII (second cerebellar homunculus), whereas executive and limbic areas are mostly connected with the posterior lobe (lobules VI and VII), which is densely interconnected with the DN. Moreover, the vermis of lobules VB–VIIIB receives afferents arising from several motor areas, including M1, supplementary motor area, and motor cingulate cortex (Coffman et al. 2011), and the neocerebellum and striatum were interconnected (Hoshi et al. 2005; Bostan et al. 2010). More precisely, DN projects through the thalamus to the striatum and to the external portion of the globus pallidus, while the subthalamic nucleus projects via the pontine nuclei to the cerebellar cortex of crus II and of lobule VIIB. From apes to humans, the telencephalization process is accompanied by an increasing number of nonmotor cerebral afferents reaching the neocerebellum (lobules VI and VII) (MacLeod et al. 2003; Whiting and Barton 2003). It can therefore be inferred that in humans, the neocerebellum contributes to parallel associative cerebrocerebellar subsystems involved in various aspects of cognition and emotion (Schmahmann 2004). The hypothesis concerning topographic arrangement of motor

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Fig. 1 Input and output organization of the cerebellar cortex (a) and dentate nuclei, the output cerebellar channel, (b) in the primate cortex as revealed by transneuronal tracers. (a1) Projections from Purkinje cells of the cerebellar cortex to the motor and association prefrontal cortices. (a2) Projections from the motor and prefrontal cortices to the granule cells of the cerebellar cortex. (b1) Dentate regions connected with the motor and association cortices. (b2) Cortical areas targeted by dentato-thalamic projections. (b3) Thalamic nuclei relaying dentate output to motor and association cortices. (From Dum and Strick 2003; with authors’ permission)

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and nonmotor function in the cerebellum was proposed by Schmahmann (1991, 2004) who regarded the cerebellum as a general modulator of cerebral activity, with the anterior and posterior cerebellum supporting and refining motor and cognitive performance, respectively. In support of this view, neuroimaging studies have shown specific cerebellar activation during emotion, language, working memory, and executive function (reviewed in: Stoodley and Schmahmann 2008), while clinical data have substantiated several but sometimes variable, cognitive, and affective impairments in patients suffering from focal cerebellar lesions (Schmahmann and Shermann 1998; Levisohn et al. 2000; Tedesco et al. 2011). Despite evidence from functional imaging and lesion studies, cerebellar involvement in cognition remains a matter of debate. For instance, some studies failed to find significant attentional or semantic impairment in cerebellar patients (Helmuth et al. 1997; Thier et al. 1999; Haarmeier and Thier 2007). Furthermore, in chronic patients, standard neuropsychological tests often turn up only minor (if any) cognitive impairments even though motor deficits are readily detected. These inconsistencies in cognitive impairments could be attributed to several factors, such as compensation for cerebellar disorders by unaffected cerebellar and cerebral regions or stronger involvement of the cerebellum during “early cognitive development rather than during cognitive performance in adulthood” (Timmann and Daum 2010). However, until recently, the nonmotor, probably genetically prewired cerebrocerebellar circuits subserving these cognitive and emotional functions could not be directly and completely identified in humans because of two limitations. First, the gold standard histological tracing methods used in animals cannot be applied to humans. Second, standard fMRI studies using the general linear model only discriminate a limited number of highly task-specific brain areas whose blood oxygenation level-dependent (BOLD) signal time series closely mimics the temporal model of the experimental task (van Dijk et al. 2010). Thus, in those cases where, for example, a cerebellar region’s BOLD signal displays a complex or subthreshold relation to the task waveform, fMRI may underestimate the number of nodes comprising a task-specific network. Recently, two complementary MRI methods have been developed which overcome these limitations and allow for functional and structural identification of large-scale brain networks: resting-state functional connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) tractography. fcMRI relies on temporal correlations between spontaneous low-frequency (0.01–0.1 Hz) fluctuations of the BOLD signal between spatially distinct but functionally related cortical and subcortical regions (Beckmann et al. 2005; Fox and Raichle 2007). Regions with synchronous spontaneous activity constitute intrinsic connectivity networks (ICNs) and may be linked by mono- or polysynaptic pathways (Greicius et al. 2008; Vincent et al. 2003). The degree to which these spontaneous fMRI signal fluctuations reflect ongoing conscious processing rather than, for example, nonconscious rhythmic waves of cortical excitability is a matter of continuing debate. Generally, two methods are used to extract these ICNs from raw fcMRI data. First, independent component analysis (ICA) is an exploratory, model-free, data-driven statistical method, which transforms the whole resting-state dataset into maximally independent spatial components

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(Beckmann and Smith 2004). Each component consists of a spatial map and its associated time series. In a typical ICA of an 8-min resting-state fMRI dataset, there may be 40 components computed, of which 10–15 may represent genuine ICNs, based on their resemblance to well-characterized task activation networks. The remaining 25–30 represent various noise sources that can also result in correlated BOLD signal fluctuations. The second method uses a region of interest (ROI) as a seed for a whole-brain correlation analysis. That is, the mean (or major Eigen) time series of an ROI is extracted and used as a regressor to search the brain for other voxels whose time series is significantly correlated with the ROI. This results in a map of functional connectivity to the ROI. The ICNs derived from resting-state fMRI studies have been shown to overlap to a large degree with maps of structural connectivity derived from DTI tractography analyses (Skudlarski et al. 2008; Greicius et al. 2009; van den Heuvel et al. 2009). Therefore, fcMRI identifies functionally related areas belonging to a common specialized structural network, whose anatomical architecture can only be established by tractography (within the limits of its spatial resolution and of its ability to detect fiber crossings). However, it is noteworthy that despite a strong correlation between functional and structural connectivity, especially concerning the DMN, topography of ICNs can be influenced by previous or ongoing cognitive processing (Hasson et al. 2009; Shirer et al. 2011) and can exhibit variability between sessions and individuals (Honey et al. 2009). Thus, ICNs may represent polysynaptic circuits and may continually reconfigure around the underlying anatomical skeleton (Honey et al. 2009). Resting-state connectivity of the cerebellar system has successfully been studied with both ROI-based and ICA-based methods. The ROI-based method was applied to the cerebellar cortex in order to delineate cerebellar subregions preferentially associated with the dentate nucleus as well as with motor, sensory, and associative cerebral cortical areas. ICA was used to demonstrate which cerebellar regions were associated with which ICNs.

Functional Connectivity ROI-Based fcMRI of the Dentate Nucleus Functional connectivity (Allen et al. 2005) was found between the left dentate nucleus, and (1) the right DN, (2) the cerebellar cortex bilaterally (anterior and posterior vermis and hemispheres), (3) the thalamus bilaterally (ventral anterior, ventral lateral) but right dorsomedial nucleus, (4) the striatum (caudate nuclei bilaterally and right putamen), (5) the right limbic cortex (insula, hippocampus, and parahippocampus), (6) the right posterior cingulate cortex, (7) the right medial occipital lobe, (8) the inferior parietal lobe (BA 39/40), (9) the right (para-)cingulate cortex (BA 24/32), (10) the dorsolateral prefrontal cortex bilaterally (BA 8/9/46), and (11) the frontal pole (BA 10). Functional connectivity was found between the right dentate nucleus, and (1) the left DN, (2) the bilateral cerebellar cortex (anterior

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and posterior vermis and hemispheres) including the fastigial/globose nuclei, (3) the thalamus bilaterally (ventral anterior, ventral lateral, dorsomedial), (4) the left hypothalamus, (5) the striatum (caudate nucleus, putamen, and pallidum bilaterally), (6) the right insula (BA 13), (7) the anterior cingulate cortex bilaterally (BA 24) with a right predominance, (8) the left occipital cortex (BA 19), and (9) the dorsolateral prefrontal cortex (BA 9/46 with an extension to BA 10). Although fcMRI data provide no information about the directionality of the connectivity, some of these regions may correspond to mono- or disynaptic targets of the DN. In monkeys, the DN projects to the motor (BA 4), premotor (BA 6 medial, i.e., (pre-)SMA, and lateral), prefrontal (BA 9/46), and posterior parietal associative brain areas via the thalamus (ventral lateral and dorsomedial) (Strick et al. 2009). The DN also targets the striatum (Hoshi et al. 2005) and the hypothalamus (Haines et al. 1997). Therefore, fcMRI of the DN may have functionally traced associative dentato-thalamocortical, dentato-striatal, and dentato-hypothalamic circuits. The remaining areas functionally connected with the DN in this study could be polysynaptic (two or more) relays or phylogenetically new relays of these circuits. It cannot be ruled out that these regions also send afferents to DN and the overlying cerebellar cortex. However, these cerebral afferents reach the cerebellum via a relay in the PN (and bulbar olivary nucleus and reticular nuclei), which were not detected in this study. This could argue in favor of a preferential detection of functional connectivity of the cerebellar output channel. Alternatively, this lack of detection of the PN may be explained by a threshold problem, low sensitivity technique (1.5 T), or low spatial resolution.

ROI-Based fcMRI of the Cerebellar Cortex The first cerebellar fcMRI study was performed by He et al. (2004) examining connectivity between the anterior inferior cerebellum and the rest of the brain. However, no exact location of the cerebellar seed region was provided, and, when referring to the figure, this region seems to be located inside the cerebellar white matter. Therefore, this study was not included in the current chapter. More recently, Sang et al. (2012), using voxel-based and cerebellar ROI-based analyses, provided interesting results concerning, in particular, functional connectivity of the vermis, on one hand, and between cerebellum and subcortical and midbrain nuclei. For instance, they showed strong coherence between vermis (lobules VIIB–IX) and the visual network, vermis (lobule VIIIB) and default mode network, as well as with caudate nucleus, crus I and II with caudate nucleus, cerebellum (lobules V, VI, VIIB and VIIIA) and lenticular nucleus, lobules V/VIIB and red nucleus, and lobules I–V/ VIII–IX and cerebral amygdala, as well as hippocampus.

ROI-Based fcMRI of the Cerebral Cortex Krienen and Buckner (2009) and O’Reilly et al. (2009) defined an anatomical parcellation of the cerebellar cortex based on their specific coherence with distinct

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cortical ROIs and using the probabilistic cerebellar atlas of Diedrischsen et al. (2009). Krienen and Buckner found correlations between the dorsolateral prefrontal cortex and lobule VII (crus I and II and VIIB, especially crus II), the medial prefrontal cortex and lobule VII (crus I), and the anterior prefrontal cortex and lobules VI and VII (crus I/II/VIIB/VIIIA) (Fig. 2). O’Reilly and colleagues corroborated these observations by showing that motor, premotor, and somatosensory cortices were correlated with the cerebellar anterior lobe (lobules V/VI/VIII), Fig. 2 Functional anatomic parcellation of the human cerebellum based on restingstate functional connectivity using ROIs located in motor cortex (MOT), dorsolateral prefrontal cortex (DLPFC), medial prefrontal cortex (MPFC), and anterior prefrontal cortex (APFC). Caudal view (top). Rostral view (middle). Dorsal view (bottom). (From Krienen and Buckner 2009; with authors’ permission)

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whereas the prefrontal cortex was functionally connected with the posterior lobe (paravermal and lateral hemisphere of lobule VIIA including crus I and II). Strong correlations were also detected between visual area MT and lobules V/VI/VIII, superior temporal gyrus including auditory areas with lobules V/VI, and inferior posterior parietal cortex with lobules VIIA (paravermis) and crus II. Therefore, two main zones were distinguished in the cerebellum: (1) a primary sensorimotor zone (lobules V/VI/VIII) containing overlapping sensory and motor domains in relation to somatomotor, visual, and auditory cortices and (2) a supramodal zone (lobule VII) containing overlapping cognitive domains in relation to prefrontal and parietal cortices. The latter associative areas were also mapped in this study and comprise the posterior frontal medial gyrus (BA 8), the middle medial gyrus (BA 9/46), the frontal pole (BA 10), the inferior parietal lobule (BA 39), the medial superior parietal lobule (BA 7b), and the posterior cingulate cortex (BA 25). Moreover, the cerebellar supramodal zone can be further segregated according to its functional links with dorsolateral, medial, and anterior prefrontal cortex. It is noteworthy that the functional connectivity between prefrontal and parietal cortices and neocerebellum is not restricted to oculomotor regions such as frontal and parietal eye fields or vermian and paravermian parts of lobule VI/VII but rather involves multiple regions in prefrontal cortex, parietal cortex, and neocerebellum. Therefore, it cannot be claimed that prefronto/parieto-cerebellar interconnections exclusively relate to the oculomotor system (Doron et al. 2010). More recently, Buckner et al. (2011) seeded small regions within the cerebellum in order to precisely determine the functionally correlated topography in the cerebral cortex during resting state. In particular, they established that the cerebellum contains at least two topographically organized, inverted representations of the complete cerebrum, with the exception of primary visual and auditory cortices. The cerebral cortex, including somatomotor, premotor, and association areas, is functionally linked to (1) a homotopic map extending from the somatomotor anterior lobe to crus I and II and (2) a mirror-image secondary map extending from crus I and II to lobule VIII. If crus I and II, in association with part of lobule VI, and lobules VIIB and IX, are in functional coherence with the association cortex, the border of crus I and II displayed strong correlations with the default-mode network. It was also found that the somatomotor map in the anterior lobe (lobules IV/V/VI) represents the foot, hand, and tongue in the rostral-to-caudal axis and was located close to the vermis. Therefore, medial lobule VI belongs to the somatomotor zone, while the lateral part of this lobule takes part in the supramodal zone.

ICA fcMRI The abovementioned studies provide a functional anatomic parcellation of the cerebellar cortex and show correlation of the neocerebellum (lobule VII) with the associative neocortex. However, most of these ROI-based studies did not examine correlations between neocerebellum and other parts of the brain and thus could not identify and segregate all the relays contributing to distinct specialized cerebroneocerebellar networks. ICA is a method that examines whole-brain connectivity

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without the priori identification of an ROI. Habas et al. (2009) applied ICA analysis to resting-state fMRI data and used an unbiased template-matching procedure to identify previously studied ICNs: (1) the default-mode network (DMN) (Greicius et al. 2003, 2004) involved in stream of consciousness, mental imagery, episodic memory retrieval, and self-reflection (Raichle et al. 2001); (2) the executive control network (ECN, divided by ICA into left and right ECNs) involved in working memory, attention, response selection, and flexibility (Seeley et al. 2007); (3) the salience network (Seeley et al. 2007) required for the processing and integration of interoceptive, autonomic, and emotional information; and (4) the sensorimotor network (Biswal et al. 1995). Distinct cerebellar contributions were found in each of these ICNs. The neocerebellum was shown to participate in (1) the DMN (lobule IX), (2) the right and left ECNs (crus I and II with a narrow extension in lobules VIIB and rostral IX), (3) the salience network (lobule VI with narrow extension in lobules VIIA: crus I and II and VIIB), and (4) the sensorimotor network (lobules V and adjacent VI) (Fig. 3). Three other structures of the cerebrocerebellar system were also identified: the PN (DMN, ECN, salience network), the DN (sensorimotor, salience networks), and the red nucleus (sensorimotor, DMN, ECN, salience network) (Fig. 4). These results are in agreement with O’Reilly et al. (2009) and Krienen and Buckner’s (2009) data, highlighting functional connectivity of lobule VII (especially crus I and II) with dorsolateral and dorsomedial (BA 9/46) prefrontal and cingulate cortices (ECNs), and frontoinsular cortex (salience network) (Fig. 4). More recently, Brissenden et al. (2016) gave support to the participation of cerebellar lobules VIIb/VIIIA to the dorsal attentional network. The ICA results, however, provide four new pieces of data. First, the cerebellar supramodal zone can be extended to the caudal part of lobule VI, which is included in the salience network and can be clearly dissociated from the more anterior sensorimotor part of the same lobule and to lobule IX participating in the DMN. This is in line with O’Reilly et al. (2009) who also found a correlation between the tonsilla and the prefrontal cortex. Second, the major part of lobule VIIA is devoted to the ECNs. These results are in accordance with the meta-analysis of cerebellar neuroimaging studies (Stoodley and Schmahmann 2008) showing involvement of lobule VI/VII (crus I) in nonmotor linguistic, spatial, and executive processes. Third, an extracerebellar relay such as the red nucleus also contributes to nonmotor circuits. This is in keeping with Nioche et al. (2009) and supports the view that during phylogeny, not only the cerebellum but also its associated nuclei have evolved in parallel with the neocortex (Ramnani 2006). Fourth, ICNs encompass cerebellar input (PN) and output channels (DN) so that an ICN may indeed represent loops reciprocally linking cerebellum and cerebral cortex (Fig. 5).

Tractography fcMRI enables identification of the neural relays contributing to a given specialized network but cannot distinguish which relays are directly connected by monosynaptic links. In other words, functional connectivity defined by fcMRI cannot distinguish

Fig. 3 Cortical (top) and cerebellar (bottom) regions functionally linked within five intrinsic connectivity networks (somatomotor, left and right executive control, default-mode, and limbic salience networks) as revealed by independent component analysis (Habas et al. 2009)

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Fig. 4 Human cerebellar topography based on restingstate functional connectivity to the frontal cortex (a) (From Krienen and Buckner 2009) and (b) to five intrinsically connected networks including somatomotor, left and right executive control, defaultmode, and limbic salience networks (From Habas et al. 2009). In (a) (pre-)motor cortex (yellow), parietal cortex (green), dorsal prefrontal cortex (red), and medial prefrontal cortex (orange). In (b) sensorimotor network (purple), default-mode network (yellow), right and left executive control network (red and blue, respectively), and salience network (green). Sps superoposterior sulcus. This figure demonstrates the substantial overlap in cerebellar functional connectivity maps obtained with ROI- and ICA-based parcellation of the cerebellum. Convergent findings include cerebellar regions connected to the sensorimotor network (yellow in a/purple in b), the executive control network (red in a/red and blue in b), the default-mode network (yellow in b, especially in lobules IX), and the salience network (orange in a/green in b)

direct connectivity between two regions from indirect connectivity possibly mediated by a third region. Two recent studies have attempted to overcome this drawback by using DTI-based tractography, a method that allows for reconstruction of white matter tracts that directly link two neural regions. Habas and Cabanis (2007), Doron et al. (2010), and Kamali et al. (2010) applied tractography to track corticopontocerebellar fibers. They found that orbitofrontal, prefrontal, pericentral, parietal, and temporal/occipital cortices project onto specific PN, which, in turn,

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Fig. 5 ICA maps showing pontine and dentate contributions to cerebrocerebellar intrinsic connectivity networks (Habas et al. 2009). Pontine nuclei (a, b) constitute the main relay of the cortical projections to the cerebellum, to which they project contralaterally via the middle cerebellar peduncle, while dentate nuclei (c, d) represent the main source of cerebellar outputs via the superior cerebellar peduncle

project via the middle cerebellar peduncle to the cerebellar cortex. More precisely, Doron et al. (2010) only described prefrontal corticopontine fibers arisen from caudal and medial superior frontal gyrus and a small region of the medial prefrontal gyrus. However, collaterals of mossy fibers from the PN to deep cerebellar nuclei could not be tracked. Ramnani et al. (2005) compared the organizational origins of corticocerebellar fibers in the cerebral peduncle (crus cerebri) between macaques and humans. This DTI study found a larger contribution to the crus cerebri from the prefrontal cortex in humans than in macaques. Within the cerebellum, the deep cerebellar nuclei, mainly the DN, are targeted by the PN (mossy fibers), bulbar olivary nucleus (climbing fibers), and the cerebellar cortex (Granziera et al. 2009). The DN are directly connected with the red nucleus and indirectly via the ventral part of the thalamus (Habas and Cabanis 2007; Granziera et al. 2009), with the cerebral cortex: sensorimotor (M1/S1), temporal (Habas and Cabanis 2007), prefrontal (BA 9), and parietal (BA 7) (Jissendi et al. 2008) cortices (Fig. 6). DN also project directly to the thalamus including mainly ventrolateral, posterior, intralaminar,

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Fig. 6 DTI-based deterministic tractography of the dentate nuclei showing, on a sagittal slice, dentatothalamo-cortical projections ending within the prefrontal (yellow fibers) and superior parietal (green fibers) cortices. (From Jissendi et al. 2008; with authors’ permission)

subparafascicular, medioventral and dorsomedian nuclei (Hyam et al. 2012; Pelzer et al. 2017), globus pallidus, mainly ispsilaterally, and to the ipsilateral substantia nigra (Milardi et al. 2016) and, indirectly, through the thalamus, to the striatal, pallidal, and subthalamic nuclei (Pelzer et al. 2013). Furthermore, Sokolov et al. (2014) identified a loop linking left crus I and right superior temporal sulcus via the superior cerebellar peduncle and the pons. Finally, Arrigo et al. (2014) described cerebello-limbic interconnections: tractograms were computed between cerebellar vermis, crus I/II and lobules VIII-IX, and hippocampus (subiculum, CA1, and fimbria). Altogether, these tractography studies confirm connections in humans between the neocerebellum and the associative cerebral cortex and, in particular, closed loops between the neocerebellum, including the DN, and prefrontal and parietal cortices. However, because of their low spatial resolution, their partial coverage of the brain, their low sensitivity to discriminate fiber crossings, and their inability to follow trajectories within low anisotropic regions, these studies may underestimate both the number of neocortical areas involved in the cerebrocerebellar system and also the number of loops. It is noteworthy that very high-field MRI (7 T) allows to perform micro-tractography visualizing, for example, T-shaped parallel fibers within the cerebellar molecular layer and that algorithm such as spherical deconvolutionbased processing can detect fiber crossings (Dell’Acqua et al. 2013). Therefore, fcMRI and tractography (i.e., functional and structural connectivity) are complementary in deciphering functional networks.

Conclusions and Future Directions fcMRI enables functional anatomic parcellation of the cerebellum into wellsegregated subregions which participate in specific, functionally distinct, largescale cerebrocerebellar networks. DTI tractography provides a complementary approach which can be used to help distinguish direct from indirect connections in

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the functional maps. Using these approaches, the cerebellar cortex can be subdivided into a polymodal sensorimotor zone (lobules IV/V/VI and VIII) and a supramodal cognitive zone (lobules VI/VII and, especially, crus I and II, and lobule IX). Subregions of the cognitive neocerebellum take part in the DMN (lobule IX), the salience network (lobule VI), and the right/left ECNs (crus I and II). Strong functional links exist between crus I and II and prefrontal, parietal, and cingulate cortices, supporting the role of the most phylogenetically recent part of the cerebellum in executive and affective functions. These intrinsically connected networks variably include the DN and PN. Lack of detection of the PN/DN in certain circuits could be ascribed to the stringent statistical postprocessing of the fcMRI data. It also cannot be ruled out that connectivity between the cerebellum and other parts of the brain may be mediated by the bulbar olivary, lateral vestibular, and reticular nuclei, as well as via the striatum (Hoshi et al. 2005; Bostan et al. 2010). It is worth noting that no functional connectivity was detected for the posterior vermis, especially lobule VII involved in limbic emotional processing, regardless of the fcMRI method performed. Thus, while functional and structural connectivity approaches have helped us begin to delineate the functional anatomy of the cerebellum, there is still much work to do.

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Middleton FA, Strick PL (1997) Dentate output channels: motor and cognitive components. Prog Brain Res 114:555–568 Middleton FA, Strick PL (2001) Cerebellar projections to the prefrontal cortex of the primate. J Neurosci 15:700–712 Milardi D, Arrigo A, Anastasi G, Cacciola A, Marino S, Mormina E, Calamuneri A, Bruschetta D, Cutroneo G, Trimarchi F, Quartarone A (2016) Extensive direct subcortical cerebellum-basal ganglia connections in human brain as revealed by constrained spherical deconvolution tractography. Front Neurosci 10:29 Nieuwenhuys R, Voogd J, van Huijzen C (2007) The human central nervous system: a synopsis and atlas, 4th edn. Springer, New York Nioche C, Cabanis EA, Habas C (2009) Functional connectivity of the human red nucleus in the brain resting state at 3T. Am J Neuroradiol 30:396–403 O’Reilly JX, Beckmann CF, Tomassini V, Ramnani N, Johansen-Berg H (2009) Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity. Cereb Cortex 20:953–965 Pelzer EA, Hintzen A, Goldau M, von Cramon DY, Timmermann L, Tittgemeyer M (2013) Cerebellar networks with basal ganglia: feasibility for tracking cerebello-pallidal and subthalamo-cerebellar projections in the human brain. Eur J Neurosci 38:3106–3114 Pelzer EA, Melzer C, Timmermann L, von Cramon DY, Tittgemeyer M (2017) Basal ganglia and cerebellar interconnectivity within the thalamus. Brain Struct Funct 22(1): 381–392 Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98(2):676–682 Ramnani N (2006) The primate cortico-cerebellar system: anatomy and function. Nat Rev Neurosci 7:511–522 Ramnani N, Behrens TEJ, Johansen-Berg H, Richter MC, Pinsk MA, Andersson JLR, Rudebeck P, Ciccarelli O et al (2005) The evolution of prefrontal inputs to the cortico-pontine system: diffusion imaging evidence from macaque monkeys and humans. Cereb Cortex 16:811–818 Sang L, Qin W, Liu Y, Han W, Zhang Y, Jiang Y, Yu C (2012) Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum with both the cerebral cortical networks and subcortical structures. NeuroImage 61(4):1213–1225 Schmahmann JD (1991) An emerging concept: the cerebellar contribution to higher function. Arch Neurol 48:1178–1187 Schmahmann JD (2004) Disorders of the cerebellum: ataxia, dysmetria of thought, and the cerebellar cognitive affective syndrome. J Neuropsychiatr Clin Neurosci 16:367–378 Schmahmann JD, Pandya DN (1997) The cerebrocerebellar system. Int Rev Neurobiol 41:31–60 Schmahmann JD, Shermann JC (1998) The cerebellar cognitive and affective syndrome. Brain 121:561–579 Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27:2349–2356 Shirer WR, Ryali S, Rykhlevskaia E, Menon V, Greicius MD (2011) Decoding subject-driven cognitive states with whole-brain functional connectivity patterns. Cereb Cortex 22:158–165 Skudlarski P, Jagannathan K, Calhoun VD, Hampson M, Skudlarska BA, Pearlson G (2008) Measuring brain connectivity: diffusion tensor imaging validates resting state temporal correlations. Neuroimage 43:554–561 Sokolov AA, Erb M, Grodd W, Pavlova MA (2014) Structural loop between the cerebellum and the superior temporal sulcus: evidence from diffusion tensor imaging. Cereb Cortex 24:626–632 Stoodley CJ, Schmahmann JD (2008) Functional topography in the human cerebellum: a metaanalysis of neuroimaging studies. Neuroimage 44:489–501 Strick PL, Dum RP, Fiez JA (2009) Cerebellum and nonmotor function. Annu Rev Neurosci 32:413–434 Tedesco AM, Chiricozzi FR, Clausi S, Lupo M, Molinari M, Leggio MG (2011) The cerebellar cognitive profile. Brain 134:3669–3683

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Radiographic Features of Cerebellar Disease: Imaging Approach to Differential Diagnosis

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Otto Rapalino

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Congenital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Agenesis, Hypoplasia, and Atrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebellar Dysplasia and Malformations of Cortical Development . . . . . . . . . . . . . . . . . . . . . . . . Congenital Posterior Fossa Cysts and Related Disorders (Poretti et al. 2016a) . . . . . . . . . . . . Acquired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebrovascular . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Traumatic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Infectious . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Autoimmune . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neurodegenerative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neoplastic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Toxic and Miscelaneous Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Many pathological processes can affect the cerebellum, often with overlapping imaging features but, in some cases, with particular radiological findings. The purpose of this chapter is to provide a concise and systematic review of cerebellar pathologies based on their imaging features that can be used for their diagnosis.

O. Rapalino (*) Neuroradiology Division, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_27

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Keywords

Magnetic resonance imaging · Computed tomography · Cerebellar hypoplasia · Cerebellar atrophy · Trauma · Stroke · Hemorrhage · Posterior fossa tumors · Cerebellar degeneration · Demyelination · Toxic encephalopathies

Introduction Pathological conditions affecting the cerebellum can be divided into congenital and acquired disorders. Acquired disorders can be subdivided into cerebrovascular, traumatic, infectious, genetic, autoimmune, neurodegenerative, neoplastic, toxic, and other metabolic processes.

Congenital Cerebellar Agenesis, Hypoplasia, and Atrophy Global cerebellar agenesis (Bosemani and Poretti 2016) Primary global hypoplasia (Poretti et al. 2014)

Secondary to congenital infections (e.g., CMV) (Bosemani and Poretti 2016) (Fig. 1a)

Secondary to prenatal medications and teratogens (Poretti et al. 2014) Predominantly vermian involvement (Poretti et al. 2014) Unilateral hypoplasia (Poretti et al. 2014, 2016b) Cerebellar atrophy (Fig. 1b)

Rare. Cerebellar remnants may be seen. Often with concurrent pontine hypoplasia Chromosomal abnormalities (e.g., trisomy 13 and 18), inborn errors of metabolism (e.g., molybdenum cofactor deficiency) and associated with other disorders or malformations Global cerebellar hypoplasia, periventricular calcifications, white matter abnormalities, malformations of cortical development, and temporal or intraventricular cysts Antiepileptic medications (e.g., phenytoin and valproic acid), alcohol, and retinoic acid Dandy-Walker malformation, Joubert syndrome, and other genetic syndromes Sequela of in utero insult (e.g., hemorrhage), PHACE(S) syndrome Regional (vermian vs. hemispheric) or diffuse cerebellar involvement

Cerebellar Dysplasia and Malformations of Cortical Development Rhombencephalosynapsis (Poretti et al. 2016a, b) (Fig. 2a) Cerebellar dysplasia (Poretti et al. 2016a) (Fig. 2b)

Dorsoventral patterning defect with vermian hypogenesis, continuity of the cerebellar hemispheres and fusion of cerebellar peduncles and dentate nuclei Abnormal foliation/fissuration, white matter arborization, and abnormal GM-WM junction. Associated with ChudleyMcCullough syndrome (mostly inferior hemispheres), (continued)

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Joubert syndrome (Poretti et al. 2016b) (Fig. 2c)

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alpha-dystroglycanopathies (global hypoplasia with cysts), and other mutations (Poretti et al. 2016a) Molar tooth sign on axial images, with thickened horizontal superior cerebellar peduncles, vermian hypo/ dysplasia, and fourth ventricle enlargement. Associated with cerebellar hemispheric hypoplasia, brainstem, and supratentorial abnormalities

Fig. 1 (a) Noncontrast CT shows bilateral cerebellar hypoplasia (without disproportionate prominence of cerebellar fissures) associated with calcifications around the right temporal horn and right cerebellar hemisphere in a case of congenital CMV infection. (b) Noncontrast axial T2-weighted image. There is bilateral cerebellar atrophy of unknown etiology in an elderly patient

Fig. 2 Axial T2-weighted images showing examples of rhombencephalosynapsis (a), superior vermian dysplasia (b), and Joubert syndrome (c)

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Congenital Posterior Fossa Cysts and Related Disorders (Poretti et al. 2016a) Dandy-Walker malformation (Fig. 3a)

Inferior vermian hypoplasia (Dandy-Walker variant) (Fig. 3b) Blake’s pouch cyst

Posterior fossa arachnoid cyst (Fig. 3c) Mega cisterna magna

Hypoplastic vermis, enlargement of fourth ventricle, and posterior fossa, often with hydrocephalus (up to 90%). 30– 50% have additional malformations (e.g., callosal dysgenesis) Selective hypoplasia of posterior vermis with wide opening of the fourth ventricle. No enlargement of the posterior fossa or hydrocephalus Fourth ventricle is enlarged but there is no vermian hypoplasia or posterior fossa enlargement. Upward vermian displacement on sagittal images Mild mass effect on the adjacent cerebellum but without fourth ventricular enlargement, hydrocephalus, or vermian hypoplasia No mass effect on the adjacent cerebellum. No posterior fossa enlargement, hydrocephalus, or vermian hypoplasia

Fig. 3 Examples of cystic pathologies affecting the cerebellum on sagittal T1-weighted images: Dandy-Walker malformation (a), inferior vermian hypoplasia (b), and a large retrovermian arachnoid cyst (c)

Acquired Cerebrovascular Ischemic Changes Global ischemia

Very small (lacunar) infarcts

Severe hypoxic-ischemic changes in adults often affect the cerebellum in addition to the basal ganglia, cerebral cortex, and hippocampi (Huang and Castillo 2008) Defined as 24 h), and the majority (60%) suffer combined audiovestibular dysfunction (Lee et al. 2009). The prognosis for isolated AICA infarction is excellent with no deaths or severe disability at 3 months among 12 patients reported by Toghi et al. (1993).

Superior Cerebellar Artery Infarction In a study of 60 patients with MRI confirmed SCA infarcts, lesions involved the lateral SCA cerebellar territory in 23%, the medial territory in 15%, combined medial and lateral territories in 15% (Fig. 8), cortical or deep borderzone territories in 30%, and combined SCA and other vascular territories in 17%; the latter commonly associated with coma and the rostral basilar syndrome (Kumral et al. 2005a). As with PICA infarction, large vessel atherosclerotic disease is more common than cardioembolism, with vertebral dissection the least common (Kumral et al. 2005a). Classically medial SCA infarcts have prominent truncal ataxia and mild limb ataxia, which is reversed with lateral SCA infarcts (Sohn et al. 2006). Cerebellar dysarthria is thought to arise from involvement of the rostral paravermian area (Urban et al. 2003), but may be seen in both lateral and medial SCA infarction (Sohn et al. 2006). The rostral trunk of the SCA supplies the vermian and paravermian surface, while the caudal trunk supplies the lateral hemispheric territory.

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Fig. 8 SCA infarct. Diffusion MRI at the level of the superior cerebellar peduncles (asterisk) demonstrates acute infarct in the left SCA territory. The contralateral normal SCA territorial supply is outlined (dotted line)

These branches, in addition to the main SCA trunk, provide direct perforating branches to the cerebral peduncles, midbrain, and colliculi (Rhoton 2000). The marginal branch of the SCA supplies the superior petrosal cerebellar surface, anastomosing frequently with the rostral trunk of the AICA and providing perforators to the middle cerebellar peduncle (Rhoton 2000). The hemispheric branches of the SCA also anastomose with the hemispheric branches of the PICA. Compared to PICA infarcts, significant swelling from large SCA infarcts is thought to be less common (7% in one study (Kase et al. 1993)). Despite this fact, SCA infarcts were found to have worse outcomes than PICA or AICA strokes with 61% rate of independent outcome and 13% rate of severe disability or death at 3 months (Tohgi et al. 1993). This may relate to the greater likelihood of SCA infarcts to involve the midbrain. If patients with infarction in the brainstem, thalamus, and occipital lobes are excluded, Kumral et al. found that 96% of SCA infarcts produced no or minor disability (Kumral et al. 2005a).

Hemorrhagic Diseases of the Posterior Fossa Aneurysmal Disease Saccular Aneurysms Saccular aneurysms occur at vessel branch points. Vertebrobasilar (VB) aneurysms account for 15% of saccular intracranial aneurysms, approximately 60% of which reside at the basilar terminus (BT) (Rhoton 2002). Posterior communicating artery (PCOM) aneurysms are generally considered as posterior circulation aneurysms. In

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the International Study of Unruptured Intracranial Aneurysms (ISUIA) (Wiebers et al. 2003) which included 4060 patients, 828 patients had posterior circulation aneurysms, of which 42% were located at the PCOM, 34% were at the BT, and the remaining 24% at vertebrobasilar locations other than the BT (Wiebers et al. 2003). Given the proximity to cranial nerves and the brainstem, unruptured posterior circulation aneurysms commonly present with cranial nerve palsy or brainstem compressive symptoms. An oculomotor palsy, occurring in 20% of PCOM aneurysms (Golshani et al. 2010), may also be caused by posteriorly directed BT aneurysms compressing the oculomotor nerve as it enters the interpeduncular fossa (Fig. 9), or by superior cerebellar artery or posterior cerebral artery aneurysms as the oculomotor nerve passes in between these vessels (Ciceri et al. 2001; Rhoton 2002; Al-Khayat et al. 2005a; Peluso et al. 2007b). An acute presentation of oculomotor palsy suggests a morphological change in the aneurysm, and can herald impending rupture (Golshani et al. 2010). Similarly facial or vestibulocochlear nerve palsy may occur with AICA aneurysms, and lower cranial nerve palsies with PICA aneurysms (Peluso et al. 2007a, 2008). Unruptured posterior circulation aneurysms have a higher risk of rupture than anterior circulation aneurysms of the same size. According to ISUIA, 5-year cumulative rupture rates are 2.5%, 14.5%, 18.4%, and 50% for posterior circulation aneurysms less than 7, 7–12, 13–24, and 25 mm or greater, respectively, compared to 0%, 2.6%, 14.5%, and 40% for similar anterior circulation aneurysms (Wiebers et al. 2003). Moreover, posterior circulation aneurysms have worse clinical outcomes following rupture. Ruptured VB aneurysms have up to 68% mortality within the first 48 h, compared to 23% for anterior circulation aneurysms (Schievink et al. 1995). Similarly, patients with ruptured VB aneurysms have poorer clinical grades if they survive to hospital admission (Schievink et al. 1995). Based on ISUIA data, posterior circulation location is a predictor of poorer clinical outcome after both surgical and endovascular treatment (Wiebers et al. 2003).

a

b

c

Fig. 9 Basilar apex aneurysm. Antero-posterior (Towne’s view) (a) and lateral (b) digital subtraction angiography of a 6 mm basilar apex aneurysm (arrow). The aneurysm projects posteriorly into the interpeduncular fossa which is well demonstrated on the CT angiogram (c). The aneurysm likely impinges on the left oculomotor nerve at its exit from the midbrain. The patient presented with an acute onset of diplopia from partial left oculomotor palsy

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In many centers, posterior circulation aneurysms are preferentially managed endovascularly (Sanai et al. 2008). The International Subarachnoid Aneurysm Trial (ISAT) (Molyneux et al. 2005) demonstrated better neurological outcomes after endovascular coiling compared to microsurgical clipping for ruptured cerebral aneurysms equally suitable for either treatment. Of note, posterior circulation aneurysms were underrepresented in the ISAT trial because most centers considered it unethical to randomize such patients due to perceived high surgical risk, particularly with BT aneurysms (Molyneux et al. 2002). In a meta-analysis of 2568 unruptured cerebral aneurysms treated surgically, of which 395 were in the posterior circulation, morbidity and mortality for non-giant (5 mm) Drainage into perimedullary spinal veins

Borden typea I II

III

Cognard typeb I IIA IIB

Rates of aggressive presentationc ICH/NHND/Total (%) 0/0/0 0/7/7 13/25/38

IIA + B

10/30/40

III IV V

38/31/69 50/33/83 75/25/100

Abbreviations: RLVD retrograde leptomeningeal venous drainage, ICH intracranial hemorrhage, NHND nonhemorrhagic neurological deficit a As presented in Borden et al. (1995) b As presented in Cognard et al. (1995) c As validated by Davies et al. (1996)

As one would expect, the management approach largely depends on the venous drainage pattern of the dAVF. Cognard/Borden-Shucart Type 1 dAVFs (i.e., absent retrograde leptomeningeal venous drainage) are generally treated conservatively because aggressive neurological presentations have been reported in only 1 (intracranial hypertension) of 85 patients in Cognard’s original series, and 1 (communicating hydrocephalus) of 55 patients examined by Davies et al. (Cognard et al. 1995; Davies et al. 1996). Occasionally, palliative embolization for intractable tinnitus is performed. Without treatment, spontaneous thrombosis of type 1 dAVFs may be seen in approximately 9% of cases, generally occurring in transverse and cavernous sinus lesions (Luciani et al. 2001; Kim et al. 2010). Importantly, untreated type 1 lesions may subsequently develop RLVD. In one series, this occurred in 4 of 99 (4%) patients, all of whom had a change in symptoms (e.g., change or loss of bruit) (Kim et al. 2010). Standard management of dural AVFs with retrograde leptomeningeal venous drainage is complete lesion obliteration (Cognard et al. 2008). Partial treatment does not reduce the risk of hemorrhage (Pierot et al. 1992). The goal of treatment is to close the microfistulous network including the proximal venous outflow, with the latter considered essential to prevent recanalization. Primary surgical intervention can be challenging as dAVFs with RLVD can also drain through intra-diploic venous channels leading to profuse bleeding from the bone flap, particularly in Borden-Shucart Type II malformations (Borden et al. 1995). This can be ameliorated using preoperative endovascular embolization (Collice et al. 2000; Lawton et al. 2008). In cases where there is sinus drainage, the surgical approach consists of skeletonization and excision of the involved segment with preservation of the adjacent functional sinus (Lawton et al. 2008). For Borden-Shucart Type III fistulas, obliteration is achieved via surgical disconnection of the draining veins after they

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b

Fig. 12 Posterior fossa dural AVF. Digital subtraction angiography of the left common carotid artery (lateral view, a) reveals the diffuse nidus of a Cognard 2A + B dAVF (dotted circle) which is supplied by multiple external carotid branches and drains primarily into the left sigmoid sinus (asterisks). The fistula was completely obliterated after trans-arterial Onyx embolization (b)

exit the dura (Collice et al. 2000; Lawton et al. 2008). This latter treatment appears safe and effective (Collice et al. 2000). Endovascular treatment options are also effective and well tolerated, and include transvenous and trans-arterial approaches (Dawson et al. 1998; Cognard et al. 2008; Macdonald et al. 2010). Transvenous coil occlusion of the affected sinus has been the standard technique for lesions primarily draining into the sinus (Type II dAVFs) (Dawson et al. 1998). In cases with RLVD only or where transvenous catheterization of the fistulous segment is difficult or impossible, trans-arterial techniques are employed. Because of its greater nidal penetration compared to n-BCA, trans-arterial Onyx embolization is becoming a preferred treatment modality (Fig. 12) (Cognard et al. 2008; Macdonald et al. 2010). Cure rates with Onyx range from 60% to 80% (Cognard et al. 2008; Lv et al. 2009; Stiefel et al. 2009; Natarajan et al. 2010), with many cured after a single treatment session (Cognard et al. 2008). Although long-term data are not available, midterm results are encouraging. One series demonstrated persistent 3-month angiographic occlusion in 100% (23/23) of patients initially cured with Onyx alone (Cognard et al. 2008). Given the often prolonged injections required for nidus obliteration, nontarget embolization is a major concern. Onyx reflux into dural arteries at the skull base may produce ischemic cranial nerve palsies (Cognard et al. 2008; Lv et al. 2009; Natarajan et al. 2010). Additionally, Onyx may traverse collateral communications between external carotid branches and the vertebral and internal carotid arteries potentially leading to cerebral infarction (Lv et al. 2009; Stiefel et al. 2009). Reported rates of permanent neurologic deficit as a treatment complication are 2.4–7.5% (Cognard et al. 2008; Lv et al. 2009; Stiefel et al. 2009). Radiosurgical treatment is generally reserved for palliative treatment of type 1 dAVFs or as part of a multimodal strategy when endovascular and/or surgical intervention have failed (Natarajan et al. 2010). Wu et al. report only a 50% obliteration rate over 24 months for non-cavernous sinus dAVFs treated with

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gamma knife radiosurgery in a cohort where radiosurgery was the primary treatment modality (Wu et al. 2006). Moreover, 8.4% of those with retrograde leptomeningeal venous drainage experienced neurological deficits including intracerebral hemorrhage (Wu et al. 2006). The persistent hemorrhage risk during the 2–3-year latency period limits the role of radiosurgery to palliation rather than primary therapy for high-risk lesions. Posttreatment catheter angiography is necessary to evaluate for the presence of residual fistula. Patients with initial angiographic cure should be followed up at a later time to assess for recurrence. The length of follow-up has not been standardized due to the lack of long-term data. Any change in symptoms should prompt angiographic evaluation for recurrent or new dAVF.

