Neuroplasticity: From Bench to Bedside [1 ed.] 0128194103, 9780128194102

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NEUROPLASTICITY: FROM BENCH TO BEDSIDE

HANDBOOK OF CLINICAL NEUROLOGY Series Editors

MICHAEL J. AMINOFF, FRANÇOIS BOLLER, AND DICK F. SWAAB VOLUME 184

NEUROPLASTICITY: FROM BENCH TO BEDSIDE Series Editors

MICHAEL J. AMINOFF, FRANÇOIS BOLLER, AND DICK F. SWAAB

Volume Editors

ANGELO QUARTARONE, MARIA FELICE GHILARDI, AND FRANÇOIS BOLLER VOLUME 184 3rd Series

ELSEVIER Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2022 Elsevier B.V. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. With respect to any drug or pharmaceutical products identified, readers are advised to check the most current information provided (i) on procedures featured or (ii) by the manufacturer of each product to be administered, to verify the recommended dose or formula, the method and duration of administration, and contraindications. It is the responsibility of practitioners, relying on their own experience and knowledge of their patients, to make diagnoses, to determine dosages and the best treatment for each individual patient, and to take all appropriate safety precautions. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-819410-2 For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

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79, The human hypothalamus: basic and clinical aspects, Part I, D.F. Swaab, ed. ISBN 9780444513571 80, The human hypothalamus: basic and clinical aspects, Part II, D.F. Swaab, ed. ISBN 9780444514905 81, Pain, F. Cervero and T.S. Jensen, eds. ISBN 9780444519016 82, Motor neurone disorders and related diseases, A.A. Eisen and P.J. Shaw, eds. ISBN 9780444518941 83, Parkinson’s disease and related disorders, Part I, W.C. Koller and E. Melamed, eds. ISBN 9780444519009 84, Parkinson’s disease and related disorders, Part II, W.C. Koller and E. Melamed, eds. ISBN 9780444528933 85, HIV/AIDS and the nervous system, P. Portegies and J. Berger, eds. ISBN 9780444520104 86, Myopathies, F.L. Mastaglia and D. Hilton Jones, eds. ISBN 9780444518996 87, Malformations of the nervous system, H.B. Sarnat and P. Curatolo, eds. ISBN 9780444518965 88, Neuropsychology and behavioural neurology, G. Goldenberg and B.C. Miller, eds. ISBN 9780444518972 89, Dementias, C. Duyckaerts and I. Litvan, eds. ISBN 9780444518989 90, Disorders of consciousness, G.B. Young and E.F.M. Wijdicks, eds. ISBN 9780444518958 91, Neuromuscular junction disorders, A.G. Engel, ed. ISBN 9780444520081 92, Stroke – Part I: Basic and epidemiological aspects, M. Fisher, ed. ISBN 9780444520036 93, Stroke – Part II: Clinical manifestations and pathogenesis, M. Fisher, ed. ISBN 9780444520043 94, Stroke – Part III: Investigations and management, M. Fisher, ed. ISBN 9780444520050 95, History of neurology, S. Finger, F. Boller and K.L. Tyler, eds. ISBN 9780444520081 96, Bacterial infections of the central nervous system, K.L. Roos and A.R. Tunkel, eds. ISBN 9780444520159 97, Headache, G. Nappi and M.A. Moskowitz, eds. ISBN 9780444521392 98, Sleep disorders Part I, P. Montagna and S. Chokroverty, eds. ISBN 9780444520067 99, Sleep disorders Part II, P. Montagna and S. Chokroverty, eds. ISBN 9780444520074 100, Hyperkinetic movement disorders, W.J. Weiner and E. Tolosa, eds. ISBN 9780444520142 101, Muscular dystrophies, A. Amato and R.C. Griggs, eds. ISBN 9780080450315 102, Neuro-ophthalmology, C. Kennard and R.J. Leigh, eds. ISBN 9780444529039 103, Ataxic disorders, S.H. Subramony and A. Durr, eds. ISBN 9780444518927 104, Neuro-oncology Part I, W. Grisold and R. Sofietti, eds. ISBN 9780444521385 105, Neuro-oncology Part II, W. Grisold and R. Sofietti, eds. ISBN 9780444535023 106, Neurobiology of psychiatric disorders, T. Schlaepfer and C.B. Nemeroff, eds. ISBN 9780444520029 107, Epilepsy Part I, H. Stefan and W.H. Theodore, eds. ISBN 9780444528988 108, Epilepsy Part II, H. Stefan and W.H. Theodore, eds. ISBN 9780444528995 109, Spinal cord injury, J. Verhaagen and J.W. McDonald III, eds. ISBN 9780444521378 110, Neurological rehabilitation, M. Barnes and D.C. Good, eds. ISBN 9780444529015 111, Pediatric neurology Part I, O. Dulac, M. Lassonde and H.B. Sarnat, eds. ISBN 9780444528919 112, Pediatric neurology Part II, O. Dulac, M. Lassonde and H.B. Sarnat, eds. ISBN 9780444529107 113, Pediatric neurology Part III, O. Dulac, M. Lassonde and H.B. Sarnat, eds. ISBN 9780444595652 114, Neuroparasitology and tropical neurology, H.H. Garcia, H.B. Tanowitz and O.H. Del Brutto, eds. ISBN 9780444534903 115, Peripheral nerve disorders, G. Said and C. Krarup, eds. ISBN 9780444529022 116, Brain stimulation, A.M. Lozano and M. Hallett, eds. ISBN 9780444534972 117, Autonomic nervous system, R.M. Buijs and D.F. Swaab, eds. ISBN 9780444534910 118, Ethical and legal issues in neurology, J.L. Bernat and H.R. Beresford, eds. ISBN 9780444535016 119, Neurologic aspects of systemic disease Part I, J. Biller and J.M. Ferro, eds. ISBN 9780702040863 120, Neurologic aspects of systemic disease Part II, J. Biller and J.M. Ferro, eds. ISBN 9780702040870 121, Neurologic aspects of systemic disease Part III, J. Biller and J.M. Ferro, eds. ISBN 9780702040887 122, Multiple sclerosis and related disorders, D.S. Goodin, ed. ISBN 9780444520012 123, Neurovirology, A.C. Tselis and J. Booss, eds. ISBN 9780444534880 124, Clinical neuroendocrinology, E. Fliers, M. Korbonits and J.A. Romijn, eds. ISBN 9780444596024 125, Alcohol and the nervous system, E.V. Sullivan and A. Pfefferbaum, eds. ISBN 9780444626196 126, Diabetes and the nervous system, D.W. Zochodne and R.A. Malik, eds. ISBN 9780444534804 127, Traumatic brain injury Part I, J.H. Grafman and A.M. Salazar, eds. ISBN 9780444528926 128, Traumatic brain injury Part II, J.H. Grafman and A.M. Salazar, eds. ISBN 9780444635211