Imaging Approach for Posterior Fossa Neurovascular Disease Numerous tools including CT, MRI, and catheter angiography are available for diagnosing and characterizing cerebrovascular disorders. The imaging algorithm is highly dependent on the disease process in question. Ischemic stroke. CT angiography (CTA) is the best noninvasive test for identifying major intracranial vessel occlusion. In one study of 44 consecutive patients who underwent CTA followed by intra-arterial therapy, CTA demonstrated 98.4% sensitivity, 98.1% specificity, and 98.2% accuracy for large vessel occlusions when compared to the gold standard digital subtraction angiography (DSA) (Lev et al. 2001). Furthermore, CTA has high interobserver reliability (Lev et al. 2001; Bash et al. 2005). Identification of vessel occlusion is facilitated by thick section (20 mm), overlapping (3 mm steps), maximum intensity projection images, which can be constructed immediately at the CT scanner console in three orthogonal planes. For CTA evaluation of stenotic disease, atherosclerotic calcification can lead to overestimation of luminal narrowing (Prokop et al. 1997), which may be improved by adjusting viewing window widths and levels (Saba and Mallarin 2009). MR angiography (MRA) is another widely used noninvasive test, and is performed with 3D time-of-flight technique (3D TOF) or after gadolinium administration. Compared to CTA, it is more sensitive to patient motion artifact, as well as to flow artifact. The latter may also result in overestimation of vessel stenosis. However, for the question of proximal artery occlusion, 3D TOF MRA performs reasonably well, with a sensitivity of 84–87% and a specificity of 85–98% compared to DSA (Bash et al. 2005; Tomanek et al. 2006). The interobserver agreement is moderate (kappa ¼ 0.5) (Tomanek et al. 2006). Another drawback to MRA is suboptimal evaluation of second-order vessels such as the MCA M2 branches. Ultimately, DSA still offers the greatest spatial and temporal resolution, allowing for accurate measurement of vessel stenosis and for dynamic assessment of collateral circulation. It is generally performed for further evaluation after noninvasive imaging or when endovascular therapy is indicated. Subarachnoid hemorrhage (SAH). Spontaneous SAH that is predominantly located in the posterior fossa can be divided into perimesencephalic or diffuse

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patterns. This distinction is important in terms of diagnostic yield of the aneurysm workup. A perimesencephalic pattern accounts for approximately 10% of SAH cases (Rinkel et al. 1993), is centered anterior to the brainstem, and can extend to involve the ambient and suprasellar cisterns. While involvement of the proximal anterior interhemispheric and proximal sylvian cisterns may occur, these cisterns should not be filled with blood and there should be no intraventricular extension (Rinkel et al. 1991). In contrast to a diffuse SAH pattern where the likelihood of aneurysm detection is high, the estimated incidence of a vertebrobasilar aneurysm in a perimesencephalic pattern is only 5% (Velthuis et al. 1999). Noninvasive vascular imaging is emerging as the first-line test for aneurysm detection. CTA has excellent sensitivity for identifying aneurysms – the largest comparative study of 64-detector CTA and DSA revealed 100% CTA sensitivity and specificity for aneurysms sized 3 mm or greater (Li et al. 2009). However, the sensitivity for tiny aneurysms (10

10

1 >10

Reference Pehlke et al. (2013) Heimer et al. (2017)

NF 1 10

AP ataxia phenotype, CD cerebellar dysgenesis, CMT1X X-linked Charcot-Marie-Tooth (CMT1X) disease, DA ataxia dominates the phenotype, DD developmental delay, FXTAS fragile-X tremor ataxia syndrome, HA hypoacusis, H-SMD hypomyelinating leukodystrophy and spondylometaphyseal dysplasia, ID intellectual disability, LPD lymphoproliferative disorder, MC manifesting carriers, MTS Mohr Tranebjaerg syndrome (deafness dystonia, optic neuropathy syndrome), NDA ataxia is a non-dominant feature, NF number of affected families reported, NP neuropathy, PA pure ataxia, PCARP posterior column ataxia and retinitis pigmentosa, PH pulmonary hypertension, PMD Pelizaeus Merzbacher disease, PMLD Pelizaeus-Merzbacher-like disease, PS parkinsonism, SCA: spinocerebellar ataxia, Uk unknown, UMNS upper motor neuron signs, XLSA/A X-linked sideroblastic anemia with ataxia, XL X-linked a Lethal in males

NDA NDA

NDA NDA

NDA

NDA

RPL10

X-linked ribosomopathy Menkes disease X-linked SCA Multisystem disease

AP NDA NDA

Gene STS AIFM1

Type of XL-ataxia X-linked ichthyosis H-SMD

Table 1 (continued)

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Fig. 1 Axial T2-weighted images showing hyperintense signals in the middle cerebellar peduncle bilaterally. Additionally, atrophy of the cerebellar hemispheres can be seen. (Reproduced from Ishii et al., Intern Med 2010;49:1205– 1208)

2016). Usually, the cerebellar volume is decreased and the ventricular volume increased. Female carriers manifest clinically in 20% of the cases with premature ovarian insufficiency, resulting in premature onset of menopause or fertility problems (Sandford and Burmeister 2014). FXTAS is caused by an intronic CGG-repeat expansion in the 50 untranslated region of the FMR1 gene on chromosome Xq27.3 (Sandford and Burmeister 2014). Rarely, FXTAS is due to point mutations. Patients with FXTAS carry a repeat number of 55–200 (FMR1 premutation) (Sandford and Burmeister 2014). If the expansion size exceeds 200, males present with fragile-X syndrome, a severe disorder completely different from FXTAS (Sandford and Burmeister 2014). The normal length of the CGG-repeat is 5–40 (Hagerman and Hagerman 2016) and transmitted in a stable fashion without increase or decrease in the repeat number between generations (Hagerman and Hagerman 2016). In normal alleles, every 9th or 10th CGG-repeat is interrupted by an AGG triplet repeat, which is assumed to maintain repeat integrity by preventing DNA strand slipping during replication (Hagerman and Hagerman 2016). In intermediate alleles (41–54 repeats) the likelihood to become unstable in successive generations increases with the number of uninterrupted CGG-repeats (Hagerman and Hagerman 2016). Retraction of the CGG-repeat expansion between generations is rare (Hagerman and Hagerman 2016).

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Fig. 2 Axial T1-weighted image showing a deepened interpeduncular fossa (open arrowhead) and abnormal superior cerebellar peduncles (thick arrowheads), constituing the “molar tooth sign.” (Reproduced from Brancati et al., Orphanet Journal of Rare Diseases 2010;5:20)

X-Linked Sideroblastic Anemia with Ataxia (XLSA) XLSA is a rare mitochondrial disorder (MID) characterized by mild, nonsymptomatic, early-onset sideroblastic anemia with hypochromia, microcytosis, marked poikilocytosis, reticulocytosis, and heavy stippling. Bone marrow examination in affected males and occasionally in female carriers may show ring siderocytes (D’Hooghe et al. 2012). In addition to anemia cerebellar ataxia dominates the phenotype (D’Hooghe et al. 2012). Ataxia is either nonprogressive or slowly progressive from the fifth decade (D’Hooghe et al. 2012). In addition to gait and trunk ataxia, patients present with dysmetria, dysdiadochokinesia, dysarthria, nystagmus, hypometric saccades, strabism, or kinetic tremor (D’Hooghe et al. 2012). Some patients develop lower limb spasticity. Cerebral imaging may show cerebellar atrophy or hypoplasia (D’Hooghe et al. 2012). Female carriers are neurologically normal but may show a dimorphic blood smear with both hypochrome, microcytic, and normal red blood cells. XLSA is caused by mutations in the mitochondrial ATP-binding cassette transporter ABCB7 gene (D’Hooghe et al. 2012). Point mutations have been detected in exons 5–16 and at the intron/exon boundaries (D’Hooghe et al. 2012). The gene

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product, ABCB7, is like frataxin, involved in the biosynthesis of iron-sulfur clusters. There are indications that ABCD7 transports components required for the maturation of cytosolic iron-sulfur clusters from the mitochondrion to the cytosol (D’Hooghe et al. 2012).

X-Linked Ataxia Due to GJB1 Mutations X-linked ataxia due to GJB1 mutations is a recently identified disorder with predominant ataxia but also involvement of the peripheral nerves (wasting, sensory, and motor nerve abnormalities) (Caramins et al. 2013a). GJB1 encodes for the connexin32 protein and allelic variants cause Charcot-Marie-Tooth disease type 1X (CMT1X). Patients with X-linked ataxia additionally presented with scoliosis, foot deformity, or spasticity (Caramins et al. 2013a). The phenotype is due to missense mutations in the GJB1 gene and has been described in two families so far (Caramins et al. 2013a).

Spinocerebellar Ataxia Due to PMCA3 Mutations Spinocerebellar ataxia (SCA) due to PMCA3 mutations is one of the X-linked ataxias with a pure cerebellar phenotype and characterized by congenital-onset ataxia, cerebellar atrophy, dysarthria, hypotonia, nystagmus, and slow eye movements (Zanni et al. 2012; Bertini et al. 2000). This type of SCA was reported in two Italian families so far. The exact consequence of PMCA3 mutations is unknown but they seem to disrupt the intracellular calcium metabolism (Bertini et al. 2000; Caramins et al. 2013a).

X-Linked Adrenoleukodystrophy X-linked adrenoleukodystrophy (X-ALD) is clinically characterized by dysarthria, cerebellar and sensory ataxia, and mild spastic paraparesis. Additionally, adrenal and gonadal impairment (hypogonadism) may be part of the phenotype (Hagerman and Hagerman 2016). Cerebral and spinal cord imaging may show atrophy of the cerebellum and upper cervical spinal cord (Hagerman and Hagerman 2016) or cerebral demyelination (Hagerman and Hagerman 2016). Rarely, X-ALD may manifest as pure cerebellar syndrome with demyelination of the dentate nucleus or the cerebellum (Kang et al. 2014a). Adrenal insufficiency occurs in 80% of males and 20% of female carriers (Rattay et al. 2020). Thus, there are patients without adrenal involvement. X-ALD is due to point mutations or deletions in the ABCD1 gene (Table 1) resulting in accumulation of very long chain fatty acids (Hagerman et al. 2001). X-ALD is the most common peroxisomal disorder in adults (Rattay et al. 2020). The unfolding disease in children can be stopped with allogenic or more recently autologous hematopoietic bone marrow transplantation (Kesserwani 2020).

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X-Linked Pyruvate-Dehydrogenase (PDH) Deficiency X-linked PDH deficiency manifests clinically with a wide range of presentations from neonatal lactic acidosis to severe leucencephalopathy (Leigh syndrome) (Hagerman and Hagerman 2016). Some patients present with dystonia and epilepsy. Less severe cases may present with intermittent ataxia exclusively (Hagerman and Hagerman 2016). X-linked PDH deficiency is due to missense mutations, deletions, or duplications in the PDHA1 gene encoding the E1-subunit of the PDH complex (Hagerman and Hagerman 2016). The genotype-phenotype correlation is poor.

X-Linked Ataxias with Ataxia as a Nondominant Feature A number of X-linked disorders present with ataxia as a nondominant phenotypic feature (Table 1). Most of them are rare and have been described only in a few families (Table 1). The most frequent of these disorders is Rett syndrome.

Management X-linked ataxias are usually diagnosed based on the clinical presentation and genetic studies. Supportive information may derive from blood chemical investigations, cerebral imaging, and nerve conduction studies (Hagerman and Hagerman 2016). Imaging of the central nervous system may show white matter lesions, basal ganglia abnormalities, or cerebellar atrophy. Most frequently, only symptomatic treatment such as physiotherapy, speech therapy, or computed devices to manage difficulties with handwriting can be offered. In X-linked PDH deficiency carbohydrate-free diet together with thiamine, carnitine, and vitamin E may have a beneficial effect with an excellent outcome in single patients. X-ADL in children can be stopped by allogenic or more recently autologous hematopoietic bone marrow transplantation (Kesserwani 2020). Genetic counseling relies on the X-chromosomal transmission of the disorders. Affected males pass the mutation to all their daughters but not to their sons. The father of an affected male will neither be affected nor a carrier. Female carriers may be clinically unaffected and have a 50% chance to transmit the mutation to their offspring. If the mother of an affected male does not carry the mutation, the mutation has to be classified as de novo. If a mother has two affected sons but does not carry the mutation, germline mosaicism has to be considered. The risk of the sibs of a proband depends on the carrier status of the mother. Male sibs carrying the mutation will be affected, and female sibs carrying the mutation will be mildly affected or asymptomatic carriers. Prenatal testing of fetuses at risk is possible on DNA from amnion cells. Preimplantation diagnosis is available in families with a known mutation.

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Conclusion X-linked ataxias are clinically and genetically heterogeneous. Clinically, ataxia may be the dominant or a nondominant phenotypic feature. Ataxia is most commonly of the cerebellar type. Other manifestations in addition to ataxia may be neurological or non-neurological in nature. X-linked ataxias, in which ataxia dominates the phenotype include FXTAS, XLSA, X-linked ataxia due to GJB1 mutations, X-linked ataxia due to PMCA3 mutations, X-ALD, and X-linked PDH deficiency. The number of X-linked ataxias is steadily increasing and it is quite likely that their number will further increase in the future. Therapy of X-linked ataxias is symptomatic. Bone marrow transplantation can be beneficial in children with X-ALD. Genetic counseling not only depends on the X-linked trait of inheritance but also on the presence or absence of germline mosaicism or if X-linked ataxia is due to a trinucleotide expansion. Early recognition of X-linked ataxias is warranted to prevent long-term misdiagnosis and to avoid application of ineffective treatment.

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spinocerebellar Degeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sporadic Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hereditary Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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The neuropathology of major types of cerebellar system degeneration is described in this chapter. Multiple system atrophy (MSA) is a major, non-hereditary spinocerebellar degeneration, characterized pathologically by the olivopontocerebellar atrophy, striatonigral degeneration, and autonomic nervous system degeneration in any combination. The occurrence of glial cytoplasmic inclusions in the oligodendrocytes is a pathologic hallmark of MSA, and involves multiple brain regions including the pontocerebellar tracts and internal capsules, as well as the other affected systems. Autosomal dominant spinocerebellar ataxias (SCAs) include several types of neurodegenerative diseases and are characterized pathologically by the combined degeneration of the cerebellum (cerebellar cortex, cerebellar nuclei) and other brain regions. Polyglutamine diseases are a major group of SCAs which is characterized by a significant correlation between CAG repeat lengths in the causative genes and disease severities. The formation of neuronal intranuclear inclusions is a characteristic feature of polyglutamine diseases. Inclusions are found in brain regions with a distribution specific to each disease. Spinocerebellar ataxia type 31, which is a common SCA in Japan, is a recently established cerebellar M. Yamada (*) Division of Neuropathology, Department of Brain Disease Research, Shinshu University School of Medicine, Matsumoto-city, Nagano, Japan e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_104

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degeneration which is characterized pathologically by a peculiar eosinophilic structure surrounding the remaining Purkinje cell bodies. Keywords

Spinocerebellar degeneration · Ataxia · Pathology

Introduction The cerebellum can be affected in various pathologic conditions, such as neurodegenerative disorders, ischemic conditions, nutritional deficiencies, metabolic disorders, inflammatory diseases, and paraneoplastic syndromes (see this volume). The major cell type affected in each disease condition is the Purkinje cell in most cases. Granule cells are less frequently affected but may be the main target in several conditions, such as Creutzfeldt-Jakob disease or methyl mercury poisoning. In this chapter, the neuropathology of major types of cerebellar system degeneration is described. This includes conventional and molecular neuropathology, which has been established by the discovery of causative gene mutations or proteins.

Spinocerebellar Degeneration Sporadic Disorders Multiple System Atrophy Multiple system atrophy (MSA) is a non-hereditary, adult-onset disorder, characterized clinically by parkinsonism, ataxia, and autonomic failure, in any combination (Burn and Jaros 2001). The term “multiple system atrophy” was first proposed by Graham and Oppenheimer (1969), based on the finding that sporadic olivopontocerebellar atrophy (OPCA), striatonigral degeneration (SND), and Shy-Drager syndrome can coexist both clinically and pathologically. Recent studies categorize MSA into two phenotypes: (1) MSA-P is the category of MSA where parkinsonism predominates, and (2) MSA-C is the category of MSA where cerebellar ataxia predominates (Gilman et al. 1999, 2008). Grossly, there is obvious atrophy of the ventral part of the pons, with marked degeneration of the middle cerebellar peduncles (Fig. 1). The cerebellar cortex and inferior olive are also atrophic. Shrinkage with discoloration is noticed in the putamen (Fig. 2), and this change is commonly accentuated in its posterolateral part. The substantia nigra is depigmented (Fig. 3). In patients with clinical features of OPCA/MSA-C type, atrophy is more prominent in the pontocerebellar system than the striatonigral system. In patients with clinical features of SND/MSA-P type, the striatonigral system is typically more severely affected. Histologically, neuron loss is commonly observed in the pontine nuclei, inferior olive, putamen, substantia nigra, intermediolateral nucleus of the spinal cord, and autonomic ganglia. In the cerebellar cortex, Purkinje cells are variably depleted (Fig. 4). The flocculus is typically less affected. In contrast to the Purkinje

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Fig. 1 Multiple system atrophy. The brain shows severe atrophy of the brainstem and cerebellum

Fig. 2 Multiple system atrophy. The coronal section of the cerebrum through the level of the mammillary bodies shows shrinkage with discoloration of the putamen

cell pathology, granule cells are preserved. Neuron loss may also be observed in the locus ceruleus, vestibular nuclei, Onuf’s nucleus, and sensory ganglia. A pathological hallmark of MSA is the presence of glial cytoplasmic inclusions (GCIs) in the oligodendrocytes (Fig. 5) (Papp et al. 1989; Nakazato et al. 1990). GCIs are immunohistochemically positive for α-synuclein (Fig. 6) (Arima et al. 1998; Tu et al. 1998; Wakabayashi et al. 1998) and appear in multiple brain regions

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Fig. 3 Multiple system atrophy. The midbrain shows marked depigmentation of the substantia nigra (upper panel), and the ventral pons is severely atrophic (lower panel)

including the motor cortex, cerebral white matter subjacent to the motor cortical areas, globus pallidus, internal capsule, olfactory bulbs, and reticular formation of the brainstem, as well as in the striatonigral and olivopontocerebellar systems. The optic nerve usually lacks the inclusions. Filamentous inclusions positive for α-synuclein are also found in the neuronal cytoplasm, axons, and nucleus in the affected regions (Fig. 7). It is interesting to note that Purkinje cells are excluded from the molecular pathology.

Late Cortical Cerebellar Atrophy Late cortical cerebellar atrophy (LCCA; also called late-onset cerebellar cortical atrophy (LOCA)) is a non-hereditary progressive disorder, characterized clinically by late-onset purely cerebellar ataxia (Marie et al. 1922). Grossly, the cerebellum shows atrophy of the cerebellar cortex that is usually accentuated in the superior half of the vermis. Histologically, Purkinje cell loss is predominant in this region, and the

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Fig. 4 Multiple system atrophy. Severe Purkinje cell loss is evident. Hematoxylin and eosin stain

Fig. 5 Multiple system atrophy. Glial cytoplasmic inclusions are evident in oligodendrocytes. GallyasBraak silver stain

cerebellar hemispheres are less affected. In some cases, Purkinje cell loss may involve extensive cortical regions in the vermis and hemispheres or may be predominant in the cerebellar hemispheres (Tsuchiya et al. 1994). In LCCA, it is common that neuronal loss is also noticed in the inferior olive, particularly in the dorsomedian part.

Hereditary Disorders Spinocerebellar Ataxia Type 1 Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited form of spinocerebellar degeneration caused by expansion of a CAG repeat in the SCA1

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Fig. 6 Multiple system atrophy. Glial cytoplasmic inclusions are positive for α-synuclein. Immunostain

Fig. 7 Multiple system atrophy. Accumulation of α-synuclein is evident in the cytoplasm and nuclei of neurons. Immunostain

gene localized to chromosome 6p23 (Zoghbi and Orr 1995). The numbers of CAG repeat units in patients with SCA1 range from 40 to 81 and correlate inversely with the age at onset and disease severity. The clinical features in the early stages of SCA1 are characterized by progressive ataxia, pyramidal impairment, and oculomotor palsy, followed in the later stages by amyotrophy and sensory disturbances. Cognitive function typically remains intact. Neuropathologic studies have revealed atrophy of the brainstem and spinal cord, which are more marked in patients with juvenile onset. The cerebellum may be atrophic, but the cerebrum typically appears normal. The brain weight mostly ranges from 1100 g to 1200 g (Iwabuchi et al. 1999). In the cerebellum, Purkinje cells are mildly to moderately depleted, but in some patients the cerebellar cortex appears almost normal. Torpedoes are occasionally observed in the granular layer. The cerebellar dentate nucleus also shows mild to

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moderate neuronal loss, associated with grumose degeneration, which is characterized by accumulation of numerous eosinophilic and argyrophilic granular materials around the somata and dendrites of dentate neurons. In the brainstem, neuronal loss is observed in the pontine nuclei and inferior olivary nucleus, although this is relatively mild in comparison with that found in SCA2. The substantia nigra, red nucleus, and cranial nerve nuclei including the vestibular and oculomotor nuclei are often affected. The spinal cord shows apparent neuronal loss in the anterior horn and Clarke’s column with degeneration of the spinocerebellar tracts. The posterior column shows various degrees of degeneration. In the cerebrum, no apparent change is evident in the cortex, white matter, striatum, or thalamus, although mild to moderate degeneration is often observed in the outer segment of the globus pallidus. The inner segment of the globus pallidus may be involved in some patients (Uchihara et al. 2006). Neuronal intranuclear inclusions (NIIs) are observed in broad areas of the brain (Duyckaerts et al. 1999), such as the cerebral cortex, striatum, globus pallidus, substantia nigra, pontine nuclei, reticular formation, inferior olive, dentate nucleus, and spinal anterior horn, with the highest incidence in the pontine nuclei. They are eosinophilic and spherical and present singly or occasionally in pairs in a nucleus. Their sizes may vary even in the same patient, ranging from ~1 to 3 μm in diameter. NIIs are inconspicuous using hematoxylin-eosin staining but easily detectable by immunohistochemistry for ubiquitin, ataxin-1 (a protein construct of the SCA1 gene), and expanded polyglutamine stretches using a monoclonal antibody 1C2 (Trottier et al. 1995). It should be noted that no inclusion has been found in Purkinje cells, which are an essential cell type depleted in SCA1 brains. The lack of prominent NIIs in Purkinje cells is also observed in the other CAG repeat diseases including SCA2, Machado-Joseph disease (MJD/SCA3; see below), and DRPLA (Hayashi et al. 1998; Koyano et al. 2002), even though mutant proteins accumulate diffusely in their nuclei. No inclusions have been reported in glial cells.

Spinocerebellar Ataxia Type 2 Spinocerebellar ataxia type 2 (SCA2) is a dominantly inherited neurodegenerative disease caused by expansion of a CAG repeat in the SCA2 gene localized to chromosome 12q24.1 (Pulst et al. 1996; Imbert et al. 1996; Orozco et al. 1989; Paulson et al. 1997; Sanpei et al. 1996). The numbers of CAG repeat units in patients with SCA2 range from 35 to 64. The clinical features in the early stages of SCA2 are characterized by progressive ataxia, diminished tendon reflexes, and slow eye movement, followed in the later stages by amyotrophy, sensory disturbance, involuntary movements, and mental deterioration. Neuropathologic studies have revealed atrophy of the cerebellum and pontine base. The substantia nigra is depigmented. The brain weight mostly ranges from 690 g to 1265 g (Durr et al. 1995; Iwabuchi et al. 1999; Orozco et al. 1989). In the cerebellum, Purkinje cells and granule cells are moderately to severely depleted, but the dentate nucleus is typically spared. In the brainstem, the pontine nuclei, inferior olive, and substantia nigra are severely affected. Moderate degeneration is also detected in the red nucleus. The involvement of the spinal anterior horn and dorsal column is variable.

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Mild degeneration may be encountered in the basal ganglia, thalamus, and cerebral cortex in some patients. Ataxin-2 has a cytoplasmic localization in normal brain, and the SCA2 gene is expressed in Purkinje cells and some specific groups of brainstem and cortical neurons (Huynh et al. 1999). Purkinje cells in SAC2 patients also possess many cytoplasmic granules immunopositive for ataxin-2 and expanded polyglutamine stretches (Huynh et al. 2000). These intracytoplasmic granules are negative for ubiquitin. In contrast to the other CAG repeat diseases, NII formation is not prominent in SCA2. Ubiquitinated NIIs have been found only in 1–2% of pontine neurons. They are also detectable in the other affected regions such as the substantia nigra, inferior olive, globus pallidus, and cerebral cortex, but not in Purkinje cells (Koyano et al. 1999).

Machado-Joseph Disease/Spinocerebellar Ataxia Type 3 Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3) is a dominantly inherited multisystem neurodegenerative disorder characterized by variable combinations of cerebellar ataxia, pyramidal signs, dystonic extrapyramidal symptoms, peripheral neuropathy with amyotrophy, nystagmus, eyelid retraction, external ophthalmoplegia, and facial fasciculations (Rosenberg 1992; Sudarsky and Coutinho 1995). Dystonia is often prominent in younger patients. The disorder is due to an unstable CAG repeat on chromosome 14q32.1. The numbers of CAG repeat units in patients with MJD range from 56 to 84. The brain weight of affected patients mostly ranges from 1000 to 1300 g. In most cases, there is obvious atrophy Fig. 8 Machado-Joseph disease/spinocerebellar ataxia type 3. Atrophy is evident in the brainstem. The cerebellum is relatively preserved

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Fig. 9 Machado-Joseph disease/spinocerebellar ataxia type 3. The midbrain shows marked depigmentation of the substantia nigra (upper panel). The pons shows moderate atrophy (lower panel)

of the brainstem (Fig. 8) and spinal cord, and the substantia nigra is depigmented (Fig. 9). The cerebellum may also be atrophic due to loss of white matter volume (Fig. 10). Atrophy with brownish discoloration is occasionally evident in the globus pallidus and subthalamic nucleus. The main lesions in MJD are located in the spinocerebellar system and cerebellar dentate nucleus (Iwabuchi et al. 1999; Yamada et al. 2004). In the spinal cord, Clarke’s column generally shows severe neuronal loss with marked degeneration of the spinocerebellar tracts. Severe degeneration is also detected in the anterior horn, with consequent degeneration of the anterior spinal roots and skeletal muscles of the extremities (a peripheral neuropathy is often found, with loss of large myelinated fibers). The involvement of the spinal posterior horn and dorsal column is variable and usually mild. In most cases, no apparent abnormality is detected in the corticospinal tract. In the brainstem, mild to moderate neuronal loss is detectable in the pontine nuclei, with accentuation in the caudal region. Neuronal depletion is also evident in the substantia nigra, reticular formation, accessory cuneate nucleus, and cranial nerve nuclei, including the nuclei of the external ocular muscles, and hypoglossal and vestibular nuclei. Although variable degrees of degeneration may be present in the red and dorsal column nuclei, the inferior olive is typically spared. The cerebellar cortical neurons are preserved in

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Fig. 10 Machado-Joseph disease/spinocerebellar ataxia type 3. The cerebellar hemisphere shows diffuse myelin pallor in the white matter. Klüver-Barrera stain

most cases, but minimal loss of Purkinje cells and occasional torpedoes are encountered in some patients. The cerebellar white matter is atrophic and shows myelin pallor due to degeneration of the pontocerebellar and spinocerebellar fibers. The dentate nucleus shows moderate to severe loss of neurons with grumose degeneration. In the globus pallidus, the internal segment is more severely affected. Severe neuronal loss is also detectable in the subthalamic nucleus. The thalamus may display mild degeneration, especially in the centromedian nucleus; however, no significant degeneration is detected in the striatum or cerebral cortex. NII formation is found in the affected brain regions (Fig. 11) and shows a relatively high incidence among the CAG repeat diseases (Paulson et al. 1997; Schmidt et al. 1998). In addition, as in other polyglutamine disorders, NIIs are detectable in other regions including the cerebral cortex, thalamus (especially the intralaminar nucleus), striatum, lateral geniculate body, inferior olive, and dorsal root and sympathetic ganglia (Yamada et al. 2001a, 2004). The distribution is generally wider in patients with a longer expansion of the CAG repeat. No inclusion has been observed in Purkinje cells (Koyano et al. 2002; Yamada et al. 2004). NIIs are spherical and eosinophilic and vary in size from ~1 to 4 μm. They are present in the nucleus as a single structure or frequently as doublets. Immunohistochemistry reveals that NIIs are positive for ubiquitin, ataxin-3, expanded polyglutamine stretches, and several transcription factors. Ultrastructurally, NIIs are non-membrane bound and contain a mixture of granular and filamentous structures, the latter being approximately ~12 to 15 nm in diameter and organized in random but sometimes parallel arrays. There is a relationship between NIIs and nuclear structures such as promyelocytic leukemia protein nuclear bodies and coiled bodies (Yamada et al. 2001a). The widespread occurrence of NIIs suggests that neurons are affected in the polyglutamine pathogenesis of MJD to a much greater extent than has been recognized by conventional neuropathologic studies. A neuropathologic study of a MJD patient, who was suspected to have died at an early stage of the

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Fig. 11 Machado-Joseph disease/spinocerebellar ataxia type 3. Intranuclear inclusions are evident in neurons of the pontine nuclei. Immunostain for expanded polyglutamine stretches with 1C2 monoclonal antibody

disease, indicated that extensive formation of NIIs may be an early pathologic change and that NII formation is related to phenotypic expression in the disease (Yamada et al. 2004). In contrast to the frequent formation of NIIs, diffuse nuclear immunolabeling for expanded polyglutamine stretches is a rare finding in MJD brains. In addition to NIIs, affected neurons possess many cytoplasmic granules immunolabeled with 1C2. Electron microscopy has shown that the granules are a subset of lysosomes (Yamada et al. 2002c). The appearance of this cytoplasmic pathology involves many brain regions with a distribution pattern generally similar to that of NII, suggesting that mutant proteins in the MJD brain are involved in both the ubiquitin/proteasome and endosomal/lysosomal pathways for protein degradation in different intraneuronal compartments. The cytoplasmic pathology is also observed in Purkinje cells of SCA6 but absent in SCA17. No pathologic changes related to polyglutamine pathology have been reported in glial cells or visceral organs.

Spinocerebellar Ataxia Type 6 Spinocerebellar ataxia type 6 (SCA6) is an autosomal dominant neurodegenerative disorder caused by expansion of a CAG repeat in the α1Α voltage-dependent calcium channel gene (Zhuchenko et al. 1997; Ishikawa et al. 1997; Ikeuchi et al. 1997). The number of CAG repeats in SCA6 patients ranges from 20 to 33. It should be noted that CAG repeat expansion in SCA6 is smaller than usual lengths of CAG repeats in other polyglutamine diseases. The main clinical feature is characterized by late-onset rather pure cerebellar ataxia. Grossly, there is marked atrophy in the cerebellum. The other brain regions and the spinal cord are usually spared (Ishikawa et al. 1999). Histologically, severe Purkinje cell loss with Bergmann’s gliosis is a consistent feature in the cerebellum. The loss is typically conspicuous in the cerebellar vermis, especially in the superior vermis. The cerebellar hemispheres show milder loss of the cell type. Granule cells are also

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affected, although the degree is milder than that of Purkinje cells. The dentate nucleus is usually spared, although some gliosis may be observed as a consequence of the deafferentation. Mild degeneration of the inferior olive may be seen in some patients (“cerebello-olivary atrophy”). Small aggregates immunopositive for expanded polyglutamine stretches are present mainly in the cytoplasm but also in the nuclei of Purkinje cells (Ishikawa et al. 2001).

Spinocerebellar Ataxia Type 7 Spinocerebellar ataxia type 7 (SCA7) is a dominantly inherited spinocerebellar degeneration characterized by retinal-cerebellar atrophy and caused by expansion of a CAG repeat in the SCA7 gene localized to chromosome 3p12–13 (Enevoldson et al. 1994; Gouw et al. 1994, 1995; Holmberg et al. 1995; Martin et al. 1994; Neetens et al. 1990). The SCA7 repeat is one of the most unstable CAG repeats known, and the number of repeats in patients ranges from 38 to 460 (van de Warrenburg et al. 2001). There is a marked variability in age at onset and severity of the symptoms. The main clinical features include a decrease of visual acuity, progressive cerebellar ataxia, dysarthria, and dysphagia. Typically, no dementia or epilepsy is noted. Patients with extremely long CAG repeat stretches show juvenile or infantile onset, more rapid disease progression, and a broader spectrum of phenotypes than those with the adult onset form. Although the SCA7 gene products are expressed throughout the brain and retina, neurodegeneration is restricted in some regions. Grossly, the brains of SCA7 patients show atrophy of the optic pathways and cerebellum. Histologically, the retinas disclose severe degeneration of the pigmented epithelium and loss of photoreceptors, bipolar cells and ganglion cells, with consecutive transneuronal degeneration from the optic nerves to optic radiations including the lateral geniculate bodies. In the cerebellum, degeneration is observed in the cortex (Purkinje cell dominant), spinocerebellar and olivocerebellar tracts, and dentate nucleus. Although the inferior olive is generally involved, the degeneration of the pontocerebellopetal system is variable. The pyramidal pathways and motor neurons in the brainstem and spinal cord (spinocerebellar tracts, dorsal columns) are also affected. Degeneration may be evident in the subthalamic nucleus, globus pallidus, and substantia nigra in some patients. The cerebral cortex and thalamus are typically free from degeneration. NIIs are detected in the affected brain regions with a relatively high incidence in the inferior olive (Holmberg et al. 1998). Interestingly, NIIs are also observed in areas of the cerebral cortex such as the supramarginal gyrus and insula. In addition to NIIs, 1C2 immunostaining reveals cytoplasmic granular staining in neurons in some brain regions including the supramarginal gyrus, hippocampus, thalamus, geniculate body, and pontine nuclei, and is not always dependent on NII formation. No pathologic changes are detectable in glial cells. In spite of the severe phenotype, infantile-onset SCA7 patients show relatively limited neuronal degeneration in the cerebellum and retina (Carpenter and Schumacher 1966; de Jong et al. 1980; Ryan et al. 1975; Traboulsi et al. 1988).

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Spinocerebellar Ataxia Type 8 Spinocerebellar ataxia type 8 (SCA8) is a hereditary neurodegenerative disorder caused by expansion of a CTG repeat in the 30 untranslated region of a gene localized to chromosome 13q21 (Koob et al. 1999). Affected individuals show progressive gait and limb ataxia, dysarthria, and nystagmus, with variable ages at onset (Day et al. 2000; Ikeda et al. 2000). Neuropathologic studies have revealed relatively pure atrophy of the cerebellum (Ito et al. 2006). Histologically, severe loss of Purkinje cells is the most prominent finding. The remaining Purkinje cells are atrophic and occasionally show somatic sprouts. Neuronal loss is also detectable in the inferior olive and substantia nigra. Although SCA8 is not a CAG repeat disease, it is interesting that 1C2-positive intranuclear inclusions and pan-nuclear staining are found in Purkinje, medullary, and dentate neurons from human SCA8 brains (Moseley et al. 2006). These inclusions are also positive for ubiquitin. 1C2-positive granular structures are detected in the cytoplasm of Purkinje cells (Ito et al. 2006). Glial cell involvement is not seen. Spinocerebellar Ataxia Type 31 Spinocerebellar ataxia type 31 (SCA31) is a form of spinocerebellar ataxia common in Japan and clinically characterized by late-onset purely cerebellar ataxia (Ishikawa and Mizusawa 2010). The disorder is due to an insertion consisting of pentanucleotide repeats including a long (TGGAA)n stretch in an intron of BEAN (brain expressed, associated with Nedd4) on chromosome 16q21-q22 (Sato et al. 2009). Grossly, brains of SCA31 patients show obvious atrophy of the cerebellum. The cerebrum and brainstem appear normal. Histologically, the cerebellum shows moderate to severe loss of Purkinje cells. In contrast to the other spinocerebellar ataxias, it is remarkable that the remaining Purkinje cells in SCA31 are associated with a peculiar eosinophilic structure which is surrounding Purkinje cell bodies (Fig. 12). The centered Purkinje cells are often shrunken. Immunohistochemically, it has been Fig. 12 The chromosome 16q-linked autosomal dominant cerebellar ataxia/ spinocerebellar ataxia type 31. A peculiar eosinophilic structure (arrow) is evident around the Purkinje cell body. Hematoxylin and eosin stain

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demonstrated that the eosinophilic structure is mainly composed of somatic sprouts of Purkinje cells and presynaptic terminals of unknown origin. Astrocytic processes are present at the outside margin of the structure.

Dentatorubral-Pallidoluysian Atrophy Dentatorubral-pallidoluysian atrophy (DRPLA) is an autosomal dominant neurodegenerative disorder caused by expansion of a CAG repeat in the DRPLA gene located on chromosome 12p13.31. The number of CAG repeat units in DRPLA patients ranges from 49 to 84. Intergenerational instability is more pronounced in paternal transmission. DRPLA patients show various symptoms, such as myoclonus, epilepsy, ataxia, choreoathetosis, and dementia, and the combinations of these symptoms depend on the age at onset (Naito 1990). Patients with earlier onset (generally below the age of 20 years) show progressive myoclonus, epilepsy, and mental retardation (juvenile type, as classified by Naito). Patients showing late disease onset (over the age of 40 years) predominantly show cerebellar ataxia and dementia (late-adult type). Patients in whom the disease appears between the third and fifth decades belong to an intermediate type and usually show ataxia and choreoathetosis (early-adult type). There is a reverse correlation between the age at onset and CAG repeat length. In contrast to the considerable heterogeneity in clinical presentation, the neuropathology of the DRPLA brain shows a relatively uniform pattern of lesion distribution, with combined degeneration of the dentatorubral and Fig. 13 Dentatorubralpallidoluysian atrophy. The brainstem and cerebellum are atrophic

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pallidoluysian systems (Fig. 13). The globus pallidus and subthalamic nucleus (Luys’ body) show consistent loss of neurons with astrocytic gliosis. In the globus pallidus, neuronal depletion is more severe in the lateral segment than in the medial segment. The dentate nucleus also shows loss of neurons, and the remaining atrophic neurons frequently exhibit grumose degeneration. Degeneration of the red nucleus is typically mild. In general, pallidoluysian degeneration is more marked than that of the dentatorubral systems in the juvenile type, and the reverse situation is observed in the late-adult type. Mild degeneration may be seen in the cerebral cortex, especially in patients showing juvenile onset. In the case of infantile onset with 80 CAG repeats, neuronal depletion occurs in multiple brain regions including the cerebral cortex, striatum, inferior olive, and cerebellar cortex (Ohama et al. 1995). Diffuse myelin pallor of the cerebral and cerebellar white matter is often reported in aged patients. Morphometric analysis has revealed a decreased number of glial cells in the affected white matter (Yamada et al. 2002b). Despite the restricted nature of the brain lesions, it is characteristic that the amount of central nervous system (CNS) tissue is significantly reduced throughout the brain and spinal cord. Brain weights of DRPLA patients often become less than 1000 g (Naito and Oyanagi 1982). Most of the brain regions lacking obvious neuronal loss show an increase of neuronal density due to atrophy of the neuropil. Thickening of the cranium is often observed in patients with juvenile onset. NII formation in the DRPLA brain is not restricted to the dentatorubral and pallidoluysian systems, but involves multiple regions including the cerebral cortex, substantia nigra, and pontine nuclei (Yamada et al. 2002a). Although the distribution is widespread, the incidence of neurons with inclusions is relatively low and ranges from ~1 to 3% even in the dentate nucleus. NIIs in DRPLA are immunohistochemically positive for atrophin-1, expanded polyglutamine stretches, ubiquitin, and transcription factors (Yamada et al. 2001b, c). Intranuclear inclusions are also detectable in glial cells (Hayashi et al. 1998; Yamada et al. 2002b), as well as in Fig. 14 Dentatorubralpallidoluysian atrophy. Mutant proteins with expanded polyglutamine stretches are diffusely accumulated in the neuronal nuclei of the cerebellar dentate nucleus. Arrows indicate intranuclear inclusions. Immunostain for expanded polyglutamine stretches with 1C2 monoclonal antibody

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non-neuronal tissues such as the kidney and pancreas (Yamada et al. 2001b). Immunohistochemistry with 1C2 antibody shows that diffuse accumulation of mutant atrophin-1 in neuronal nuclei is the predominant pathologic condition (Fig. 14), rather than NII formation, and involves a wide range of CNS regions including the dentatorubral and pallidoluysian systems (Yamada et al. 2001b). The extent and frequency of neurons showing the diffuse nuclear pathology changes markedly and strikingly depending on the CAG repeat length, suggesting that neuronal dysfunction caused by mutant protein accumulation, rather than neuronal depletion, is responsible for the development of various clinical features in DRPLA. Neuronal nuclei with accumulation of mutant atrophin-1 show deformity with marked nuclear membrane indentations (Takahashi et al. 2001). Immunohistochemistry with 1C2 antibody also reveals the presence of granular staining in the neuronal cytoplasm, with a distribution pattern resembling that of diffuse nuclear staining (Yamada et al. 2004). In addition to NII formation, filamentous inclusions are also observed exclusively in the cytoplasm of dentate nucleus neurons (Fig. 15) (Yamada et al. 2000). The morphology of these structures is indistinguishable from the skein-like inclusions observed in motor neurons in amyotrophic lateral sclerosis; however, they are immunohistochemically positive for atrophin-1, expanded polyglutamine stretches, and ubiquitin, but negative for TDP-43, the TAR DNA-binding protein 43. Light and electron microscopic features of NIIs in DRPLA are essentially similar to those of MJD.

Friedreich’s Ataxia Friedreich’s ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by homozygous expansion of GAA repeats in the frataxin gene located on chromosome 9q13–21.1. The number of GAA repeat units in FRDA patients ranges from 120 to 1700. Compound heterozygotes have one expansion and one point mutation. Symptoms of FRDA usually appear around the beginning of the second decade of life and include ataxia, sensory loss, and muscle weakness, as Fig. 15 Filamentous inclusion positive for expanded polyglutamine stretches (arrow) is evident in the neuronal cytoplasm of the cerebellar dentate nucleus. Immunostain for expanded polyglutamine stretches with 1C2 monoclonal antibody

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well as the common signs of scoliosis, foot deformity, and hypertrophic cardiomyopathy (Pandolfo 2009). Diabetes may be developed in some patients. Grossly, the spinal cords of FRDA patients are usually small, with atrophy of the posterior nerve roots. Both the transverse and anteroposterior diameters of the spinal cord are reduced. Histologically, the spinal cord shows marked degeneration of the posterior columns and corticospinal tracts. There is severe loss of neurons in the Clarke’s column with degeneration of the dorsal spinocerebellar tracts. The accessory cuneate nucleus in the medulla also shows severe loss of neurons, with degeneration of the ventral spinocerebellar tracts. The neuronopathy in the dorsal root ganglia causes the loss of the peripheral sensory nerve fibers. Cranial nerves, such as the trigeminal, glossopharyngeal, and vagus nerves, are also affected. Purkinje cell loss is usually minimal, but neuron loss is detectable in the cerebellar dentate nucleus. In advanced cases, the superior cerebellar peduncles are thinned. The inferior olivary nuclei are preserved. Most patients exhibit loss of the Betz and other pyramidal neurons in the motor cortex. Degeneration may be evident in the subthalamic nucleus, globus pallidus (the external segment), substantia nigra, auditory nuclei, and retinal ganglion cells (Pandolfo 2008).

Early-Onset Ataxia with Ocular Motor Apraxia and Hypoalbuminemia/ Ataxia-Oculomotor Apraxia Type 1 Early-onset ataxia with ocular motor apraxia and hypoalbuminemia/ataxiaoculomotor apraxia type 1 (EAOH/AOA1) is an autosomal recessive hereditary ataxia caused by mutations in the APTX (Date et al. 2001; Moreira et al. 2001). EAOH/AOA1 is characterized by early-onset slowly progressive ataxia, ocular motor apraxia, peripheral neuropathy, and hypoalbuminemia. MRI imaging exhibits atrophy of the cerebellum, particularly of the cerebellar vermis. Neuropathologically, the cerebellum shows marked atrophy (Fig. 16), and severe Purkinje cell loss is the most characteristic feature in the brains of EAOH/AOA1 (Fig. 17). The loss is more accentuated in the cerebellar vermis. Degeneration is also apparent in the posterior columns and spinocerebellar tracts (Fig. 18). Neuron loss is detectable in the spinal anterior horns and dorsal root ganglia. There are no obvious pathologic changes in the cerebral cortex or basal ganglia. No inclusions have been reported in neurons or glial cells (Tada et al. 2010). Marinesco-Sjo¨gren Syndrome Marinesco-Sjögren syndrome is an autosomal recessive disorder characterized by cerebellar ataxia, cataracts, intellectual disability, and progressive muscle weakness and caused by mutations in SIL1 (Goto et al. 2014). The autopsy brain shows atrophy of the cerebellum, brain stem tegmentum, and optic nerves (Sakai et al. 2008). Histologically, the cerebellum shows severe loss of Purkinje cells (Fig. 19). The cerebellar granule cells may be affected. There are also abnormalities in the retinal ganglion cells and cytoarchitecture in the cerebral cortex. The skeletal muscles in the extremities show myogenic changes with the formation of rimmed vacuoles.

2632 Fig. 16 Early-onset ataxia with ocular motor apraxia and hypoalbuminemia/ataxiaoculomotor apraxia type 1. The cerebellum is severely atrophic

Fig. 17 Early-onset ataxia with ocular motor apraxia and hypoalbuminemia/ataxiaoculomotor apraxia type 1. The cerebellar cortex shows severe Purkinje cell loss. Hematoxylin and eosin stain

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Fig. 18 Early-onset ataxia with ocular motor apraxia and hypoalbuminemia/ataxiaoculomotor apraxia type 1. Degeneration is evident in the posterior columns and spinocerebellar tracts. The corticospinal tracts are also affected. Klüver-Barrera stain

Fig. 19 Marinesco-Sjögren syndrome. The cerebellum shows severe loss of Purkinje cells

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Conclusions and Future Directions The discovery of causative proteins or gene mutations has triggered the development of novel neuropathology in spinocerebellar degenerations. It is now likely that the dynamics of the molecular-dependent lesion distribution may be responsible for a variety of clinical phenotypes in ataxic diseases. To understand the pathogenesis of each disease, it will be necessary to clarify the pivotal role of the molecular pathology in the development of selective neuronal degeneration in the central nervous system.

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General Predictions of Functional Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medical Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Idebenone in Friedreich’s Ataxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Riluzole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acetylleucine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aminopyridines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cognitive Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Motor Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impairments in Motor Performance and the Adaptation of Movements . . . . . . . . . . . . . . . . . . Animal Cerebellar Lesion Models Indicate Long-Term Adaptation and Effects of Motor Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Motor Rehabilitation in Human Cerebellar Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current Praxis of Motor Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Open Questions in Cerebellar Motor Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Studies on Mechanisms of Motor Adaptation and Motor Rehabilitation . . . . . . . . . . Conclusions and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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W. Ilg (*) Section Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany e-mail: [email protected] D. Timmann Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_105

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Abstract

Cerebellar disorders primarily affect motor functions and can lead to significant and serious restrictions in activities of daily living. Possibilities for medical interventions are rare and limited to specific diseases and symptoms. Furthermore, motor rehabilitation for patients suffering from cerebellar damage is challenging, since the cerebellum is known to play an important role for the execution as well as for the (re)-learning of precise movements. This chapter reviews the current state of the art in medical intervention and rehabilitation, focusing on presenting new results on motor rehabilitation in cerebellar disease. Recent studies indicate that even in the case of degenerative cerebellar diseases, intensive and continuous motor training can reduce ataxia symptoms and increase motor performance relevant to daily living. In addition, current studies in the area of motor learning – in combination with modern imaging techniques – in cerebellar disease are described. These results offer promising perspectives for a deeper understanding of remaining motor learning capacities in cerebellar disease and thus might help in the future to optimize motor rehabilitation for individual patients. Keywords

Motor rehabilitation · Motor adaptation · Motor learning · Dynamic balance · Multi-joint coordination · Physiotherapy · Treadmill training · Walking aids · Medical intervention · Cognitive rehabilitation · Internal models · Degenerative disease · Continuous training · Visoumotor adaptation · SARA · ICARS · Everyday living · Cerebellar ataxia · Ataxic gait · Dysmetria · Movement disorder · Balance disorder · Riluzole · Idebenone · Friedreich’s ataxia · Recovery · Short-term adaptation · Long-term adaptation · Aminopyridines · Learning strategies · Compensatory strategies · Spinocerebellar ataxia · Downbeat nystagmus · Quality of life · Resting state analysis · Deep cerebellar nuclei · Dyssynergia · Cerebellar tremor · Exergames · Preclinical ataxia

Introduction Cerebellar dysfunction can induce a variety of motor impairments including ataxia of upper and lower limb movements, disordered oculomotor control, dysarthria, and ataxia of stance and gait (Diener and Dichgans 1996; Holmes 1939; Bastian 1997, 2011; Bodranghien et al. 2016). There are various causes of cerebellar disease, including stroke, cerebellar tumors, multiple sclerosis, and degenerative disease. Functional recovery heavily depends on the cause and site of the lesion. Within this spectrum, degenerative cerebellar diseases are especially hard to treat, since – despite greatly improved understanding of the genetic underpinnings (Schöls et al. 2004; Klockgether 2011) – no cure or drug treatments to ameliorate ataxia or decelerate disease progression are yet available. Genetic therapies are currently developed for a subset of hereditary ataxias, but will be available only in the future

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(Scoles and Pulst 2018). Furthermore, motor rehabilitation is also challenging for this patient population, since the cerebellum is known to play an important role in motor learning. Therefore, poor recovery or low benefit of physiotherapeutic training may be a consequence of damaging structures critically involved in relearning of motor skills (Thach and Bastian 2004; Bastian 2006). However, more recent results deliver pieces of evidence that patients with degenerative cerebellar diseases can benefit from intensive and continuous motor training. This chapter will review the state of the art of medical intervention and rehabilitation, focusing on new results and developments in the field of motor rehabilitation and motor adaptation in cerebellar disease.

General Predictions of Functional Recovery The cause, site, and extent of brain lesions are generally thought to be important predictors of the degree of functional recovery. For example, functional deficits seem more marked following a hemorrhage compared to an ischemic infarct, but have better chances of recovery if survived. Outcome has only been systematically studied in cerebral hemorrhage, but is likely the same if the hemorrhage occurs within the cerebellum (Weimar et al. 2003). In focal cerebellar lesions, either due to tumor surgery or stroke, lesion site appears to be more important than extent. Lesion extent does not predict long-term outcome. Rather, functional recovery is worse in lesions affecting the deep cerebellar nuclei and its output pathway, the superior cerebellar peduncles (Schoch et al. 2006; Konczak et al. 2005; Kelly et al. 2001). Because the latter are almost exclusively supplied by the superior cerebellar artery (Amarenco 1991), stroke in the territory of the superior cerebellar artery seem to have a worse prognosis than stroke affecting the posterior and anterior inferior cerebellar arteries. Furthermore, additional extra-cerebellar stroke lesions involving the cerebral hemispheres or brain stem also negatively affect recovery of walking and other functional capacities after stroke (Gialanella et al. 2005). In progressive degenerative cerebellar ataxias, neuronal loss is caused by genetic factors with autosomal dominant inheritance as in the spinocerebellar ataxias (SCA) (Schöls et al. 2004) or a recessive trait like in Friedreich’s ataxia (FA) (Durr et al. 1996). An increasing number of mutations underlying autosomal recessive ataxias have been identified in recent years (Fogel 2018). On the other hand, many sporadic cases of cerebellar degeneration escape the detection of causative factors and are currently classified as sporadic adult-onset ataxia of unknown etiology (SAOA) (Klockgether 2010). Advances in genetics have shown that a small fraction of the SAOAs are caused by genetic disease in particular late-onset recessive ataxias (Giordano et al. 2017). Others turn into multiple system atrophy of the cerebellar type (MSA-C) during the course of the disease. Although clinical presentation is variable in many subtypes, SCA and SAOA mostly present with predominantly cerebellar ataxia, whereas in FA afferent deficits are generally the major cause of ataxia. In general, degenerative ataxias seem to be the most difficult group of ataxias to treat, due to the progressive nature. In addition, virtually all parts of the cerebellum

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are affected, although degeneration is frequently most prominent in the midline (Schulz et al. 2010; Hulst et al. 2015). In contrast, ataxia following stroke, neurosurgery, or trauma affects only circumscribed regions of the cerebellum, but leaves other regions intact. These regions may compensate for the defective parts. In addition, in the case of focal lesions, effects of neural plasticity are likely more effective because there is no competition with ongoing progressive neurodegeneration. Whereas patients with focal lesions clearly improve in motor functions over time, patients with degeneration slowly deteriorate (Schoch et al. 2007). Thus, in patients with progressive degenerative diseases, it would be a major achievement if they stayed on the current status of motor function as long as possible or progression of functional impairment was slowed down. In patients with focal lesions, on the other hand, it is currently unknown to what extent functional improvement is due to spontaneous recovery or interventions like physiotherapeutical training.

Medical Intervention Medication is of restricted use in cerebellar ataxia. Focal cerebellar disorders, such as cerebellar stroke, tumors, or lesions in multiple sclerosis, are treated according to the respective evidence-based clinical practice guidelines. Causal treatment of cerebellar degenerations is not available with the rare exceptions of a few, autosomal recessive ataxias with known metabolic defects (Fogel and Perlman 2007; Jinnah et al. 2018). As yet, no medication is known which ameliorates the clinical symptoms of cerebellar ataxia except treatment of attacks in episodic ataxias and treatment of downbeat nystagmus (Giordano et al. 2013) (see section “Aminopyridines”). In contrast, standard medications are available to treat accompanying extra-cerebellar symptoms in degenerative cerebellar disease such as extrapyramidal disorders, bladder dysfunction, and migraine. Over the years, a number of different drugs have been tested for symptomatic treatment of cerebellar ataxia (see for reviews: Trujillo-Martin et al. 2009; Revuelta and Wilmot 2010; Zesiewicz et al. 2018; Ilg et al. 2014). Many studies describing positive effects were open-label trials and performed in a small number of patients. As yet, most of these positive effects could not be replicated in subsequent studies using larger patient populations and a randomized placebo-controlled double-blind clinical trial design. Noneffective treatments include serotonergic drugs (5-hydroxytryptophan and buspirone), nutritional supplements (creatine and L-carnitine), antioxidants (vitamin E, coenzyme Q10, idebenone), and others (amantadine, gabapentin, lithium in SCA3, deferiprone, and erythropoietin in Friedreich’s ataxia). Different antiepileptic drugs have been tried to treat cerebellar tremor, for example, clonazepam, levetiracetam, primidone, and topiramate. None showed clear effects. In more recent years, idebenone in Friedreich’ ataxia, riluzole, acetylleucine, and aminopyridines have been in the focus of interest as possible treatment options in cerebellar ataxia. Their possible therapeutical indications and results of drug trials will be discussed in more detail.

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Idebenone in Friedreich’s Ataxia Idebenone, a short-chain derivative of coenzyme Q10, is both an antioxidant and electron carrier and is therefore thought of particular help in Friedreich’s ataxia (Schulz et al. 2009; Mancuso et al. 2010). A number of studies showed that echocardiographic parameters of cardiac hypertrophy improved using conventional doses of idebenone (Mariotti et al. 2003). A more recent study suggested that high dosages may also ameliorate neurological symptoms (Di Prospero et al. 2007). However, the results of two subsequent phase III randomized placebo-controlled double-blind drug trials in comparatively large study populations failed to support the effectiveness of high-dosage idebenone both for neurological and cardiac study endpoints (Lagedrost et al. 2011; Lynch et al. 2010). Thus, different to initial belief, idebenone (and other antioxidant therapies) does not appear a treatment option in Friedreich’s ataxia. Based on the known pathomechanisms of the disease, other treatment options are currently evaluated or developed, such as agents to increase the frataxin level (histone deacetylase inhibitors, e.g., nicotinamide; Libri et al. 2014), and other gene-based strategies (Strawser et al. 2017). As yet, an effective medical treatment of Friedreich’s ataxia is lacking.

Riluzole Riluzole is thought to be a neuroprotective agent that has been administered in different neurodegenerative disorders with varying success. Using a randomized, placebo-controlled, and double-blind study design, Ristori et al. (2010) found positive effects in 38 patients with various forms of chronic ataxias. 50 mg of riluzole given twice daily was followed by significant effects on a clinical ataxia rating score (ICARS) after 8 weeks of treatment. These results were not confirmed in a second study of the same group in a more homogeneous study population including 55 patients with spinocerebellar ataxias (most of them SCA1 or SCA2) or Friedreich’s ataxia (Romano et al. 2015). In this study, patients were treated for 1 year. Although a significant improvement after 8 weeks was not found, after 1 year of treatment, half of the treated patient population showed a mild benefit based on a clinical ataxia rating scale. Results showed a large variability and need to be confirmed in future studies. Of note, a previous study in a large group of patients with MSA (almost 400; most of them suffering from MSA-P) did not show any beneficial effects, neither on ameliorating symptoms nor in slowing the disease (Bensimon et al. 2009).

Acetylleucine The amino acid acetyl-DL-leucine has been shown to act on vestibular neurons in animal studies. Because of the known interactions between the cerebellum and the vestibular system, it has been suggested to be a potential candidate to treat ataxia. As

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yet, however, findings in open-label case series are contradictory (Strupp et al. 2013; Pelz et al. 2015). Furthermore, no beneficial effects were observed in the cerebellar type of multiple system atrophy (Scigliuolo et al. 2017). Results of a larger, controlled study have not been published as yet (Feil et al. 2017).

Aminopyridines In recent studies aminopyridines proved to be effective in treating both episodic ataxia type 2 (EA2) and downbeat nystagmus (Strupp et al. 2017 for review). Aminopyridines are potassium channel blockers, which were commonly believed to increase the inhibitory drive of cerebellar Purkinje cells. According to animal data, they restore the diminished precision of pacemaking in Purkinje cells (Alvina and Khodakhah 2010). Both 4-aminopyridine and 3,4 diaminopyridine have been used, and, except for differences in dosages, effects appear to be the same. In EA2 acetazolamide is long been known to reduce attacks (Griggs et al. 1978). 4-Aminopyridine is a useful alternative in cases where acetazolamide lost its effect or severe side effects occur (e.g., recurrent kidney stones). 4-Aminopyridine and dalfampridine have been shown both to reduce attacks (Strupp et al. 2011; Claassen et al. 2013) and to ameliorate interictal cerebellar signs (Schniepp et al. 2011). Results of a controlled study should be soon available which compared fampridine versus acetazolamide versus placebo (EAT2TREAT; 2013-000107-17, www. clinicaltrialsregister.eu). Downbeat nystagmus (DBN) leads to unsteadiness of gait and vertigo. Blurred vision and oscillopsia are additional symptoms (Strupp and Brandt 2009). Idiopathic DBN refers to cases with unknown etiology and secondary DBN to cases with known etiology. Secondary DBN is most frequently due to cerebellar degeneration. 3,4-Diaminopyridine reduces DBN in approximately 50% of the patients (Strupp et al. 2003). Treatment worked best in patients without structural lesions of the cerebellum and brain stem (i.e., idiopathic DBN). Positive effects have also been described in SCA6 and other hereditary ataxias (Tsunemi et al. 2010). Upbeat nystagmus is a less common type of nystagmus in cerebellar degeneration. 4-Aminopyridine appears to be effective (Glasauer et al. 2005). As yet, there is no convincing evidence that aminopyridines ameliorate accompanying ataxic symptoms. Results are contradictory in the literature (Sprenger et al. 2005; Tsunemi et al. 2010; Giordano et al. 2013). As yet, results of a larger, controlled study are lacking, but should be available soon (FACEG study comparing fampridine versus placebo; 2012-005312-26, www.clinicaltrialsregister.eu). Use of aminopyridines is off-label. A retarded form of 4-aminopyridine has been approved as Ampyra ® (fampridine) for treatment of gait disorders in multiple sclerosis in the United States in 2009. 3,4-Diaminopyridine has been approved as Firdapse ® (amifampridine) for treatment of Lambert-Eaton syndrome in Europe in 2010. Treatment is generally well tolerated. Similar to acetazolamide transient perioral or digital paraesthesias, headache and nausea are possible side effects. In higher dosages, aminopyridines can cause cardiac arrhythmias and seizures.

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Cognitive Rehabilitation Neuroanatomical, functional imaging and human lesion studies suggest involvement of the cerebellum in cognitive function (Stoodley and Schmahmann 2009; Strick et al. 2009; Koziol et al. 2014; Sokolov et al. 2017). In addition, many degenerative cerebellar disorders with extra-cerebellar involvement present with neuropsychological abnormalities (Burk 2007). The cerebellum appears to contribute particularly to executive functions and language. Deficits are more marked in acute than in chronic disease. Whereas dysfunction is generally subtle in adults with chronic cerebellar disease and appears more marked in childhood disorders, significant intellectual disability is reported in pre- and perinatal cerebellar disorders (Timmann and Daum 2010 for review). Thus, neuropsychological assessment should be part of the clinical workup in patients with cerebellar disorders, in particular in children and acute disease, e.g., using a recently published bedside screening test in cerebellar disease (Hoche et al. 2018). Cognitive dysfunction may require rehabilitation. As yet, however, studies examining the effect of neuropsychological training in cerebellar disease are sparse. Two case reports in patients suffering from acute cerebellar hemorrhage report no or modest improvement of executive functions following cognitive training (Maeshima and Osawa 2007; Schweizer et al. 2008), whereas Ruffieux et al. (2017) reported improvement in a case suffering from acute cerebellar hemorrhage. In contrast, remarkable improvement of executive dysfunction was observed in patients with acute ischemic stroke regardless whether cognitive training was administered or not (Pierscianek et al. 2007). Systematical studies are clearly required to establish which method improves Schmahmann’s syndrome and its numerous impacts on daily life (van Dun et al. 2018).

Motor Rehabilitation Impairments in Motor Performance and the Adaptation of Movements The cerebellum is involved in the control of various kinds of motor behavior such as speech, oculomotor control, limb movements, and balance. The functional role of the cerebellum is not the generation but more the shaping and fine-tuning of movements. Therefore, cerebellar damage does not cause loss of movement, but instead leads to abnormalities in movement characterized by increased variability and poor accuracy (Bastian 2006). In the case of limb movements, and in particular goaldirected movements of the upper extremities, typical ataxia symptoms are dysmetria (hypermetria and hypometria), cerebellar tremor, and dyssynergia, the lost ability to move joints simultaneously (Manto 2009; Bastian et al. 1996; Vilis and Hore 1980). In addition, the cerebellum plays a critical role in balance, postural control, and coordination of lower limb movements during gait and goal-directed

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stepping (Ilg and Timmann 2013; Morton and Bastian 2004). Therefore, gait disturbance is a major symptom of cerebellar pathology (Marquer et al. 2014). Cerebellar ataxic gait is typically characterized by an increased step width, variable foot placement, irregular foot trajectories, and a resulting instable stumbling walking path (Diener and Dichgans 1996; Morton and Bastian 2004; Holmes 1939; Ilg et al. 2007) with a high risk of falling (van de Warrenburg et al. 2005; Schniepp et al. 2016). The underlying control mechanisms for the execution of accurate movements are suggested to involve the implementation of internal forwards models involving the cerebellum, which predict sensory consequences of actions (Bastian 2006). Thus, it has been proposed that the cerebellum calculates a current “state estimate” – by combining sensory information about the last known position of the limb with predictions of its responses to recent movement commands – which is used to accurately plan and control goal-directed movements (Miall et al. 2007). Such mechanisms are of particular importance in movements in which predictive control strategies are necessary. Examples for impaired predictive control mechanisms are (i) the predictive compensation of joint interaction forces (Bastian et al. 1996), (ii) the timing and modulation of long-loop reflexes when movements are perturbed (Kurtzer et al. 2013), as well as (iii) impaired anticipatory posture adjustments and miscalibrated postural responses to external perturbations (Horak and Diener 1994; Timmann and Horak 2001). Within its functional role on shaping and fine-tuning of movements, the cerebellum is well-known to be important for the adaptation of motor patterns to changing conditions. Therefore, the internal forward models are suggested to be adapted to the new conditions by practice-dependent motor learning based on sensory prediction errors (Bastian 2006 for review). Importantly, motor adaptation to changing conditions is constantly required in everyday life, for example, by adapting arm control to its new dynamics when holding an object (e.g., a cup), adjusting grip force to an empty or full bottle, or adjusting leg control when wearing heavy shoes in winter. Impairments of cerebellar patients in (short-term) practice-dependent motor learning have been shown for various motor tasks including the adaptation of limb movements to additional loads (Ilg et al. 2008; Manto et al. 1995), visuomotor reach adaptation (Deuschl et al. 1996; Martin et al. 1996; Werner et al. 2009), force field reach adaptation (Maschke et al. 2004; Smith and Shadmehr 2005; Rabe et al. 2009), and adaptation of gait pattern to a split-belt treadmill (Morton and Bastian 2006). In addition, it has been shown that cerebellar patients are impaired in the automaticity of recently practiced movements (Lang and Bastian 2002). However, all these experiments show the impairments in shortterm motor adaptation. The capabilities of such patients to adapt or to relearn movements over a longer duration of time have not yet been examined. Thus, it remains still an open question, whether such patients have lost the ability of practice-dependent motor learning or whether they require longer-duration or higher-intensity training to learn (Morton and Bastian 2007).

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Animal Cerebellar Lesion Models Indicate Long-Term Adaptation and Effects of Motor Training Results from animal studies support the hypothesis that in spite of cerebellar impairments, especially long-term, improvements of motor functions are possible. Barash et al. (1999) studied the effects of small lesions of the oculomotor vermis which impaired the ability of monkeys to rapidly adapt saccadic eye movements. However, the capability of slow recovery from dysmetria was still preserved. Since the examined lesions were small, it is not clear whether the long-term adaptation process was accomplished by compensation of adjacent areas in the cerebellum or from other brain areas. In addition, animal studies suggest that degenerative processes in the cerebellum are decelerated by intensive motor training. Studies in rats and mice showed that motor training prevents or reduces cerebellar degeneration caused by alcoholicinduced degeneration disease, age, and also SCA 1 (mouse model) (Carro et al. 2001; Larsen et al. 2000; Fryer et al. 2011). Fuca et al. (2017) found that motor training led to increased survival of Purkinje cells and cerebellar circuitry in tambaleante mutant mice. Exercising demanding and new complex multi-joint movements appear to outperform “pure exercise” (Klintsova et al. 2004; Kleim et al. 2007; Black et al. 1990). Possible preventive training effects are likely more effective and lasting when started at an early, i.e., asymptomatic or preclinical, disease stage (Maas et al. 2015; Fuca et al. 2017).

Motor Rehabilitation in Human Cerebellar Disease Since the cerebellum has been described as one key player in learning and adaptation of motor patterns, the benefit from physiotherapeutic training has been under debate for a long time for patients with cerebellar lesions and in particular for patients suffering from degenerative cerebellar disease, (Morton and Bastian 2009) and is still not fully understood. For a long time, relatively few clinical studies have evaluated physiotherapeutic interventions in patients with cerebellar ataxia. Some of them showed benefits for retraining posture and balance control. Using increasingly demanding balance and gait tasks, improvements were reached for increased postural stability in clinical measures and less dependency on walking aids in everyday life (Gill-Body et al. 1997; Balliet et al. 1987). Locomotion training on treadmills with (Cernak et al. 2008; Freund and Stetts 2010) or without (Vaz et al. 2008) body-weight support has been proposed in particular for patients with more severe ataxia, who are not able to walk freely. However, many are single case studies with different types of cerebellar disease and severity of ataxia. This heterogeneity in patient populations made it very difficult to compare and evaluate intervention methods in existing studies. More recently, two more systematic clinical studies in larger cohorts have shown that motor rehabilitation can be beneficial to individuals with degenerative cerebellar disease (Ilg et al. 2009; Miyai et al. 2012). The benefits of intensive whole-body

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coordinative training have been demonstrated on balance and mobility function in degenerative cerebellar disease in an intraindividual case-control design (Ilg et al. 2009, 2010). Sixteen patients have been tested suffering from progressive ataxia due to cerebellar degeneration (n ¼ 10) or degeneration of afferent pathways (n ¼ 6). The physiotherapeutic program consisted of a 4-week course of intensive training with three sessions of 1 h per week. Exercises included the following categories: (1) static balance, e.g., standing on one leg; (2) dynamic balance, e.g., sidesteps, climbing stairs; (3) whole-body movements to train trunk-limb coordination; (4) steps to prevent falling and falling strategies; and (5) movements to treat or prevent contracture (see for more details Ilg et al. 2009). Results indicated a significant reduction of ataxia symptoms measured by the clinical ataxia scale SARA (Schmitz-Hübsch et al. 2006) after 4 weeks intervention. Quantitative movement analysis revealed specific improvements in dynamic balance in posture and gait as well as in intralimb coordination. Retention of effects has been shown to depend crucially on continuous training. Assessments after 12 months showed that benefits were meaningful for their everyday life in patients executing continuous motor training and persisted after 1 year, despite a gradual decline of motor performance and gradual increase of ataxia symptoms due to progression of underlying neurodegeneration (Ilg et al. 2010). Further evidence is given for the efficiency of motor rehabilitation in degenerative cerebellar disease by another study combining physiotherapy with occupational therapy (Miyai et al. 2012). In 42 patients with pure cerebellar degeneration, a 12-h intervention per week for 4 weeks revealed improvements of ataxia severity, gait speed, fall frequency, and activities of daily living measured by a Functional Independence Measure (Keith et al. 1987). Improvements were more prominent in trunk ataxia than in limb ataxia. Patients with mild ataxia severity experienced a more sustained improvement in ataxic symptoms and gait speed (Miyai et al. 2012). Although functional status tended to decline to the baseline level within 24 weeks, gains were maintained in more than half of the participants. In Keller and Bastian (2014), the feasibility of a 6-week home balance exercise program was examined. An individually designed exercise program was conducted to provide a significant challenge to the person’s balance. Improvement was observed in locomotor performance in people with cerebellar ataxia. First evidence is delivered by the study of Milne et al. (2017) that ambulant or non-ambulant individuals with Friedreich’s ataxia can profit from a 6-week outpatient rehabilitation program. The program consisted of 2–3 h of physiotherapy, supervised gym exercises, and aquatic physiotherapy, three times per week. A 6-week home exercise program followed the rehabilitation. Change in the Friedreich Ataxia Impact Scale body movement subscale (Cano et al. 2009) indicated a significant improvement in health and well-being in the intervention group compared to the control group. In order to develop a rehabilitation program which motivates in particular children with ataxia to train their motor performance intensively and continuously over a long period of time, exergames were examined by Ilg et al. (2012). Ten children with progressive spinocerebellar ataxia trained 8 weeks with three Microsoft Xbox Kinect ® video games. The strategy of the videogame-based training aimed to train

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motor capacities like goal-directed limb movements, dynamic balance, and wholebody coordination (Fig. 1c, d). Assessment revealed a reduction in ataxia symptoms by ~2 points on average in the SARA ataxia score (Schmitz-Hübsch et al. 2006) after 8 weeks. The improvement in ataxia during home-training was dependent on the intensity of hometraining: the more intensive the training periods at home, the higher the reduction in SARA gait and posture. Importantly, children were highly motivated throughout the whole demanding training period, and they experienced feelings of success about their own movements. In summary, this study provides proof-of-principle evidence that, despite progressive cerebellar degeneration, children are able to improve motor performance by intensive coordination training. Moreover, it suggests that directed training of whole-body-controlled video games might present a highly motivational, cost-efficient, and home-based rehabilitation strategy to train dynamic balance and interaction with dynamic environments. In a follow-up study, Schatton et al. (2017) examined the effectiveness of a 12-week home-based training with body-controlled videogames in 10 young subjects with advanced degenerative ataxia unable or barely able to stand. The exergames were executed mainly in sitting position in order to exercise trunk stability (Fig. 1e). After intervention, ataxia symptoms were reduced (SARA 2.5 points), with benefits correlating to the amount of training. This study provides first evidence that, even in advanced stages, subjects with degenerative ataxia may benefit from individualized training, with effects translating into daily living and improving underlying control mechanisms (Table 1).

Discussion Current Praxis of Motor Rehabilitation Recent clinical studies show that intensive motor training including exercises for multi-joint coordination and balance can reduce ataxia symptoms in patients suffering from degenerative cerebellar disease equivalent to gaining back functional performance of 2 or more years of disease progression (Ilg et al. 2010). Thereby, continuous training seems in particular crucial for patients with degenerative diseases for stabilizing improvements and should become standard of care. However, motor rehabilitation in degenerative cerebellar disease remains a challenge and requires a careful and individual analysis of the patient’s current motor capacities and condition in everyday life. In general, a combination of restorative and compensatory techniques may be utilized. The relative emphasis depends on the severity of cerebellar ataxia and its pattern of progression (Marsden and Harris 2011; Bonney et al. 2016; Bastian 1997). Such compensatory techniques can include (i) replacing rapid multi-joint movements with slower movements with sequential single joints movements (Bastian 1997), (ii) the rehearsal of eye movements for goal-directed stepping (Crowdy et al. 2002), (iii) the training of more cognitive strategies to execute gait and to adjust to different movement conditions (Taylor et al.

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Fig. 1 (a and b) Snapshot of a demanding exercise: training of dynamic balance and multi-joint coordination. (b) Illustration of an experiment testing dynamic balance capacities. Patients have to compensate the perturbation of the accelerating treadmill (accelerating phase 1 s) by anteriordirected steps. The red and the blue characters show one and the same patient before (red) and after (blue) the intervention period. After intervention patients were able to compensate the perturbation more efficiently and in a more secure way (Ilg et al. 2009). (c and d) Screenshots from the game “Light race” used in the exergaming exercises. The patient performs dynamic stepping movements in order to control the avatar to step onto the highlighted areas on the floor (figures reproduced with permission from Microsoft Xbox Kinect ® (Ilg et al. 2012). (e) Snapshot from an ataxia subject training with the game “Tilt City” using the Nintendo Wii Balance Board ® (Schatton et al. 2017)

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Table 1 Overview of studies examining motor rehabilitation in cerebellar disease Reference (Balliet et al. 1987)

Patient group Five patients after traumatic brain injury with cerebellar involvement

(Gill-Body et al. 1997)

Two patients with different cerebellar etiologies

(Cernak et al. 2008)

One child after cerebellar/brain stem infarct

(Ilg et al. 2009)

16 patients (10 cerebellar, 6 afferent degeneration)

(Miyai et al. 2012)

42 patients with cerebellar degeneration

(Ilg et al. 2012)

10 children with cerebellar degeneration

(Keller and Bastian 2014)

14 patients with cerebellar ataxia

(Burciu et al. 2013)

19 patients with pure cerebellar degeneration

(Bunn et al. 2014)

12 patients with spinocerebellar ataxia type 6

Main result Using increasingly demanding balance and gait tasks, improvements were reached for increased postural stability in clinical measures and less dependency on walking aids in everyday life Individualized treatment programs to train balance. The outcomes suggest that patients with cerebellar lesions, acute or chronic, may be able to learn to improve their postural stability Locomotion training on treadmill with weight support in conjunction with physical therapy can be an effective way to improve ambulatory function in individuals with severe cerebellar ataxia Four weeks of intensive coordination training improves gait in terms of velocity, lateral sway, and variability of intralimb coordination pattern; improvements in subjective important movements in daily life Four weeks of physiotherapy in combination with occupational therapy improves gait speed and fall frequency Six weeks of video game-based coordination training in children improves velocity, step length variability, and dynamic balance Improvement in locomotor performance observed after a 6-week home balance exercise program. Exercises are individually designed to provide a significant challenge to the person’s balance Two weeks of training on a balance task increased balance performance in cerebellar patients. In contrast to controls, patients revealed significantly more post-training gray matter volume in the dorsal premotor cortex Participants undertook balance exercises in front of optokinetic stimuli during weeks 4–8, training intervention was feasible, and outcome measures reveal trends toward balance improvements (continued)

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Table 1 (continued) Reference (Fonteyn et al. 2014)

Patient group 10 patients with cerebellar ataxia

(Kaut et al. 2014)

17 patients with spinocerebellar ataxia types 1, 2, 3, and 6

(Milne et al. 2017)

10 patients with Friedreich’s ataxia

(Schatton et al. 2017)

10 children with advanced degenerative ataxia

(Im et al. 2017)

19 patients with degenerative cerebellat ataxia caused by SCA2, SCA3, SCA6, IDCA, MSA-C

(Bultmann et al. 2014)

23 patients with acute and isolated cerebellar infarction

Main result Training gait adaptability training on a treadmill with virtual obstacles projected on the belt’s surface can lead to increased obstacle avoidance capacity and dynamic stability Whole-body vibrations (WBV) can lead to improvements of gait and posture. The use of stochastic WBV could provide a supplementation to treat ataxia and can be combined with physiotherapeutical training Change in the Friedreich Ataxia Impact Scale body movement subscale indicated a significant improvement in health and well-being in the intervention group compared to the control group Twelve weeks of home-based training with body-controlled video games resulted in reduction of ataxia symptoms. Movement analysis revealed improvements in posture control mechanisms Twelve weeks of locomotor training emphasized the relearning of proper gait movement strategies through intensive practice that enhances the patient’s perception and control of the essential components of gait Two weeks of treadmill training with increasing velocity. After 3 months mild ataxia in the lower limbs and gait persisted, postural impairment fully recovered. Treadmill training did not show significant effects

2010; Im et al. 2017), and (iv) the training of secure fall strategies instead of training to avoid falls. Best evidence for beneficial interventions exist for coordination and balance training (Balliet et al. 1987; Gill-Body et al. 1997; Ilg et al. 2009; Keller and Bastian 2014; Miyai et al. 2012; Synofzik and Ilg 2014), which is (i) adapted on the severity of the ataxia and (ii) consists in increasingly demanding exercises for multi-joint coordination and balance. These approaches should be used as long as possible to activate the remaining capabilities for balance and coordination, in order to potentially decelerate the process of degeneration of functional motor capabilities (which has not yet shown in human but only in animal studies). However, these types of

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exercise might be limited to stages of disease, in which the patients are able to stand without help and have also some gait capabilities. In more severe cases, in which free standing and walking is not possible anymore, treadmill training (Vaz et al. 2008; Cernak et al. 2008; Freund and Stetts 2010) with potential weight support may be helpful to increase walking capabilities (with the use of mobility aids) and to preserve general fitness as far as possible. The exergames training component needs to be limited to a sitting position exercising trunk stability (Schatton et al. 2017). The use of mobility aids is dependent on disease stage and individual preferences. Clinical observation suggests that some individuals with ataxia find light touch contact – e.g., with the use of Nordic poles – more useful as a strategy than conventional walking aids like traditional walking sticks (Bonney et al. 2016). This strategy would also help to use and train remaining balance capacities. In even more severe cases, the use of walkers for ensuring the safeness of mobility will be first choice. Furthermore, in severe cases of upper limb ataxia, when basic activities of daily living like eating are impaired, the use of orthotics – in order to stiffen mechanically several degrees of freedom – can help to improve functional performance (Gillen 2002; Bonney et al. 2016). Taken together, such individualized tailored strategies might help to maximize the function of each individual subject in his or her particular disease state and might – at least in some cases – slow down a possible downward spiral of ataxia-related immobility and further deterioration of coordinative functions.