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Vol. 129, The human auditory system: Fundamental organization and clinical disorders, G.G. Celesia and G. Hickok, eds. ISBN 9780444626301 Vol. 130, Neurology of sexual and bladder disorders, D.B. Vodušek and F. Boller, eds. ISBN 9780444632470 Vol. 131, Occupational neurology, M. Lotti and M.L. Bleecker, eds. ISBN 9780444626271 Vol. 132, Neurocutaneous syndromes, M.P. Islam and E.S. Roach, eds. ISBN 9780444627025 Vol. 133, Autoimmune neurology, S.J. Pittock and A. Vincent, eds. ISBN 9780444634320 Vol. 134, Gliomas, M.S. Berger and M. Weller, eds. ISBN 9780128029978 Vol. 135, Neuroimaging Part I, J.C. Masdeu and R.G. González, eds. ISBN 9780444534859 Vol. 136, Neuroimaging Part II, J.C. Masdeu and R.G. González, eds. ISBN 9780444534866 Vol. 137, Neuro-otology, J.M. Furman and T. Lempert, eds. ISBN 9780444634375 Vol. 138, Neuroepidemiology, C. Rosano, M.A. Ikram and M. Ganguli, eds. ISBN 9780128029732 Vol. 139, Functional neurologic disorders, M. Hallett, J. Stone and A. Carson, eds. ISBN 9780128017722 Vol. 140, Critical care neurology Part I, E.F.M. Wijdicks and A.H. Kramer, eds. ISBN 9780444636003 Vol. 141, Critical care neurology Part II, E.F.M. Wijdicks and A.H. Kramer, eds. ISBN 9780444635990 Vol. 142, Wilson disease, A. Członkowska and M.L. Schilsky, eds. ISBN 9780444636003 Vol. 143, Arteriovenous and cavernous malformations, R.F. Spetzler, K. Moon and R.O. Almefty, eds. ISBN 9780444636409 Vol. 144, Huntington disease, A.S. Feigin and K.E. Anderson, eds. ISBN 9780128018934 Vol. 145, Neuropathology, G.G. Kovacs and I. Alafuzoff, eds. ISBN 9780128023952 Vol. 146, Cerebrospinal fluid in neurologic disorders, F. Deisenhammer, C.E. Teunissen and H. Tumani, eds. ISBN 9780128042793 Vol. 147, Neurogenetics Part I, D.H. Geschwind, H.L. Paulson and C. Klein, eds. ISBN 9780444632333 Vol. 148, Neurogenetics Part II, D.H. Geschwind, H.L. Paulson and C. Klein, eds. ISBN 9780444640765 Vol. 149, Metastatic diseases of the nervous system, D. Schiff and M.J. van den Bent, eds. ISBN 9780128111611 Vol. 150, Brain banking in neurologic and psychiatric diseases, I. Huitinga and M.J. Webster, eds. ISBN 9780444636393 Vol. 151, The parietal lobe, G. Vallar and H.B. Coslett, eds. ISBN 9780444636225 Vol. 152, The neurology of HIV infection, B.J. Brew, ed. ISBN 9780444638496 Vol. 153, Human prion diseases, M. Pocchiari and J.C. Manson, eds. ISBN 9780444639455 Vol. 154, The cerebellum: From embryology to diagnostic investigations, M. Manto and T.A.G.M. Huisman, eds. ISBN 9780444639561 Vol. 155, The cerebellum: Disorders and treatment, M. Manto and T.A.G.M. Huisman, eds. ISBN 9780444641892 Vol. 156, Thermoregulation: From basic neuroscience to clinical neurology Part I, A.A. Romanovsky, ed. ISBN 9780444639127 Vol. 157, Thermoregulation: From basic neuroscience to clinical neurology Part II, A.A. Romanovsky, ed. ISBN 9780444640741 Vol. 158, Sports neurology, B. Hainline and R.A. Stern, eds. ISBN 9780444639547 Vol. 159, Balance, gait, and falls, B.L. Day and S.R. Lord, eds. ISBN 9780444639165 Vol. 160, Clinical neurophysiology: Basis and technical aspects, K.H. Levin and P. Chauvel, eds. ISBN 9780444640321 Vol. 161, Clinical neurophysiology: Diseases and disorders, K.H. Levin and P. Chauvel, eds. ISBN 9780444641427 Vol. 162, Neonatal neurology, L.S. De Vries and H.C. Glass, eds. ISBN 9780444640291 Vol. 163, The frontal lobes, M. D’Esposito and J.H. Grafman, eds. ISBN 9780128042816 Vol. 164, Smell and taste, Richard L. Doty, ed. ISBN 9780444638557 Vol. 165, Psychopharmacology of neurologic disease, V.I. Reus and D. Lindqvist, eds. ISBN 9780444640123 Vol. 166, Cingulate cortex, B.A. Vogt, ed. ISBN 9780444641960 Vol. 167, Geriatric neurology, S.T. DeKosky and S. Asthana, eds. ISBN 9780128047668 Vol. 168, Brain-computer interfaces, N.F. Ramsey and J. del R. Millán, eds. ISBN 9780444639349 Vol. 169, Meningiomas, Part I, M.W. McDermott, ed. ISBN 9780128042809 Vol. 170, Meningiomas, Part II, M.W. McDermott, ed. ISBN 9780128221983 Vol. 171, Neurology and pregnancy: Pathophysiology and patient care, E.A.P. Steegers, M.J. Cipolla and E.C. Miller, eds. ISBN 9780444642394 Vol. 172, Neurology and pregnancy: Neuro-obstetric disorders, E.A.P. Steegers, M.J. Cipolla and E.C. Miller, eds. ISBN 9780444642400 Vol. 173, Neurocognitive development: Normative development, A. Gallagher, C. Bulteau, D. Cohen and J.L. Michaud, eds. ISBN 9780444641502 Vol. 174, Neurocognitive development: Disorders and disabilities, A. Gallagher, C. Bulteau, D. Cohen and J.L. Michaud, eds. ISBN 9780444641489 Vol. 175, Sex differences in neurology and psychiatry, R. Lanzenberger, G.S. Kranz, and I. Savic, eds. ISBN 9780444641236 Vol. 176, Interventional neuroradiology, S.W. Hetts and D.L. Cooke, eds. ISBN 9780444640345 Vol. 177, Heart and neurologic disease, J. Biller, ed. ISBN 9780128198148 Vol. 178, Neurology of vision and visual disorders, J.J.S. Barton and A. Leff, eds. ISBN 9780128213773 Vol. 179, The human hypothalamus: Anterior region, D.F. Swaab, F. Kreier, P.J. Lucassen, A. Salehi and R.M. Buijs, eds. ISBN 9780128199756

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Vol. 180, The human hypothalamus: Middle and posterior region, D.F. Swaab, F. Kreier, P.J. Lucassen, A. Salehi and R.M. Buijs, eds. ISBN 9780128201077 Vol. 181, The human hypothalamus: Neuroendocrine disorders, D.F. Swaab, R.M. Buijs, P.J. Lucassen, A. Salehi and F. Kreier, eds. ISBN 9780128206836 Vol. 182, The human hypothalamus: Neuropsychiatric disorders, D.F. Swaab, R.M. Buijs, F. Kreier, P.J. Lucassen, and A. Salehi, eds. ISBN 9780128199732 Vol. 183, Disorders of emotion in neurologic disease, K.M. Heilman and S.E. Nadeau, eds. ISBN 9780128222904 All volumes in the 3rd Series of the Handbook of Clinical Neurology are published electronically, on Science Direct: http://www.sciencedirect.com/science/handbooks/00729752.