Open Questions in Cerebellar Motor Rehabilitation The above-described first positive results gained in motor rehabilitation of patients suffering from degenerative cerebellar disease raise many new questions. These relate on the one hand to further clinical studies, in order to evaluate and to compare the efficiency of training approaches in larger patient populations and to find reliable predictors of training benefits. On the other hand, further research in motor adaptation is needed, in order to understand the mechanisms of improving functional performance.

Motor Rehabilitation for Upper Extremities There is still a clear lack of rehabilitation studies for upper limb movements in cerebellar disease. Although upper limb rehabilitation is very common in stroke patients (e.g., Platz et al. 2001; Taub et al. 2003), there are only few attempts to transfer similar approaches to cerebellar ataxia. In Richards et al. (2008) modified constraint-induced movement therapy protocols for goal-directed arm movements have been applied to three chronic stroke patients, suffering from ataxia due to extracerebellar lesions (basal ganglia, thalamus). Participants improved on either the Fugl-Meyer Test (Fugl-Meyer et al. 1975) or the Wolf Motor Function Test (Wolf et al. 1989) and increased their daily use of the impaired upper extremity.

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In principle, the concept of motor training with increasingly demanding coordination exercises could also be transferred to goal-directed upper limb movements. It would be highly interesting whether an intensive and continuous training of manipulating different objects (inducing different arm dynamics) could lead to improvements in adjusting upper limb movements to changing conditions relevant for everyday life. Another approach to train these adaptation capabilities could be the use of a robotic manipulandum to exercise upper limb movements with different perturbations like velocity-dependent force fields (Vergaro et al. 2011). The benefits and relevance of these approaches for patients’ everyday life and the transfer to different movements have to be evaluated in clinical studies.

Further Clinical Studies in Different Disease Stages The majority of studies, which have shown improvements in motor performance, focused on ambulatory patients, which are able to walk with or without walking aid. Thus, further studies are needed to examine whether patients with more severe impairments also benefit from physiotherapeutical training (adjusted to their impairments, e.g., for arm movements) or whether the capacity to improve motor performance relies on a specific level of residual cerebellar integrity. Long-Term Studies and Quality of Life More generally, there is a fundamental need of long-term studies to evaluate the benefits of physiotherapeutical treatments in patients’ everyday life. Although currently no specific instruments exist to assess the quality of life in cerebellar patients, the use of questionnaires commonly applied in chronic disease has been proposed (see Trujillo-Martin et al. 2009 for review). Two recent studies examined the application of health-related quality of life scales in degenerative cerebellar ataxia (Schmitz-Hübsch et al. 2010) and Friedreich’s ataxia (Paulsen et al. 2010), which quantified the dimensions of mobility, usual activities, pain, depression, and self-care. Results showed that severity, extent of extra-cerebellar involvement, and the presence of a depressive syndrome are the most important predictors of subjective health status in degenerative ataxias (Schmitz-Hübsch et al. 2010). When performing long-term studies with patients suffering from degenerative disease, one has to keep in mind that progression of degeneration is different in specific types of diseases (e.g., for SCA 1,2,3,6; see Jacobi et al. 2011, 2015). Thus, long-term benefits have to be regarded in the light of natural history studies for specific diseases. In future research, long-term studies have also to include preclinical mutation carriers of SCAs (Maas et al. 2015; Jacobi et al. 2013), since possible preventive training approaches are likely more effective and lasting when started at an early, i.e., asymptomatic or preclinical disease stage. Recent studies have examined adequate outcome measures for preclinical intervention trials (Ilg et al. 2016; Rochester et al. 2014), since clinical scores like SARA or ICARS are not sensitive enough in the preclinical stage (Storey 2015).

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Prediction of Intervention Benefits A very important question for effective rehabilitation is to find reliable predictors for the outcome and potential benefit of physiotherapeutical motor training in individual patients. Further studies have to show whether clinical ataxia scores (i.e., ICARS or SARA) or more sophisticated quantifications of neural degeneration and lesion sites using modern brain imaging methods can be exploited for a reliable outcome prediction. It has been shown that lesion site is critical for motor recovery in cerebellar patients with focal lesions after tumor resection or stroke. Lesions are not fully compensated, affecting the deep cerebellar nuclei (Konczak et al. 2005; Schoch et al. 2006). In a similar way, involvement of deep nuclei may be also a crucial factor in motor rehabilitation for degenerative cerebellar disease. Thus, patients with a degeneration predominantly affecting the cerebellar cortex (i.e., SCA6) may benefit more (and longer in progress of degeneration) from motor rehabilitation compared to patients suffering from a degeneration predominantly of the deep nuclei (i.e., SCA3, Friedreich’s ataxia). Another indicator could be cerebellar volume of all or specific parts of the cerebellum, which has been shown to correlate negatively with severity of ataxia symptoms (Richter et al. 2005; Kansal et al. 2017). MRI studies provide first evidence that the various subtypes of degenerative cerebellar disease lead to different degeneration patterns in the cerebellar cortex as well in the deep nuclei (Ying et al. 2009; Du et al. 2010; Stefanescu et al. 2015). Deeper knowledge in disease-specific degeneration patterns could also help to develop more efficient training approaches for individual patients. The aim is to find adequate predictors for the potential benefits an individual patient can expect from a specific motoric training and thus to provide efficient training programs for different stages of cerebellar impairment. Indeed, one of such predictors for the rehabilitation outcome could be the capability for short-term motor adaptation. In Hatakenaka et al. (2011), it was shown that impaired short-term motor adaptation correlated with reduced rehabilitation gains in ataxic patients with infratentorial stroke.

Future Studies on Mechanisms of Motor Adaptation and Motor Rehabilitation Although it has been shown by quantitative movement analysis that patients can improve in specific motor behaviors like multi-joint coordination and dynamic balance (Ilg et al. 2009), there is no direct evidence that these functional improvements are related specifically to motor learning. For example, a more efficient use of sensory signals could also cause the functional improvements on dynamic balance. Therefore, further studies are needed in order to clarify (i) whether associated changes in neural substrates can be identified either within the cerebellum and its connections or in other brain structures compensating the cerebellar deficit and (ii) in which way the functional improvements are related to capabilities in motor learning.

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Modern Brain Imaging Techniques Modern structural and functional brain imaging techniques are of possible help. Voxel-based morphometry (VBM) has been shown to reveal training-related changes (Draganski et al. 2004). Thus, VBM might be one method to show to what extent neural changes take place in cerebellar and extra-cerebellar motor circuits or whether areas related to non-motor, e.g., cognitive strategies (frontal lobe), may step in. Burciu et al. (2013) performed a voxel-based morphometry (VBM) study in patients with cerebellar degeneration. A 2-week postural training resulted in a significant improvement of balance in these patients. Comparing gray matter volumes before and after training revealed an increase primarily within non-affected neocortical regions of the cerebellar-cortical loop, more specifically the premotor cortex. Gray matter changes were observed within the cerebellum as well but were less pronounced. Thus, these first data suggest that training may lead to training-related compensatory changes in cerebellar-cortical networks and, to a smaller extent, even of remaining cerebellar circuitry itself. Dynamic causal modelling analysis, resting state functional MRI, and diffusion tensor imaging (DTI) are further options. These techniques are able to show functional connectivity and training-related network alterations. For example, alterations in networks including the cerebellum have been identified, which correlate to the degrees of motor adaptation in visuomotor adaptation tasks in healthy subjects (Albert et al. 2009; Della-Maggiore et al. 2009). More recently, Tzvi et al. (2017) found that changes in fMRI signal and functional connectivity in the cortico-striatocerebellar motor learning network were associated with learning performance in patients with cerebellar degeneration in a sequence learning task. The Relationship Between Short-Term Motor Adaptation Alternative Learning Methods and Motor Rehabilitation There are several open questions concerning the relationship between motor adaptation tasks and motor training in rehabilitation: (i) Do cerebellar patients show motor adaptation in long-term studies over weeks with high intensities? (ii) Could the short-term adaptation capability be a valuable predictor of the outcome of longterm motor rehabilitation? (iii) Can cerebellar patients potentially use alternative motor learning mechanisms like reward-based or user-dependent learning, which have been suggested to be less dependent on the cerebellum? As cerebellar patients have shown to be impaired in establishing and recalibration of internal forward models by error-based learning, it has been hypothesized that those patients could potentially use alternative motor learning mechanisms like reward-based learning or user-dependent learning. These learning mechanisms have been suggested to be less or not dependent on the integrity of the cerebellum (Doya 2000; Criscimagna-Hemminger et al. 2010; Izawa et al. 2010; Schultz et al. 1997). However, recent studies delivered evidence that this hypothesis might be oversimplified, showing an influence of the cerebellum also on reward-based motor learning on multiple levels. For instance, a study combining the visuomotor adaptation paradigm with reward-based feedback indicates that cerebellar dysfunction may negatively influence reward-based learning by increased motor variability

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rather than by impairments of the learning mechanisms itself (Therrien et al. 2016). However, cerebellar patients were able to learn under the closed-loop reinforcement schedule and retained much more of the learned reaching pattern compared to when they performed error-based learning (Therrien et al. 2016). Further studies on those methods could deliver valuable hints for optimizing motor learning exercises also in the framework of physiotherapeutical motor training.

Noninvasive Brain Stimulation Techniques Transcranial direct current stimulation (tDCS) has been suggested to be of potential use in the treatment of cerebellar ataxia (for review see Grimaldi et al. 2014). This is partly based on the observation that cerebellar tDCS improves cerebellar-dependent learning in healthy subjects. For example, Galea et al. (2009) and Jayaram et al. (2011) have shown that anodal cerebellar tDCS facilitates short-term visuomotor adaptation in healthy subjects. This and other findings of cerebellar tDCS, however, have been difficult to replicate in subsequent studies (Jalali et al. 2017). Likewise, initial findings of cerebellar tDCS have been contradictory in patients with cerebellar degeneration (Hulst et al. 2017; John et al. 2017; Benussi et al. 2017; Pozzi et al. 2014). Prior its clinical application, the lack of consistency of cerebellar tDCS effects in learning paradigms needs to be understood in healthy subjects and cerebellar disease. There are others forms of noninvasive brain stimulation which may also be useful to support learning-related processes in cerebellar patients, for example, transcranial alternating current stimulation (tACS), repetitive transcranial magnetic stimulation (rTMS), and paired associative stimulation (PAS) (Grimaldi et al. 2014). Initial findings show beneficial effects of rTMS in patients with cerebellar degeneration and cerebellar stroke (Bonni et al. 2014; Kim et al. 2014). Future studies are needed to better understand the impact of noninvasive brain stimulation of the cerebellum on different forms of learning, and initial findings in patients need to be replicated in larger patient populations.

Conclusions and Future Directions In conclusion, rehabilitation of cerebellar ataxia remains a major challenge for patients, physicians, and therapists in particular for degenerative cerebellar disease. Recent advances in both clinical rehabilitation and research on motor adaptation provide the basis for future studies to broaden our knowledge in this challenging field of motor rehabilitation. The overarching aim is to provide individualized rehabilitation programs that result in an improvement of the patients’ quality of life.

References Albert NB, Robertson EM, Miall RC (2009) The resting human brain and motor learning. Curr Biol 19(12):1023–1027 Alvina K, Khodakhah K (2010) The therapeutic mode of action of 4-aminopyridine in cerebellar ataxia. J Neurosci 30(21):7258–7268

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Tzvi E, Zimmermann C, Bey R, Munte TF, Nitschke M, Kramer UM (2017) Cerebellar degeneration affects cortico-cortical connectivity in motor learning networks. NeuroImage Clin 16:66–78. https://doi.org/10.1016/j.nicl.2017.07.012 van de Warrenburg BP, Steijns JA, Munneke M, Kremer BP, Bloem BR (2005) Falls in degenerative cerebellar ataxias. Mov Disord 20(4):497–500 van Dun K, Overwalle FV, Manto M, Marien P (2018) Cognitive impact of cerebellar damage: is there a future for cognitive rehabilitation? CNS Neurol Disord Drug Targets 17(3):199–206 Vaz DV, Schettino Rde C, Rolla de Castro TR, Teixeira VR, Cavalcanti Furtado SR, de Mello Figueiredo E (2008) Treadmill training for ataxic patients: a single-subject experimental design. Clin Rehabil 22(3):234–241 Vergaro E, Squeri V, Brichetto G, Casadio M, Morasso P, Solaro C, Sanguineti V (2011) Adaptive robot training for the treatment of incoordination in Multiple Sclerosis. J Neuroeng Rehabil 7:37 Vilis T, Hore J (1980) Central neural mechanisms contributing to cerebellar tremor produced by limb perturbations. J Neurophysiol 43(2):279–291 Weimar C, Weber C, Wagner M, Busse O, Haberl RL, Lauterbach KW, Diener HC (2003) Management patterns and health care use after intracerebral hemorrhage. A cost-of-illness study from a societal perspective in Germany. Cerebrovasc Dis (Basel, Switzerland) 15(1–2): 29–36 Werner S, Bock O, Timmann D (2009) The effect of cerebellar cortical degeneration on adaptive plasticity and movement control. Exp Brain Res 193(2):189–196 Wolf SL, Lecraw DE, Barton LA, Jann BB (1989) Forced use of hemiplegic upper extremities to reverse the effect of learned nonuse among chronic stroke and head-injured patients. Exp Neurol 104(2):125–132 Ying SH, Landman BA, Chowdhury S, Sinofsky AH, Gambini A, Mori S, Zee DS, Prince JL (2009) Orthogonal diffusion-weighted MRI measures distinguish region-specific degeneration in cerebellar ataxia subtypes. J Neurol 256(11):1939–1942 Zesiewicz TA, Wilmot G, Kuo SH, Perlman S, Greenstein PE, Ying SH, Ashizawa T, Subramony SH, Schmahmann JD, Figueroa KP, Mizusawa H, Schols L, Shaw JD, Dubinsky RM, Armstrong MJ, Gronseth GS, Sullivan KL (2018) Comprehensive systematic review summary: treatment of cerebellar motor dysfunction and ataxia: report of the guideline development, dissemination, and implementation subcommittee of the American Academy of neurology. Neurology 90(10):464–471. https://doi.org/10.1212/WNL.0000000000005055

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Antoni Matilla-Duen˜as, Jon Infante, Carmen Serrano-Munuera, Yerko Iva´novic-Barbeito, Ramiro Alvarez, and Ivelisse Sa´nchez

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Treatments for Autosomal Recessive Spinocerebellar Ataxias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Friedreich’s Ataxia (FRDA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ataxias with Vitamin E and Coenzyme Q10 Deficiencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abetalipoproteinemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cerebrotendinous Xanthomatosis (CTX) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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A. Matilla-Dueñas (*) Functional and Translational Neurogenetics Unit, Department of Neuroscience, Health Sciences Research Institute Germans Trias i Pujol (IGTP), Badalona, Barcelona, Spain e-mail: [email protected] J. Infante Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL, University of Cantabria, Santander, Spain e-mail: [email protected] C. Serrano-Munuera Neurology Section, Hospital Sant Joan de Déu de Martorell, Barcelona, Spain e-mail: [email protected] Y. Ivánovic-Barbeito Servicio de Neurología, Unidad de ELA y enfermedades neuromusculares, Complejo Hospitalario Universitario de Canarias, La Laguna, Tenerife, Spain Neurology Department, Hospital Puerta del Sur HM, Móstoles, Madrid, Spain R. Alvarez Neurodegeneration Unit, Neurology Service, Department of Neuroscience, University Hospital Germans Trias i Pujol (HUGTiP), Badalona, Barcelona, Spain e-mail: [email protected] I. Sánchez Functional Biology and Experimental Therapeutics Laboratory, Functional and Translational Neurogenetics Unit, Department of Neuroscience, Health Sciences Research Institute Germans Trias i Pujol (IGTP), Badalona, Barcelona, Spain e-mail: [email protected] © Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0_106

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Refsum’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ataxia-Telangiectasia (AT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Treatments for Autosomal Dominant Spinocerebellar Ataxias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Treatments for Episodic Ataxias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emerging Therapeutic Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physical Therapy in Cerebellar Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physical Therapy Examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Physical Therapy Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Concluding Remarks and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cross-References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

In the last decade, substantial scientific progress has enabled a better understanding of the pathogenesis of cerebellar diseases and the improvement of their diagnoses. Extensive preclinical work is expanding the possibilities for using experimental models to analyze disease-specific mechanisms and to approach candidate therapeutic strategies to create a rationale for clinical trials that might finally lead to successful treatment. At present, drug treatment of cerebellar disorders has shown limited effectiveness, and current treatment is primarily supportive. Until effective and selective pharmacological treatment leading to a better quality of life as well as increased survival of patients with cerebellar diseases is found, physical and sensory rehabilitation techniques are revealing effective approaches for improving the patient’s quality of life. The objective of this chapter is to provide an updated summary of the treatments currently available for cerebellar disorders, in particular for spinocerebellar ataxias, and to discuss the new emerging therapeutic strategies that result from the intensive ongoing basic and translational research devoted to cerebellar diseases. Keywords

Ataxia · Spinocerebellar ataxias · Motor incoordination · Machado-Joseph disease · Friedreich’s ataxia · Dentatorubral-pallidoluysian atrophy · Nonprogressive episodic ataxias · Channelopathies · Motor incoordination · Ataxia and non-ataxia symptoms · Cerebellum · Brain stem · Spinal cord · Neurodegeneration · Movement disorders · Purkinje cells · Molecular deficits · Polyglutamines · Genetic counseling · Therapeutic strategies · Ataxia scales · Physiotherapy Abbreviations

AT CoQ DRPLA EA FRDA

Ataxia-telangiectasia Coenzyme Q Dentatorubral-pallidoluysian atrophy Episodic ataxia Friedreich’s ataxia

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FXTAS ICARS SARA SCA

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Fragile X tremor and ataxia syndrome International Cooperative Ataxia Rating Scale Scale for the assessment and rating of ataxia Spinocerebellar ataxia

Introduction Damage to the cerebellum has been associated with a wide range of movement disorders including incoordination, reduced manual dexterity, postural instability, and gait disturbances (Manto 2008). Because ataxia is the most common neurological deficit resulting from dysfunction of the cerebellum, this chapter will mostly focus on the treatment of ataxic disorders. Cerebellar ataxic movement patterns result from the impairment of the timing and duration of muscle activation or the magnitude and scaling of force production during voluntary movement, as the cerebellum is thought to be instrumental in these crucial elements of motor control. Drug treatment of cerebellar diseases has shown limited effectiveness, and therefore treatment is primarily supportive. With very few exceptions, such as in those ataxias associated with vitamin E and CoQ deficiencies, there are no disease-modifying therapies for cerebellar diseases. However, medications such as 5-hydroxytryptophan, clonazepam, and others that will be discussed herein have been reported to have limited benefits in a few cerebellar conditions (Ogawa 2004; Matilla-Dueñas et al. 2006; Ferrara et al. 2009; Manto and Marmolino 2009; Trujillo-Martin et al. 2009; Strawser et al. 2017; Table 1). Very recently there have been encouraging advances in clinical ataxia research. Collaborative study groups throughout the world have developed and validated ataxia rating scales and instrumented outcome measures. These are now being used to rigorously define the natural history of these diseases, thus laying the foundation for well-designed clinical trials (Schmitz-Hubsch et al. 2010). Hereditary ataxias may have certain clinical features that respond very well to symptomatic medical therapy. Parkinsonism, dystonia, spasticity, urinary urgency, sleep pathology, fatigue, and depression are all common in many of the different ataxia subtypes and very often respond to pharmacologic intervention as in other diseases. Much of the clinical interaction between the neurologist and the ataxia patient focused on identifying and treating these symptoms. As in cases of infarctions, hemorrhages, and neoplasms, surgical and medical treatment, radiotherapy, or chemotherapy to treat the original cause of the cerebellar diseases is commonly followed by physical therapy. Treatment of the core clinical feature of these diseases – ataxia – is thus predominantly rehabilitative (reviewed in Watson 2009 and Fonteyn et al. 2014). The value of good physical therapy far exceeds any potential benefit from medications that a physician might prescribe to improve balance and coordination. Furthermore, speech and swallowing are often affected. In more severe cases, aspiration risk can be very significant and life-threatening. Routine monitoring of swallowing by speech therapists, often including modified barium swallowing tests, is indicated in most patients.

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Table 1 Summary of the existing treatments in the spinocerebellar ataxias. Only those treatments in clinical trials or about to be tested in patients have been included Ataxia Treatment Autosomal recessive ataxias Friedreich’s ataxia Idebenone 450–2,250 mg/day

Ataxias with vitamin E deficiency

Status

Conclusions/observations

Completed

Idebenone 180–2,250 mg/day

Completed

Pioglitazone Vitamin E + CoQ10

Ongoing Completed

Alpha-tocotrienol quinone

Completed

Omaveloxolone

Completed/ ongoing

Deferiprone

Completed

Erythropoietin

Completed

CEPO

Completed

HDACis

Completed

Interferon gamma-1b Replacement strategies Oligonucleotidebased Polyamides

Completed Preclinical

No improve cardiac hypertrophy or function. Trend for improvement in neurological function in open-label extension No effects on cardiomyopathy or neurological symptoms clinicaltrias.gov Increased serum levels but no clinical benefit No effect on visual acuity. Possible effect on ataxia progression Mild improvement in neurological function. Extended trial is ongoing Controversial results ranging from mild clinical improvement to worsening ataxia Frataxin levels improved without clinical improvement Increased frataxin without clinical improvement Increases frataxin mRNA levels with few adverse effects No clinical improvement TAT-fused frataxin

Preclinical

Under experimentation

Preclinical

Gene therapy Vitamin E

Preclinical Treatment of choice

RRR- α-tocopherol

Completed

Increase frataxin levels in vitro Under experimentation Ataxia and mental retardation are reversed if treated early. In older individuals, disease progression can be halted Stabilization of clinical symptoms with 800 mg/kg/ day (continued)

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Table 1 (continued) Ataxia Ataxias with Coenzyme Q10 deficiency Abetalipoproteinemia

Treatment Coenzyme Q10

Status Treatment of choice

Conclusions/observations Slows progression of ataxia

Vitamin E together with α-tocopherol

Treatment of choice

Ataxia-telangiectasia Cerebrotendinous xanthomatosis

Betamethasone CDCA 15 mg/kg/day

Completed Treatment of choice

Initial treatment is crucial to avoid progression of the disease. Massive oral doses of α-tocopherol (100–150 mg/ kg) are required Improves ataxia scales Decreases cholestanol levels leading to improvement of neurological symptoms Lowers phytanic acid levels and improves symptoms

Westminster-Refsum diet Autosomal dominant ataxias SCA1 Lithium

Refsum’s disease

SCA2

SCA3

SCA6 SCA38

NMDA antagonists, deep brain stimulation Amantadine, dopaminergic, anticholinergic drugs Lithium Riluzole Clonazepam, buspirone, hydroxytryptophan, lamotrigine, tandospirone Amantadine, dopaminergic, anticholinergic drugs Varenicline

Treatment of choice Completed Completed

Clinical benefits. Considerable adverse effects Some benefits regarding ataxic symptoms

Completed

Alleviate tremor, bradykinesia, or dystonia

Completed Ongoing Completed

No clear benefit

Completed

Alleviate tremor, bradykinesia, or dystonia

Completed

Trend for improvement of ataxia but inconclusive results Improved SARA measures No effect on global ataxia progression but slower progression of some quantitative scores Some benefits regarding ataxic symptoms Improvement of clinical symptoms and cerebellar hypometabolism

Valproic acid Lithium

Completed Completed

Acetazolamide, gabapentin Docosahexaenoic acid

Completed Completed

Some benefits regarding ataxic symptoms

(continued)

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Muscle cramps Myoclonus

Restless leg syndrome

Saccadic intrusions Spasticity

Episodic ataxias Episodic ataxia type 1 (EA1) Episodic ataxia type 2 (EA2)

Attack rates

Mixed ataxias Spinocerebellar ataxia and Friedreich’s ataxia

Treatment Varenicline Memantine Botulinum toxin Benzodiazepines, b-blockers, chronic thalamic stimulation Magnesium, quinine, mexiletine Piracetam

Status Ongoing Completed Completed Completed

Ineffective Clear benefits. Small dosage Symptoms ameliorate

Completed

Symptoms ameliorate

Completed

Dopaminergic treatment, rotigotine, tilidine Memantine Baclofen, memantine, tizanidine with dopamine treatment Botulinum toxin

Completed

Symptoms ameliorate. Also used to treat dementia/ cognitive decline Clear benefits

Completed Completed

Clear benefits Clear benefits

Completed

Clear benefits. Small dosage

Completed

Clear benefits

Treatment of choice

Clear benefits. It should not be prescribed to patients with liver, renal, or adrenal insufficiency Clear benefits

Carbamazepine, valproic acid, ACTZ ACTZ

4-Aminopyridine, CHZ 3,4-Diaminopyridine

Completed

Carbamazepine, sulthiame

Completed

Riluzole

Completed

Completed

Conclusions/observations

Improves downbeat nystagmus Reduce the frequency of attacks, but the response is heterogeneous Slow progression of ataxia scores

Treatments for Autosomal Recessive Spinocerebellar Ataxias The heterogeneity of this group of diseases, which includes an extraordinary variety of gene mutations originating from different pathogenic mechanisms, places the task of reviewing all the potential or hypothetical future treatments beyond the scope of a single chapter. We shall therefore limit this review to the most common autosomal

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recessive ataxias together with those in which successful therapeutic options have been explored.

Friedreich’s Ataxia (FRDA) Biochemical investigations have revealed the role of frataxin, the protein associated with FRDA, in the assembly of iron-sulfur clusters (ISCs) in the mitochondrion (reviewed in Pandolfo and Pastore 2009). A GAA triple repeat expansion in intron 1 of the frataxin (FXN) gene inhibiting frataxin expression is the most common type of mutation causing FRDA. As a consequence of frataxin deficiency, iron is accumulated in mitochondria leading to a loss of mitochondrial function. Cells from FRDA patients become highly sensitive to oxidants causing further mitochondrial damage and respiratory chain dysfunction. Two major categories of drugs are or have been tested for FRDA based on its pathogenesis: drugs related to mitochondrial function (including antioxidants such as idebenone, coenzyme Q10, and alphatocotrienol quinone; iron chelators such as deferiprone; and other drugs like pioglitazone and omaveloxolone) and drugs aiming to increase frataxin expression such as erythropoietin (EPO), interferon gamma, and transactivators of transcription (TAT). Histone-deacetylase inhibitors and gene therapy are experimental treatments currently being investigated. Idebenone is the antioxidant that has been the most widely used drug in FRDA treatment since the initial report of its successful use in the reduction of the left ventricular mass of three FRDA patients with cardiac hypertrophy (Rustin et al. 1999). In one of the first open-label trials in which nine patients were treated with 5 mg/kg/day, cerebellar improvement was considered to be notable in mildly symptomatic patients after the first 3 months of therapy. Treatment during the early stages of the disease was found to reduce the progression of cerebellar manifestations (Artuch et al. 2002). Several open-label studies suggested favorable effects on cardiac hypertrophy associated with FRDA and neurological dysfunction. In summary, early placebo-controlled pilot trials found a dose-dependent response on neurological function assessed by the ICARS (Trouillas et al. 1997) particularly in young and still-ambulatory patients (Di Prospero et al. 2007) and a minor reduction in cardiac mass after 1 year (Mariotti et al. 2003) but no effect on primary endpoints like oxidative stress markers and respiratory chain function (Di Prospero et al. 2007; Schöls et al. 2001). Unfortunately, two large phase III trials (IONIA and MICONOS) failed to replicate these effects (Lagedrost et al. 2011; press release on the MICONOS trial by Santhera Pharmaceuticals). The MICONOS study, a large, randomized, double-blind, placebo-controlled trial, tested the efficacy and safety of three doses of idebenone and placebo over a 12-month treatment period. The primary endpoint of the study, mean change in the ICARS score from baseline, did not reveal significant differences between the active dose arms and placebo. Secondary endpoints also failed to reveal statistically significant differences between the placebo and active dose groups, and even cardiac benefit could not be proved. In the IONIA study, idebenone at two different doses did not decrease left ventricular

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hypertrophy or improve cardiac function in 70 pediatric subjects with FRDA (Lagedrost et al. 2011). However, the open-label extension of this study showed a trend for improvement in neurological function over an 18-month period in pediatric patients (Meier et al. 2012). According to the results from the abovementioned trials, idebenone would not be effective at improving either neurological or cardiac parameters in FRDA patients. However, it is possible that an effect on cardiomyopathy might be expected in some cases. Further controlled studies in subgroups of Friedreich’s ataxia like patients with severe hypertrophic cardiomyopathy and early stages of the disease are warranted to clarify potential beneficial effects. Simultaneous treatment with both coenzyme Q10 and vitamin E in low and high doses were compared in a randomized, double-blind clinical trial in 50 patients over a 2-year period. Serum CoQ10 and vitamin E levels, which had previously determined to be in low levels in these patients, reached normal values as a result of the treatment. The primary and secondary endpoints were not significantly different between the therapy groups. The comparison of the ICARS scores with crosssectional data showed an overall 49% improvement. There were no differences between both groups in the endpoints. The best predictor of a positive clinical response to this double therapy was low serum CoQ10 and vitamin E levels (Cooper et al. 2008). EPI-743 (alpha-tocotrienol quinone) is an agent having structural features of both vitamin E and coenzyme Q. A double-blind placebo-controlled trial with EPI-743 was conducted on FRDA patients over a 6-month period (Zesiewicz et al. 2017). The drug was well-tolerated, but the study did not meet its primary endpoint of improvement of low contrast visual acuity. After 18 months of open-label treatment, patients had better scores on neurological outcome measures when compared to natural history data. A recent open-label pilot study used high doses of intramuscular thiamine in 34 subjects with FRDA to evaluate the clinical effect and influence on frataxin expression. The authors reported improvements or stabilization on some clinical parameters; however the design of the study prevents from reaching solid conclusions (Costantini et al. 2016). A 2-year prospective, randomized double-blind trial of pioglitazone versus placebo was initiated in 2012 (https://clinicaltrials.gov/ct2/show/NCT00811681), but the results of the trial have not been published yet. Pioglitazone is a peroxisome proliferator-activated receptor γ (PPARγ) ligand that induces the expression of enzymes involved in the mitochondrial metabolism, including the superoxide dismutase. This drug appears to counteract the disabled recruitment of antioxidant enzymes in FA patients. RTA-408 (omaveloxolone), a molecule with anti-inflammatory and antioxidant properties, has been tested in a multi-site phase II double-blind placebo-controlled trial. Results from the study demonstrated the induction of Nrf2 with associated improvements in mitochondrial and neurological function. Given the positive results, the follow-up/continuation of this study is expected to begin at the end of 2017. Resveratrol, a potential mitochondrial-enhancing agent, has shown some success in early trials in FRDA. An open-label trial reported some benefit at high doses,

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without effect on frataxin levels, but this was confounded by the presence of side effects (Yiu et al. 2015). Several studies have evaluated the effect of deferiprone, an iron chelator, in FRDA. Combination therapy of deferiprone and idebenone demonstrated neurological stabilization, reduction in iron on magnetic resonance imaging (MRI) of the dentate nucleus, and decreased cardiac hypertrophy (Velasco-Sánchez et al. 2011). Another study using three different doses of deferiprone showed worsening ataxia with intermediate and high doses, while all groups exhibited decreased cardiac hypertrophy (Pandolfo and Hausmann 2013). In contrast, triple therapy with deferiprone, idebenone, and riboflavin demonstrated no clear neurologic or cardiac benefit (Arpa et al. 2014). After finding that recombinant human erythropoietin (rhuEPO) significantly increased frataxin expression levels in in vitro studies (Sturm et al. 2005), an open-label clinical pilot study to evaluate safety and efficacy of rhuEPO was designed. Eight adult FA patients received 2,000 IU rhuEPO three times a week subcutaneously for 6 months. The scores in different ataxia rating scales and frataxin levels improved significantly after treatment, and the values measuring oxidative stress decreased (Boesch et al. 2007, 2008). Because of the side effects of EPO on hematopoiesis and tumor growth, efforts to develop EPO derivative molecules avoiding binding the erythropoietin receptor resulted in the synthesis of carbamylated erythropoietin (CEPO). Two open-label studies of EPO in patients with FRDA also found prolonged increases in frataxin but without improvement in clinical parameters (Saccà et al. 2011; Nachbauer et al. 2011). More recently, two double-blind placebo-controlled trials also did not demonstrate differences in clinical outcomes between the placebo and EPO drug treatment groups (Mariotti et al. 2012; Boesch et al. 2014). Nicotinamide (vitamin B3) has properties as HDAC inhibitor and has been shown to upregulate the expression of frataxin in preclinical studies. Recently, in an openlabel trial, nicotinamide showed a significant and sustained upregulation of frataxin protein in the plasma of 10 patients with FRDA over an 8-week period of daily dosing. The drug was well-tolerated, but no clinical benefit could be demonstrated given the short duration of the study. Further trials are therefore warranted to establish its long-term safety and clinical efficacy (Libri et al. 2014). Histone deacetylase (HDAC) inhibitors revert silent heterochromatin to an active chromatin conformation and therefore have been evaluated as molecules reverting gene expression changes. HDAC inhibition is a persistent reversible phenomenon, which in theory should permit the intermittent administration of the drug. Such a regimen would minimize toxic side effects by reducing drug exposure while at the same time allowing sustained upregulation of frataxin protein levels. This is an important consideration since uncommon but serious side effects had been reported with the use of other HDAC inhibitors in the past. Among these HDAC inhibitors, pimelic diphenylamide has stood out as an efficient upregulator of frataxin expression (Rai et al. 2010). Most recent studies on cell and animal models of FRDA showed more specific HDAC inhibitors are able to reverse the mutation-induced silencing of the FXN gene, leading to

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downstream upregulation of frataxin protein levels in the central nervous system and the heart (Chutake et al. 2016; Codazzi et al. 2016). The synthetic HDAC inhibitor RG2833 completed a phase I clinical trial in 2013, with an outcome showing increased frataxin mRNA levels and few adverse events. However, metabolites formed in the body were potentially deleterious (Soragni et al. 2014). A new generation of HDAC inhibitors is being developed to enhance potency and prevent the formation of harmful metabolites. In a cell and mouse models of FRDA, interferon gamma-1b led to increased frataxin expression and also to improved motor performance (Tomassini et al. 2012). Two small pilot studies were unable to demonstrate an increase in frataxin levels; however one of them suggested some clinical benefits (Seyer et al. 2015; Marcotulli et al. 2016). These small studies led to a phase II multicenter study in 90 FRDA patients in the United States (STEADFAST, www.clinicaltrials.gov). No significant differences were observed in clinical scores between patients and controls in a preliminary analysis, and the trial was discontinued. The HIV-1 transactivator of transcription (TAT), an arginine-rich cell penetrant peptide, is being exploited in replacement therapy strategies for transducing fulllength proteins not only across the cell membrane but also into intracellular organelles including the mitochondrion (Del Gaizo and Payne 2003; Vyas and Payne 2008; Rapoport and Lorberboum-Galski 2009). Through this method TAT-frataxin has been shown to rescue FRDA-derived fibroblasts and FXN knockout mouse models (Vyas et al. 2012). Future clinical trials will examine the safety and efficacy of this approach. Based on the empiric observations that some polyamide compounds such as beta-alanine-linked pyrrole-imidazole polyamides bind GAA/TTC tracts with high affinity and disrupt the intramolecular DNA-associated regions, they were tested for their ability to increase frataxin gene transcription and protein levels with positive results in cell culture. This has proven to increase frataxin protein levels (Burnett et al. 2006). Similar effects have been obtained with pentamidine and related small molecules (Grant et al. 2006; Gottesfeld 2007). Oligonucleotide-based approaches are also being tested in preclinical studies for activating FXN gene expression and ameliorating or restoring frataxin levels. Perhaps the most promising potential therapy to replace the loss of frataxin in FRDA is gene therapy. Findings from mouse studies show that injection of AAV9frataxin reverses the functional features of cardiomyopathy and increases frataxin expression (Perdomini et al. 2014; Gerard et al. 2014; Piguet et al. 2018). In addition to AAV, other viral delivery systems could also be useful in FRDA. Alternative gene therapy approaches have focused on the high capacity of the herpes simplex virus type 1 (HSV-1) amplicon vectors expressing the entire 80 kb FRDA genomic locus to successfully transduce onto FRDA patient frataxin-deficient fibroblasts and in a FRDA mouse model (Gomez-Sebastian et al. 2007; Lim et al. 2007). Other innovative strategies designed to place exogenous frataxin protein into the mitochondria of patients include the administration of frataxin previously encapsulated with peptides in nanoparticles (Nabhan et al. 2016).

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Ataxias with Vitamin E and Coenzyme Q10 Deficiencies The treatment of choice for the ataxia with vitamin E deficiency is lifelong high-dose oral vitamin E supplementation. Some symptoms including ataxia and mental deterioration can be reversed if treatment is initiated early in the disease process. In older individuals, disease progression can be stopped, but deficits in proprioception and gait unsteadiness generally remain (Gabsi et al. 2001; Mariotti et al. 2004). With treatment, plasma vitamin E concentrations can become normal. No therapeutic studies have been performed on a large cohort to determine the optimal dosage and evaluate outcomes. Reported doses of vitamin E range from 800 mg to 1500 mg or 40 mg/kg body weight in children. The used vitamin E preparations are the chemically manufactured racemic form, all-rac-α-tocopherol acetate, or the naturally occurring form, RRR-α-tocopherol. It is not currently known whether affected individuals should be treated with allrac-α-tocopherol acetate or with RRR-α-tocopherol. It is known that alphatocopherol transfer protein (alpha-TTP) stereoselectively binds and transports 2R-α-tocopherols. For some ATTP mutations, this stereoselective binding capacity is lost, and affected individuals cannot discriminate between RRR- and SRR-α-tocopherol (Traber et al. 1993; Cavalier et al. 1998). In this instance, affected individuals would also be able to incorporate non-2R-α-tocopherol stereoisomers into their bodies if they were supplemented with all-rac-α-tocopherol. Since potential adverse effects of the synthetic stereoisomers have not been studied in detail, it seems appropriate to treat with RRR-α-tocopherol, despite the higher cost. Several studies have reported the stabilization of the clinical symptoms and even some improvement with twice-daily doses of 800 mg of RRR-α-tocopherol in patients presenting ataxia with vitamin E deficiency (Amiel et al. 1995; Yokota et al. 1997; Martinello et al. 1998). Furthermore, fat-enriched meals are recommended in these patients. Oral antioxidant therapy with CoQ10 has slowed the progression of ataxia in patients who are specifically deficient in those components (Hirano et al. 2006; Pineda et al. 2010).

Abetalipoproteinemia The disease in patients with abetalipoproteinemia is directly related to vitamin E deficiency (reviewed in Kayden 2001). Substitution therapy with vitamin E presents complex problems due to severe intestinal malabsorption and requires a close dietetic control to take into account all the aspects involved in the management. In this disease, the lipoproteins transporting α-tocopherol are missing. An early-onset treatment with vitamin E is crucial to avoid or halt the progression of the neurological symptoms. Initial parenteral administration of vitamin E is recommended followed by massive oral doses of α-tocopherol at 100–150 mg/kg. Plasma levels of vitamin E often fail to reflect the whole body content of vitamin E, and the adequacy of vitamin replacement may be difficult to gauge from serum

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concentrations. However, this dose has been shown to improve the overall neurological state of the patient if treatment is started early (Zamel et al. 2008). Vitamins A, D, and K and other dietary supplements must be given. The disease requires lifelong controls to avoid or minimize secondary nervous system damage.

Cerebrotendinous Xanthomatosis (CTX) Cerebrotendinous xanthomatosis (CTX) is a lipid storage disease in which several bile alcohols, particularly cholestanol, are accumulated. Treatment with chenodeoxycholic acid (CDCA) decreases the cholestanol levels, and this leads to the improvement of cognition, psychiatric, motor clinical, and neurophysiological parameters (Berginer et al. 1984). As observed with other metabolic ataxias, earlier treatment usually results in better results (Yahalom et al. 2013). The recommended doses are 15 mg/kg/day in three daily doses. Other treatments include the use of pravastin, a 3-hydroxy-3-methylglutaryl (HMG)-CoA reductase inhibitor, or the combination of both chenodeoxycholic acid and pravastin (Salen et al. 1994; Verrips et al. 1999). More aggressive treatments of CTX with LDL-apheresis have shown contradictory results (Ito et al. 2003; Dotti et al. 2004).

Refsum’s Disease Refsum’s disease features are directly related to the progressive deposition of phytanic acid in different tissues. Thus, the main objective of treatment has been to lower the phytanic acid levels mainly by providing the Westminster-Refsum diet (Baldwin et al. 2010). As patients with Refsum’s disease may suffer from severe clinical exacerbations, therapeutic lipapheresis has been considered in these conditions (Gutsche et al. 1996; Weinstein 1999). Liver cell transplantation is under consideration as a treatment option in Refsum’s disease patients (Sokal et al. 2003; Najimi and Sokal 2005).

Ataxia-Telangiectasia (AT) Betamethasone has been used to improve ataxia symptoms in AT. Two 20-day cycles of oral betamethasone at the dosage of 0.03 mg/kg/day improved ataxia scores (SARA) in all patients (Broccoletti et al. 2011). In a double-blind, randomized, placebo-controlled crossover trial, oral betamethasone (0.1 mg/kg/day for 2  10 days with 10-day intermediate tapering) improved ataxia assessed by ICARS by 17 points (about 30%) compared to placebo (improvement of 4.5 points) (Zannolli et al. 2012). Still, long-term effectiveness and safety need to be established.

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Treatments for Autosomal Dominant Spinocerebellar Ataxias There are currently no known effective pharmacologic treatments to reverse or even substantially reduce motor disability caused by cerebellar degeneration in most of the autosomal dominant spinocerebellar ataxias (SCAs) or related cerebellar disorders, although some benefits on ataxic and non-ataxic symptoms have been reported in a few therapeutic clinical trials (extensively reviewed in Ogawa 2004; Matilla-Dueñas et al. 2006; Manto and Marmolino 2009; Trujillo-Martin et al. 2009; Ilg et al. 2014). Some benefits regarding ataxic symptoms have been reported with acetazolamide and gabapentin in SCA6 (Nakamura et al. 2009). Riluzole was shown to produce a significant benefit after 8 weeks in a group of patients with different types of ataxia (Ristori et al. 2010). Recently the same group carried on a multicenter double-blind placebo-controlled study in 60 patients with spinocerebellar ataxia and FRDA (proportion 2:1). The treatment arm received riluzole 50 mg twice a day for 1 year. The proportion with decreased SARA score was 50% in the riluzole group versus 11% in the placebo group. No severe adverse events were recorded (Romano et al. 2015). Longer studies and disease-specific trials are needed to confirm whether these findings can be widely applied in clinical practice. Lithium exerts neuroprotective effects in preclinical models of polyglutamine disorders and therefore has been tried in some SCA subtypes (Watase et al. 2007). A randomized, phase II, clinical trial of lithium carbonate has been completed in a cohort of 60 patients with Machado-Joseph disease (SCA3). After 48 weeks lithium was safe and well-tolerated, but it had no effect on progression when measured using the Neurological Examination Score for the Assessment of Spinocerebellar Ataxia (NESSCA) (Saute et al. 2014). Nevertheless, some quantitative ataxia scores showed significantly slower progression. In SCA2, a small phase II trial in 20 patients showed no differences in SARA score or brain volume change after 48 weeks (Saccà et al. 2015). Valproic acid (VPA) is a drug used clinically to treat bipolar and seizure disorders. For its properties as HDCA inhibitor, it has been tested in a small randomized, double-blind, placebo-controlled trial in 36 SCA3 patients for 12 weeks. Multidose VPA treatment improved SARA measures of locomotor function, with some adverse effects (Li-Fang Lei et al. 2016). After a few case reports, the efficacy of varenicline in SCA3 was assessed in a randomized placebo-controlled trial over 8 weeks. Twenty patients participated in the study. Varenicline improved SARA sub-scores for gait, stance, and rapid alternating movements as well as the timed walking test in phase I of the study (4 weeks). Nevertheless, a high dropout rate of 40% prevented the completion of the pre-planned crossover design (Zesiewicz et al. 2012). Further studies will have to determine the usefulness of this drug in cerebellar ataxias. Recently, supplementation with docosahexaenoic acid has been shown to be beneficial in a small trial in SCA38 patients (Manes et al. 2017). Treatment with memantine has been shown ineffective for improving tremor and behavior in a randomized, double-blind, placebo-controlled trial in FXTAS (Seritan et al. 2014).

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Amantadine and dopaminergic and anticholinergic drugs have been used to alleviate tremor, bradykinesia, or dystonia in SCA2 and SCA3 (Botez et al. 1991; Tuite et al. 1995; Buhmann et al. 2003). Restless legs and periodic leg movements in sleep usually respond to dopaminergic agonists or clonazepam (Schols et al. 1998; Hening et al. 2010; Zintzaras et al. 2010). Spasticity in SCAs is effectively treated with the GABA analog baclofen or tizanidine. In selected cases where other treatments have failed, botulinum toxin has been successfully used to treat dystonia and spasticity in SCA3 (Freeman and Wszolek 2005), although caution and small dosage are recommended since unusually severe and long-lasting muscular atrophy occurs in some SCA3 patients with this treatment due to subclinical involvement of motor neurons in the anterior horn in the degenerative process. Intention tremor has been ameliorated with benzodiazepines, β-blockers, or chronic thalamic stimulation. Muscle cramps, which are often present at the onset of the condition in SCAs 2, 3, 7, and DRPLA, are alleviated with magnesium, quinine, or mexiletine (Kanai et al. 2003). Piracetam has been used to treat myoclonus and/or dementia/cognitive decline (De Rosa et al. 2006; Kanai et al. 2007; Ince Gunal et al. 2008). In spite of the lack of effectiveness in the treatment of ataxia symptoms in most SCAs, treatment in some spinocerebellar ataxias has proven successful. Furthermore, most autoimmune cerebellar ataxias, such as anti-glutamic acid decarboxylase (GAD)-antibody-positive cerebellar ataxia and gluten ataxia, have proven to be treatable with intravenous immunoglobulin administration (Lock et al. 2006; Nanri et al. 2009). In the remaining ataxias, physiotherapy (discussed later in this chapter) is currently being used as an effective treatment alternative. Ataxia improves with daily autonomous training of gait and stance in combination with physiotherapy (Ilg et al. 2009, 2010). Other neurological symptoms such as dysarthria and dysphagia warrant logopedic treatment to maintain the ability to communicate and to prevent pneumonia from aspiration.

Treatments for Episodic Ataxias Several different drugs are reported to improve symptoms in EA1 and EA2, but so far there have been no controlled studies documenting or comparing the efficacy of these different drugs. Carbamazepine, valproic acid, and acetazolamide (ACTZ) have proven effective for EA1 (Eunson et al. 2000; Klein et al. 2004); and ACTZ (Griggs et al. 1978), 4-aminopyridine (Strupp et al. 2004, 2008), and chlorzoxazone (CHZ) (Alvina and Khodakhah 2010a) have been effective in EA2 cases. The response to acetazolamide is often dramatic in EA2 (Griggs et al. 1978; Jen et al. 2004) and is considered the treatment of choice. ACTZ should not be prescribed to individuals with liver, renal, or adrenal insufficiency. Acetazolamide, a carbonic anhydrase (CA) inhibitor, may reduce the frequency and severity of the attacks in some but not all affected individuals with episodic ataxias. Chronic treatment with ACTZ may result in side effects including paresthesias, rash, and formation of renal calculi.

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Antiepileptic drugs (AEDs) such as carbamazepine may significantly reduce the frequency of the attacks in responsive individuals; however, the response is heterogeneous as some individuals are particularly resistant to drugs (Eunson et al. 2000). Anticonvulsant drugs such as sulthiame may reduce the attack rates. During this treatment, abortive attacks were still noticed lasting a few seconds, and troublesome side effects were paresthesias and intermittent carpal spasm (Holtmann et al. 2002). The potassium channel blocker 4-aminopyridine has been found to be effective in stopping attacks in patients with EA2 (Strupp et al. 2003; Alvina and Khodakhah 2010b). Furthermore, 3,4-diaminopyridine was demonstrated in a placebocontrolled study to improve downbeat nystagmus, which is often observed in patients with EA2 (Strupp et al. 2003).

Emerging Therapeutic Strategies In the last decade, intensive scientific research has been devoted to identifying molecular pathways underlying cerebellar neurodegeneration (Matilla-Dueñas et al. 2010, 2014) with the aim of discovering and establishing effective and selective therapeutic strategies to treat cerebellar diseases. Among them, a few innovative approaches yielding promising results are being investigated at the preclinical and in some cases at the clinical level including the use of RNA interference (RNAi) aiming to inhibit the expression of mutated polyglutamine proteins in those SCAs caused by expanded polyglutamine mutations, prevention of protein misfolding and aggregation by overexpression of chaperones and by pharmacological treatments, the regulation of gene expression by treatment with HDAC inhibitors, and also gene therapy. Intracerebellar injection of vectors expressing short hairpin RNAs was shown to selectively decrease the expression of mutant proteins and profoundly improves disease phenotypes in SCA1 and SCA7 transgenic mice (Xia et al. 2004; Ramachandran et al. 2014; Keiser et al. 2016). While these results show that RNAi therapy improves cellular and behavioral characteristics in preclinical trials, its application in patients to protect or even reverse disease phenotypes shall be delayed until proper toxicity tests are assessed. Another promising RNA-targeted therapy is based on antisense oligonucleotides (ASO). Specific ASOs downregulating both wild-type and mutant ataxin in SCA2 and SCA3 mouse models have been tried and showed improved motor function and pathogenicity markers (Scoles et al. 2017; Moore et al. 2017). As another target, molecular chaperones provide a first line of defense against misfolded, aggregationprone proteins. Many studies have analyzed the effects of chaperone overexpression on the inclusion body formation and toxicity of pathogenic polyQ fragments in cell culture, and it is clear that overexpression of molecular chaperones might prove beneficial for the treatment of cerebellar diseases (Muchowski and Wacker 2005). They prevent inappropriate interactions within and between non-native polypeptides, enhance the efficiency of de novo protein folding, and promote the refolding of proteins that have become misfolded as a result of the mutations and cellular stress (Chan et al. 2000). Chemical and molecular chaperones might also prevent toxicity

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by blocking inappropriate protein interactions, by facilitating disease protein degradation or sequestration, or by blocking downstream signaling events leading to neuronal dysfunction and apoptosis. The first proof-of-concept studies supporting such idea were performed using Congo red, thioflavin S, chrysamine G, and Direct Fast yellow which proved to be effective in suppressing molecular aggregation in vitro and in vivo and ameliorate symptoms (Heiser et al. 2000; Sanchez et al. 2003); albeit their efficacy in vivo is limited by their variable abilities to cross the blood-brain barrier and bioavailability such that proper pharmacologic analogs may need to be developed for further clinical considerations. Other low molecular mass chemical chaperones, such as the organic solvent dimethyl sulfoxide (DMSO) and the cellular osmolyte glycerol, trimethylamine n-oxide, and trehalose, appear to ameliorate cell death triggered by mutant ataxin-3 by increasing its stability in their native conformation (Yoshida et al. 2002). More recently trehalose has been shown to attenuate the gait ataxia and gliosis in SCA17 mice (Chen et al. 2015). Results from a 6-month open-label phase II study in SCA3 patients showed stabilization of ataxia symptoms over the study period (Unpublished results, Bioblast Pharma). Trehalose was identified in an in vitro screen for inhibitors of polyglutamine aggregation, and its administration reduces brain and cerebellar atrophy, improves motor dysfunction, and extends the life span of mice resembling the polyglutamine disorder Huntington’s disease (Tanaka et al. 2004). In vitro experiments suggest that the beneficial effects of trehalose result from its ability to bind and stabilize polyglutamine-containing proteins. Two trehalose analogs, lactulose and melibiose, were tested in SCA models (Lin et al. 2016). More recently, a new generation of small chemical compounds that directly target polyQ aggregation without significant cytotoxicity have been identified in high-throughput screens using cell-free assays or by targeting cellular pathways (Heiser et al. 2002; Zhang et al. 2005). These compounds decrease the molecular aggregation in cultured cells and brain slices and can rescue neurodegeneration in a drosophila model, although no effect was detected in mouse models possibly due to the bioviability issues of the compounds. By a different mechanism, a small molecule that acts as a co-inducer of the heat-shock response by prolonging the activity of heat-shock transcription factor HSF1, arimoclomol, significantly improves behavioral phenotypes, prevents neuronal loss, extends survival rates, and delays disease progression in a mouse model of neurodegeneration (Kieran et al. 2004). Similarly, activation of heat-shock responses with geldanamycin inhibits aggregation and prevents cell death (Rimoldi et al. 2001). This suggests that pharmacological activation of the heat-shock response may therefore be an effective therapeutic approach for treating neurodegenerative diseases. However, excessive upregulation of chaperones might lead to undesirable side effects, such as alterations in cell cycle regulation and cancer (Mosser and Morimoto 2004). Therefore, a delicate balance of chaperones will likely be required for a beneficial neuroprotective effect. For instance, chemical or molecular chaperones, used in combination with a pharmacological agent that upregulates the synthesis of molecular chaperones, might be a valid therapeutic approach for treating spinocerebellar ataxias caused by polyglutamine expansions. Aggregate formation has also been successfully targeted with inhibitors of transglutaminase, such as

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cystamine, which reduces apoptotic cell death and alleviates disease symptoms (Dedeoglu et al. 2002; Karpuj et al. 2002). Compounds directly targeting mitochondrial function such as coenzyme Q10 (Shults 2003), creatine (Ryu et al. 2005), and tauroursodeoxycholic acid (TUDCA) (Keene et al. 2002) or autophagy, such as the mTor inhibitor rapamycin and various analogous (Ravikumar et al. 2004), have proven effective at reducing cellular toxicity in animal models and are currently being tested in clinical trials in a few ataxia subtypes (Menzies and Rubinsztein 2010). Caspase activation, which usually precedes neuronal cell death, has been targeted by inhibiting their expression, recruitment, and consequent activation onto “apoptosome-like signaling structures” by CrmA and FADD DN (Sanchez et al. 1999) or by enzymatic inhibitors including minocycline, zVAD-fmk, and cystamine, respectively (Ona et al. 1999; Sanchez et al. 1999; Lesort et al. 2003). In general, the inhibitors of the different caspases have been shown to decrease microglial activation, prevent disease progression, delay onset of symptoms, enhance inclusion clearance, and extend survival rates in several mouse and cell models of neurodegeneration (Ona et al. 1999; Chen et al. 2000; Lesort et al. 2003). Other agents promoting the clearance of mutant proteins in the CNS or which are Ca2+ signaling blockers and stabilizers, such as specific inhibitors of the NR2B subunit of N-methyl-D-aspartate glutamate receptors, blockers/antagonists of metabotropic glutamate receptor mGluR5, and inositol 1,4,5-trisphosphate receptor InsP3R1 such as remacemide; intracellular Ca2+ stabilizers such as dantrolene; dopamine stabilizers such as mermaid-ACR-16; dopamine depleters and agents inducing anti-excitotoxic effects such as riluzole; or agents which alleviate cognitive components such as horizon-dimebon appear to be at least partially beneficial for the treatment of some neurological symptoms in spinocerebellar ataxias (Gauthier 2009; Liu et al. 2009; Mestre et al. 2009). Neuroprotective drugs like olesoxime have proven to increase microtubule dynamics, re-establish neuritic outgrowth, improve myelination, and prevent apoptotic factor release and oxidative stress in amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) (Bordet et al. 2007) and are potential drugs to be tested in ataxias. Inhibition of potassium channels with 3,4-diaminopyridine has proven efficient in normalizing motor behaviors in young SCA1 mice and in restoring normal Purkinje cell volume and dendrite spine density and the molecular layer thickness in older SCA1 mice. Aminopyridines, such as fampridine and diaminopyridine, increase PC excitability and are also efficient for treating downbeat nystagmus (Strupp et al. 2008; Alvina and Khodakhah 2010b; Tsunemi et al. 2010). Peroxisome biogenesis dysregulation has been identified as the underlying causative deficits in some cerebellar diseases in which bile acid supplements and dietary restriction of phytanic acid are indicative (Regal et al. 2010), and therefore treatment targeting this pathway is potential of being explored. The roles that some proteins implicated in cerebellar diseases play in transcription and, more importantly, the effects mediated by some of their co-transcriptional regulators in the suppression of cytotoxicity are being used as targets to modulate the pathological effects, thus opening the path for new therapeutic strategies for treating some spinocerebellar conditions. Recent progress in histone deacetylase

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(HDAC) research has made possible the development of inhibitors for specific HDAC family proteins, and these compounds could prove effective candidates for the treatment of spinocerebellar ataxias (Dokmanovic and Marks 2005; Thomas et al. 2008). Neuroprotective and neurorestoration strategies addressing specific bioenergetics defects might hold particular promise in the treatment of spinocerebellar conditions. Drugs, such as rasagiline, a selective irreversible monoamine oxidase B inhibitor, have been shown efficient in protecting neuronal cells against apoptosis through induction of the pro-survival Bcl-2 protein and neurotrophic factors providing an experimental rationale for rasagiline as a disease-modifying molecule (Naoi et al. 2009). Rasagiline is expected to enter a few phase III clinical trials shortly. Recent alterations of the insulin growth factor (IGF-1) pathway have been reported to be implicated in SCA1, SCA3, and SCA7 (Gatchel et al. 2008; Saute et al. 2011), suggesting that in vivo neuroprotection exerted by IGF-1 potentially through the PP2A-regulated PI3K/AKT signaling pathway could potentially be used to halt cerebellar neurodegeneration (Fernandez et al. 2005; Leinninger and Feldman 2005; Sánchez et al. 2013). Clinical trials with IGF-1 on AT and SCA3 patients are underway. Most recently, the protective effects of the modulation of the GSK3beta and the mTOR pathway in cell model SCA1 have been demonstrated (Sanchez et al. 2016). Observational studies have shown that the mTOR activator DL-acetyl leucine shows promising results in SCA patients and serves as the bases for a full clinical trial (ALCAT) which has been completed with encouraging results (Schniepp et al. 2016; www.clinicaltrialsregister.eu/ctrsearch/trial/2015-000460-34/DE8). Gene therapy and stem cell and grafting approaches are being experimentally considered for treating spinocerebellar neurodegenerations as well (Chintawar et al. 2009; Erceg et al. 2010; Louboutin et al. 2010). Delivery of proteins or compounds by viral vectors onto the cerebellum represents one such gene therapeutic approach (Louboutin et al. 2010). Vectors used are capable of transducing neurons and microglia very effectively and thus can be used for gene delivery targeting to the cerebellum in vivo. Neural cell replacement therapies are based on the idea that neurological function lost during neurodegeneration could be improved by introducing new cells that can form appropriate connections and replace the function of lost neurons. This cell replacement therapeutic strategy although potentially effective is still in early experimental stages (Erceg et al. 2010), and the use and the process for reprogramming human somatic cells from accessible tissues, such as the skin or blood, to generate functional “disease- and patient-specific” neurons from embryonic-like induced pluripotent stem cells (iPSCs) present several technical challenges (Saha and Jaenisch 2009; Tenzen et al. 2010). Since neurogenesis does occur in the adult nervous system, another approach is based on the stimulation of endogenous stem cells in the brain, cerebellum, or spinal cord to generate new neurons. Studies to understand the molecular determinants and cues to stimulate endogenous stem cells are underway (Gage 2002). A recent study by Lee and colleagues suggested slowed progression of patients presenting the cerebellar subtype (MSA-C) of multiple systemic atrophy who had been treated with mesenchymal stem cell grafts (Lee et al. 2008). More recently, two clinical trials have looked at the safety and efficacy of stem cell transplantation in SCA patients

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(Dongmei et al. 2011; Jin et al. 2013). Both reported favorable outcomes; however both trials were open-label, and substantial placebo effects cannot be discarded. Although promising and further preclinical work is necessary to define the molecular mechanisms underlying these effects, we are only starting to learn the potential and challenges of these emerging therapies, especially their efficacy in treating human cerebellar neurodegeneration. In vivo gene editing through the CRISPR/Cas9 technology is a promising therapeutic strategy albeit still at early stages in preclinical stages. Promising results were obtained in vitro with the excision of the GAA expanded repeat in cells from Friedreich’s ataxia patients using gene-editing technology (Li et al. 2015). Still, much work needs to be done to translate this approach to the clinic. Another non-pharmacological approach for the treatment of ataxia is exploring the potential use of both invasive and noninvasive brain stimulation. Several case reports have shown the effectiveness of thalamic deep brain stimulation in improving tremor and ataxia in FXTAS patients (dos Santos Ghilardi et al. 2015; Weiss et al. 2015). Also, thoracic epidural spinal cord stimulation had a mild beneficial effect in improving gait and balance in a single patient with SCA7 (Sidiropoulos et al. 2014). Regarding noninvasive cerebellar stimulation, two techniques have been used, transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). In TMS, a rapid electrical current is delivered through a coil generating a magnetic field that can reach neural tissue inducing a rapidly changing electric field that can depolarize neurons. In tDCS, a small steady current is passed between two large electrodes applied over the scalp. This current has neuromodulatory effects eliciting increases or decreases of neuronal excitability underneath the electrodes (Nitsche and Paulus 2011). Recent studies showed that cerebellar stimulation might have a role as a therapeutic intervention (Grimaldi et al. 2014). A sham-controlled study in 74 spinocerebellar ataxia patients delivered multiple single pulses of TMS over the cerebellum and described a significant reduction of truncal ataxia (Shiga et al. 2002). More recently, tDCS was investigated in a 2-week, double-blind, randomized sham-controlled trial showing a significant improvement in all performance scores (SARA, ICARS, 9-Hp test, and 8-m walking time) in treated patients compared to patients who underwent sham stimulation (Benussi et al. 2017). The abovementioned studies suggest that noninvasive stimulation has the potential of becoming a therapeutic option and rehabilitative approach for patients with neurodegenerative ataxia. tDCS might complement drug therapy both in children and in adults by modulating residual cerebellar circuits and promoting plasticity, especially at an early stage (Ferrucci et al. 2019; Ferrucci and Priori 2018; Mitoma and Manto 2018).

Physical Therapy in Cerebellar Diseases The cerebellum integrates sensory input, mainly proprioceptive and vestibular, with voluntary motor action to assure coordinated and automated timing, duration, and amplitude of muscle activity in normal movement. It guarantees equilibrium and vestibular oculomotor control (midline cerebellar structures), accurate limb

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movement (cerebellar hemispheres and outflow tracts), and modulated speech (paramedian structures). It also plays a role in motor learning. Cerebellar damage typically results in varying degrees of instability of stance and gait, clumsy target maneuvers, slowed alternating movements, postural or action tremor of trunk or limbs, decreased muscle tone, slurred speech, dizziness, and nystagmus or saccade inaccuracies, among other oculomotor signs. In addition, bladder/sphincter dyssynergia causes frequent or urgent incontinence. When the cerebellum is damaged, the activity of daily living (ADL) is disturbed (Miyai 2012). SCA patients may suffer all symptoms or just some of them, but unfortunately they will be progressive in most patients. Since few pharmacological options are available, most treatments rely heavily on rehabilitation therapy including exercise/physical therapy programs and speech and swallow evaluation and training. However, the cerebellum is known to play a crucial role in both motor control and motor learning. Therefore, the benefits of physiotherapy, speech and occupational therapy, for patients with degenerative ataxia have been a long time under controversy. Although motor learning is impaired due to cerebellar damage, rehabilitation techniques can improve gait and ADL. There is also evidence that both transcranial magnetic stimulation and transcranial direct current stimulation modulate the activity between the cerebellum and the primary motor cortex circuits, impacting both motor and cognitive contributions of the cerebellum (Grimaldi et al. 2014) that might be helpful to complete rehab interventions. In this regard, impairment of cerebellar patients in practice-dependent motor learning has been shown for various motor tasks (Maschke et al. 2004). Additionally, most of the research has been done with case studies or case series with heterogeneous populations, interventions, and outcomes (Martin et al. 2009), and no information regarding the long-term effectiveness of physiotherapy is available. This has made it difficult to determine whether the lack of benefit retention after an exercise program is due to the neurodegeneration, to the lack of an appropriate physical therapy program, or to the inability to retain the newly learned movement patterns. Because of the low prevalence of these diseases, no large, double-blind, randomized, controlled trials have been assayed to demonstrate the actual value of such interventions along with the insufficient evidence to support the efficacy of any specific therapy. Since 2014 there are many interesting observations in children (Ilg et al. 2014) improving motor performance by intensive coordination training and new easily adaptable technologies as videogames based on biofeedback that may provide a Class III evidence for ataxia rehabilitation (Ilg et al. 2012). Based on the principle that symptomatic treatments can be useful independently of the etiology of the problem, as are considered in rehabilitation programs mainly pointing to the syndromic approach of the disease, much of the successful work done with Friedreich’s ataxia patients is currently applied to treat SCA patients.

Physical Therapy Examination A comprehensive natural history is a critical feature when examining SCA patients since these diseases can involve multiple systems, thus data about previous

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interventions and surgeries should be collected and the cardiovascular and musculoskeletal systems carefully reviewed (Maring and Croarkin 2007). Additionally, gaining insights into psychosocial factors is essential in the interview process since the progressive nature of the symptoms could subjectively influence an individual’s perception of his or her quality of life to various degrees (D’Ambrosio et al. 1987). The examination should consist of a complete history, a thorough review of the systems, and the implementation of the best available tests and measures to describe patients’ impairment and functional limitations. In routine clinical settings, traditional measurements of symmetry, range of motion, and muscle strength are good indicators of specific impairments of the musculoskeletal system. Cranial nerves should also be tested for signs of impairment of ocular movements, acuity and visual field deficits, hearing loss, dysarthria, and dysphagia. A complete test of the sensory system is recommended since sensory neuropathy may be present and may contribute to the ataxia symptoms (Perlman 2004; Maring and Croarkin 2007). Finally, testing velocity and the independence of the gait are easy to achieve and represent important functional measurements in SCA patients. Such a complete physical therapy exam would eventually offset the risk of falling and would prevent accompanying injuries and erosion of self-confidence during the physical therapy sessions (Perlman 2004). Composite rating scales have been proposed in order to improve reliability and validity of performance measures including the International Cooperative Ataxia Rating Scale (ICARS), the Ataxia Clinical Rating Scale, the Ataxia Functional Composite Scale, the Brief Ataxia Rating Scale, the Functional Ataxia Scoring Scale, the Inherited Clinical Rating Scale, the Northwestern University Disability Scale, and the Scale for the Assessment and Rating of Ataxia (SARA) (MoralesSaute et al. 2012). All of them show good interrater and test-retest reliabilities. Among them, only the International Cooperative Ataxia Rating Scale, the Ataxia Clinical Rating Scale, and the Inherited Ataxia Clinical Rating Scale demonstrated a good relationship between score and disease duration (Maring and Croarkin 2007). ICARS is the more widely used clinical scale up to date, and it has been correlated with cerebellar volume measures in patients with pure cerebellar degeneration (Richter et al. 2005). However, internal validity is unclear, and more recent scales such as SARA can be completed faster and may have better construct validity (Schmitz-Hubsch et al. 2006). Other tools reported in single-case follow-up or cohort studies include the Berg Balance Score (Berg 1989), the timed unsupported stance test, the Functional Ambulatory Category (FAC) test, the 10-meter walk test, the Outpatient Physical Therapy Improvement in Movement Assessment Log (OPTIMAL), the transverse abdominal thickness, and the kinematic analysis and isometric endurance (Maring and Croarkin 2007; Freund and Stetts 2010), Goal Attainment Scaling (GAS) (Kiresuk et al. 1994), and Functional Independence Measure (FIM) (Keith et al. 1987). Recently, quantitative movement analysis of the gait and static and dynamic balance tasks have revealed a specific behavior in patients with degenerative ataxia and intensive coordinative training. Essentially, patients with cerebellar ataxia showed significant improvement in intralimb coordination, balance control in gait,

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and balance tasks as opposed to patients with afferent ataxia. In patients with severe disease, i.e., SCA, the use of functional imaging might be really helpful to assess visible effects on neural plasticity (Sarva and Shanker 2014).

Physical Therapy Interventions The aim of physical therapy is to maintain the individual’s independence in all environmental contexts for as long as possible. The physical therapist will contribute to educate patients and family members about the effects of the disease on the function of lifestyle, potential interventions, and realistic expectations about them. However, there is little evidence regarding specific physical therapy interventions in ataxia patients (Class III); therefore programs shown to be beneficial in other patient populations with ataxia could be reasonably recommended (Sliwa et al. 1994; Perlmutter and Gregory 2003; Harris-Love et al. 2004; Ilg et al. 2012, 2014; Miyai et al. 2012). Those programs include aerobic fitness, maintenance of biomechanical alignment, and counseling for assistive or adaptive devices, which would preserve the independence of mobility. Physiotherapy exercises might be complemented with training based on recently developed commercially available videogame technology (“exergames”) (Ilg et al. 2012). Most authors agree that the main working goals of physical therapy are to develop strategies to optimize sensorial information, to improve balance in stance by postural reaction and postural stabilization, to develop strategies for an independent gait, to improve the quality and control of movement in different body postures, to exercise against resistance to improve hypotonia as well as to adjust motor control, to calibrate the motor control of speech, and to improve coordination. Motor coordination can be trained using Frenkel’s method (Vaz et al. 2008; Martin et al. 2009). Essentially, Heinrich Sebastian Frenkel designed a method to improve motor control through repetitive exercises. In general, treatment is recommended early in the course of the disease, the patient should start with easy and wide exercises, and once they are perfectly performed, the next level of complexity would be recommended. All exercises should be performed with open and closed eyes, fast movements should precede the slow ones, and the proximal joints and trunk should be approached from the beginning. A report of progression should be registered. Frenkel’s method should be complemented with a Bobath concept approach to physiotherapy. The Bobath concept incorporates a biopsychosocial approach and is based upon recovery as opposed to compensation (Graham et al. 2009). The main principles are as follows: (1) Human motor behavior is based upon continuous interaction between the individual, the environment, and the task; (2) the individual focuses on the goal rather than the specific movement in the acquisition of motor skills; (3) learning and adaptation of motor skill involve a process associated with practice and experience. Contemporary practice in the Bobath concept utilizes a problemsolving approach to the individual’s clinical presentation and personal goals. Treatment guides the individual towards efficient movement strategies for task performance. The

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method in Bobath concept focuses particularly on two interdependent aspects: the integration of postural control and task performance and the control of selective movement for the production of coordinated sequences of movement. Intervention is directed at analyzing and optimizing all factors contributing to efficient motor control. The Bobath concept also seeks to utilize appropriate sensory input to influence postural control and the internal representation of a postural body schema. One of the main strategies for improving postural control in relation to gravity and the environment is the alignment of body segments in relation to each other and the base of support. Selective movement and movement patterns will be accessed by facilitating taskspecific patterns of muscle activation and the therapist aims to utilize afferent input to reeducate the internal reference systems to enable the patient to have more movement choices and greater efficiency of movement. In addition to both the Frenkel’s method and Bobath concept, single-case reports have shown the benefit of trunk stabilization training and locomotor training using body-weight support on a treadmill (Cernak et al. 2008; Freund and Stetts 2010). In conclusion, individualized physical therapy, including traditional and biopsychosocial methodology, is proposed as one of the main symptomatic treatments for SCA patients. Therapy will have reasonable goals since small steps may represent a great motivation and may increase adherence to treatment leading to a real and sustainable change in patients’ lives and their families.

Concluding Remarks and Future Directions As with other cerebellar diseases, the cerebellar ataxias are devastating neurological diseases for which, currently, there are yet no effective and selective pharmacological or biological treatments available that reverse or even substantially reduce motor disability caused by cerebellar pathology. The recent progress on the understanding of cerebellar diseases has been possible through the combined efforts of worldwide international academic networks. However, further experimental and clinical research is needed to further understand their pathogenesis, to validate and define the role of the updated clinical diagnostic criteria, and to enhance the assessment of the disease. This research would also help to develop novel supportive neuroimaging methods and other clinical investigations that might improve the diagnostic precision and facilitate early diagnosis and treatment. Importantly, more effort is necessary to define disease-modifying therapeutic strategies. Currently, physical therapy is the sole form of intervention that can improve walking ataxia in affected individuals, and the effectiveness of physiotherapy for adults with severe cerebellar dysfunction is currently under assessment. These studies are of particular interest because they show how individuals with cerebellar damage can learn to improve their movements and recover the control of their balance and proprioceptive contributions enabling them to achieve personally meaningful goals in everyday life after proper training. Remarkably, video games may be included in the rehabilitation protocol as they are widely available and can turn out a new home-based biofeedback therapy. Until effective and selective

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pharmacological treatment which ultimately should lead to a better quality of life and increased survival of patients with cerebellar diseases, physical and sensory rehabilitation are meanwhile revealing effective approaches for improving the patient’s quality of life. Taken together, all the data resulting from the most recent intensive research highlight that providing effective treatments to ataxia patients is no longer a utopia, but it is possible in the foreseeable future.

Cross-References ▶ Adaptive Filter Models ▶ Approach to the Differential Diagnosis of Cerebellar Ataxias ▶ Autosomal Dominant Spinocerebellar Ataxias and Episodic Ataxias ▶ Autosomal Recessive Cerebellar Ataxias ▶ Cerebellar Control of Eye Movements ▶ Cerebellar Control of Posture ▶ Cerebellar Control of Speech and Song ▶ Cerebellar Influences on Descending Spinal Motor Systems ▶ Cerebellar Motor Disorders ▶ Cerebellar Thalamic and Thalamocortical Projections ▶ Cerebellum and Eyeblink Conditioning ▶ Cerebellum and Timing ▶ Cerebro-cerebellar Connections ▶ Clinical Scales of Cerebellar Ataxias ▶ Delineation of Cerebrocerebellar Networks with MRI Measures of Functional and Structural Connectivity ▶ Functional Topography of the Human Cerebellum Revealed by Functional Neuroimaging Studies ▶ General Management of Cerebellar Disorders: An Overview ▶ Mitochondrial Disorders ▶ MR Spectroscopy in Health and Disease ▶ Neuropathology of Ataxias ▶ Vestibulocerebellar Functional Connections ▶ Visual Circuits from Cerebral Cortex to Cerebellum; The Link Through Pons ▶ X-Linked Ataxias Acknowledgments The research of this work was mainly funded by the Spanish Health Institute Carlos III (CPII/00029; FIS PI14/00136; FIS PI17/00534). Antoni Matilla Dueñas was a Miguel Servet Investigator in Neuroscience supported by the Spanish Health Institute Carlos III (ISCIII; CP08/00027 CPII14/00029).