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Foreword

We are delighted to introduce the first volume in the Handbook of Clinical Neurology series to be devoted entirely to neuroplasticity. Neuroplasticity is the capacity of neural circuits or networks to change through growth and reorganization, for instance as a result of learning, environmental influences, practice, or psychologic stress. In development, the mechanisms involved are neurogenesis, neuronal migration and differentiation, the formation of connections, and systemwide modifications of brain structures. By these means, the brain achieves novel functions, such as ocular dominance or language acquisition. Plasticity of the brain during development is not a new concept. In 1793, the Italian anatomist Michele Vicenzo Malacarne trained animals extensively for years and discovered that the cerebellum of the trained animals was substantially larger than that of the untrained animals. In addition, Darwin described in 1871 that the brains of hares and rabbits that grew up confined in boring hutches were 15%–30% smaller than those of their wild counterparts. Later it was shown that, when animals are placed in an “enriched environment,” a large enclosure full of objects that are renewed each day and in which they can play with one another, their brains grow and develop more synapses. Children who are seriously neglected during their early development may have smaller brains; their intelligence and linguistic and fine motor control may be impaired permanently, and they may be impulsive and hyperactive. Their prefrontal cortices can be particularly undersized. However, neuroplasticity was once thought by neuroscientists to manifest only during childhood. Santiago Ramón y Cajal (1852–1934) wrote: “Once development is completed, the sources of growth and regeneration of axons and dendrites are irrevocably lost. In the adult brain, nervous pathways are fixed and immutable; everything may die, nothing may be regenerated. It is for the science of the future to change, if possible, this harsh decree.” However, later Cajal described regenerative processes after lesions. Research has shown now that the brain rewires also during maturation and aging. Activity-dependent synaptic plasticity maintains the lifelong basis for our learning ability and memory capacity, allowing us to acquire a wide range of skills, from motor actions to complex abstract reasoning. In several brain areas, human neurogenesis occurs even during adulthood. However, plasticity in the adult human brain is certainly much more restricted than during development, being mainly expressed as changes in the strength of excitatory and inhibitory synapses. Attempts to regenerate connections during adulthood have met with limited success. It is therefore of special interest that the main topic of this new volume of the Handbook of Clinical Neurology deals with noninvasive protocols to probe synaptic plasticity in the cortex in order to treat brain disorders that occur especially in the elderly. Stimulation is performed, for instance, by different protocols of repetitive transcranial magnetic stimulation, anodal transcranial direct current stimulation, and transcranial alternating current stimulation. Stimulation can induce short- and long-term changes of synaptic excitability, which are promising tools for enhancing recovery in patients with brain disorders. In addition, the brain–machine interface is a promising therapeutic avenue for the treatment of many neurologic conditions. Emerging evidence suggests a greater efficacy with fewer adverse effects during adaptive deep brain stimulation compared to conventional deep brain stimulation. Neuroplasticity phenomena by the various stimulation techniques have been induced, for instance, in Parkinson’s disease, Alzheimer’s disease, stroke, spinal cord injury, and disorders of consciousness. Importantly, it appears that poststroke visual plasticity is dynamic, with a critical window of opportunity early on to attain more rapid and extensive recovery of a larger set of visual perceptual abilities. Such stimulation procedures are now being applied in psychiatry. The proven brain stimulation methods for treating depression cause plastic changes and include acute and maintenance electroconvulsive therapy, acute and maintenance transcranial magnetic stimulation, and chronically implanted vagus nerve stimulation. The effects of stimulation are followed by clinical measures, magnetic resonance imaging or spectroscopy, positron emission spectroscopy with fluorodeoxyglucose, or electroencephalography.

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It should be noted that the outcomes of neuroplasticity are not necessarily adaptive. They can also cause pathologic processes, as is discussed for various forms of dystonia that are thought to be due to maladaptive plasticity in nonmotor basal ganglia circuits. We were very fortunate to have as editors for this volume Angelo Quartarone from the Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy; Maria Felice Ghilardi from the Department of Molecular, Cellular, and Biomedical Sciences, City University of New York School of Medicine and Neuroscience Program, Graduate Center of the City University of New York, New York, NY, United States; and Franc¸ois Boller from the Department of Neurology, George Washington University Medical School, Washington, DC, United States. They have assembled an excellent, international, and multidisciplinary group of scientists and clinicians for this comprehensive volume. We are very grateful to the volume editors and to all the contributors for their efforts. We are confident that clinicians in various disciplines, as well as neuroscientists, will find much in these volumes to appeal to them. In addition to the print-on-demand version, the volume will also be available electronically on Elsevier’s ScienceDirect website, which is popular with readers and will facilitate the book’s accessibility. Indeed, all the volumes in the present series of the Handbook of Clinical Neurology are available electronically on this website. As always, it is a pleasure to thank Elsevier (our publisher) and in particular Michael Parkinson in Scotland, Nikki Levy and Kristi Anderson in San Diego, and Punithavathy Govindaradjane at Elsevier Global Book Production in Chennai, for their unfailing and expert assistance in the development and production of this volume. Michael J. Aminoff Dick F. Swaab

Preface

We now know that the brain’s landscape is continuously changing, with new synapses forming or increasing in size and other ones disappearing or reducing in size. Importantly, these morphologic variations in the brain are accompanied by performance changes. This capacity of our brain to change has been defined by the word “plasticity,” derived from the Greek “plasτikοs” meaning “moldable.” We are also starting to understand that experience, sleep, and age regulate plasticity-related processes, while injuries, inflammatory processes, deposition of abnormal proteins, and stress-related factors may alter this equilibrium by reducing “good” plasticity or by inducing “bad” plasticity and eventually leading to functional and morphologic alterations at the brain circuits level as well as to the emergence of behavioral dysfunctions and performance abnormalities. The acknowledgment of the importance of plasticity in neurologic and psychiatric disease is, however, a very recent acquisition, although rooted in the work of Cajal more than 100 years ago, along with other pioneers. Indeed, in contrast to the idea that the neurons were static, supported by Golgi in 1898, Cajal supported the notion that, based on his investigations on evolution, development, and trauma, neurons were dynamic, plastic entities capable of growing and shrinking depending upon environmental factors. He reasoned that neural expansions and retractions were part of the plasticity-related phenomena needed to maintain homeostasis. He also hypothesized that neuronal plasticity played a significant role in memory formation, learning, sleep, and mental disorders. Most interestingly, based on his observation of lizards during hibernation, Cajal postulated that during sleep there was neuronal disconnection and, in that period, neuronal retraction occurred with the dendrites of pyramidal cells shrinking. These concepts were then developed by the experimental work of one of his pupils, Lorente de No, that linked memory formation to increased synaptic strength, an idea further expanded by the theoretic model of Hebb in 1949 proposing that synaptic modification needed for learning and memory occurred as a consequence of coincidence between pre- and post-synaptic activity. Nevertheless, the first experimental evidence of synaptic plasticity in the mammalian brain was provided, independently of Hebb’s theory, first by Lomo in 1966 and then by Bliss and Lomo in 1973 with the discovery of long-term potentiation (LTP). Briefly, high-frequency or tetanic stimulation of hippocampal excitatory synapses in the rabbit’s brain induced a long-lasting increase in the synapses’ strength, an increase that persisted for days. Since then, LTP, which likely provides the most important base for learning and memory processes, has been described for synapses throughout the brain in different animal species. For obvious reasons, LTP recordings in humans obtained with the same protocols used in animal models have been very limited. In an interesting paper by Chen and colleagues in 1996, LTP was elicited with tetanic stimulation in hippocampal tissue from individuals undergoing surgery as a treatment for intractable temporal lobe epilepsy. The degree of LTP induced was rather modest because of ceiling effects, as synapses in epileptic tissue are already potentiated by epileptic activity and are near to saturation. It is now possible to deliver high-frequency or tetanic transcranial magnetic stimulation (TMS) in awake, intact human subjects, translating the protocols used in animal studies for LTP or its opposite, long-term depression (LTD). Another approach to induce LTP or LTD in human subjects is the paired associative stimulation paradigms in which electric stimulation of peripheral nerves is coupled with TMS applied over the contralateral sensory-motor cortex. These techniques are relatively safe and are now widely used in many neurophysiology laboratories around the world. Since the hippocampus and surrounding structures are relatively deep and do not have well-defined behavioral output, the majority of these experimental paradigms focus on the motor cortex so that electromyographic responses can be used as a reliable readout. Besides TMS, other techniques can now be used to evaluate the capacity for functional and structural plasticity at the system level such as high-density electroencephalography, functional magnetic resonance imaging (MRI), and diffusion MRI. In this volume, we provide overviews on the evaluation of plasticity-related phenomena at synaptic and at the system level based on these and other techniques in physiologic conditions as well as in several neurologic and psychiatric