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Index

A Abetalipoproteinemia, 2677 Accessory motor features, 2446–2447 Accidental involution, 1696 Aceruloplasminemia, 2292 Acetazolamide, 1711, 1722, 1723, 1748, 2543, 2680 N-acetylaspartate, 777 Acetylcholinesterase (AChE), 664 Acetylleucine, 2643 Achaete/scute like1, 25 Achaete-Scute Family BHLH Transcription Factor 1, 126 Acquired cerebellar lesions, 2127 Acquired disorders, 722 Acquired disruption, 2114 Actinopterygian fish, 1650, 1660 Action myoclonus-renal failure syndrome, 2198, 2220 Action potential, 1158–1159 Action sequences, 1941 Activation voltage, 1744, 1745, 1749 Active perception, 1516, 1528, 1531 Activities of daily living (ADL) assessment, 2037 Acute cerebellar lesions, 1865–1866 Acute disseminated encephalomyelitis, 731 Acutely dissecting aneurysms, 755 Adaptive behavior and cerebellum, 1527–1528 role of cerebellum in, 1526 Adaptive filter models, 1504 initial plausibility, 1509 LTD, 1511–1513 LTP, 1510–1511 molecular layer interneurons, 1505 STDP, 1505–1509 Adaptive learning, 1498–1500 Adenine nucleotide translocator (ANT), 2564

Adenosine breakdown and uptake of, 1065–1066 hypoxia and ischemia, 1066 receptors in cerebellum, 1058–1061 release, 1061–1065 signalling in cerebellum, 1057 Adenosine triphosphate (ATP) expression of P2 receptor in cerebellum, 1050–1051 extracellular metabolism, 1055–1057 mechanical stimulation, 1048 P2 receptors, 1048–1050 role in glial signalling, 1053–1055 synaptic actions, 1051–1053 Adiadochokinesia, 1840 Adiadochokinesis, 1906 Adjustable pattern generator (APG) model, 1387 ADP (after depolarization), 1048, 1197, 1198 Adrenal steroid hormones, 366–367 α-Adrenergic receptors, 1724 Adult cerebellar cortex, 46–48 Adult neurogenesis, 1639–1640 Adult-onset NCL, 2204, 2205 Adynamia, 2002 AF4 proteins, 1671–1673 cofactor of transcriptional elongation and chromatin remodeling, 1674–1677 Affect, 616, 618 Affective impairment, 2115 Affective processing, 1938 ω-Agatoxin-IVA, 1737, 1748 Agrammatism, 1354, 1948 AHP (after hyperpolarization), 1197, 1198 AICA infarction, 2238 Alcohol, 157–159 Alcoholism, 789

© Springer Nature Switzerland AG 2022 M. U. Manto et al. (eds.), Handbook of the Cerebellum and Cerebellar Disorders, https://doi.org/10.1007/978-3-030-23810-0

2701

2702 Allopregnanolone, 1117 biological actions in pineal gland, 1128 biological actions in Purkinje cell, 1121–1123 mode of action, 1127–1129 in neonatal rat, 1120 Alpha dystroglycanopathy, 2080 Alpha-ketoglutarate dehydrogenase, 2565 Alpha-synuclein-positive structures, 2455 Alpha-tocotrienol quinone, 2674 Aluminum, 2388 Alzheimer’s disease, 2448 Amino-acid-coding RNA-s, 1570 Amino acid neurotransmitters, 1695 γ-Aminobutyric acid (GABA), 777, 778, 1694 3-Aminopyridine (3-AP), 298 Aminopyridines, 2644 Amiodarone, 2288, 2375 amos, 27 AMPAR-binding protein (ABP), 940 AMPA receptors (AMPARs) cornichon homologues, 939–940 intracellular protein partners, 940–942 regulation of, 932 SAP, 943 AMPAR subunits, 930, 932, 933, 935, 938–940, 943, 944 Amphibian and reptile models, 1611–1612 Amyloid angiopathy, 2244 Androgen(s), 368 receptor, 368, 370 Aneurysmal disease distal cerebellar aneurysms, 756–757 fusiform aneurysms, 754–756 saccular aneurysms, 751–754 Animal models, 1606 Animal-related cerebellar toxicity, 2395 Animal studies, 1607 Anorexia nervosa, 2103 Anterior cerebral artery (ACA), 1910 Anterior diencephalon, 10 Anterior inferior cerebellar artery (AICA), 455–456, 460, 1860 infarction, 749–750 Anterior interposed nucleus, 541–542, 630, 637–638 Anterior interstitial cell groups (AICG), 533 Anterior intraparietal area, 688 Anterograde transneuronal transport, 691 Anti-ataxic drug, 1748, 1751 Anticipation (related to dynamic mutations), 2066, 2207

Index Anticipatory postural adjustments (APAs), 1385, 1846 Anticonvulsants amiodarone, 2375 carbamazepine, 2371–2372 phenytoin, 2371 valproic acid, 2373 vigabatrin, 2372 Anti-dipeptidyl-peptidase-like protein-6, 2275–2276 Anti dromic activation, 1220 Anti-glutamic acid decarboxylase ataxia, 2265–2266 Anti-Hebbian plasticity, 1448 Anti-mGluR1 antibodies, 2330 Anti-myelin-associated glycoprotein ataxia, 2276 Antineoplastics Ara-C, 2373 capecitabine and 5-FU, 2373 cisplatin, oxaliplatin and taxol, 2374 epothilone D, 2374 methotrexate, 2374 Antisense oligonucleotides (ASO), 1412, 2681 Anti-thyroid drugs, 358, 362 Anti-Yo antibodies, 2328 Apical dendrites, 907, 910–913, 915, 917 Aplasia, 2118, 2120 Apoer2, 51 Apolipoprotein E receptor 2, 51 Apoptosis, 1691, 1741, 1750 Apoptosis inducing factor (AIF), 439 Apparent diffusion coefficient, 2323, 2325 Apraxia, 1980 Aqueductal stenosis, 2140 Ara-C, 2373 Arachnoid cyst, 2085 Aripiprazole, 2181 Arm tremor, 2445 Aromatase, 367–368 Arrow-model, 1563 ARSACS, 393 Arterial ischemic stroke, 1930 Arteriovenous malformation (AVM), 757–760 Arthrogryposis multiplex congenita (AMC), 2473 Articulatory-associated activation, 804 as-c complex, 27 Ascl1, 25, 29, 34, 35 Ascorbate, 777, 780 Asenapine, 2181 Association areas, 610–612 Associative learning, 886

Index Astrocytoma, 788 Astronauts brain structure and behavior, changes in, 1423–1424 impact of space environmental factors (see Space environmental risk factors, on MGVHB axis) inescapable stress, 1427 vagus nerve signaling and heart abnormalities, 1422–1423 Ataxia(s), 390, 650, 967, 1696, 1701, 1734, 1735, 1737, 1738, 1741, 1743, 1744, 1746, 1748–1749, 1774–1776, 2167–2168, 2446, 2447 ADCA, 2061–2062 ARCAs, 2057–2060 dysarthria, 1837 early-onset, 393–394 episodic, 2062, 2680–2681 gait, 1846, 2646 genetic, 391 genetic testing, 2068 hereditary, 2669 idiopathic late-onset cerebellar, 2064–2065 late-onset, 394–395 of limbs, 1838–1846 mitochondrial cerebellar, 2063–2064 molecular genetics of, 2065–2067 monoparesis, 1908, 1915 natural history and pathophysiological approaches, 2055–2057 and non-ataxic symptoms, 2679 physical therapy interventions, 2688–2689 quadriparesis, 1908 rating scales, 2687 spastic, 2065 spinocerebellar (see Spinocerebellar ataxia) of stance, 1846 tetraparesis, 1908 therapeutic strategies, 2681–2685 with vitamin E deficiency, 2476 X-linked cerebellar, 2062–2063 Ataxia neuropathy spectrum (ANS), 2580–2581 Ataxia scales, 2671 BARS, 2041–2044 FARS, 2037–2039 ICARS, 2036–2037, 2043, 2044 SARA, 2039–2041, 2043, 2044 Ataxia- telangiectasia (AT), 1930, 2059, 2060 Ataxia with oculomotor apraxia type 1, 2474 type 2, 785, 2475

2703 Ataxic hemiparesis (AH), 1904 afferent and efferent pathways, role of, 1914–1915 basal ganglia, 1913 brainstem and cerebellum, 1913–1914 cerebral cortex, 1910–1912 diagnostic testing, 1916–1917 etiology of stroke, 1916 frequency of, 1909–1910 head trauma, 1909 hemorrhagic stroke, 1909 history, 1905 limb weakness, 1905 neurological signs and symptoms, 1907 nonischemic AH, 1908 painful AH, 1907 prognosis, 1917–1918 sensory abnormalities, 1906 sensory AH, 1907–1908 severity, 1908 subcortical lesions, 1912 thalamus and internal capsule, 1912–1913 treatment, 1917 Ataxic mutation in Syrian hamster applications, 1766 breeding and properties, 1759–1762 characterization, 1758 future research, 1771 genetics, 1764–1765 histology, 1762–1764 origin of discovery and hereditary mode, 1759–1760 vs. pcd mice, 1769–1770 Ataxin-2, 2622 Atherosclerosis, 1916–1918 Atlas of the cerebellar cortex, 1882, 1883 Atlas of the cerebellar nuclei, 1882–1883 ato, 27 Atoh1, 25, 28–34, 70, 74, 75, 84, 91, 103, 104, 434–435 Atoh5, 28 atonal, 27, 29 Atonal homolog1, 25 ATP, see Adenosine triphosphate (ATP) Atrophin-1, 2207 Attention, 2122, 2124, 2125 deficit disorders, 1927 Attention deficit hyperactivity disorder (ADHD), 616, 986, 1000, 1327–1328, 2103 Autism, 227, 1000, 1171, 1928 cerebellum in multiple domains impaired in, 2160–2161

2704 Autism (cont.) characterization, 2160 incidence, 2160 structural pathologies of cerebellum in, 2161–2164 Autism spectrum disorders (ASD), 389–391, 421, 422, 615–616, 2026, 2102 Autoantibody, 967 Autoimmune polyglandular syndromes (APS), 2292 Autonomic failure, 2412, 2413, 2418 Autonomic influences, 614–615 Autophagic pathways, 1692 Autosomal dominant ataxia, 2437 Autosomal dominant cerebellar ataxias (ADCAs), 785, 2061–2062 anticipation, 2500–2501 clinical classification, 2488 clinical description of subforms, 2511–2535 diagnosis, 2541, 2542 epidemiology and frequency, 2495–2496 general clinical presentation, 2508–2510 genetic bases, 2497–2500 history, nomenclature and classification, 2485 neuroimaging, 2510–2511 neuropathology, 2501–2503 pathogenesis, 2503–2508 Autosomal dominant spinocerebellar ataxia type 28 (SCA28), 2583–2584 Autosomal recessive cerebellar ataxias (ARCAs), 2057–2060 type 1, 2471–2473 type 2, 2473 Autosomal recessive spastic ataxia of Charlevoix-Saguenay, 785, 2469–2471 Auxiliary subunits, 930, 945, 946 Avian models, 1612 Axon, 2451, 2453 competition, 1147, 1148 initial segment, 273, 274 swellings, 2451 Axon-target interactions, 294 Axoplasmic transport studies, 218

B Babinski’s sign, 1905, 1906 BAF complex, 416, 420 Baltic myoclonus, 2195–2200 Barbiturates, 2221 Basal ganglia, 693–697, 1743, 1746, 1750 Basal interstitial nucleus, 500

Index Basic helix-loop-helix (bHLH), 26, 28, 29 transcription factors, 15, 84 Basilar apex (terminus) aneurysms, 753 Basilar artery (BA), 741, 743, 744 Basilar artery occlusion (BAO), 746–747 Basilar dolichoectasia, 754, 755 Basilar terminus (BT), 751 Basket cell(s), 86, 89, 269, 272–274, 882, 884, 960, 1015, 1689, 1690, 2453, 2456 Basket/stellate cells, 994, 996 Bax, 1691 Bayesian statistics, 1492 Bechterew’s nucleus, 515, 516 Benign paroxysmal positional vertigo, 1816, 1832 Benzene derivatives, 2389 Benzodiazepine, 2009 Bergmann glia (BG), 123–125, 127–130, 134 cells, 931, 935 processes, 141, 143, 150 Beta-fluoroethyl acetate, 2392 Betamethasone, 2678 Big Pharma model, 1569 Bilateral cerebellar infarcts, 2241 Bilateral leg ataxia, 1908 Binomial data, 1875 Bioinformatics cerebellar gene regulation in time and space, 345–346 FANTOM5 consortium, 346–347 Biotinylated dextran amine (BDA), 561, 564, 666 Biparous, 27 Bismuth, 2377 Bivalent modification, 413 Blake pouch cyst, 2083, 2084 Blonanserin, 2181 Blood oxygen level dependent (BOLD), 1476–1478 signal time series, 706 Bobath concept, 2688 Bone morphogenetic protein (BMP) signaling, 25, 30, 75, 86 cerebellar ventricular zone, 76–77 Purkinje cell migration, 78 rhombic lip development, 73–75 Bonferroni corrections, 1874 Boucher-Neuhäuser syndrome, 2294 Brachium conjunctivum, 1218, 1219, 1228, 1655 Brain-derived neurotrophic factor (BDNF), 164, 2104, 2186 Brain injury, 2098

Index Brain malformations, 2118, 2120 Brainstem, 1810, 1815, 1818, 1820, 2455 Brainstem ischemic syndromes, 742 medullary ischemic syndromes, 742–743 midbrain ischemic syndromes, 745–746 pontine ischemic syndromes, 743–745 Brain tumor, 1909 Branched-chain ketoacid dehydrogenase (BCKADH), 2565 Brief Ataxia Rating Scale (BARS), 2041–2042, 2044 clinical application, 2042 validation, 2042 Bulimia nervosa, 2103 Burst firing, 1159, 1171

C Ca2+/calmodulin-dependent kinase type II (αCamKII), 870 Ca2+-calmodulin-dependent protein kinase (CaMK), 164 Ca2+ channelopathy, 1711 Ca2+ channels, 1716, 1717 Ca2+ dyes, 151 Ca2+ homeostasis, 1747 Ca2+ signaling, 1719 Ca2+ spikes amplitude and frequency components, 153 cortical layers, 154 cytoskeletal elements, 155 EGL, 154 IGL, 154, 155 intrinsic programs, 155 ML, 154 PCL, 154 Cacna1a, 1400, 1403–1405, 1734, 1735, 1738–1742, 1744, 1747, 1749, 1750 CACNA1A gene, 1711, 1720 CACNA1G, 1408–1409 CACNB4, 1411 Cadherin-catenin cell-adhesion complex, 943–944 Caenorhabditis elegans, 1609 Caffeine, 158, 160, 1711, 1723, 1724 Calbindin, 386, 960 Calcineurin inhibitors, 2376 Calcineurin phophatase (CaN), 164 Calcium, 1259, 1263, 1265, 1776, 1778, 1781, 1782 buffers, 385–387 signaling, 416, 417

2705 Calcium-activated potassium channels (BK), 1196, 1198, 1200 Calretinin, 386, 1655 cAMP response element-binding protein (CREB), 2507 Carbamazepine, 2371–2372 Carbonic anhydrase, 1711 Carbon monoxide, 2391 Cardioembolic stroke, 1916, 1918 Carrier frequency, 2060 Carrier testing, 2062 Caspase-3, 1691 Catechol-o-methyl transferase (COMT), 2105 Category fluency, 1947 Cat models, 1616–1617 cato, 27 Cav2.1, 1200, 1403–1405 CaV2.1 channel, rolling Nagoya mouse ataxia, 1748–1749 Cacna1a mutations, 1738–1741 CaV2.1-α1, 1739 electrophysiology, 1743–1746 LEMS, 1749–1750 migraine, 1749 CaV3.1, 1200, 1408 Cell fate specification, 79 Cell proliferation, 412, 415 Cellular plasticity, in CN, 1262 excitability plasticity, 1265 mossy fiber inputs, to CN neurons, 1262–1263 Purkinje cell CN pathway, 1263–1265 short-term, 1265 structural plasticity, 1266 Celphos, 2388 Central lateral (CL), 668 Central lobe, 1653 Central lobule, 461 Central nervous system (CNS) abnormalities, 1968, 2153–2154 Centrum medianum (CM), 668 Cerebellar abnormalities, 2026 Cerebellar activation complex sensorimotor tasks, 806–807 executive function tasks, 810–811 eye movements, 806 fractured somatotopy, 804–805 language and reading, 808–809 social/emotional/affective processing, 811–813 spatial processing tasks, 810 Cerebellar adaptation, 1465

2706 Cerebellar agenesis, 2087 cerebellar development, 2115–2117 classification systems, 2119–2120 neuroradiological studies, 2123 pathological mechanisms of cerebellar anomalies, 2117–2119 Cerebellar astrocytes molecular profiles, maturation of, 129–131 morphological features, maturation of, 128–129 and neurons, 125–126 origin of, 124–125 phenotypic heterogeneity of, 122–124 postnatal amplification of, 126–127 Cerebellar ataxia, 1613, 1908, 1910, 1915, 2056, 2284, 2291, 2295, 2486, 2487, 2509, 2517, 2518, 2520, 2522–2526, 2529, 2531, 2533–2535, 2642, 2649, 2657 Cerebellar atrophy, 723, 728, 731, 2486, 2510, 2512, 2518, 2519, 2521–2525, 2527– 2534, 2540, 2575, 2581–2584, 2588, 2590, 2608–2610 Cerebellar cognitive-affective syndrome (CCAS), 618, 1353, 1982, 1998, 2001, 2004, 2010, 2024, 2122, 2127, 2161 adults and children, 1971 anatomy, 1956 anterior lobe and lobule VIII, 1958 behavioral abnormalities, 1964 behavior and personality style, 1962 bilateral anterior ponto-cerebellar infarcts, 1967 cerebellar infarction, 1968 cerebellar infarcts, 1965 cerebellar lesions, 1966 cerebellar vermis and fastigial nucleus, 1958 cerebellum, 1977 cerebrocerebellar communication, 1957 in children, 1968 cognition and emotion, 1965 cognitive and behavioral deficits, 1964 cognitive and language impairments, 1972 component, 1969 contralateral thalamic nuclei, 1957 cortical networks, 1959 dentate nucleus, 1958 developing nervous system, 1977 disturbances, 1962 emotion, 1972 executive functions, 1969 interconnected brain systems, 1978 language, 1967 lateralized verbal-visual dichotomy, 1969 malformations, 1977

Index metalinguistics, 1967 neurobehavioral observations, 1961 neuropsychological findings, 1963 parieto-occipital lobe regions, 1965 pathological laughing and crying, 1971 PFS, 1970 pharmacological treatments, 1982 PICA, 1965 principal features and clinical relevance, 1964 recognition, 1982 sensorimotor cerebellum, 1958 somatotopic representation, 1957 spatial cognition, 1978 spino-olivary pathways, 1957 tumor/arteriovenous malformation, 1967 verbal fluency, 1961, 1966 verbal learning and verbal memory, 1966 vermian arteriovenous malformation, 1968 visual-spatial impairments, 1969 visual-spatial organization, 1969 Cerebellar control of posture anatomical aspects, 1381 cerebellum and learning postural tasks, 1388–1394 cerebellum in learning, 1386–1388 genetic approach, 1385 historical aspects, 1382 plasticity in cerebellum, 1386 postural deficit, 1383 Cerebellar cortex, 266, 267, 270, 274, 601, 603, 690–695, 973, 976, 982 CB1R immunoreactivity in, 1007 endocannabinoids in, 1016 motor, cognitive, and affective function in, 820–821 Cerebellar cortical atrophy, 784 Cerebellar (cortical) degeneration, 1862–1863 Cerebellar cortical dysplasia, 2088–2089 Cerebellar degeneration, 730, 731, 1363, 1369, 1693, 1696, 1899 Cerebellar degenerative disorders, 1942 Cerebellar-dependent behavior, 420–421 Cerebellar development, 149 Atoh1 (Math1), 434–435 cell type specific genes and gene networks, 440–442 En2, 431–434 physiological and metabolic control of development, 437–439 Rora (RORα), 435–436 targetomes, 431 Cerebellar disease, 1974, 1981 autoimmune, 729 cerebrovascular ischemic changes, 724

Index congenital and acquired disorders, 722 congenital posterior fossa cysts, 724 CT, 723 dysplasia, 722 genetic, 729 hemorrhage, 725 hypoplasia, 722 infectious, 727 neoplastic, 731 neurodegenerative, 731 traumatic, 726 vascular pathologies, 726 Cerebellar disorders BARS, 2041–2044 FARS, 2037–2039 ICARS, 2036–2037, 2043, 2044 pediatric perspective, 2043 SARA, 2039–2041, 2043, 2044 Cerebellar dysfunction, 984–986 Cerebellar dyslexia of Nicolson, 1928 Cerebellar function, 1016, 1018 Cerebellar functional topography, 798 activation during cognitive tasks, 807–813 activation during sensorimotor tasks, 804–807 anatomical invesigations, 799–800 clinical support for, 800–802 cross-domain relative topography, 813–815 diffusion tensor imaging, 799 functional connectivity data, 802–804 meta-analyses of neuroimaging, 813–814 MRI brain studies in humans, 799 multi-domain imaging, 814–815 Cerebellar GABAergic neurons, 70 Cerebellar gene regulation in time and space (CbGRiTS) project, 345–346 Cerebellar glomeruli, 268 Cerebellar glutamatergic neurons, 70 Cerebellar granule cells (CGCs), 1099, 1741 Cerebellar hemisphere, 2023, 2024, 2026 Cerebellar hemorrhage, 2099, 2243–2244 Cerebellar hypoplasia (CH), 722, 723, 729, 1926, 2085–2086, 2119 Cerebellar inhibitory interneurons, 54 Cerebellar ischemic syndromes, 747–751 Cerebellar lesions, 1361–1363, 1366, 1829, 1837, 1892, 1899, 1939, 1948 Cerebellar lobules, 611 Cerebellar localization, 603 Cerebellar malformations arachnoid cyst, 2085 blake pouch cyst, 2084 cerebellar agenesis, 2087 cerebellar cortical dysplasia, 2088–2089 cerebellar hypoplasia, 2085–2086

2707 congenital muscular dystrophies, 2080 cystic posterior fossa malformations, 2082–2083 Dandy walker malformation, 2083 global cerebellar hypoplasia, 2087 isolated inferior vermian hypoplasia, 2084 Lhermitte–Duclos disease, 2090 mega cisterna magna, 2083 molar tooth malformations, 2080–2082 pontocerebellar hypoplasia, 2088 rhombencephalosynapsis, 2078–2079 unilateral cerebellar abnormalities, 2087 Cerebellar module, 1276, 1277 Cerebellar molecular layer interneurons, 70 Cerebellar motor syndrome, 1961 DCN, 1960 dichotomy, 1960 dysarthria, 1960 motor function, 1959 motor impairment, 1960 SCA territory infarction, 1961 somatotopic representation, 1960 stroke, 1960 voxel-based lesion-symptom, 1960 Cerebellar mutants, 266 Cerebellar mutism, 1929 Cerebellar mutism syndrome (CMS) in adults, 2003–2004 age related discrepancy, 1998 and CCAS, 1998, 2010 in children, 1999–2003 functional lateralization, 2008 pathophysiological explanations and hypotheses, 2006–2007 preoperative neurocognitive assessments, 2004–2005 risk factors, for POPCMS, 2005–2006 treatment and rehabilitation, 2008–2010 Cerebellar neurodegeneration, 2566 Cerebellar neuroepithelium, 15–18 Cerebellar neurogenesis, 1637–1639 Cerebellar neurons, 84–89 Cerebellar neuropsychiatric rating scale, 1981 Cerebellar nuclei (CN), 69, 70, 73, 74, 76, 77, 208, 560, 628–630, 683, 684, 688, 689, 692, 693, 1145, 1151, 1167, 1170, 1195, 1216, 1218–1220, 1222, 1224, 1227, 1230, 1253, 1262, 1689, 1866–1868 anatomical and molecular classification, 217 anterior interposed nucleus, 541–542 autism, 227 caudomedial group, 498 cellular plasticity in, 1262–1266 cerebellar morphogenesis, 211–213 collateral olivocerebellar projection to, 532

2708 Cerebellar nuclei (CN) (cont.) collaterals terminating in, 576 compartmentation of, 569–571 defects, 221–224 dentate nucleus, 500, 543–547 development in mammals, 211–220 efferent projections, 218–219 eye-blink conditioning, learning mechanisms (see Eye-blink conditioning) fastigial nucleus, 500, 538–541 functional considerations, 1254–1256 GABAergic neurons, 214–215 glutamatergic CN projection, 1253 glutamatergic neurons, 215–216 human malformations, 224–227 in humans, 219–220 Joubert syndrome, 224–226 pontocerebellar hypoplasia, 226–227 posterior interposed nucleus and interstitial cell groups, 542–543 of rat, 499 rebound firing, activation of, 1258–1259 relay cells, 500 rhombencephalosynapsis, 226 rostrolateral group, 498 spike rate, modulation of, 1256–1258 thanatophoric dysplasia, 226 zebrin-positive or zebrin-negative regions of, 533 Cerebellar nucleo-vestibular connections, 640 Cerebellar nucleus (CN), 84, 89, 666, 1381, 1386, 1388 interneurons, 1245–1247 neuronal types and their basic properties, 1241 projection neurons (see Projection neurons) Cerebellar oligodendrocytes differentiation of, 133 origin of, 131–132 Cerebellar output channels, 684–689 Cerebellar patients, 1834, 1838, 1839, 1846 Cerebellar peduncular myelinolysis, 2367 Cerebellar plate anteroposterior subdivisions, 15–16 dorsoventral subdivisions, 16–18 subdivisions, 13–14 Cerebellar primordium, 4–7, 177 fate maps, 7 localization of, 6 MHB domain, 9 rotation of, 8

Index Cerebellar rhombic lip, 70 roof plate-derived Bmp signaling, 73–75 roof plate-derived secreted molecules, 75 Cerebellar slices, 150, 153, 157, 160 Cerebellar somatotopy, 1279 Cerebellar stimulation, 692 Cerebellar stroke, 1859–1861, 2395 AICA ischemic stroke, 2238 ataxia, 2233 bilateral cerebellar infarcts, 2241 cerebellar hemorrhage, 2243–2244 clinical features, 2231–2235 cognitive functions, 2234 complications of, 2242 diagnosis, 2245–2247 dizziness, 2232 dysarthria, 2233 headache, 2232 non-territorial small infarcts, 2240–2241 ocular motor dysfunction, 2234 PICA infarction, 2238–2239 SCA infarction, 2240 spectrum of, 2237 treatment, 2247–2248 venous infarction or hemorrhage, 2244–2246 Cerebellar surgery, 1972 Cerebellar synapses, 267 Cerebellar timing, 1370 Cerebellar toxicity of alcohol blood studies, 2368 cerebellar atrophy, 2367–2368 clinical findings, 2366–2367 neuropathological findings, 2368 pathogenesis, 2369 posture and gait analysis, 2368 prognosis, 2370 risk factors, 2370 treatment, 2370 Cerebellar tremor, 1841, 2642 Cerebellar tumor, 1861–1862 biological evaluation, 2322 clinical presentation, 2321 hemangioblastoma, 2324–2325 medulloblastoma, 2322 metastases, 2324 neuroimaging, 2321 pilocytic astrocytomas, 2323–2324 Cerebellar ventricular zone, 70 Bmp signaling, Purkinje cell migration, 78 roof plate-dependent Bmp and Wnt signals, 76–77 Shh signals, 77–78

Index Cerebellar vermis, 9, 15 Cerebellar volume, 1928 Cerebellectomy, 1699 Cerebelless, 33 Cerebellin 1 precursor protein, 271 Cerebellitis, 789 clinical presentation, 2306–2307 epidemiology, 2306 investigations, 2307–2311 pathogenesis, 2311 treatment, 2311–2312 Cerebello-bulbo-cerebellar loops, 644 Cerebello-mesencephalic cistern, 461 Cerebellopontine angle, 456 Cerebellothalamic fibers, 666 Cerebello-thalamocortical pathways, 684 Cerebellum, 266, 270, 272, 276, 311, 318, 452, 735, 1121, 1125, 1128, 1336, 1346, 1777, 1778, 1780, 1782, 1784, 1814, 1816, 1820, 1913–1914, 1938, 1944, 1948, 2114–2128, 2450, 2451, 2455, 2669, 2684–2686 AMPARs and plasticity in, 932 anatomical substrates, 1347–1348 autism spectrum disorders, 615–616 and basal ganglia, 693–697 bioinformatics strategies, gene identification (see Bioinformatics) cerebellar vermis, 1974 contribution to absence seizures, 1721 development, 335, 336 developmental innovations in evolution of, 112 in episodic dystonia, 1719–1721 germinal zones and lineage specifications, 337–338, 341 glial cells, 344–345 glutamate receptor auxiliary and interacting protein partners, 932–933 grammar processing, 1352 internal models, 1348–1350 intracranial and noninvasive stimulation of, 2025 kainate receptor interacting proteins in, 944–945 laterality, 1350–1351 linguistic deficits in cerebellar patients, 1353 MRS in cancer, 788 MRS in metabolic disorders, 788 MRS in neurodegenerative diseases, 784–786 neurochemical profile of, 782–784

2709 neuropsychiatric impairments, 1975 and pain modulation, 613–614 psychoneurotic symptoms, 1974 regional origins, 101, 102 role in motivation and emotion, 2023 sequence detection theory, 1950 in somatosensory processing, 1939–1940 spatial cognition, 1943 structural and functional imaging, 1975 structure, 335, 2022 temporal patterning and development of, 107 therapeutic implications, 618 verbal fluency, 1352 and working memory, 1351 Cerebellum-like structures, 1438 adaptive function in, 1449 vs. cerebellum, 1442 circuitry of, 1440–1442 evolution of, 1444 features of, 1438 future research, 1452 parallel fiber synaptic plasticity, 1448–1449 patterns of gene expression in, 1443–1444 sensory predictions in, 1445–1447 in vertebrate groups, 1439–1440 Cerebral cortex, 596, 597, 599, 600, 602 Cerebral cortical sensory, 1280 Cerebral cortices, 2382 Cerebro-cerebellar circuits, 1982 Cerebro-cerebellar loops, macro-architecture of, 690–692 Cerebro-cerebellar participation, 819 Cerebro-cerebellar pathways, 1277 cerebro-olivocerebellar pathways, 1284–1293 cerebro-ponto-cerebellar pathways, 1278–1284 Cerebro-pontine pathway, 1278 Cerebrospinal fluid (CSF), 2183 Cerebrotendinous xanthomatosis, 2678 Ceruloplasmin, 2292 CHARGE syndrome, 421 Chd7, 415, 420, 421 Chelators, 2382 Chemical weapons, 2391 Chemoaffinity hypothesis, 196 Chemokine receptor 4 (CXCR4), chemokine ligand 12 (CXCL12) system, 222 Cherry-red spot myoclonus syndrome, 2217–2219 Chiari malformations, 2136

2710 Chiari malformations (cont.) Chiari type I, 2137–2140 Chiari type II, 2140, 2141 Chiari type III, 2140 Chiari type IV, 2140–2142 features, 2137 historical aspects, 2136–2137 imaging techniques, roles of, 2142–2143 incidental discovery, 2146 medications, 2146 pathogenesis of, 2143–2144 prognosis, 2146–2147 rehabilitation, 2146 surgery, 2144–2145 tracheostomy, 2145–2146 Childhood Ataxia and Cerebellar Group of the European Pediatric Neurology Society (CACG-EPNS), 2044 Chlorzoxazone, 1718 Choline, 779 Choroid plexus, 454 Choroid plexus epithelium (ChPe), 68, 71–79 Chromatin, 410–413, 418–422 remodeling, 415–417, 422, 423 Chronic cerebellar lesions, 1864–1865 Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS), 2276–2277 Cingulate cortex, 608–609, 617 Cingulopontine fibers, 609 Citric acid cycle, 2565 Classical conditioning, 1336, 1338, 1698 Climbing fibers, 52–53, 270–271, 864, 912, 958, 1194, 1195, 1202, 1206–1208, 1216, 1218, 1220, 1222, 1224, 1225, 1228–1231, 1253, 1254, 1256, 1257, 1263, 1265, 1277–1280, 1284–1291, 1293, 1540, 1542, 1548, 1652, 1656, 1742, 1747 adenosine release, 1065 axonal projection patterns of neurons, 583–586 behavioral consequences, 1163–1168 dendritic translocation, 314–316 distribution of, 564, 566 functional differentiation and selective strengthening, 311–314 mono-reinnervate mature Purkinje cells, 298 multi-innervation, 292 neurons, 89 origin, 560

Index outgrowth and elimination, 1144–1148 post-synaptic space with, 289 vs. Purkinje cells, 287 reactive transcommissural, 296 reinnervation of mature Purkinje cells, 296–298 responses, 290 signals, 1506 single OC axons and aldolase C expression, 567–569 spatiotemporal patterns, 1162–1165 synapse elimination, early phase of, 316–318 synapse elimination, late phase of, 318–323 synapse elimination, 293 synaptogenesis, 311 terminals translocation, 287 types of, 294 Clinical heterogeneity, 2445 Clock-like function, 1195, 1208 Clozapine, 2180 Clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system, 1412 CN-GABA interneurons, 84 CN-GABA-ION neurons, 84 CN-Glu neurons, 84, 85, 88 Coactivators, 355, 356 Cocaine, 2379 Cochlear nucleus, 92 Coenzyme Q10 deficiency, 2067, 2582–2583 Coffin-Siris syndrome (CSS), 422 Cognition, 608, 618, 1941–1949 apraxia, 1980 cerebellum, 1975 conceptual reasoning, 1976 long-term memory, 1980 visual memory, 1976 Cognitive behavioral therapy (CBT), 2182 Cognitive development, 2116 Cognitive features, 2447–2448 Cognitive function, 2127 Cognitive impairment, 706, 2122, 2127 Cognitive/neuropsychological evaluations, 1981 Cognitive neuroscience, 1982 Cognitive problems, 1926, 1928 Cognitive rehabilitation, 2009, 2645 Coherent neuronal oscillations, 1286 Collateral fibers, 602 Compartmental model, 105 Compensatory techniques, 2649 Complex behavior, 1526, 1531 and cerebellum, 1528–1529

Index Complex-fusiform cells, 186 Complex spike, 1194, 1198, 1201, 1202, 1206, 1207 Compound muscle action potentials (CMAPs), 2467 Computational hypothesis of learning, 1392 Computational theory, 1538, 1541 Computed tomography (CT), 723, 1910–1912, 1916 Concussion, 2340 Conditioned stimulus (CS), 1227, 1260–1262 Congenital disorders of glycosylation (CDG), 2295 type 1a, 2088 Congenital hypothyroidism, 2286 Congenital muscular dystrophies, 2080 Connexin36, 1148 Constructive Interference in Steady-State (CISS) image, 728 Construct validity, 2035 Consumer genomics, 1594 Contactin 1, 250 Continuous data, 1875–1877 Continuous positive airway pressure (CPAP), 2425 Continuous training, 2648, 2649 Contralateral cerebral peduncle (CP) stimulation, 1293 Contusion, 2340–2341 Conventional volumetric analysis, 1879 Convergence of cerebellar projections, 647–648 Copper, 2385–2386 Corepressors, 355, 356, 361 Cornichon homologues, 938–940 Corollary discharge, 602 Corona radiata, 1908–1910, 1912, 1918 Corpus cerebelli, 1649, 1650, 1652 caudal region, 1650 Purkinje cells of, 1651 teleost, 1650 Cortex, 1908–1912, 1914, 1915, 1918 Cortical computational algorithm, 1550–1552 Cortical myoclonus, 2265 Cortico-cerebellar-thalamic-cortical (CCTC) brain circuit, 1328 Corticofugal Purkinje axon, 181–182 Cortico-nuclear module, 1254 Corticonuclear projection, 518–523 in primates, 537–538 Corticonuclear topographical relationship, 585 Corticopontine cells, 597 Corticopontine fibers, 597, 598, 600 Corticopontine neurons, 683

2711 Corticopontine pathway, 600, 602 Cortico-ponto-cerebellar system, 601–602 Corticorubral projection, 516 Corticospinal tract, 632, 641, 646, 1907, 1908, 1910, 1912, 1918 Corticosteroids, 2248 Corticotropin releasing factor (CRF), 1075 distribution in cerebellum, 1076 functional roles in cerebellum, 1082–1086 ligand-receptor mismatch, 1086–1087 receptors in cerebellum, 1080–1082 Corticovestibular projection, 639 Cranial tremor, 2445 Creatine, 779 Creatine kinase, 782 Crista cerebelli, 1650 Crossed axons of neurons in the medial ventral horn (CMVH), 581 Crossed cerebellar atrophy, 2354 Crossed cerebellar diaschisis (CCD), 1914, 1915, 2350 Cross-modal transfer, 1261 Crural paresis, 1905 Culmen lobule, 461 Cutaneous receptive field plasticity, 887 Cybernetics, 1564 Cyclic guanosine-30 ,50 -monophosphate (cGMP), 156–158, 869 cGMP-dependent protein kinases, 1029–1030 granule cells in signalling, 1030–1037 ion channels, 1028–1029 phosphodiesterases, 1029 Cyclic nucleotide-gated (CNG) channels, 1028 Cyclic nucleotide signaling, 156–157 Cysteamine, 1106, 1107, 1111 Cystein sulfonic acid decarboxylase (CSAD), 1106 Cystic posterior fossa malformations, 2082–2083 Cytarabine, 2373 Cytoarchitectonic areas, 683, 685 Cytochrome oxidase, 1693 Cytomegalovirus (CMV), 2118

D Dandy-Walker malformation (DWM), 1927, 2083, 2140, 2152 central nervous system abnormalities, 2154 diagnosis, 2152–2153 etiology, 2152

2712 Dandy-Walker malformation (DWM) (cont.) management, 2155–2156 non-CNS abnormalities, 2154–2155 prognosis, 2156 symptomatology, 2153 Darkschewitsch nucleus, 515–518 Declarative memory, 1948 Decomposition of movement, 1839 Deep cerebellar nuclei, 277, 981, 984, 1018, 1195, 1205, 2022, 2641, 2655 Default-mode network, 711 Degeneration, 415, 417, 420, 422, 2456 ataxias, 1862, 1863 cerebellar disease, 2640, 2642, 2647–2649, 2655 metabolic pathways, 2564–2565 method, 561 Deiters’ lateral vestibular nucleus, 519 Delay conditioning, 1257, 1260, 1266 Delayed-onset cerebellar syndrome, 2354 Delayed-onset intention tremor, 2354 Delayed traumatic intracerebral hemorrhage, 2341 Delta-9-tetra-hydrocannabinol, 1700 Dementia, 1977, 2448 De Morsier syndrome, 2295 Demyelinating disease, 1909 Dendrite(s), 314–316, 1782 growth, 415–419 pruning, 416, 420 Dendritic lamellar bodies, 1150 Dendritic spines, 270, 1743 Dendritic tree, 185–187, 189–191 De novo mutation, 2057, 2062 Dentate nucleus (DN), 500, 543–547, 692, 694 Dentatorubral-pallidoluysian atrophy (DRPLA), 2493, 2509, 2534–2535, 2628–2630, 2680 Dentatorubral-pallidoluysian atrophy (DRPLA), 2061, 2065, 2206 clinical manifestations, 2208–2209 diagnosis, 2210 EEG characteristics, 2210 genetics, 2207 pathology, 2208 prevalence, 2207 Depolarization-induced depression, 965 Depolarization-induced potentiation of inhibition (DPI), 963 Depolarization-induced suppression of inhibition (DSI), 963, 1009 Depression, 617, 2449 and anxiety, 2103

Index Desensitization, 152 Designer receptors exclusively activated by designer drugs (DREADD), 1288 Development, 311, 312, 316, 1784 disorders, 1000 Diabetes insipidus, 2292, 2293, 2295 Diaschisis, 2235 DIDMOAD syndrome, 2293 Diffuse axonal injury, 2341 CT imaging, 2346, 2347 Diffusion tensor imaging (DTI), 1881, 2143 Diffusion-weighted imaging (DWI), 1906, 1908, 1911, 1916, 1918, 2102 Digital subtraction angiography (DSA), 752, 759, 762, 763 Diphenoxylate-atropine, 2379 Disability, 2443, 2448, 2449 Discriminant validity, 2035, 2045 Disrupted MGVHB axis, in space, 1421–1424 Disruption, 2114, 2117–2120, 2127 Disruptor of telomeric silencing-1 (DOT1)mediated chromatin remodeling, 1675, 1680 Distal cerebellar aneurysms, 756–757 Distal intracranial posterior circulation territory, 452 Divergence of cerebellar projections, 645–647 DNA, 415 amplification techniques, 2271 methylation, 410, 411, 418–419, 422, 423 sequences, 411 DNA methyltransferase 3A (Dnmt3a), 419 Dnmt3a, see DNA methyltransferase 3A (Dnmt3a) Dolichocephaly, 2154 Dopamine, 1695 agonists, 2008 Dorsal accessory olive (DAO), 504, 1143, 1218 Dorsal cap of Kooy, 1143, 1149, 1195, 1198, 1199, 1208 Dorsal column nuclei, 508–510, 1151 Dorsal column nucleus neurons, 576–578 Dorsal hindbrain, 90, 91 Dorsal light response, 1659 Dorsal midline, 68, 71 Dorsal motor nucleus of vagus, 455 Dorsal neuroepithelium, 10 Dorsal premotor cortex, 685 Dorsolateral hump, 630, 637 Dorsolateral protuberance, 500 Dorsomedial cell column (DMCC), 501, 1143

Index Dose-related nystagmus, 2371 Downbeat nystagmus (DBN), 1817–1820, 1833, 2642, 2644 Down syndrome, 1927 Dreher, 76 Drosophila, 1610 Drosophila melanogaster, 25 Drug abuse and addiction cocaine, 2379 herbs, 2380 heroin, 2379–2380 methadone, 2380 phencyclidine, 2380 Drug-induced dysfunction, 2288 Dural arteriovenous fistula (dAVF), 760–763 Duret hemorrhage, 2341 Dynamic balance, 2648, 2649, 2655 Dynamic clamp, 1257 Dynamic model, 1489 Dynamic mutations, 2055, 2057, 2061, 2065–2066 Dysarthria, 1836–1838, 2001, 2002, 2121, 2233 Dysarthric speech, 1363 Dysdiadochokinesia, 1840 Dysgraphias, 1948 Dysmetria, 1586, 1839, 1905, 1913, 1914, 2645, 2647 of thought, 1979 of thought hypothesis, 1829 Dysphagia, 1838 Dysphoric mood, 1972 Dysplastic cerebellar gangliocytoma, 2090 Dysprosody, 1838 Dysrhythmia, 2455 Dysrythmokinesia, 1841 Dyssynergia, 2645

E EAAT1, 1411 Early B-cell Factor 2 (Ebf2), 50 Early-onset ataxias, 393–394 Early-onset ataxia with ocular motor apraxia and hypoalbuminemia/ataxiaoculomotor apraxia type 1 (EAOH/ AOA1), 2631, 2632 Eating disorders, 2103 Ecto-ATPase activity, 1055 Ectonucleotidases, 1062 Ectopic Purkinje cells, 50 Edible morels, 2393 Efferent neurons, 1652–1656 Ekerot’s D2 zone, 528

2713 Electrical coupling, 1196, 1204, 1205 Electrical stimulation, 1280 Electrical synapses, 1155–1156 Electric shock, 2395 Electroconvulsive therapy (ECT), 2182 Electromicrographic analyses, 1547 Electromyogram (EMG), 1108 Electromyographical studies, 1750 Electrophysiology, 1743–1746, 2449 Emboliform, 462 Embryological structures, 2119 Embryonic development, 71, 72, 77 Eminentia granuralis, 1650, 1657 Emotion, 607–610, 1938, 2021, 2023, 2026 facial expressions, 2024, 2026 Endocannabinoids, 890, 894, 1006, 1204 biosynthesis and degradation, 1006–1008 in cerebellar cortex, 1016 global signaling, 1011 local signaling, 1011 long-term depression, 1013 release in Purkinje cells, 1010 retrograde signaling, 1009–1010 signaling in cerebellar circuitry, 1015 targets of, 1008 Endocrine disorders diabetes and cerebellar ataxia, 2291–2294 hypogonadism and cerebellar ataxia, 2294–2296 parathyroid disorders, 2289–2290 thyroid disorders, 2284–2289 Endothelin-1 receptor, 1695 Endplate, 1746, 1747, 1750 Engrailed-2 (En2), 431–434 Enhancer, 411–413, 415, 416, 418, 423 Environmental influences, 354, 355 Enzyme replacement therapy (ERT), 2222 Ependymoma, 788 Ephrin-A2 ligand expression, 53 Ephrins, 1140 Epidemiological Catchment Area program survey, 2179 Epidural hematomas, 2341 CT imaging, 2347, 2348 Epigenetic regulation, of cerebellum, 410–412 ATP-dependent chromatin remodeling enzymes, 415–417 cerebellar-dependent behavior, epigenetic control of, 420–421 DNA methylation, 418–419 genome-wide changes, 412–414 histone tail modifiers, 417–418 perspectives on, 419–420

2714 Epilepsy, 1735, 1738, 1741, 1748–1750, 1909, 1918 Episodic ataxias (EAs), 2062, 2535, 2543, 2680–2681 EA1, 2536 EA2, 2536–2539 EA3, 2539 EA4, 2539 EA5, 2540 EA6, 2540 EA7, 2540 Episodic ataxia type 1 (EA1), 1410 Episodic ataxia type 2 (EA2), 785, 1404, 1405, 1412, 1748, 1750 Episodic ataxia type 5 (EA5), 1411 Episodic ataxia type 6 (EA6), 1411 Episodic dystonia cerebellum in, 1719–1721 triggers of, 1724–1725 Epothilone D, 2374 ERα, 368–369 ERβ, 368–369 Error-based learning, 1948 Error signal, 1168 Essential tremor accessory motor features, 2446–2447 as cerebellar disorder, 2455–2457 clinical feature, 2443–2449 cognitive featues, 2447–2448 definition, 2442 electrophysiological studies, 2449 epidemiology, 2443 neuroimaging, 2450 pathological features and pathophysiology, 2450–2455 psychiatric features, 2448–2449 tremors, 2443–2445 Estradiol, 367, 368, 1117 biological actions in Purkinje cell, 1123 deficiency in ArKO mice r, 1125 mode of action, 1123–1126 Ethanol, 158, 159 Ethnicity, 2068 N-Ethylmaleimide sensitive fusion protein, 942 Eucalytus oil, 2393 European Commission (EC), 2495 Eurydendroid cells, 1629, 1638, 1651, 1652 Event-related fMRI analyses, 816 Everyday life, 2646–2649, 2654 Excitatory amino acid transporter (EAAT), 1402 Excitatory postsynaptic currents, 998, 1747

Index Excitatory synapses, 844 Excitotoxic apoptosis, 1691 Executive, 2122, 2125–2127 control network, 711 functions, 1946 function tasks, 810–811 Exergames, 2648, 2649, 2653 Exploration behavior, 1699 Exploration strategies, 1943 External cuneate nucleus (ECN), 89, 90 External germinal layer (EGL), 440 External globus pallidum, 694 External granular layer (EGL), 125, 127, 128, 142, 143, 175, 177–181, 192 Extinction, 1260 Extra-axial lesions epidural hematomas, 2341 imaging, 2347–2348 subarachnoid hemorrhage, 2342 subdural hematoma, 2342 Extrapyramidal dysfunction, 1743 Extrapyramidal symptoms (EPS), 2180 Eyeblink conditioned response and cerebellar dysfunction, 1326–1329 critical neural circuitry, 1321–1326 topography of, 1320 Eyeblink conditioning, 807, 1017, 1263, 1369 cross-modal transfer, 1261 delayed, 1260 trace conditioning, 1261 VOR, adaptation of, 1261 Eye-hand coordination, 2446 Eyelid response, 1698 Eye movements, cerebellar control close-loop phase, 1312 external loop, 1312 floccular complex, 1303–1306 forward model, 1312 internal feedback loop, 1312 inverse model, 1312 motor learning, 1309–1312 nodulus and uvula complex, 1306–1307 OMV and FOR, 1307–1309 F False indigo flower, 2395 Familial hemiplegic migraine type 1 (FHM1), 1404, 1405, 1741, 1749, 1750 FANTOM5 consortium, 346–347 Fastigial efferent projections, 218 Fastigial nucleus, 454, 500, 538–541, 609, 617, 618, 633, 666, 675

Index Fastigial oculomotor region (FOR), 1307, 1308, 1312 Fate-mapping techniques, 101 Fatty acid oxidation, 2565 Fear conditioning, 1659 Feedback-based movement control, 1493 Feedback learning, 1393 Feedforward control, 1465 Fetal alcohol spectrum disorder (FASD), 132, 157 Fetal Minamata disease (FMD), 159 FGF8 signaling, 10, 13, 15, 25, 1141, 1632 Fibroblast growth factors, 103 Fibrous astrocytes, 123 Floccular complex (FL) anterior and posterior, 1303 electrical stimulation, 1303 neuronal integrator, 1303 neuronal responses, 1304–1306 optokinetic reflex, 1303 role of, 1304 ventral paraflocculus, 1303 Flocculus, 452, 639 Focal lesions, 1942 Folium lobule, 461 Folium P, 536 Forward genetics screens, 1624 Forward internal model, 1462–1465, 1467–1469, 1471, 1472 Forward model, 1489–1493 Founder mutation, 2067 Fractal chaos, 1578 Fractal dimension, 1590–1593 FractoGene concept, 1572 Fractured somatotopy, 804–805 Fragile X-associated tremor ataxia syndrome (FXTAS), 2167, 2604, 2607 Fragile X mental retardation protein (FMRP), 2165 Fragile X syndrome, 1927 Fragile X tremor/ataxia syndrome (FXTAS), 2063, 2066 Frataxin, 2468, 2576 Frenkel’s method, 2688 Friedreich ataxia (FRDA), 393, 785, 2036, 2054, 2059, 2060, 2434, 2467–2469, 2570–2578, 2630–2631, 2643, 2673–2676 Friedreich Ataxia Rating Scale (FARS), 2037 clinical application, 2039 validation, 2038–2039 Functional connectivity data, 802–804

2715 Functional connectivity magnetic resonance imaging (fcMRI) analyses, 1958 Functional magnetic resonance imaging (fMRI) studies, 1959 Functional neuroimaging studies, 1931, 2024 Functions, 2117, 2122, 2125, 2126, 2128 Fusiform aneurysms, 754–756 FXN contains seven exons, 2468

G GABA, 1097, 1099, 1102, 1104, 1206, 1254, 1655 GABAA receptors, 148, 163, 273–275, 962, 964, 965, 967 GABAA-receptor subunit alpha 1 (Gabra1), 247 GABA(B) receptor, 962–964 GABAergic cells, 1219 GABAergic CN neurons, 70, 76, 77 GABAergic/glycinergic interneurons, 1245–1246 GABAergic interneurons, 124, 126, 272–274 axogenesis and dendritogenesis of, 246 deep cerebellar mass and prospective white matter in, 242 dendritic orientation of molecular layer, 248 diversity and classification of, 236 Golgi cells and non-Golgi, 255–256 granule cell layer, 252–255 maturation in molecular layer, 244–252 origins of, 238 postmigratory, 245 Ptf1a and delineation, 239–241 subsets of, 242 GABAergic lineages, 338 GABAergic neurogenesis., 33 GABAergic neurons, 85–86 behavioral abnormality, 966–967 cerebellar ataxia, 967 and cerebellar neuronal circuits, 959 in cerebellar nuclei, 961–962 glutamatergic synaptic inputs, 963 GABAergic synapses, 183 Gadolinium, 2386–2388 Gait, 1696 abnormality, 2446 β-Galactosidase (β-gal) protein, 215 Gamma-amino-butyric acid (GABA), 973, 2456 Ganglionic layer, 1651, 1655

2716 Gap Junctions, 1148–1151, 1195, 1201, 1204, 1206–1208 Gaucher disease, 2210 clinical manifestations, 2211–2212 diagnosis, 2212 EEG characteristics, 2213 epidemiology, 2210 genetics, 2210 pathology, 2211 Gaze-evoked nystagmus, 1812, 1833 Gbx2, 1139 GC neuron dendritic morphogenesis, 33 Gene expression, 411, 412, 414, 415, 417–419, 423 Gene regulatory network, 346 Genetic counselling, 2063, 2066, 2610, 2688 Genetic factors, 2117 Genetic fate mapping, 34, 49, 70, 71 Genetic heterogeneity, 2611 Genetic inducible fate mapping (GIFM), 338 Genetic micro-compartmentation, 104 Genetic model, 1640 Genetic switch, 432, 440, 442 Genetic testing, 2542 Genome, 410, 412–415, 418, 423 informatics, 1562 sequencing, 2061 Geographic groups, 2060 Gephyrin, 274 Germanium, 2389 Glasgow coma scale (GCS) score, 2244 Gli2, 31 Glial cells, 344–345 Glial fibrillary acidic protein (GFAP), 2166 Gliogenesis cerebellar astrocytes, 122–131 cerebellar oligodendrocytes, 131–133 Global cerebellar hypoplasia, 2087 Global mapping, 1354 Globose, 462 Globular cells, 995 Globus pallidus, 664, 667–673, 675, 676 Glomerular synapses, 844 GluA2, 942 Glucocerebrosidase gene, 2210 Glucocorticoid receptor (GR), 366 Glucocorticoids, 366–367 Glucose, 780 tolerance, 1108, 1109 GluD2, 269, 271, 1409 GluK2/5 heteromers, 944 GluRδ2, 1690 Glutamate, 273, 778, 892, 895, 1204

Index Glutamate decarboxylase (GAD), 967, 1217, 1219 Glutamate receptor(s), 269, 271, 274, 1401, 1403, 1409, 1694 in cerebellar neurons and glia, 931 Glutamate receptor interacting protein (GRIP), 940–942, 945 Glutamatergic CN neurons, 1258, 1267 Glutamatergic neurons, 70, 73, 84, 85, 88 Glutamic acid decarboxylase (GAD), 1104, 2164 Glutamine, 779 Glutathione, 780 Gluten ataxia, 2259–2265 Gluten-free diet, 2262 Glycine, 275 Glycinergic projection neurons, 1244–1245 Glycoprotein, 271 Golden ratio, 1578–1581 Goldfish, 1649, 1650, 1654, 1657 Golgi cell(s), 86, 274–275, 905, 907, 959, 961, 996, 1282, 1652 beta-band resonant population oscillations, 920–921 climbing fibers, 912 complex triphasic response to peripheral stimulations, 916–918 dendrites, 253 excitatory synaptic inputs, 910–912 Golgi cell–mediated control, 908 granule cell inputs, 911–912 inhibitory synaptic inputs, 912–915 large receptive fields and modulated discharge patterns, 918–919 morphological and neurochemical characterization, 906 mossy fiber inputs, 910–911 neurochemically heterogenous group of cells, 908–909 spontaneous firing pattern, 916 synaptic connections, 910 in vivo studies, 915–916 Golgi method, 562 Gonadal hormones, 367–371 G-protein-coupled receptor, 980 G-protein-dependent, 853 Gracile lobule, 454 Grafting studies, 90 Granular layers, 1714, 1715 Granule cell(s), 69, 73, 74, 268, 274, 275, 316, 317, 430, 433–440, 442, 993, 1522, 1523, 1691, 1716, 1719, 1720 alcohol, 157–159

Index Ca2+ spikes, 153–156 cerebellar network and cerebellar glomerulus, 839 clonal expansion, 30 cortical layers, 142–145 cyclic nucleotide signaling, 156–157 development, 29–32 differentiation, 111, 162, 164 diversity of, 108–110 double migration process, 839 EGL and IGL, 150–151 fate-mapping, 102 granule cell activity in vivo, 848–850 granule cell connectivity, 840 granule cell models, 849–851 intrinsic electroresponsiveness, 842–844 intrinsic programs, 145–148 light stimulus, 161–162 long-term synaptic plasticity, 847–848 MeHg, 159–161 mutation of bHLH genes in, 105 neurogenesis, 192–193 neuronal migration, 141 NMDA receptors, 149–150 patch-clamp and imaging techniques, 838 pathologies of, 853–855 PCL, 151–153 precursors, 142, 152 progenitors, 1635 receptors and transduction pathways, 841 short-and long-range loops, 840 synaptic transmission, 844–847 Granule cell layer (GCL), 266, 268, 276, 905, 907, 908, 912, 913, 915, 919, 921, 1547, 1550, 1551, 1652 feedback inhibition and oscillations, 921 Granule-cell-Purkinje-cell (gcPc) synapses, 1522–1525 Granule neuron, 412–420, 423 Grasping deficits of higher-order motor control related to, 1899 force control, 1894 internal forward models, 1894–1896 living without a cerebellum, 1896–1898 and reaching deficits, 1892 Gravity dependent nystagmus, 1814–1816 GRID2, 1409–1410 Grip force, 1493, 1495, 1496, 1897, 1898 GRM1, 1409 Grooming, 1699 Gut-associated lymphoid tissues (GALT), 1419 Gut-heart axis, 1422

2717 Gut microbiota, 1418 and gut structure in space, 1421, 1422 symbiosis, 1419

H Hand transport, 1893 Handwriting abnormalities, 1845 Harmaline, 1155, 1171, 1198, 1200, 1207, 2449 Hashimoto ataxia, 2267, 2287–2288 Head tremor, 2444, 2446, 2450 Hearing loss-ataxia-myoclonus (HAM), 2592 Heat-shock protein (HSP), 47, 2504 Hebbian, 1262, 1263 Hemangioblastoma, 2324–2325 Hemicerebellectomy (HCb), 1943 and changes in motor cortical physiology, 1801–1802 and endocannabinoids, 1793 and experimentally induced neuroplasticity, 1790–1792 and maze learning, 1799–1801 model, 1790 and neuron-glia crosstalk in neurodegeneration, 1795–1797 for studying axotomy-induced neurodegeneration, 1792–1797 at various developmental stages and motor recovery, 1797–1799 Hemiparesis, 1905, 1906, 1908, 1912 Hemispheres, 2114, 2116, 2127, 2128 Hemorrhagic stroke, 1904, 1909 Herbs, 2380 Hereditary ataxia, 1758, 2055, 2434, 2437 Harding’s classification of, 2055 Hereditary disorders dentatorubral-pallidoluysian atrophy, 2628–2630 EAOH/AOA1, 2631 friedreich’s ataxia, 2630–2631 Machado-Joseph disease/spinocerebellar ataxia type 3, 2622–2625 Marinesco-Sjögren syndrome, 2631 spinocerebellar ataxia type 1, 2619–2621 spinocerebellar ataxia type 2, 2621–2622 spinocerebellar ataxia type 31, 2627 spinocerebellar ataxia type 6, 2625–2626 spinocerebellar ataxia type 7, 2626 spinocerebellar ataxia type 8, 2627 Heroin, 2379–2380 Heterochronic transplantation, 180 Heteroplasmic cell, 2565 Heteroplasmy, 2063

2718 Heterosynaptic competition, 325 Heterotopic Purkinje cells, 2453 Hibernation, 1762 High-flow vascular malformations, 757–763 Hindbrain, 68, 69, 71, 72, 75–78, 90–92 Hindlimb locomotor defects, 1759 Hippocampus, 1738, 1742, 1744 Histone, 410, 412, 415 acetylation, 410, 412, 419 high levels of, 412 methylation, 410 modifications and transcriptional regulators, 413 post-translational modification of, 410 tail modifiers, 417–418 variant, 411, 416 Histone acetyltransferases (HATs), 418, 2508 Histone deacetylases (HDACs), 418, 419 inhibitors, 2675 HIV-associated cerebellar ataxia, 2277–2278 Holmes ataxia, 2294 Homeoproteins, 1570 Homolateral ataxia, 1905 Homomeric and heteromeric P2X receptors, 1049 Horizontal fissure, 461 Horizontal optokinetic stimulation (HOKS), 473 Hormone receptors, 355, 356 Horner’s syndrome, 2344 Horseradish peroxidase (HRP), 596, 597 Hoxa2, 101 Hox genes, 8, 101, 1140–1142 4H syndrome, 2296 Human CaV2.1-channelopathies, rolling Nagoya mouse, see CaV2.1 channel, rolling Nagoya mouse Human cerebellar topography, 713 Human disease, epigenetics, 421–422 Human evolution, 1530–1532 Huntington disease (HD), 2497 Hypercupremia-induced cerebellar ataxia syndrome (HICA), 2385 Hypermetria, 1839 Hyperparathyroidism, 2290 Hyperpolarization, 1258, 1259, 1263–1265 Hyperpolarization-activated cation channels, 1196 Hyperpolarization-activated cyclic nucleotidegated (HCN) channels, 1028 Hyperpolarizing phase, 1157 Hyperthermia, 2390 Hyperthyroidism, 2286

Index Hypertonia, 649 Hypertrophic basket cell axonal processes, 2454 Hypesthesia, 1906, 1907 Hypogonadotropic hypogonadism, 2294–2296 Hypogranular cerebellum, 291 Hypometric movements, 1973 Hyponatremia, 2367 Hypoparathyroidism, 2289 Hypoplasia, 2114, 2115, 2118, 2119, 2123 Hypothalamic areas, 645 Hypothalamo-pituitary-adrenal (HPA) axis, 366, 367 Hypothalamus, 609, 610, 614 Hypothyroidism, 357–359, 2286 Hypotonia, 649, 1844, 1906, 2123

I Iatrogenic steroids, 2100 Idebenone, 2643, 2673 Idiopathic late-onset cerebellar ataxia (ILOCA), 2064–2065, 2435 with cerebellar-plus syndrome, 2436 Immediate early genes (IEGs), 414, 416, 418 Immune mediated ataxia (IMA) anti-dipeptidyl-peptidase-like protein-6 ataxia, 2275–2276 anti-glutamic acid decarboxylase ataxia, 2265–2266 anti-myelin-associated glycoprotein ataxia, 2276 chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids, 2276–2277 gluten ataxia, 2259–2265 HIV-associated cerebellar ataxia, 2277–2278 Miller Fisher syndrome, 2273–2275 opsoclonus-myoclonus ataxia syndrome, 2269–2270 post infectious cerebellitis, 2270–2272 primary autoimmune cerebellar ataxia, 2266–2269 Immunohistochemical methods, 523 Immunoreactivity, 689 Immunotherapy, 2268 Implicit learning, 1944 Inborn error of metabolism, 788 Independent component analysis (ICA), 706 Indirect limbic inputs, 615 Inducible nitric oxide synthases, 1027 Inescapable stress, astronauts, 1427

Index Infantile NCL, 2203 Infantile neuroaxonal dystrophy, 2220 Infantile-onset spinocerebellar ataxia (IOSCA), 2581–2582 Infarct, 1904–1908, 1910, 1912–1918 Infectious diseases, 1909 Inferior medullary velum, 454 Inferior olivary nucleus (ION), 84, 89, 1194 Inferior olive (IO), 501–504, 628, 632, 640, 641, 645, 1010, 1216, 1217, 1219, 1220, 1222, 1224, 1225, 1228–1230, 1253– 1255, 1267, 1442, 1443, 1656, 1658 afferent connections of, 504–518 afferents from tectum and pretectum, 513–514 central and medial tegmental tract, 514–518 dorsal column nuclei, 508–510 excitable properties of, 1196–1198 features of, 1195–1196 frequency in, 1198 impaired electrotonic coupling in, 1207 inhibitory receptors in, 1207 nuclei, 959 optokinetic and vestibular projections to, 510–513 properties of, 1208 sensory trigeminal nuclei, 507–508 ventral spino-olivary pathways, 505–507 Inferior olive neurons, 1689, 1690, 1692, 1701 action potential waveforms, 1158–1159 electrical synapses in, 1155–1156 glomeruli and gap junctions, 1148–1151 inputs and origin, 1151 Marr-Albus-Ito hypothesis, 1168–1170 migration, 1143 motor timing model, 1170–1171 network models, 1161–1162 neurotransmitters and receptors, 1151–1152 origin, 1139–1142 pathology, 1171–1173 single cell model, 1159–1161 subdivisions and cell types, 1143–1144 subthreshold oscillations and spike timing, 1152–1155 synaptic modification of oscillations and coupling, 1156–1158 Infratentorial tumors, 1929 Inhibition, 1256, 1257, 1261, 1263, 1265, 1266 interneurons, 470 neurons, 2455 synapses, 846 Inositol-triphosphate receptor type 1 (IP3R1), 1775, 1776

2719 Insulin, 1108 Insulin-like growth factor 1 (IGF-1), 161–163 signaling pathway, 1677–1678 Insulin receptors, 1108, 1110 Integrin-linked kinase (ILK), 128 Intellectual disability, 421, 422 Intention tremor, 1906, 2445, 2446, 2455 Internal auditory arteries, 456 Internal capsule, 1905, 1908–1910, 1912, 1913, 1915, 1918 Internal consistency, 2035 Internal forwards models, 2646, 2656 Internal granular layer (IGL), 145 Internal models, 1894, 1896, 1899 Internal models and cerebellum, 1348–1350 and central nervous system, 1463–1465 cognitive and emotional dysfunction, 1477 electrophysiological investigations, 1470–1476 forward model, 1462–1463 functional imaging studies, 1468–1469 inverse model, 1462 language processing, 1477 motor control, 1465 motor deficits in patients, with cerebellar disease, 1465–1468 non-invasive cerebellar stimulation, 1469–1470 for tool use, 1476–1477 International Cooperative Ataxia Rating Scale (ICARS), 1897, 2036, 2043, 2044, 2655 cerebellar features, 2036 clinical application, 2037 validation, 2036–2037 International Study of Unruptured Intracranial Aneurysms (ISUIA), 752 International Subarachnoid Aneurysm Trial (ISAT), 753 Interneurons, molecular layer, see Molecular layer interneurons Interpositus nucleus, 1260 Interrater reliability, 2035 Interstitial cell groups, 498, 543, 630, 636 Interstitial nucleus of Cajal, 643, 644 Interstitiospinal tract, 643–644 Intraarterial thrombolysis, 2247 Intra-axial lesions concussion, 2340 contusion, 2340–2341 diffuse axonal injury, 2341 imaging, 2345–2346 secondary traumatic brainstem lesions, 2341 Intraaxonal staining method, 563

2720 Intracellular staining method, 562 Intracortical plexus, Purkinje axon, 182–184 Intracranial vertebral arteries, 452 Intra-parenchymal hemorrhage (IPH), 764–765 Intravenous immunoglobulins, 2262 Intraventricular hemorrhage (IVH), 2100 Intrinsic electroresponsiveness, 842–844 Intrinsic programs granule cell migration in vivo, 148 period of 0-20 hours in vitro, 146 period of 20-40 hours in vitro, 146 period of 40-60 hours in vitro, 146 time-dependent changes, 148 In utero electroporation, 85 Inverse dynamics internal model, 1462, 1465, 1470 In vitro explant experiments, 78 In vivo imaging, 1624, 1637, 1639 Iodothyronine deiodinase, 360 Ionotropic GABA receptor, 962 Ipsilateral hemiparesis, 1906 Ipsilateral superficial radial (SR) nerve, 1293 Ischemia, 1066 Ischemic and hemorrhagic infarctions, 1930 Ischemic diseases, posterior fossa, 741–751 Ischemic stroke (IS), 763, 1905, 1906, 1908– 1910, 1916–1918 Isolated inferior vermian hypoplasia, 2084 Isometrataxia, 1843 Isoniazid, 2377 Isthmic neuroepithelium, 9–10 Isthmic organizer, 1139, 1141 ITPR1, 1406–1407 J Joubert syndrome, 224–226, 1926, 1978, 2080 Juvenile NCL, 2204, 2205 K Kainate receptors, 870, 930–933, 944, 945 Kallman syndrome, 2295 Kamin blocking, 1228 KCNA1, 1410 KCNC3, 1405–1406 KCND3, 1407 Kdm5c, 418, 422 Kdm6a, 417, 418 Kdm6b, 417, 418 Kearns–Sayre syndrome (KSS), 2592–2594 Kinesie paradoxale, 602 Kinetic tremor, 2442, 2443, 2445 King effect, 1583

Index KRIP6, 946 KV1.1, 1410 KV3.3, 1405, 1407 KV4.3, 1407 L Lactate, 777, 780, 783 Lafora disease clinical manifestations, 2215 diagnosis, 2216 EEG characteristics, 2216 genetics, 2214 pathology, 2214–2215 prevalence, 2213 Lambert-Eaton myasthenic syndrome (LEMS), 1735, 1749–1750, 2330 Lamotrigine, 2221, 2373 Langerhans histiocytosis, 2293 Language, 1947–1949, 1981, 2122, 2123, 2126–2128 functions, 1980 and reading, 808–809 Large-artery atherosclerosis, 1916–1918 Large glutamatergic projection neurons, 1242–1243 Laser-capture microdissection (LCM), 1677 Late cortical cerebellar atrophy, 2618 Late infantile NCL, 2204 Late-onset ataxia, altered cerebellar development, 394–395 Late-onset cerebellar cortical atrophy, 2618 Lateral cerebellar nucleus (LCN), 638 Lateral descending motor system, 632 Lateral medullary infarcts (LMI), 742 Lateral reticular nucleus (LRN) neurons, 89, 90, 469, 574 axonal trajectories, 571–573 collaterals terminating in cerebellar and vestibular nuclei, 576 distribution of terminals in Cx, 573–576 Lateral vestibular nucleus, 628 Lateral vestibulospinal tract, 638 Lead, 2383–2385 Leading process, 142, 144–146, 148 Leaner, 1738, 1740, 1742, 1746, 1748 Learning, 1254, 1256, 1258, 1260–1263, 1265, 1266, 1268, 2116, 2121–2126 mechanisms, 2656, 2657 Leg tremor, 2445 Lesion approach, 1896 Lesion delineation, 1864 Lesions, 2455, 2456 Letter fluency, 1947

Index Lewy bodies, 2453, 2455 Lhermitte–Duclos disease, 2090 Lhx1, 36 Lhx5, 36 Light–dark cycle, 161 Limb ataxia, 2233 Limbic cerebellum, 2023 Limbic system cerebellar connections with, 608–609 definition, 607–608 Lindane, 2377 Lineage trace analysis, 91 Linearity, 2035 Lithium salts, 2374–2375 Lmx1a, 29, 70, 73, 76, 221, 343 Lmx1b, 76, 1141 Lobule-based volumetric analysis, 1878 Lobus caudalis, 1649 Local field potentials (LFPs), 915 Locus ceruleus, 2453, 2455 Locus coeruleus, 976–977, 1709, 1713, 1715, 1724 Long-term adaptation, 2647 Long-term depression (LTD), 865, 867–873, 932, 997, 1013, 1033, 1257, 1261, 1263, 1265–1267, 1309, 1313, 1508, 1509, 1511–1513 blockade of, 1510 investigations of, 1510 in vivo LTD, 1512–1513 Long-term memory, 1980 Long-term potentiation (LTP), 865, 869, 870, 872–874, 997, 1262, 1263, 1265, 1325, 1508–1511 Louis-Bar syndrome, 1930 Lower rhombic lip (lRL), 16 L-Triiodothyronine (T3), 356, 360 L-type channels, 1719, 1723, 1724 Lugaro cells, 237, 276, 907, 910, 912, 913, 915, 917, 961, 995 Lurcher mouse abnormalities in endocrine and immune systems of, 1695–1696 behavioral characteristics, 1696–1699 breeding and colony maintenance, 1701 experimental influencing, 1699–1701 morphological and cellular changes, 1687– 1689 neurochemical abnormalities, 1693–1694 neurotransmitters and receptor system abnormalities, 1694–1695 pathogenesis of neurodegeneration in, 1690–1693

2721 M Machado-Joseph disease, 1976, 2622–2625, 2679 Macrogyric portion, 689 Magnetic resonance imaging (MRI), 728, 729, 776, 1910, 1916, 1917, 2450, 2456 Magnetic resonance spectroscopic imaging (MRSI), 780 Magnetic resonance spectroscopy (MRS), 777 of cerebellum in cancer, 788 of cerebellum in metabolic disorders, 788 cerebellum in neurodegenerative diseases, 784–786 challenges in cerebellum, 780–782 proton, 777 Malformation, 2117–2120, 2122, 2127 Manganese, 2385 Marinesco–Sjögren syndrome, 2295, 2631, 2633 Marr-Albus-Ito hypothesis, 1168–1170, 1387 Marr’s model, 1565 Mash1, 25 Maternal deprivation, 366 Maternally inherited Leigh syndrome (MILS), 2591 Math1, 25, 84, 104 See also Atoh1 Mechanistic level, 2453 MeCP2, see Methyl-CpG-binding protein 2 (MeCP2) Medial accessory olive, 501, 1143 Medial cerebellar nucleus, 633–636 Medial descending motor system, 632 Medial intraparietal area, 688 Medial medullary infarcts (MMI), 743 Medial vestibulospinal tract, 638 Medical interventions, 2642–2644 Medulla oblongata, 452 Medullary ischemic syndromes, 742–743 Medulloblastoma, 30, 788, 1972, 2322 Mefloquine, 2377 Mega-cisterna magna, 2083–2084 Megalographia, 1846 MELAS/MERRF overlap syndrome, 2590 Memory, 1939, 2121, 2122, 2125, 2126 Meningeal carcinomatosis, 2325 Mercury, 2382–2383 Mesenchymal stem cell (MSC) therapy, 2420 Mesodiencephalic junction, 514–518, 1151, 1152, 1158, 1172, 1220 Metabotropic glutamate receptor type 1 (mGluR1), 1774–1776 Metabotropic P2Y receptors, 1050

2722 Metastases, 2324 Methadone, 2380 Methyl-CpG-binding protein 2 (MeCP2), 419, 421, 422 Methylmercury (MeHg), 159–161 Metronidazole, 2378 mGluR1 receptors, 293, 1409 Microbiota-gut-brain [MGB] axis, 1417 cerebellum role, 1420–1421 sexually dimorphic nature, 1428–1429 space environmental factors, 1424–1428 Microexplant cultures, 146, 151–153, 155, 156, 160, 162 Microgravity conditions, 1427 incrased vagal activation, 1422 Salmonella enterica growth, 1425 Microgyric portion, 689 Microiontophoresis, 973 Microzone, 1254 Midazolam, 2009 Midbrain, 452 ischemic syndromes, 745–746 Midbrain–hindbrain (MHB) domain, 9, 13, 2119 Middle intracranial posterior circulation territory, 452 Midline, 1143, 1144, 1146 Midodrine, 2424 Migraine, 1735, 1741, 1749 Miller Fisher syndrome, 2273–2275 Mineralocorticoid(s), 366 Mineralocorticoid receptor (MR), 366 Mitochondria cerebellar ataxias, 2063–2064 degradative metabolic pathways, 2564–2565 oxidative phosphorylation and respiratory chain, 2566 protein transport, 2563 substrate carriers, 2564 Mitochondrial disorders, 729 ANS, 2580–2581 coenzyme Q10 deficiency, 2582–2583 FRDA, 2570–2578 IOSCA, 2581–2582 MEMSA, 2579–2580 POLG-related ataxias, 2578–2579 SCA28, 2583–2584 XLSA/A, 2583 Mitochondrial DNA (mtDNA) cerebellar disorders, 2584–2592 large-scale rearrangements, 2592–2594 Mitochondrial dynamics, 2565–2566

Index Mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS), 2587–2589 Mitochondrial inheritance, 2055, 2069 Mitochondrial recessive ataxia syndrome (MIRAS), 2580, 2581 Mitogen-activated protein kinases (MAPK), 869 Modified ICARS (MICARS), 2042 Modified Rankin Scale, 1918 Modified rota-rod test, 1766 Modules, 647 Molar tooth malformations, 2080–2082 Molar tooth sign, 225, 1926 Molecular chaperones, 2681, 2682 Molecular layer, 143, 144, 1545–1548, 1552, 1650, 1653, 2452 Molecular layer interneurons (MLIs), 70, 76, 272–274, 1505, 1509, 1510 function of, 885–887 physiological properties, 884–885 synaptic plasticity, 887–895 Monocarboxylate transporter, 360 Monoclonal antibody, 689 Monozygous twins, 616 Moonwalker mouse mutation, 1776–1778 behavioral phenotype, 1780–1781 impaired dendritic and synaptic development, 1781–1783 loss of cells, 1780–1781 morphological changes, 1780–1783 pathophysiology, 1778–1780 Mormyrid fish, 1650 Morris water maze, 1943 Mossy fiber(s), 53–54, 187, 191, 197, 198, 267–269, 910–911, 958, 993, 999, 1256, 1261–1263, 1266, 1278, 1279, 1293, 1652, 1657 axonal projection patterns of neurons, 583–586 morphology of, 571, 577 neurons, 89 origin, 560 reconstruction of, 581 Mossy fiber-granule cell synapses, 1031–1032 Mossy fiber terminals (MFTs), 469 Motivation, 2021, 2023 Motor, 2115, 2116, 2120–2123, 2125–2127 adaptation, 2646, 2655–2657 command, 1439, 1447, 1450, 1488 control, 1659 control theory, 1312 coordination, 885, 2688

Index cortex, 1382, 1385–1387, 1390, 1392 learning, 807, 865, 873, 874, 886, 1165, 1167–1170, 1254, 1256, 1262, 1263, 1266, 1697, 1700, 2447, 2456, 2655, 2656 performance, 1163, 1167 skills tests, 1696 timing model, 1170–1171 Motor disorders, 1828 ataxia of limbs, 1838–1846 dysarthria, 1836–1838 dysphagia, 1838 oculomotor disturbances, 1832–1836 symptoms, 1831–1832 topography of cerebellar deficits, 1847–1851 Motor-evoked potentials (MEPs), 2147 Motor rehabilitation animal cerebellar lesion, 2647 future studies, 2655–2657 in human cerebellar disease, 2647–2649 impairments in motor performance and adaptation of movements, 2645–2646 long-term studies and quality of life, 2654 for upper extremities, 2653–2654 Motor thalamus, 662 afferents, 664–669 cortical areas, projections to, 673–674 cyto-and chemoarchitecture, 663 general topography of projections, 674–675 MI, projections to, 669–670 nomenclature, 663 premotor cortex, projections to, 672–673 SMA and pre-SMA, projections to, 670–672 Mouse gene expression, 72 Mouse models for inherited ataxia, 1613–1615 Mouse mutant, rolling Nagoya, see Rolling Nagoya (RN) mouse Mouse mutant analyses, 78 Movement disorders, 2669 Multidimensional generalized vector–matrix approach, 1571 Multi-joint coordination, 2649, 2655 Multiple system atrophy (MSA), 785, 2057, 2064, 2410, 2437, 2616–2618 anticholinergics, 2422 autonomic symptoms, 2422–2425 cerebellar ataxia, 2422 clinical features, 2412 constipation, 2424 diagnostic criteria, 2412–2414 dopaminergic agents, 2421

2723 dystonia, 2422 epidemiology, 2411 erectile dysfunction, 2424 investigations, 2414–2416 motor symptoms, 2420–2422 neuropathology, 2417–2418 NMDA receptor antagonist, 2421 non-medical therapy and palliative care, 2425 orthostatic hypotension, 2423 parkinsonian symptoms, 2420 pathogenesis of, 2418–2419 progression, 2416 selective serotonin reuptake inhibitor, 2421 sialorrhea, 2422 symptomatic treatment, 2420–2425 therapy, 2419 urinary dysfunction, 2423 Multiple system atrophy of the cerebellar type (MSA-C), 617 Multisensory integration (MSI), 2126 Mutagenesis screen, 1637 Mutants, 1633 Mutant TRs, 365 Mutism, 1353 Mycoplasma genitalium, 1582–1584 Myelinolysis, 2367 Myoclonic epilepsy and ragged red fibers (MERRF), 2200–2202 Myoclonic epilepsy myopathy sensory ataxia (MEMSA), 2579–2580 Myoclonic epilepsy with ragged-red fibers (MERRF), 2584–2587 Myo-inositol, 778

N N-acetylcysteine, 2221 National Institutes of Health (NIH), 2495 Stroke Scale, 1908 Nauta method, 561 Necrosis, 1686, 1693 Necrotic cell death, 1691 Neonatal adversity, 2100 Neonatal reinnervation, 296 Neosynaptogenesis, 299, 301 Nephrin, 1142 Nephrocystin3 (Neph3), 18 Nerve conduction studies, 2469 Nerve terminals, 1734, 1739, 1742, 1746–1748 NETO2, 945–946 Network analysis, 346

2724 Neural integrator, 1810–1811 ocular motor, 1811–1812 vestibular, 1812–1813 Neural integrator network, 1811 Neural net elements, 1581 Neural tube, 4, 6–8, 10, 12–14, 16, 1140, 1142 closure, 4, 7 Neurexin, 271 Neurobehavioral tests, 1961 Neurochemical profile, 777, 781 NeuroD, 28–33 Neurodegeneration, 779, 786, 2682, 2684 Neurodegenerative disorders, 2448 Neuroepithelium, 4, 10, 13–18, 84, 87, 90 Neurofascin, 247, 274 Neurofilaments, 2451 Neurog1, 25, 28, 34, 35 Neurog2, 25, 28, 34, 35 Neurogenesis, 35–38 cerebellar, 101, 103 evolutionary perspective on, 110–111 and secondary proliferation, 107–108 Neurogenin1, 25 Neurogenin2, 25, 126 Neuroimaging, 2114, 2115, 2117, 2124–2126, 2128, 2450 Neurological disease, 2442, 2443, 2457 Neurological disorders, 141 Neuromodulators, 388 Neuromuscular junction (NMJ), 1734, 1737, 1739, 1747–1750 Neuronal ceroid lipofuscinosis (NCL), 2202 clinical-pathological manifestations-EEG findings, 2204–2206 diagnosis, 2206 genetics, 2203–2204 incidence, 2203 Neuronal development, 380 Neuronal growth, 1121 Neuronal intranuclear inclusions, 2621 Neuronal migration cell adhesion molecules, 141 environmental toxins, 141 genetic mutations, 141 neuron-glia interactions, 141 Neuronal nitric oxide synthase (nNOS), 55, 869 Neuronal progenitors, 76, 77 Neuronal protection, 369 Neuronal subtypes, 86 Neurons, 2453, 2455 Neuropathic pain, 2146 Neuropathy, ataxia, and retinitis pigmentosa (NARP), 2590–2591

Index Neuropeptides, 1074 Neuropharmacological inactivation, 1291 Neuropsychiatric manifestations, 1973 Neuropsychological testing, 1962, 1967 Neurosteroids, 1116 biosynthesis in Purkinje cell, 1120 formation in the Purkinje cell, 1119 identification, 1117 Neurotransmitter(s), 141 release, 1735, 1737, 1739, 1747, 1750 Neurotransplantation research, 1699 Neurotrophins, 1693 Ngn1, 25 Ngn2, 25 Nicotinamide, 2675 Nicotine, 2379 Nitric oxide soluble guanylyl cyclase, 1027–1028 synthases, 1027 NMDA, 1204 NMDA receptors, 292, 293, 854 NMDA-type glutamate receptors, 149–150 Nna1 expression in wild-type and mutant hamsters, 1765 Nociception, 613 Nodulus, 454, 628, 639 Nodulus and uvula complex, 1306 electrical stimulation and lesion studies, 1306 neuronal response, 1306–1307 oculomotor system, 1306 Noncoding triplets, 1592 Non-crossed axons of Clarke’s column neurons (NCC), 580 Non-crossed axons of marginal Clarke’s column neurons (NMCC), 580 Non-GABAergic interneurons, 1245–1246 Non-genomic mechanism, 367 Non-genomic thyroid hormone actions, 360 Non-mammallian animal models, 1609 Amphibian and reptile models, 1611–1612 fish models, 1610–1611 non-vertebrate animal models, 1609–1610 Non-motor, 2122 Non-mouse rodent models, 1615 Non-primary sensorimotor, 1281 Non-rodent mammal models, 1616 cat models, 1616–1617 primate models, 1616 Non-saccular aneurysms, 754 Non-territorial small infarcts, 2240–2241 Non-vertebrate animal models, 1609–1610 Noradrenaline, 893, 895, 1695

Index Noradrenergic axons, 1715 Noradrenergic receptors, 979–984 Norepinephrine actions in cerebellum, 974 iontophoresis, 977 modulatory actions in cerebellum, 973 neuromodulatory transmitter, 979 on Purkinje neurons, 976–977 as a putative inhibitory transmitter, 972 synergistic effect, 974 Normalization of cerebellar cortex, 1866–1868, 1880 Norrbottnian form, 2211 Notch, 30 BMP signalling, 126 signaling, 28 Novel strategy, 1947 Noxious stimulus, 613 NRm stimulation, 1231 N-type Ca2+ channel, 153 Nuclear localization, 2507 Nuclear neurons, 1474 Nuclear receptors, 361, 365 Nuclear transitory zone (NTZ), 31 Nucleocortical glycinergic neurons, 1244 Nucleo-olivary fibers, 537 Nucleo-olivary (NO) pathway anatomical features of, 1217–1219 cerebellar learning, regulation of, 1225–1229 indirect cerebellar control, of olivary excitability, 1230–1231 inferior olive, electrotonic coupling in, 1229–1230 neurophysiological properties of, 1219–1221 spontaneous Purkinje cell activity, regulation of, 1222–1225 Nucleo-olivary (NO) projection, 1243 β-Nucleus, 1143, 1151, 1152 Nucleus accumbens (NAcc), 615 Nucleus lateralis valvulae, 1657 Null method, 475 Null mutants, 85 NuRD complex, 415–418, 422 Nystagmus, 643, 650, 1833, 2234

O Observation-learning, 1943 Ocular hypermetria, 1834 Ocular oscillations, 1820 Ocular tilt reaction (OTR), 1836, 2234

2725 Oculomotor abnormalities, 2446, 2455 Oculomotor system, 1697 Oculomotor vermis (OMV), 918, 1307–1309, 1311, 1312 Oculopalatal tremor, 1820–1823 Olanzapine, 2180 Olig2 expression, 35, 339, 1655 Olig3, 1142 Oligonucleotide therapeutics, 1413 Olivary glomeruli, 1152 Olivary hypertrophy, 2355–2356 Olivocerebellar axons axonal trajectories of, 563–566 thin collaterals of, 566–569 Olivocerebellar degeneration, 1686 Olivocerebellar fibers, 1278 Olivocerebellar loop, 1195, 1207 Olivocerebellar projection autoradiography of [3H]leucine, 524 to cerebellar nuclei, 532 flocculus and nodulus, 533 ipsilateral hind-and forelimb projections, 527 in primates, 537–538 in rabbit, 525 spino-olivocerebellar climbing fiber paths, 525 topographical organization, 523 transverse climbing fiber branching, 529 zebrins, 529–533 zonal organization, 526 Olivocerebellar system, 193, 1195, 1199, 1204, 1208 Olivocorticonuclear modules, 1276 Olivopontocerebellar atrophy (OPCA), 784, 2486, 2501, 2510, 2516, 2520, 2542 Omaveloxolone, 2674 Opsoclonus-myoclonus ataxia syndrome, 2269–2270 Opsoclonus myoclonus syndrome (OMS), 1971 Optic tectum, 1650, 1660 Optimal control theory, 1490 Optogenetic methods, 1281 Optogenetics, 1260, 1267 Optokinetic reflex (OKR), 982, 1302, 1303 Optokinetic system, 510–513 Organic anion transporter, 360 Orthostatic hypotension, 2423 Oscillations extrinsic control of, 1204–1206 and olivary output, 1202 Oscillatory motor control, 920 Otx2, 1139