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disorders in both patients and animal models. This evaluation is crucial, as it can provide useful and new information as well as innovative ways to redefine causes, characteristics, consequences, and approaches to neurologic and psychiatric conditions. Importantly, new nosological classifications based on plasticity-related changes could enhance our ability to reshape damaged brain circuits, exploiting procedures that promote and guide “good” plasticity processes. Another important aim of this volume is to discuss the conceptual and experimental bases for the utilization of invasive and noninvasive neuromodulation techniques but also of aerobic exercise and sleep as novel therapeutic tools to harness and increase plasticity in neurologic and psychiatric conditions. These approaches singly or in combination may enhance the effects of rehabilitation or other interventions to rewire the brain and spinal cord circuits and partially or completely restore functions. Indeed, the aim of this volume is to foster debate and promote research with innovative techniques for understanding brain function. Most interestingly, some chapters discuss reasons for incorporating into diagnosis and care the growing evidence that plasticity may be a key to unravel the puzzles of neuropsychiatric conditions. Finally, we dedicate this volume to all our colleagues and the investigators who have devoted their work to this research field. In particular, we dedicate this volume to Giorgio Innocenti, the author of the opening chapter, a neuroanatomist and neurophysiologist who devoted his efforts to study the organization, development, and plasticity of the cerebral cortex and interhemispheric interactions in animals and humans, and who left us prematurely a few months ago. Angelo Quartarone and Maria Felice Ghilardi wish to acknowledge the support of the DOD grant number: W81XWH-19-1-0810 for the editing of this book. Angelo Quartarone Maria Felice Ghilardi Franc¸ois Boller

Contributors

M. Adzic Department of Molecular Biology and Endocrinology, Vinca Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia D. Agalliu Departments of Pathology and Neurology, Columbia University Irving Medical Center, New York, NY, United States M. Ajčević Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital; Department of Engineering and Architecture, University of Trieste, Trieste, Italy M. Alegre Clinical Neurophysiology Section, Clínica Universidad de Navarra; Systems Neuroscience Lab, Program of Neuroscience, CIMA, Universidad de Navarra; IdisNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain F. Asci IRCCS Neuromed Institute, Pozzilli (IS), Italy G. Avvenuti MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy S. Bagnato Unit of Neurophysiology and Unit for Severe Acquired Brain Injuries, Rehabilitation Department, Giuseppe Giglio Foundation, Cefalù (PA), Italy

A. Bhattacharya Department of Neurology, National Institute of Mental Health & Neurosciences, Bengaluru, India F. Blandini Department of Brain and Behavioral Sciences, University of Pavia; Movement Disorders Research Center, IRCCS Mondino Foundation, Pavia, Italy F. Boller Department of Neurology, George Washington University Medical School, Washington, DC, United States F. Bove UOC Neurologia, Fondazione Policlinico Universitario Agostino Gemelli IRCCS; Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Rome, Italy A. Buoite Stella Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, Trieste, Italy A. Busza Department of Neurology, University of Rochester, Rochester, NY, United States P. Calabresi Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore; UOC Neurologia, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy

G. Bernardi MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy

F. Capone Neurology, Neurophysiology and Neurobiology Unit, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy

S. Bhardwaj Department of Neurology, National Institute of Mental Health & Neurosciences, Bengaluru, India

K.A. Caulfield Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States

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CONTRIBUTORS

D. Centonze Unit of Neurology & Neurorehabilitation, IRCCS Neuromed, Pozzilli; Laboratory of Synaptic Immunopathology, Department of Systems Medicine, Tor Vergata University, Rome, Italy R. Chen Division of Neurology, Department of Medicine, University of Toronto; Division of Brain, Imaging and Behavior, The Edmond J. Safra Program in Parkinson's Disease, Krembil Research Institute, Toronto, ON, Canada L. Christiansen Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark L.G. Cohen Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States G. Cosentino Translational Neurophysiology Research Unit, IRCCS Mondino Foundation; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy M. Cotelli Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy A. de Iure IRCCS San Raffaele Roma, Laboratory of Experimental Neurophysiology, Rome, Italy

I. El Atiallah Department of Systems Medicine, University of Rome 2 Tor Vergata, Rome, Italy D. Ferrazzoli Department of Neurorehabilitation, Hospital of Vipiteno (SABES-ASDAA), Vipiteno-Sterzing; Department of Parkinson's Disease, Fresco Parkinson Center, Movement Disorders and Brain Injury Rehabilitation, “Moriggia-Pelascini” Hospital—Gravedona ed Uniti, Como, Italy R. Ferri Sleep Research Centre, Oasi Research Institute – IRCCS, Troina, Italy M. Feurra Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation G. Foffani HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales; CIBERNED, Instituto de Salud Carlos III, Madrid; Neural Bioengineering, Hospital Nacional de Parapl
ejicos, SESCAM, Toledo, Spain F. Gardoni Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy F. Garretti Department of Pathology, Columbia University Irving Medical Center, New York, NY, United States

L.M. DelRosso Department of Pediatrics, Seattle Children's Hospital, Seattle, WA, United States

M.S. George Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States

R. Di Iorio Neurology Unit, Policlinico Agostino Gemelli IRCCS, Rome, Italy

V. Ghiglieri San Raffaele University, Rome, Italy

V. Di Lazzaro Neurology, Neurophysiology and Neurobiology Unit, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy M. Di Luca Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy

M.F. Ghilardi Department of Molecular, Cellular, and Biomedical Sciences, City University of New York School of Medicine and Neuroscience Program, Graduate Center of the City University of New York, New York, NY, United States A. Guerra IRCCS Neuromed Institute, Pozzilli (IS), Italy

CONTRIBUTORS K.R. Huxlin Flaum Eye Institute, University of Rochester, Rochester, NY, United States R. Iansek Clinical Research Centre for Movement Disorders and Gait, National Parkinson Foundation Center of Excellence, Monash Health, Cheltenham; School of Clinical Sciences, Monash University, Clayton, VIC, Australia E. Iezzi Unit of Neurology & Neurorehabilitation, IRCCS Neuromed, Pozzilli, Italy G.M. Innocenti† Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden F. Iodice Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy I.U. Isaias Department of Neurology, University Hospital W€ urzburg and Julius Maximilian University W€ urzburg, W€ urzburg, Germany S. Ivkovic Department of Molecular Biology and Endocrinology, Vinca Institute of Nuclear Sciences, National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia B.P. Johnson Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States W.T Ketchabaw Department of Neurology, Center for Brain Plasticity and Recovery, Georgetown University Medical Center, Washington, DC, United States J.H. Ko Department of Human Anatomy and Cell Science, University of Manitoba; Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada †

Deceased

xv

G. Koch Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara; Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy A.A. K€ uhn Department of Neurology, Movement disorders and Neuromodulation Unit, Charit
e—Universit€atsmedizin Berlin, Berlin, Germany K. Laaksonen Department of Neurology, Helsinki University Hospital, and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland G. Lanza Department of Surgery and Medical-Surgical Specialties, University of Catania, Catania; Sleep Research Centre, Oasi Research Institute – IRCCS, Troina, Italy R. Lofredi Department of Neurology, Movement disorders and Neuromodulation Unit, Charit
e—Universit€atsmedizin Berlin, Berlin, Germany A. Mancini Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy P. Manganotti Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital, University of Trieste, Trieste, Italy E. Marcello Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy G. Marino Dipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Rome; Dipartimento di Medicina, Università degli Studi di Perugia, Perugia, Italy J.H. Martin Department of Molecular, Cellular, and Biomedical Sciences, Center for Discovery and Innovation, City University of New York School of Medicine; Neuroscience Program, Graduate Center of the City University of New York, New York, NY, United States

xvi

CONTRIBUTORS

K.C. Martin Department of Neurology, Center for Brain Plasticity and Recovery, Georgetown University Medical Center, Washington, DC, United States

A. Quartarone Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy

F. Miraglia Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy

J. Radulovic Department of Neuroscience; Department of Psychiatry and Behavioral Sciences, Albert Einstein Medical College, Bronx, NY, United States

C. Monahan Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States

S. Rossi Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy

M. Montanari Department of Systems Medicine, University of Rome 2 Tor Vergata, Rome, Italy F. Motolese Neurology, Neurophysiology and Neurobiology Unit, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy

P.M. Rossini Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome, Italy E.L. Saionz Medical Scientist Training Program, University of Rochester, Rochester, NY, United States

P. Ortelli Department of Neurorehabilitation, Hospital of Vipiteno (SABES-ASDAA), Vipiteno-Sterzing; Department of Parkinson’s Disease, Fresco Parkinson Center, Movement Disorders and Brain Injury Rehabilitation, “Moriggia-Pelascini” Hospital—Gravedona ed Uniti, Como, Italy

E. Santarnecchi Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy; Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States

P.K. Pal Department of Neurology, National Institute of Mental Health & Neurosciences, Bengaluru, India

G. Sciamanna Laboratory of Neurophysiology and Plasticity, IRCCS Fondazione Santa Lucia, Rome, Italy

S. Pelucchi Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy

A. Sette Center for Autoimmunity and Inflammation, La Jolla Institute for Immunology, La Jolla, CA, United States

B. Picconi IRCCS San Raffaele Roma, Laboratory of Experimental Neurophysiology; University San Raffaele, Rome, Italy

H.R. Siebner Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre; Department of Neurology, Copenhagen University Hospital Bispebjerg; Department of Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark

A. Pisani Department of Brain and Behavioral Sciences, University of Pavia; Movement Disorders Research Center, IRCCS Mondino Foundation, Pavia, Italy N.G. Pozzi Department of Neurology, University Hospital W€ urzburg and Julius Maximilian University W€ urzburg, W€urzburg, Germany

D. Spampinato Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy

CONTRIBUTORS M. Stampanoni Bassi Unit of Neurology & Neurorehabilitation, IRCCS Neuromed, Pozzilli, Italy A.P. Strafella The Edmond J. Safra Program in Parkinson’s Disease, Neurology Division, Department of Medicine, Toronto Western Hospital & Krembil Brain Institute, University Health Network; Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada D. Sulzer Departments of Pathology, Psychiatry, and Pharmacology, Columbia University Irving Medical Center; Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, United States A. Suppa Department of Human Neurosciences, Sapienza University of Rome, Rome; IRCCS Neuromed Institute, Pozzilli (IS), Italy M. Todisco Translational Neurophysiology Research Unit, IRCCS Mondino Foundation; Department of Brain and Behavioral Sciences, University of Pavia; Movement Disorders Research Center, IRCCS Mondino Foundation, Pavia, Italy

xvii

P.E. Turkeltaub Department of Neurology, Center for Brain Plasticity and Recovery, Georgetown University Medical Center; Research Division, MedStar National Rehabilitation Hospital, Washington, DC, United States K. Udupa Department of Neurophysiology, National Institute of Mental Health & Neurosciences, Bengaluru, India F. Vecchio Brain Connectivity Laboratory, Department of Neuroscience & Neurorehabilitation, IRCCS San Raffaele Roma, Rome; Department of Technical and Applied Sciences, eCampus University, Novedrate (Como), Italy D. Volpe Department of Rehabilitation, Fresco Parkinson Center, Villa Margherita, S. Stefano Riabilitazione, Vicenza, Italy N.S. Ward Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology; Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom M. Wiley Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States

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Contents Foreword ix Preface xi Contributors xiii Section I 1.

Introduction

Defining neuroplasticity G.M. Innocenti† (Stockholm, Sweden)

Section II

3

Neuroplasticity: Basic mechanism and assessment at system level

2.

Basic mechanisms of plasticity and learning A. Mancini, A. de Iure, and B. Picconi (Perugia and Rome, Italy)

21

3.

Local sleep: A new concept in brain plasticity G. Avvenuti and G. Bernardi (Lucca, Italy)

35

4.

Sleep and homeostatic control of plasticity G. Lanza, L.M. DelRosso, and R. Ferri (Catania and Troina, Italy and Seattle, United States)

53

5.

Transcranial magnetic stimulation as a tool to induce and explore plasticity in humans A. Suppa, F. Asci, and A. Guerra (Rome and Pozzilli (IS), Italy)

73

6.

EEG as a marker of brain plasticity in clinical applications P. Manganotti, M. Aj
cevic, and A. Buoite Stella (Trieste, Italy)

91

7.

Tools to explore neuroplasticity in humans: Combining interventional neurophysiology with functional and structural magnetic resonance imaging and spectroscopy L. Christiansen and H.R. Siebner (Hvidovre and Copenhagen, Denmark)

8.

Metabolic imaging and plasticity J.H. Ko and A.P. Strafella (Winnipeg and Toronto, Canada)

Section III 9.

105

121

Neuroplasticity in movement disorders

Parkinson's disease: Alterations of motor plasticity and motor learning 135 K. Udupa, A. Bhattacharya, S. Bhardwaj, P.K. Pal, and R. Chen (Bengaluru, India and Toronto, Canada)

10. Alpha-synuclein and cortico-striatal plasticity in animal models of Parkinson disease G. Marino, P. Calabresi, and V. Ghiglieri (Rome and Perugia, Italy)

153

11. Plasticity, genetics, and epigenetics in L-dopa-induced dyskinesias F. Bove and P. Calabresi (Rome, Italy)

167

†

Deceased

xx

CONTENTS

12. Noninvasive neuromodulation in Parkinson's disease: Neuroplasticity implication and therapeutic perspectives G. Cosentino, M. Todisco, and F. Blandini (Pavia, Italy)

185

13. Plasticity, genetics and epigenetics in dystonia: An update G. Sciamanna, I. El Atiallah, M. Montanari, and A. Pisani (Rome and Pavia, Italy)

199

14. Neuroplasticity in dystonia: Motor symptoms and beyond A. Quartarone and M.F. Ghilardi (Messina, Italy and New York, United States)

207

Section IV

Brain oscillations in neurological disorders

15. General principles of brain electromagnetic rhythmic oscillations and implications for neuroplasticity 221 P.M. Rossini, F. Miraglia, F. Vecchio, R. Di Iorio, F. Iodice, and M. Cotelli (Rome, Novedrate (Como) and Brescia, Italy) 16. Noninvasive brain stimulation and brain oscillations S. Rossi, E. Santarnecchi, and M. Feurra (Siena, Italy, Boston, United States and Moscow, Russian Federation)