2726 Otx2-Gbx2 boundary, 11–12 Otx genes, 101 Output channels, 684–689 Oxidative phosphorylation (OXPHOS), 2562–2564, 2566, 2567, 2570, 2578 Oxidative stress-induced cell death, 366

P p53, 1691 Paced auditory serial addition task (PASAT), 811 Pain, 613–614 Paired-pulse facilitation, 1101 Palatomyoclonus, 1171, 1172 Pancreatic transcription factor 1a (Ptf1a), 85, 126 Paralimbic cortices, 610 Parallel fiber(s) (PFs), 269–270, 864, 865, 867, 869–871, 1361, 1440, 1442, 1540, 1650, 1743, 1747 activity in, 1441 excitation, 1548 long-term depression at, 1444 and molecular layer inhibitory synaptic strengths, 1549 on Purkinje cell, 1541–1544 signals, 1505, 1506 synaptic plasticity, 1448–1449 termination, 1441 Parallel fiber–Purkinje cell synapses, 1032–1033 Paraneoplastic cerebellar ataxia antibodies in, 2327 with anti-channels blockers, 2330 anti-CV2/CRMP5 antibodies, 2329 anti-Hu antibodies, 2328 anti-mGluR1 antibodies, 2330 anti-Ri antibodies, 2330 anti-Tr antibodies, 2329 with anti-Yo antibodies, 2328 clinical and biological features of, 2326–2328 treatment, 2331 Paraquat, 2392 Parasagittal stripes, 46 Parasitic cystic lesion, 728 Parasolitary nucleus, 513 Parkinsonism, 2445 Parvalbumin, 386, 960 Patch-clamp and imaging techniques, 838 Pathogenetic mechanisms, 2117

Index Pause, 1257, 1266 Pax2, 35, 1141 Pax6, 88, 343 Pax8, 362 Pediatric cerebellar stroke study, 1971 Pedunculo-cerebellar sulcus, 461 Pendular eye oscillations, 1820 Perampanel, 2220 Perceptual timing neuroimaging studies, 1367–1368 neuropsychological studies, 1365–1367 Pericellular nest, 287 Perinatal critical period, 367 Perinatal hypothyroidism, 357, 361 Periodic alternating nystagmus, 1816–1817, 1833 Peristimulus time histogram (PSTH), 1282 Perospirone, 2181 Persistent sodium current, 1259 Personality, 2448 Petrosal surface, 452 PF-excitatory postsynaptic currents, 871 PHACE syndrome, 2152 Phaseolus vulgaris-leucoagglutinin (PHA-L), 561, 571 Phencyclidine, 2380 Phenotypes, 335, 338 Phenotypic heterogeneity, 2611 Phenytoin, 2371 Phonemic cluster, 1947 Phonemic fluency, 1352 Phosphocreatine, 777 Phosphodiesterases, 1029 Phospholipase A2 (PLA2), 869 Phospholipase C (PLC), 154 Photic stimulation, 2216 Physiological activity, of Purkinje cells calcium buffers, 385–387 calcium channels, 383–384 potassium channels, 383 sodium channels, 382–383 synapses, 387–388 Physiotherapy, 2648, 2680, 2686, 2688–2689 Pial arteriovenous malformations, 757–760 PICA infarction, 2238 Picture arrangement subtest, 1941 Pilocytic astrocytomas, 2323–2324 Pinceau, 273, 274 Pineal gland, 1117 biological action of allopregnanolone, 1128–1129 neurosteroid identification, 1127–1129 as site for neurosteroidogenesis, 1126–1127

Index Pituitary adenylate cyclase-activating polypeptide (PACAP), 151–153 Plasticity, in CN, 1194, 1202, 1205, 1262 excitability plasticity, 1265 mossy fiber inputs, to CN neurons, 1262–1263 Purkinje cell CN pathway, 1263–1265 short-term, 1265 structural, 1266 POLG-related ataxias, 2578–2579 Polychlorinated biphenyls (PCBs), 2382 Polycomb repressive complex 2 (PRC2), 417, 420 Polyglutamine (polyQ), 2495, 2497 disorders, 2679, 2682 tract, 2055 Polysomnography, 2217 Pons, 596, 597, 1908–1910, 1913, 1914, 1918 cortical projection, pathway of, 597–599 corticopontine and collicular fibers, 599–600 Pontine gray nucleus (PGN), 89 Pontine ischemic syndromes, 743–745 Pontine nuclei (PN), 596, 599–602, 610, 615, 692, 694 Pontine nucleus neurons, 578–579 Pontine visual cells, 601 Pontocerebellar atrophy, 732 Pontocerebellar fibers, 601 Pontocerebellar hypoplasia, 226–227, 2088 Pore-forming α1 subunit, 1734, 1739 Positron emission tomography, 1914, 1917, 1918 Posterior circulation, 452 aneurysms, 740, 751–753, 756 Posterior communicating arteries, 458 Posterior communicating artery aneurysms, 753 Posterior fossa, 2114, 2115, 2117, 2119, 2123, 2124 hemorrhagic diseases, 751–757 ischemic diseases, 742–751 posterior fossa neurovascular disease, imaging approach, 763–765 Posterior fossa infections bacterial infections, 2302–2305 cerebellitis, 2306–2312 human prion diseases, 2312–2314 Posterior Fossa Society, 1997 Posterior fossa syndrome (PFS), 1353, 1970 CMS and CCAS, 1970 emotional lability, 1970 surgical approach, 1970

2727 Posterior fossa trauma, 2339 clinical presentation, 2342–2344 control of intracranial pressure, 2352 control of vital functions, 2352 CT and MRI imaging, 2344–2350 epidemiology, 2339–2340 extra-axial lesions, 2341–2342 future research, 2357 intra-axial lesions, 2340–2341 long-term complications, 2354–2356 management, 2352–2353 pathophysiology, 2350–2351 SPECT and PET, 2350 traumatic vascular lesions, 2342 vertebral artery dissection, 2353 Posterior inferior cerebellar artery (PICA), 453–455, 457, 1836, 1844, 1860, 1870 infarction, 748–749 Posterior interposed nucleus, 542–543, 636 Posterior parietal cortex, 683, 688, 689, 691, 697 Posterior Reversible Encephalopathy Syndrome, 734 Post infectious cerebellitis, 2270–2272 Postinhibitory rebound, 1266 Postmitotic cells, 88 Postmitotic neurons, 141 Postmortem studies, 2445, 2451 Postnatal development, 268 Post-operative cerebellar mutism, 1972 Post-operative pediatric cerebellar mutism syndrome (POPCMS), 1997, 1999, 2000, 2007, 2009, 2010 dentato-thalamo-cortical pathway, 2005 emergence and clinical course of, 2007 incidence rate of, 1998 long-term cognitive consequences of, 2002 neurocognitive impairments, 2003 and PLI, 2005 prototypical feature of, 2001 risk factors for, 2005–2006 symptom of, 2000 Post-pedunculotomy reinnervation, 296 Posttranslational modifications, 2505 Postural tremor, 1842, 2443, 2445 Posture and gait analysis, 2368 P/Q type calcium channel, 1196, 1198, 1200 Pravastin, 2678 P2 receptor expression pattern in cerebellum, 1050–1051 functional effects in cerebellum, 1051–1055

2728 Precerebellar nucleus, 644 Precerebellar systems, 89, 91 Preclinical ataxia, 2654 Precursor, 412, 414–420 Prediction, 1939 errors, 1498 Prediction interval (PI), 2044 Premature children, 1928 Premotor cortex, 672–673 Prenatal exposure to alcohol, 1928 Preolivary nuclei, 516 Prepulse inhibition (PPI), 1103, 1699 Presupplementary motor area (Pre-SMA), 670–675, 686 Pre-surgical language impairment (PLI), 2005 Presynaptic differentiation, 416 Pretectal complexes, 1151 Preterm birth, 2096 Preterm infants, 2097, 2099 with unilateral cerebral injuries, 2101 Primary autoimmune cerebellar ataxia (PACA), 2266–2269 Primary central nervous system lymphoma, 2325 Primary dendrite, 1651, 1653 Primary motor cortex (MI), 669–670, 1282, 1283, 1286, 1289 Primate models, 1616 Principal cells, 1441–1444 Principal component analysis, 2035 Principal olive, 1143, 1172 Prion diseases clinical presentation, 2312–2313 epidemiology, 2312 investigations, 2313 pathogenesis, 2314 Private clouds, 1594 Procainamide, 2376 Procedural learning, 1528, 1530, 1532, 1944, 1946 Procedural memory, 1948 Progesterone, 1120 biological actions in Purkinje cell, 1121–1123 mode of action, 1122, 1124–1126 Progressive Multifocal Leukoencephalopathy (PML), 728 Progressive myoclonic epilepsies action myoclonus-renal failure syndrome, 2220 causes of, 2195

Index cherry-red spot myoclonus syndrome, 2217–2219 coeliac disease, 2220 description, 2195 DRPLA, 2206–2210 Gaucher disease, 2210–2213 genetics/proteomics of, 2196–2197 infantile neuroaxonal dystrophy, 2220 Juvenile form of Huntington's disease, 2220 Lafora disease, 2213–2217 myoclonic epilepsy and ragged red fibers, 2200–2202 neuronal ceroid lipofuscinosis, 2202–2206 treatment, 2220–2223 Unverricht-Lundborg disease, 2195–2200 Progressive supranuclear palsy, 2416 Projectional map, 198 Projection neurons glycinergic, 1244–1245 large glutamatergic, 1242–1243 small, GABAergic, 1243 Proliferation, 72, 74–79 Promoter, 411–418, 423 Proneural genes, 25, 27, 29, 35, 434, 440 Proportional hemiparesis, 1905 Prospective white matter (PWM), 124, 126, 127, 133 Protein aggregates, 2504 Protein interacting with C-kinase (PICK1), 940, 941, 945, 946 Protein kinase A (PKA), 872, 980 Protein kinase C (PKC), 152, 154, 867 Protein kinase C γ (PKCγ), 1775, 1779, 1782 Protein phosphatases, 869 Protein quality control, 2504 Protoplasmic astrocytes, 123 Proximal intracranial posterior circulation territory, 452 Pseudochoreoathetosis, 1906 Pseudohypertrophy, 1820, 2355 Pseudohypoparathyroidism, 2290 Pseudopseudohypoparathyroidism, 2290 Psychiatric disorders, 367 Psychiatric features, 2448–2449 Ptf1a, 76, 77, 103, 1142 Purinergic signalling, 1066–1067 Purkinje axon development corticofugal Purkinje axon, 181–182 intracortical plexus, 182–184 intrinsic mechanisms and environmental control, 184–185

Index Purkinje cell(s), 49, 70, 76–78, 86–89, 175, 194, 266, 287, 295, 381, 412, 414–421, 433–442, 518–523, 560, 864, 905, 907, 912, 913, 915, 916, 918, 931, 932, 934, 935, 940, 942, 945, 946, 960, 972, 993, 1117, 1147, 1194, 1195, 1197, 1201, 1207, 1208, 1216–1218, 1220–1225, 1228–1231, 1253, 1254, 1256, 1257, 1259–1261, 1263–1267, 1276, 1277, 1280, 1283, 1303, 1304, 1306, 1312, 1321, 1324–1325, 1336, 1386–1387, 1505, 1509, 1510, 1513, 1523, 1541, 1651, 1690–1692, 1700, 1711, 1714, 1719, 1739, 1742, 1743, 1745, 1746, 1975, 2451–2457, 2500–2504, 2506, 2508, 2519, 2521, 2524, 2526, 2528, 2531–2533, 2566, 2575, 2584, 2588– 2590, 2593, 2683 acquisition and extinction, 1338 adult firing patterns, 381 axon collaterals, 276–277 biochemical heterogeneity, parasagittal stripes of protein expression, 193–194 biological actions of progesterone, allopregnanolone and estradiol, 1121–1123 biosynthesis of neurosteroids, 1120 bodies, 2154 burst firing, 1159 in cerebellar cortex, 1165 cerebellar cortex and formation, 177 cerebellar cortical layering, transient biochemical heterogeneity, 196–197 cerebellar function, 191 climbing fibers synaptogenesis, 311 corticofugal Purkinje axon, development of, 181–182 death, 1691 degeneration, 1780 dendrites, 186, 187, 189, 190, 1548 dendritic arborization, 1782 dendritic differentiation, sequential phases of, 185–187 dendritic growth, 1782 dendritic protrusions, 1145 discharge properties of, 980 discovery of, 1118–1120 diversity of, 108–110 dynamical state, 1547 dysfunction, 1776 expression changes in Mwk, 1783

2729 extrinsic and intrinsic factors, Purkinje dendritic growth, 189–190 granule cell neurogenesis, 192–193 homosynaptic and heterosynaptic competition, 323–325 intracortical plexus of Purkinje axon, development of, 182–184 intrinsic determinants, Purkinje cell dendritogenesis, 187–188 intrinsic mechanisms and environmental control, of Purkinje axon development, 184–185 migration pathways, 49 minimum CS-US interval, 1340 model, 1545 mode of action of progesterone and estradiol, 1124–1126 mutation of bHLH genes in, 105 parallel fibers, 190–191, 1542–1544 pause responses, 1336–1337 physiological activity of (see Physiological activity, of Purkinje cells) plasma membrane, 1778 Purkinje cell monolayer, formation of, 179–181 RORα, formation of Purkinje cell dendrites, 188–189 signals, 1470, 1472 Sonic Hedgehog, 107 spatial distribution, 108 spikes, 1162 stripe patterning and foliation, 50 structural role, 55 substype specification, 50 temporal properties, 1338–1340 ventricular neuroepithelium, 176–177 zebrin expression profile, 381 Purkinje cell degeneration mutation in mice, 1767–1769 vs. ataxic hamsters, 1769–1770 Purkinje cell function, within synaptic network, 292 Purkinje cell layer (PCL), 123–125, 127, 128, 133, 145 Purkinje neurons, 976–977, 981, 1572, 1581, 2369, 2373, 2374, 2381, 2392 Pyramidal sign, 1905, 1913 Pyramidal tract, 1904, 1911 Pyramis, 454 Pyruvate dehydrogenase complex (PDHC), 2565

2730 Q Quadriataxic hemiparesis, 1908 Quail-chick chimera transplantation method, 7 Quality of life, 2654 Quetiapine, 2180

R Rabies virus, 647, 690, 693–696 Radial migration, 142, 143, 151, 152 Radioligand binding studies, 1061 Rapid automatized naming (RAN), 809 Rasagiline, 2420 Rate of migration, 142, 149 Rebound burst, 1259 Rebound depolarization, 997, 1198 Rebound potentiation (RP), 963 Receptive field, 600, 602 Recovery, 2641–2642 Recursive algorithm rule, 1572–1573 Red nucleus, 640, 641, 1151 Reelin, 51, 369 protein expression, 221 signaling, 178–180 signaling system, 2164–2165 Reflexes, 649, 650 Refsum’s disease, 2678 Regional grey matter, 800 Region of interest (ROI)-based fcMRI cerebellar cortex, 708 cerebral cortex, 708–710 dentate nucleus, 707 RegNetwork, 347 Regression analysis, 2268 Regressive-atrophic dendrites, 186 Rehabilitation program, 2124 Relief of space-occupying lesions, 2353 Repeat length, 2499, 2500, 2503, 2510, 2515–2517, 2522, 2535 Repetitive TMS, 1368 Replenishment model, 105 Representative autosomal dominant ataxias, 1613 Rescorla-Wagner model, 1225, 1229 Resistance to thyroid hormone, 364, 365 Respiratory chain (RC), 2566–2569 Resting membrane potential, 163, 164 Resting state analysis, 2656 Resting state functional connectivity MRI (fcMRI), 706 independent component analysis, 710–714 ROI-based, 707–709 tractography, 711–715

Index Resting tremor, 2442 Resveratrol, 2674 Reticular formation, 632–638 Reticulospinal tract, 637–640 Reticulotegmental nucleus (RTN), 89 Retinoic acid, 75, 1139–1142 Retinoic acid related orphan receptor (ROR), 361 Retinoid-related orphan receptor alpha (RORα), 188–189 Retinoid X receptor, 356 Retrograde leptomeningeal venous drainage (RLVD), 760 Retrograde transneuronal tracers, 1282 Retrograde transneuronal transport, 693 Rett syndrome, 422 Reversible posterior leukoencephalopathy syndrome, 2376 Rhombencephalon, 1657 Rhombencephalosynapsis, 226, 1927, 2078–2079 Rhombic lip (RL), 16, 17, 125, 342, 1140–1142 stem cells, 84, 104 zone, 209 Rhombic lip (RL) development roof plate-derived Bmp signaling, 73–75 roof plate-derived secreted molecules, 75 Rhombomere 1 (Rh1), 69, 70, 73–76, 101, 102, 2115 Rhombomeres, 7, 90, 1140–1142 Rhythmic activity, 1198, 2449 Rifampicin, 2420 Riluzole, 2420, 2643 Risperidone, 2181 Robo3, 1145 Robotic mouse deregulation of IGF-1 signaling pathway in, 1677–1678 genetic and molecular basis, 1671–1678 phenotype, neuropathology and behavior, 1669–1671 Rodent animal models, 1612–1613 mouse models for inherited ataxia, 1613–1615 non-mouse rodent models, 1615 Rolling Nagoya (RN) mouse, 1734 CaV2.1 channel (see CaV2.1 channel, rolling Nagoya mouse) cerebellar Purkinje cells, 1746 dysfunction of cerebellar synapses and neuromuscular junction, 1746–1748 histological analyses, 1741–1743 phenotypic description, 1735–1737

Index Roof plate, in cerebellar neurogenesis, 86, 90 cellular and molecular mechanisms, 71–73 cerebellar rhombic lip, development of, 73–75 cerebellar ventricular zone, 75–78 Ror-alpha, 249 Rora (RORα), 435–436 Rubral tremor, 2354 Rubrospinal tract, 637–640 Ryanodine receptors (RyR), 1724, 1742

S Saccade adaptation, 1311 Saccadic plasticity, 1308 Saccular aneurysms, 751–754 Saxitoxin, 2393 SCA13, 393, 394 SCA1, 785, 786 SCA2, 785, 786 SCA41, 393 SCA6, 785, 786 SCA8, 785 SCA infarction, 2240 Scale for the Assessment and Rating of Ataxia (SARA), 2039–2040, 2044, 2649, 2654 clinical application, 2041 validation, 2040–2041 Schizophrenia, 618, 789, 1328, 2102, 2178 atypical antipsychotics, 2180 CBT, 2182 and cerebellum volume reduction, 2183–2184 classifications, 2179 diffusion tensor imaging studies, 2185–2186 ECT, 2182 pharmacological mechanism of neuroleptic therapy, 2181–2182 prevalence and mortality, 2179 progressive volume reduction in, 2184–2185 psychotherapies, 2182 risk factors, 2179 SST, 2182 structural magnetic resonance imaging studies, 2182–2183 susceptibility genes and neuronal disconnectivity in, 2186 typical antipsychotics, 2179 volume reduction theory of, 2186–2187 Schmahmann’s syndrome, 1353 Scorpions, 2395

2731 Screening, 1624 Script(s), 1941–1942 sequencing, 1941 Secondary traumatic brainstem lesions, 2341 Secreted signals, 68 Selective synapse elimination, 289 Semantic cue retrieval, 1947 Semilunar lobule, 454 Sensorimotor learning, 1368–1369 Sensorimotor projections, 799 Sensory ataxia, 2056 Sensory ataxia neuropathy dysarthria and ophthalmoplegia (SANDO), 2580 Sensory ataxic neuropathy dysarthria ophthalmoparesis, 2067 Sensory feedback, 1490, 1492, 1498 Sensory output model, 1489 Sensory prediction, 1489 Sensory prediction error (SPE), 1463, 1467, 1469, 1472, 1474 Septo-optic dysplasia, 2295 Sequence detection theory, 1949, 1950 Sequencing for language processing, 1947–1948 script, 1941 writing, 1948 Serial reaction time task, 1944, 1945 Serotonergic fibers, 993 Serotonergic modulation in cerebellar cortex, 993–996 in deep cerebellar nuclei, 996–998 Serotonin, 991, 993, 1204, 1695 immunoreactive fibers, 993 levels in cerebellum, 1000 receptors, 389 Seven in absentia homolog (SIAH) enzyme, 1672–1673 Sexual differentiation, 365 Sexually dimorphic neurogenesis, 368 Shared circuits model (SCM), 1516 Shh signaling, 77–78 Short latency response (SLR), 1260 Short-term adaptation, 2656 Short-term depression (STD), 1265 Short-term synaptic plasticity, 873 Sialidosis type 1, 2217–2219 Signaling centers, 68, 71, 78 Simple-fusiform cells, 185 Simple spikes, 1337, 1340–1342 Single cerebellar afferent fibers, 562 Single-photon emission computed tomography, 1914, 1915, 1917, 1918 Skew deviation, 1836

2732 SLC1A3, 1411 Slit/Robo guidance system, 219 Slit, 1143 Small cerebellar infarcts, 2240 Smoothened overexpression, 31 Snf2h, 415, 420, 421 Snf2l, 415 Social cognition, 1974 in cerebellar disorders, 1974 and social emotion, 1974 task activation, 812 Social/emotional/affective processing, 811–813 Social skill training (SST), 2182 Soluble guanylyl cyclase, 1027–1028 Somatic/perisomatic territories, 289 Somatosensory cerebral cortices, 1284 Somatosensory cortex, 1279 Somatosensory evoked potentials (SEPs), 1914, 1915, 1918, 1939, 2147 Somatosensory mismatch negativity, 1939 Somatostatin (SST), 150–151, 1105 Somatostatin receptors (SSTRs), 150 Somatotopical localization, 506 Somatotopy, 1957 Sonic hedgehog (SHH), 30, 31 Sox9, 35 Space environmental risk factors, on MGVHB axis, 1424 diet, 1424 gravity, 1425 minimizing, 1429–1430 radiation, 1425–1427 stress, 1427–1428 Space exploration, 1431 Spastic ataxias, 2065 Spasticity, 1906 Spatial dysgraphia, 1949 Spatial learning, 1697 Spatially unbiased infra-tentorial (SUIT) atlas template of the human cerebellum, 1866–1868, 1882, 1883 Spatial navigation, 810 Spatial orientation, 1697 Specification of cerebellar neurons, 84–89 Specificity, 271–272 Spetzler-Martin AVM grading, 759 Spike-timing dependent plasticity (STDP), 1505–1510, 1513 Spiking, 1252, 1256, 1257, 1262 Spinal atrophy, 784 Spinal cord, 2684, 2685 neurons, 580–583 Spinobulbar muscular atrophy (SBMA), 2497

Index Spinocerebellar ataxia (SCA), 391, 617, 784, 967, 1392, 1393, 1976, 2037, 2040, 2055, 2167, 2437–2438, 2496, 2609, 2641, 2643, 2648 autosomal dominant ataxia treatment, 2679–2680 autosomal recessive ataxia treatment, 2672–2678 clinical signs, 2509 genetic bases, 2497–2500 polyglutamine SCAs, 2503–2508 SCA10, 2522 SCA11, 2522–2523 SCA12, 2523 SCA1, 2511–2515 SCA13, 2523–2524 SCA14, 2524–2525 SCA15/SCA16, 2525–2526 SCA17, 2526–2527 SCA18, 2527 SCA19 and SCA22, 2527–2528 SCA20, 2528 SCA21, 2528 SCA2, 2515–2516 SCA23, 2528–2529 SCA25, 2529 SCA26, 2529 SCA27, 2530 SCA28, 2530, 2531 SCA29, 2531 SCA30, 2531–2532 SCA31, 2532–2533 SCA32, 2533 SCA3, 2516–2518 SCA35, 2533–2534 SCA36, 2534 SCA4, 2518 SCA5, 2518–2519 SCA6, 2519–2520 SCA7, 2520–2521 SCA8, 2521–2522 treatment, 2670–2672 type 1, 2619–2621 type 2, 2621–2622 type 31, 2627–2628 type 3, 2622–2625 type 7, 2626 type 8, 2627 Spinocerebellar ataxia type 13 (SCA13), 1405–1406, 1409 Spinocerebellar ataxia type 15 (SCA15), 1406–1407 Spinocerebellar ataxia type 18 (SCA18), 1409

Index Spinocerebellar ataxia type 19 (SCA19), 1407 Spinocerebellar ataxia type 28 (SCA28), 2583–2584 Spinocerebellar ataxia type 29 (SCA29), 1407 Spinocerebellar ataxia type 41 (SCA41), 1407–1408 Spinocerebellar ataxia type 42 (SCA42), 1408–1409 Spinocerebellar ataxia type 44 (SCA44), 1409 Spinocerebellar ataxia type 6 (SCA6), 1400, 1403–1405, 1862, 1863, 2625–2626 Spinocerebellum, 2022 Spinogenesis, 272 Spino-olivary fibers, 505–507 Spino-olivocerebellar climbing fiber paths (SOCPs), 523, 525 Spino-olivocerebellar pathways, 1291 Spontaneous cerebellar hemorrhage, 2243 Spontaneous postsynaptic currents, 1051 Sporadic adult onset ataxia (SAOA), 1862, 1863 of unknown aetiology, 2064 Sporadic disorders late cortical cerebellar atrophy, 2618 multiple system atrophy, 2616–2618 Staggerer, 270, 361 State estimation, 1490 behavioral evidence of, 1493–1494 and cerebellum, 1494–1497 Statins, 2377 Stellate cells, 86, 88, 89, 269, 273, 274, 882, 883, 887–890, 960, 1010, 1015, 1650, 1652, 1689, 1690 Sternberg working memory task, 816 Steroid(s), 355, 367, 368 Steroid receptor coactivator (SRC)-1, 361 Stress, 1711, 1713 responses, 365, 366 Stretch reflex, 1107 Stroke, 729, 1962 Structural abnormalities, 2450, 2456 Structural plasticity, 1266 Student t-tests, 1875 Subarachnoid hemorrhage (SAH), 763–764, 2342, 2348 Subdural hematoma, 2342 CT imaging, 2347, 2349 Submarginal strand, 1143 Suboccipital cerebellar surface, 452 Substrate reduction therapy, 2222 Subthalamic nucleus (STN), 694–696 Subthreshold oscillations (STO), 1196, 1198– 1200, 1204, 1208, 1209

2733 Subtraction analysis, 1868, 1869, 1871–1874 Superficial siderosis, 2356 of the CNS, 2356 Superior cerebellar artery (SCA), 458, 463, 464, 1860, 1863, 1870, 1961 infarction, 750–751 Superior cerebellar peduncles (SCP), 218 Superior colliculus, 596, 599, 600, 642, 643 Superior surface, 452 Supervised learning, 1392 Supplementary motor area (SMA), 669–674, 685 Swimming, 1659 Symmetrical bilateral T2 hyperintensities, 734 Symptomatic palatal tremor, 2355 Synapse(s), 1734, 1735, 1739, 1743, 1745–1748 elimination, 310, 316–318 specific, 1260, 1263 Synapse-associated proteins (SAP), 942–943 Synaptic nuclear envelope protein 1, 2472 Synaptic plasticity, 873, 992, 998 activity-dependent changes in membrane excitability, 894–895 activity-induced LTP and LTD, 889 decrease of functional postsynaptic AMPA receptor number, PF-PC synapses, 868–869 GABA release, 890–894 intracellular Ca2+ increase, involvement of, 867–868 kinase and phosphatase signaling pathways, 869–870 parallel fiber stimulation, AMPAR phenotype, 889 PF-LTD, 865 PF-LTP, 872 presynaptic receptors, PF-PC synapses, 870–871 short and long-term, 887 synaptic AMPA receptor expression, 889 transcription factors, protein synthesis, 871–872 Synaptic transmission, 992, 993, 997, 1710, 1716, 1717 Synaptic vesicles (SVs), 1033 Synaptogenesis, 271–273, 311, 1121–1126 Synchronization oscillations, 1201 of STOs, 1205 Synchrony, 1155, 1161, 1163, 1165 System theory, 1564

2734 T Tacrolimus, 2376 Tangential migration, 142, 151 Targetomes, 431 Taurine, 779 amino acids in cerebellar granule cells, 1100 GABA receptors, 1102 immunoreactivity, 1098 locomotor activity, 1102 mitochondrial dysfunction, 1100 neuromodulator role, 1098 prepulse inhibition, 1103 in somatostatin expression, 1105 stretch reflex, 1108 Tecto-olivary pathway, 540 Tectospinal tract, 642–643 Telencephalization process, 704 Telencephalon-cerebellar pathways, 1657 Teleost fish, 1648, 1652, 1656, 1659 Tensor network theory, 1562, 1563 cerebellar neural nets, 1565 of vestibulocollic reflex, 1574 Tentorial surface, 452 Testosterone, 367, 370 Test-retest reliability, 2035 Tet enzymes, 419 Thalamic nuclei, 662 Thalamus, 452 Thallium, 2388 Thanatophoric dysplasia, 226 Therapeutic strategies, 2681–2685 Theta, 1261 Theta burst stimulation (TBS), 614 4th ventricle roof plate, 68, 71–73, 75, 76 Thyroid hormone, 133 animal models, 361–365 effect on cerebellum, 357–361 molecular mechanisms, 356 response element, 356 Thyrotropin (TSH), 365 Thyroxine (T4), 356, 357, 359, 360, 365 Time-lapse recordings, 160 Timing, 1252, 1256, 1259–1263, 1266, 1340–1342, 1939 Tissue plasminogen activator (tPA), 1386 Tissue-type plasminogen activator (tPA), 153 Toluene derivatives, 2389 Tonic firing, 1265 Tonsil, 454 Torpedoes, 2451, 2452 Tottering, 1735, 1738, 1740, 1742, 1746, 1748

Index Tottering mouse (tg/tg) altered synaptic transmission, 1716–1717 behavioral phenotype, 1712–1714 low-frequency oscillations in, 1721–1723 as model of human calcium channelopathy, 1711–1712 morphological and histochemical alterations, 1714–1715 P/Q-type channel dysfunction in, 1715–1716 Purkinje cell dysfunction in, 1717–1719 upregulation of L-type Ca2+ channels in, 1719 Toxic-induced cerebellar syndrome (TOICS) alcohol, 2366–2371 aluminum, 2388 amiodarone, 2375 anticonvulsants (see Anticonvulsants) antineoplastics, 2373–2374 baptisia poisoning, 2395 bismuth, 2377 calcineurin inhibitors, 2376 carbon monoxide, 2391 causes, 2364 chemical weapons, 2391 copper, 2385–2386 cyanide, 2394–2395 dimethylamine borane, 2393 diphenoxylate-atropine, 2379 drug abuse and addiction (see Drug abuse and addiction) edible morels, 2393 Eucalytpus oil, 2393 gadolinium, 2386–2388 germanium, 2389 herbicides/insecticides/pesticides, 2392 hyperthermia, 2390 isoniazid, 2377 lead, 2383–2385 lindane, 2377 lithium salts, 2374–2375 manganese, 2385 mefloquine, 2377 mercury, 2382–2383 metronidazole, 2378 nicotine, 2379 procainamide, 2376 saxitoxin, 2393 scorpions, 2395 seasonal ataxia, 2394 statins, 2377 tacrolimus, 2376 thallium, 2388

Index toluene/benzene derivatives, 2389 uranium, 2389 vanadium, 2389 TRα, 362–365 TRβ, 364–365 Trace conditioning, 1260, 1261 Tracheostomy, 2145–2146 Tract-tracing studies, 799 Trailing process, 142, 148 Transcranial direct current stimulation (tDCS), 1469 Transcranial magnetic stimulation (TMS), 1361, 1363–1365, 1469, 1477, 1496, 2025 Transforming growth factors-β (TGFβ), 103 Transgenic mouse model, 786 Transglutaminase 2 antibodies, 2262 Transient receptor potential channel 3 (TRPC3), 1401, 1774–1776 Transmembrane AMPAR regulatory proteins (TARPs), 933 Transmitter release, 997 Transneuronal tracing, 638 Transoral odontoidectomy, 2145 Transsynaptic tracers, 682, 695 Transynaptic viral tracer studies, 799 Trauma, 1909, 1917 Traumatic cerebellar lesions, 2343 Traumatic vascular lesions, 2342 imaging, 2348–2350 Treadmill training, 2653 Trehalose, 2682 Tremor(s), 650, 1171, 1172, 1198, 1200, 1204, 1207, 2375, 2443–2445 TR gene knockout, 356, 362 Triangle of Guillain-Mollaret, 645 Tricarboxylic acid cycle, 2565 Trigeminal nerve, 458 Trigeminal nuclei, 507–508, 1158 Trigemino-olivary projection, 508 Trinucleotide repeat, 2055, 2066 TRPC3, 1407–1408 T-type calcium channel activation, 1200, 1259 Tuber, 454 Tuberous sclerosis complex mouse model of autism, 616 Type 1 cannabinoid receptor, 871 Tyrosine hydroxylase (TH), 1742, 1747 U UDP, 1048 Unc5c mutant mice, 219 Uncinate tract, 633

2735 Unconditioned stimulus (US), 1257, 1260, 1320–1322, 1325 Uncoupling proteins (UCPs), 2564 Unilateral cerebellar abnormalities, 2087 Unilateral cerebellar aplasia (UCA), 2118, 2119 Unilateral labyrinthectomy (UL), 485 Unipolar brush cells (UBCs), 69, 70, 73–75, 268, 275, 909, 961, 1652, 1777 Universal Cerebellar Impairment, 1979 Universal Cerebellar Transform (UCT), 1979 Unruptured posterior circulation aneurysms, 752 Unverricht-Lundborg disease, 2195 clinical manifestations, 2199 diagnosis, 2200 EEG characteristics, 2200 genetics, 2198 incidence, 2195 pathology, 2198 Upbeat nystagmus (UBN), 1817–1820 Upper rhombic lip (uRL), 16, 25, 29, 32–34, 36 Uranium, 2389 Urinary dysfunction, 2423 Urocortin, 1075 distribution in cerebellum, 1076–1080 functional role in cerebellum, 1087–1089 immunoreactivity, 1076 in situ hybridization for, 1078 UTP, 1048 Uvula, 454

V Vagus nerve activity [VNA], 1422 Valproate, 2221 Valproic acid, 2373 Valvula cerebelli, 1649, 1652, 1654, 1657 Vanadium, 2389 Velate astrocytes, 123, 130 Velocity storage time constant, 1813 Ventral anterior nucleus (VA), 663 Ventral funiculus olivocerebellar pathway (vfSOCP), 505, 506 Ventral lateral intraparietal area, 688 Ventral lateral nucleus anterior division (VLa), 664 Ventral lateral nucleus pars caudalis (VLc), 663–669, 671–676 Ventral lateral nucleus pars medialis (VLm), 663 Ventral lateral nucleus pars oralis (VLo), 663 Ventral posterior lateralis nucleus pars oralis (VPLo), 664–673, 675

2736 Ventral posterior lateral nucleus pars oralis (VPLo), 663 Ventral posterior lateral thalamus (VPL), 664 Ventral premotor area, 685 Ventral tegmental area, 608 Ventricular neuroepithelium, 175–177, 191 Ventricular zone (VZ), 25, 30, 33, 49, 84, 209 Ventrolateral outgrowth, 1143 Verbal fluency, 1352, 1947, 1966 Verbal short-term memory, 1976 Vermal lobules, 806 Vermis, 452, 609, 612–614, 616, 617, 783, 784, 789, 2114, 2116, 2127, 2128 Vertebral arteries (VAs), 740, 741 Vertebral artery dissection, 2344 Vertebrate neurogenesis, 28 Vertebrobasilar arterial system, 453 Vertebrobasilar (VB) aneurysms, 751 Vertebrobasilar artery junction, 455 Vertical nystagmus, 1817–1820 Very low density lipoprotein receptor (VLDLR), 51 Very preterm (VPT) birth long-term consequences of, 2102–2103 prevalence, 2097 Vesicular glutamate transporter (VGLUT2) expression, 57 Vestibular ataxia, 2056 Vestibular nuclear neurons, 1245 Vestibular nuclei (VN), 455, 1253, 1256, 1261, 1265, 1381, 1384 Vestibular ocular reflex (VOR), 982 Vestibulocerebellar functional connections abnormal cerebellar functions, 489, 490 cerebellar functions, 488, 489 cerebellar Purkinje cells, 474 climbing/mossy fiber circuity, 486, 487 CSs and SSs, 473, 475–477 golgi cells, UL, 484 granule/unipolar brush cells, 479 granule cells/unipolar brush cell, 476, 478 microlesion, β-nucleus, 480, 483 mossy/climbing fiber, 471 mossy fiber, 472, 474 SSs, climbing fiber, 487, 488 stellate/basket/Lugaro cells, 478, 480 stellate/golgi cell, 481 UL, 485, 486 unilateral electrolytic microlesions, 483 vermal lobules, 469, 470 vestibulo-cerebellum, 469 Vestibulocerebellum, 650, 2022

Index Vestibulolateral lobe, 1650, 1652, 1654 Vestibuloocular reflex (VOR), 1256, 1261, 1265, 1302–1306, 1309–1311, 1527, 1810, 1836 Vestibulospinal tracts, 638–640 Vigabatrin, 2372 Virus transport, 684–686, 688 Visceral functions, 610 Visual input, 596, 599–603 Visual spatial functions, 1980 Visual vermis, 533 Visuomotor adaptation, 1467, 1468, 2656, 2657 Visuospatial, 2122, 2127, 2128 Visuospatial learning, 1944 Vitamin C, 780 Vldlr, 51 Voltage-clamp, 1743, 1744, 1747 Voltage-dependent Ca2+ channels (VDCC), 437, 438 Voltage-gated Ca2+ channels, 1401, 1734, 1738 Voltage-gated potassium channel, 1401 KV1.1, 1410 KV3.3, 1405 KV4.3, 1407 Voltage-gated sodium channel, 1401 von Hippel–Lindau (VHL) disease, 2293, 2324 Voxel-based lesion-symptom mapping, 801 Voxel-based morphometry (VBM), 1877, 1880–1881, 2656 Voxel-wise statistical mapping, 1874–1877

W WAIS-R Block Design test, 1965 Walker Warburg syndrome, 2080 Walking aids, 2647, 2653 Wallenberg syndrome, 455 Wavelets, 1153, 1158 Weaver, 270 phenotype, 224 Wechsler Adult Intelligence Scale-Revised, 1941 Weight-catching task, 1897 Wernicke-Korsakoff syndrome, 2367, 2373 Wheat germ agglutinin-horseradish peroxidase (WGA-HRP), 561, 608 White matter compartments, 518, 519 Whole exome sequencing (WES), 2067 Whole genome sequencing (WGS), 2067 Wisconsin card sorting test, 810 Wnt1, 91, 1141 Wnt signaling, 25, 75–77

Index Wolfram disease, 2293 Word retrieval, 1947 Working memory, 1351, 1698, 1947, 1948 tasks, 811 Writing, 1948

X Xath1, 28 Xath5, 28 X-chromosomal transmission, 2604, 2610 Xenopus laevis, 28, 32, 1611 X-linked adrenoleukodystrophy (X-ALD), 2609 X-linked ataxia, 2065, 2067, 2604, 2605 due to GJB1 mutations, 2609 management, 2610 with ataxia as non-dominant feature, 2610 X-linked cerebellar ataxias, 2062–2063 X-linked pyruvate-dehydrogenase (PDH) deficiency, 2610

2737 X-linked sideroblastic anemia with ataxia (XLSA), 2583, 2608 XneuroD, 28 Z Zebrafish, 1651, 1655, 1660 adult neurogenesis, 1639–1640 afferents and efferents, 1630–1631 cerebellar anatomy and architecture, 1625– 1627 cerebellar cell layers, cell types and circuitry, 1627–1630 cerebellar germinal zones and progenitor domains, 1633–1635 cerebellar neurogenesis, 1637–1639 midbrain-hindbrain positioning, 1632–1633 Zebrin II+ stripes and II-stripes, 46 Zebrin II, 1277, 1653 Zic1, 30 Zipf’s law, 1575–1576 Ziprasidone, 2180