239

17. Brain oscillatory dysfunctions in dystonia R. Lofredi and A.A. K€ uhn (Berlin, Germany)

249

18. Brain oscillations and Parkinson disease G. Foffani and M. Alegre (Madrid, Toledo, and Pamplona, Spain)

259

19. Adaptive deep brain stimulation: Retuning Parkinson's disease N.G. Pozzi and I.U. Isaias (W€ urzburg, Germany)

273

Section V

Plasticity and rehabilitation

20. Biomarkers of plasticity for stroke recovery K. Laaksonen and N.S. Ward (Helsinki, Finland and London, United Kingdom)

287

21. New tools for shaping plasticity to enhance recovery after stroke F. Motolese, F. Capone, and V. Di Lazzaro (Rome, Italy)

299

22. Neuroplasticity of spinal cord injury and repair J.H. Martin (New York, United States)

317

23. Reward and plasticity: Implications for neurorehabilitation B.P. Johnson and L.G. Cohen (Bethesda, United States)

331

24. Rehabilitation in movement disorders: From basic mechanisms to clinical strategies D. Ferrazzoli, P. Ortelli, R. Iansek, and D. Volpe (Vipiteno-Sterzing, Como and Vicenza, Italy and Cheltenham and Clayton, Australia)

341

25. Rehabilitation of visual perception in cortical blindness E.L. Saionz, A. Busza, and K.R. Huxlin (Rochester, United States)

357

26. The role of plasticity in the recovery of consciousness S. Bagnato (Cefalù (PA), Italy)

375

CONTENTS 27. Plasticity of the language system in children and adults K.C. Martin, W.T. Ketchabaw, and P.E. Turkeltaub (Washington, United States) Section VI

xxi 397

Inflammation, autoimmunity, and plasticity

28. Synaptic dysfunction in early phases of Alzheimer's Disease S. Pelucchi, F. Gardoni, M. Di Luca, and E. Marcello (Milan, Italy)

417

29. T cells, a-synuclein and Parkinson disease F. Garretti, C. Monahan, A. Sette, D. Agalliu, and D. Sulzer (New York and La Jolla, United States)

439

30. Multiple sclerosis: Inflammation, autoimmunity and plasticity M. Stampanoni Bassi, E. Iezzi, and D. Centonze (Pozzilli and Rome, Italy)

457

Section VII

Plasticity in cognitive and psychiatric disorders

31. Alzheimer disease and neuroplasticity G. Koch and D. Spampinato (Ferrara and Rome, Italy)

473

32. From chronic stress and anxiety to neurodegeneration: Focus on neuromodulation of the axon initial segment 481 J. Radulovic, S. Ivkovic, and M. Adzic (Bronx, United States and Belgrade, Serbia) 33. Shaping plasticity with non-invasive brain stimulation in the treatment of psychiatric disorders: Present and future M.S. George, K.A. Caulfield, and M. Wiley (Charleston, United States)

497

Index

509

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Section I Introduction

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Handbook of Clinical Neurology, Vol. 184 (3rd series) Neuroplasticity: From Bench to Bedside A. Quartarone, M.F. Ghilardi, and F. Boller, Editors https://doi.org/10.1016/B978-0-12-819410-2.00001-1 Copyright © 2022 Elsevier B.V. All rights reserved

Chapter 1

Defining neuroplasticity GIORGIO M. INNOCENTI*,† Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden

Abstract Neuroplasticity, i.e., the modifiability of the brain, is different in development and adulthood. The first includes changes in: (i) neurogenesis and control of neuron number; (ii) neuronal migration; (iii) differentiation of the somato-dendritic and axonal phenotypes; (iv) formation of connections; (v) cytoarchitectonic differentiation. These changes are often interrelated and can lead to: (vi) system-wide modifications of brain structure as well as to (vii) acquisition of specific functions such as ocular dominance or language. Myelination appears to be plastic both in development and adulthood, at least, in rodents. Adult neuroplasticity is limited, and is mainly expressed as changes in the strength of excitatory and inhibitory synapses while the attempts to regenerate connections have met with limited success. The outcomes of neuroplasticity are not necessarily adaptive, but can also be the cause of neurological and psychiatric pathologies.

INTRODUCTION The term “plasticity” referred to the nervous system is often used, but rarely defined. It includes changes in neural structure and/or function often pooled together as “brain remodeling” (Merzenich et al., 2014). Therefore, the term has unclear boundaries that I will try to sharpen in this chapter. Neuroplasticity is at the roots of why the nervous system exists at all. Indeed, the nervous system exists so that an input from the environment is transformed into an output by the animal. Neuroplasticity however exceeds the normal, more, or less reflexive elaboration of the response to a stimulus in that the nervous system is modified by the environmental input. This is precisely what happens when the animal learns, but l will keep learning at the periphery of the present chapter (see Chapter 2 by Mancini et al.). Neuroplasticity includes a broad variety of phenomena spanning from development to adulthood. Therefore, it should not be surprising that it might be difficult to

ascribe the origin of the concept unequivocally to one of the founders of our discipline (discussed in Jones, 2000, 2004; Berlucchi and Buchtel, 2009). The many facets of neuroplasticity will be dealt briefly here; each of them would be worth a full chapter. Most of the data are derived from animal studies where it is easier to identify the underlying mechanisms and therefore might guide the interpretation of human cases. Other reviews exist which detail different aspects of neuroplasticity (e.g., Williams, 1988; Sur and Leamey, 2001; Rouiller and Olivier, 2004; Voss and Zatorre, 2012; Sur et al., 2013; Medini, 2014; Merzenich et al., 2014; Castaldi et al., 2020; La Rosa et al., 2020; Magee and Grienberger, 2020; Pan and Monje, 2020).

DEVELOPMENTAL PLASTICITY The developing brain is exquisitely plastic and this provides an exaggerated image of mechanisms some of which still exist in the adult. Developmental plasticity

*Correspondence to: Angelo Quartarone, Policlinico Universitario, Via Consolare Valeria, 1, Messina, 98125, Italy. Tel: +39-090-22127898, Fax: +39-090-2212789, E-mail: [email protected] † Deceased

4

G.M. INNOCENTI

is restricted to epochs in the life of the brain usually called “critical periods” or “sensitive periods”. Since different aspects of brain development can be modified, several sensitive periods exist whose temporal boundaries can be modified as well, i.e., terminated precociously (e.g., Innocenti et al., 1985; Zufferey et al., 1999) or extended (below). Sources of developmental neuroplasticity relate to the following

Neurogenesis and the control of neuronal number Neuronal number can be manipulated either by preventing the regular neuronal death which occurs after neurogenesis or by exaggerating it. This aspect of neuronal plasticity has a time-honored history. In the first half of the last century observations by the fathers of experimental embryology including Detwiler, Shorey, Hamburger, and Levi-Montalcini demonstrated that limb excision caused loss in the number of motor neurons and spinal ganglia neurons in amphibia and chicks while peripheral grafts had the opposite effect. This line of work led to the concept that neuronal death occurs in normal development and that the competitive success for the innervation of the peripheral territory (skin or muscle) is necessary for neuronal survival. This concept eventually led to the discovery of neurotrophins (reviewed in Hamburger, 1988). The view that the mere competition for trophic factors in the periphery regulates neuronal survival was challenged by the discovery of intrinsically different fitness of spinal ganglia neurons. In the cerebral cortex, cell number is regulated by two factors: (i) the number of cells leaving the cell cycle (the Q fraction) vs that of the reentering the cell cycle (the P fraction), in the proliferative ventricular zone, and (ii) the developmental death of neurons and neuronal precursors (apoptosis). Manipulating the first factor by acting on the mitotic inhibitor p27 led to either increase or decrease of cortical layers thickness indicating changes in neuron number (Caviness et al., 2003). Interfering with apoptosis in caspase-3 orEphA7knock out mice led to enlarged cerebral cortex with a tendency to gyration (Roth et al., 2000; Depaepe et al., 2005). Microcephaly is a human condition characterized by decreased neuronal numbers. The causes include infections (Devakumar et al., 2018) but the pathogenesis, arrested neuronal production, or excessive neuronal death, is uncertain.

Neuronal migration The journey leading neurons from the site of generation in the periventricular proliferative zone to their final location in cortex is a well-regulated series of events, which

normally leads the earliest generated neurons to the bottom of the cortex and the later generated neurons to the top (Rakic, 1974). This journey can be dramatically altered in the “reeler” mouse where the absence of the extracellular matrix protein reelin leads to a reversed and somewhat scrambled distribution of neuronal birthday in cortex, with the early generated neurons at the top and the later neurons below (Caviness, 1976; Prume et al., 2018). Incoming thalamocortical axons, which normally are guided into the cortex by the early generated neurons at the bottom of the cortex take an abnormal trajectory to the top of the cortex, before diving down (Caviness, 1976). They are accompanied by oligodendrocytes which are not seen in the wild type mouse (Prume et al., 2018). Other connections, including callosal connections are preserved in the “reeler” (Simmons et al., 1982). Some visual functions and receptive field properties are preserved as well (Sinex et al., 1979; Dr€ager, 1981; Simmons and Pearlman, 1983). Somatosensory functions are preserved (Guy and Staiger, 2017). On the whole the “reeler” and the experimentally induced microgyria (below) are examples of functional resilience of cerebral cortex against severe anatomical alterations. Less dramatic alterations of neuronal migration were described in hypothyroidism (Berbel et al., 1993) or as neuronal ectopias of various origin sometimes associated with epilepsy (reviewed in Luhmann, 2016).

Neuronal differentiation The acquisition of neuronal phenotype involves changes at the soma-dendritic complex and at the axon. These changes are related to the genetic makeup of the neuron but require interaction with the cellular environment, which in turn might mediate interaction with the environment of the animal. The acquisition of both the dendritic and the axonal phenotype involves progressive and regressive events. The progressive events comprise elongation, mediated by growth cones, radial growth, formation of spines or synaptic boutons and branching. The regressive events, are extremely common across structures, systems, and species and involve elimination of part of the dendritic arbor (Leuba and Garey, 1984; McMullen et al., 1988; Ramoa et al., 1988; Ulfhake et al., 1988; Koester and O’Leary, 1992). In extreme cases the regressive events can change the overall neuronal morphology from the pyramidal to the spiny stellate typology (Vercelli et al., 1992; Callaway and Borrell, 2011). The dendritic changes involve modifications of the dendritic microtubules (Khatri et al., 2018; Parcerisas et al., 2020) under the control of dendritic competition (Linden and Serfaty, 1985), activity (Callaway and Borrell, 2011; Skelton et al., 2020), experience

DEFINING NEUROPLASTICITY (Breach et al., 2019; Villanueva Espino et al., 2020). The areal location of cortical neurons, not their target, was found to be related to the morphology of dendritic arbors (Vercelli and Innocenti, 1993).

5

Axonal differentiation involves elongation to target, guided by environmental cues, target recognition, target ingrowth, synaptogenesis (reviewed by Kolodkin and Tessier-lavigne, 2011; Zhang et al., 2017; Balaskas et al., 2019). The formation of connections is characterized both by progressive and regressive events. The latter consist in the massive elimination of long transient axons, initially described for the callosal connections of the cat (Innocenti et al., 1977; Innocenti, 1981; Berbel and Innocenti, 1988; LaMantia and Rakic, 1990) and later generalized to several systems and species, particularly intra-hemispheric and corticospinal projections (O’Leary and Stanfield, 1986; De León Reyes et al., 2019; reviewed in Innocenti and Price, 2005). Axonal selection occurs near the target (reviewed in Innocenti, 2020). At the time of cortical ingrowth transient short branches and synapses are generated mainly in the white matter while the distribution of intracortical branches and boutons is as in the adult, although it undergoes a phase of exuberant synaptogenesis (Innocenti and Price, 2005; Innocenti, 2020). Subsequent radial axonal growth paralleled by cytoskeletal changes (Guadano-Ferraz et al., 1990; Riederer et al., 1990) leads to myelination of axons whose diameter exceeds the threshold of 0.2 mm (Berbel and Innocenti, 1988). Continuing growth leads to cohorts of different axonal diameters in various CNS pathways, notably those leaving different cortical areas (Tomasi et al., 2012; Innocenti et al., 2014).

which continues to this day. Subsequent work was performed in rodents with improved anatomical resolution. Neurons receiving from the deprived eye were found to lose synaptic spines (Coleman et al., 2010; Yu et al., 2011; Sun et al., 2019). Studies aimed at defining the conditions which terminated the critical period discovered the role of GABAergic transmission (Huang et al., 1999; Fagiolini and Hensch, 2000), specified the role of perineuronal extracellular matrix and the behavior of geniculo-cortical terminations (reviewed in Hensch, 2005; see also Berardi et al., 2004). Studies succeeded at reopening the critical period in mature animals by locally infused norepinephrine (Kasamatsu et al., 1979), reducing intracortical inhibition (Harauzov et al., 2010; Cisneros-Franco and De Villers-Sidani, 2019), deleting proteins of the Major Histocompatibility Complex (Adelson et al., 2016), grafting embryonic inhibitory neurons (Davis et al., 2017), subministering the antidepressant fluoxetine (Steinzeig et al., 2019), injuring the optic nerve (Vasalauskaite et al., 2019), depriving the animal of somatosensory and auditory input (Teichert et al., 2019). These studies raise the hope that recovering juvenile plasticity might be used to counteract pathologies of the adult brain (H€ubener and Bonhoeffer, 2014). A different concept of plasticity: homeostatic plasticity was put forth (reviewed in Turrigiano and Nelson, 2004). It signifies that neurons deprived of input tend to increase their firing. Confirming this concept, after short (2 h) periods of monocular deprivation, in adult humans, the BOLD signal was boosted for the deprived eye in V1, V2, V3 and V4, specifically for high spatial frequency of the stimulus, consistent with the involvement of the parvocellular input to the cortex (Binda et al., 2018).

Activity dependent formation of connections: Ocular dominance

Plasticity of cortical connections

The final acquisition of the axonal phenotype is expressed in the formation of interneuronal connections. This step is controlled by activity. The best studied example is the shift of ocular dominance in the primary visual areas. The field was initiated by the findings that closing one eye during early life led to loss of the responses to that eye in visual area 17 (V1) of the cat and signs of neuronal atrophy in LGN neurons. Raising the kitten with artificially induced strabismus led to loss of binocularly responsive neurons (Hubel and Wiesel, 1965; Wiesel and Hubel, 1965). The work was later generalized to the macaque monkey where the loss of responses to the deprived eye could be ascribed to the loss of geniculocortical projection concerned with that eye (Hubel et al., 1977). These findings had an enormous resonance,

The selection of juvenile cortico-cortical connections from the exuberant stock mentioned above is modulated by different conditions. One is the peripheral input in the form of organized thalamocortical input (Shatz, 1977) or retinal input. Two changes were caused by these manipulations: loss of projections which would normally be maintained (Innocenti and Frost, 1980; Zufferey et al., 1999) and maintenance of projections which would normally be eliminated (Shatz, 1977; Callaway and Katz, 1991; Zufferey et al., 1999; De León Reyes et al., 2019). These results suggested that cortical axons are labile at birth and require activity for their stabilization and maintenance. Short periods of normal vision are sufficient to stabilize the connections and trigger their further differentiation (Innocenti et al., 1985; Zufferey

Formation of connections

6

G.M. INNOCENTI

et al., 1999; Box 1.1). Modification of cortical connections in development, with stabilization of connections normally deleted, were also caused by hypothyroidism (Berbel et al., 1993) and early cortical lesions (Restrepo et al., 2003). Pietrasanta et al. (2012) have reviewed the consequences of deprivation on the development of callosal connections in rats and their role in the binocularity of cortical responses.

In humans, Friston has over the years supported the view of schizophrenia as a disconnection syndrome presumably caused by failed stabilization of connections in development (reviewed in Friston et al., 2016). Impaired development of middle and posterior sector of the Corpus Callosum where described in 6-16 year old children with early-onset bipolar disorder (Lopez-larson et al., 2013) and in congenitally blind children (Ptito et al., 2008; Cavaliere et al., 2020, and below).

BOX 1.1. THE DEVELOPMENT OF CALLOSAL AXONS BETWEEN VISUAL AREAS 17 AND 18 IN CATS BINOCULARLY DEPRIVED OF VISION WITH EYELID SUTURE. Binocular eyelid suture prevents pattern vision, resembling bilateral cataract. It massively reduces the number of axons interconnecting the primary visual areas of the two hemispheres and the loss appears to be irreversible (Innocenti and Frost, 1980; Innocenti et al., 1985). The majority of the remaining axons are severely stunted; they are thinner and exhibit fewer branches, and synaptic boutons (Figs. 1.1 and 1.2). The effects are already seen after 1 month of deprivation. However, 10 days of normal visual experience after natural eye opening (at around 7 days) prevent the loss of callosal axons (Innocenti et al., 1985) and after 8 days of normal visual experience the arbors developed nearly normally in spite of binocular deprivation (Fig. 1.3). This suggests that even a limited amount of normal visual experience can stabilize the juvenile axon and triggers its normal development. Intraareal connections are similarly affected. They lose the normal patchy distribution of terminals and single axons are severely stunted (Figs. 1.4 and 1.5). These concepts might apply to other conditions where deprivation has deleterious consequences, in particular to the acquisition of language (Innocenti, 2007). Interestingly the distributions of CC axon diameters from areas 17 and 18 in the cat (Houzel et al., 1994) and in the monkey (Tomasi et al., 2012) were never previously compared and appear to be similar.

Fig. 1.1. Binocular deprivation by eyelid suture for at least 60 months stunts the development of callosal axons interconnecting areas 17 and 18 in the cat (D axons). The B axons are from normally reared adult cats. From Zufferey, P.D., et al., 1999. The role of pattern vision in the development of cortico-cortical connections. Eur J Neurosci 11, 2669–2688. doi: 10.1046/j.14609568.1999.00683.x, modified.

visual callosal axons 57 100.0 80.0 60.0 20.0 0.0

54

52

40.0

20

26

21

10

7 0-45

3

7 0.46-0.90

0.91-1.35

cat normal

1.36-1.80

monkey

3

1.81-2.25

cat BD

Fig. 1.2. Binocular deprivation results in thinner callosal axons interconnecting the visual areas 17 and 18 in the cat. Notice the previously unknown similar distribution of diameters of visual callosal axons in cats (Houzel et al., 1994) and monkey (Tomasi et al., 2012). The number of axons in each class of diameters is on the corresponding column.

Fig. 1.3. A short period of normal vision followed by binocular deprivation triggers a nearly normal development of callosal axons. From Zufferey, P.D., et al., 1999. The role of pattern vision in the development of cortico-cortical connections. Eur J Neurosci 11, 2669–2688. doi: 10.1046/j.1460-9568.1999.00683.x, modified.

Fig. 1.4. Binocular deprivation prevents the clustered distribution of local connections in the primary visual areas of the cat. Three-dimensional reconstruction of the occipital pole of two representative P60 animals. The concentric regions on the dorsal surface of the brains represent the core of injection, containing densely packed biocytin-labelled cell bodies (black), the region of diffusely distributed (yellow) and clustered (blue) axons. From Zufferey, P.D., et al., 1999. The role of pattern vision in the development of cortico-cortical connections. Eur J Neurosci 11, 2669–2688. doi: 10.1046/j.1460-9568.1999.00683.x, modified.

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Fig. 1.5. Binocular deprivation by eyelid suture stunts the development of local axons in area 17 of the cat. From Zufferey, P.D., et al., 1999. The role of pattern vision in the development of cortico-cortical connections. Eur J Neurosci 11, 2669–2688. doi: 10.1046/j.1460-9568.1999.00683.x, modified.

Cytoarchitectonic/areal specializations In the somatosensory cortex of rodents, the mystacial vibrissae (whiskers) are represented at the cortical level by “barrels,” that is, cytoarchitectonic specializations in layer iv consisting, in the mouse, of a cellular rich wall and cellular poor hollow (Woolsey and Van der Loos, 1970). These specializations are exquisitely plastic in development. Cauterization of the whiskers in newborn mice leads to the disappearance of the corresponding “barrel” (Van Der Loos and Woolsey, 1973). In contrast, supernumerary vibrissae cause the appearance of supernumerary barrels (Van der Loos et al., 1984). A threshold number of axons are required to innervate the vibrissa follicle for the supernumerary barrel to appear and there is a linear correlation between the number of axons and the size of the barrel (Welker and Van der Loos, 1986). These findings spurred the powerful hypothesis that the sensory periphery has a direct control of cortical cytoarchitectonics (van der Loos and D€ orfl, 1978). The concept was confirmed by the finding that retinal ablation in fetal monkey gave rise to a new cytoarchitectonic field between areas 17 and 18 (Rakic et al., 1991; Magrou et al., 2019). The mechanisms involved in the thalamic

specification of barrel field architecture were reviewed (Dimou and G€otz, 2012; Martini et al., 2018). Prenatal alcohol exposure decreased the size of the barrel field (Chappell et al., 2008). Some degree of columnar organization of cell bodies is a feature of cortical cytoarchitecture noticed and discussed for more than 50 years (Bonin and Mehler, 1971 and quotations therein). The concept of “minicolumns” was revived recently (reviewed in Buxhoeveden and Casanova, 2002) as it appears to be at the crossroad between the developmental concept of “radial unit” (Rakic, 1988) and the physiologically defined “cortical columns” (reviewed in Mountcastle, 1997). The radial arrangement of cortical neurons varies across species which, sometimes, requires sophisticated morphometric methods (Rafati et al., 2016). Nevertheless, it was claimed to be altered in psychiatric conditions, including autism (Casanova et al., 2006; Casanova and Casanova, 2019). Microgyria refers to the occurrence of abnormally small gyri at selective cortical sites, with abnormal lamination whereby mainly superficial layers are maintained while deep layers are mostly deleted. This defect appears spontaneously due to ischemic insults which interfere

DEFINING NEUROPLASTICITY with neuronal survival and migration in development. It can be induced in developing animals by different methods including the application of ibotenic acid which mimics the ischemic insult (Innocenti and Berbel, 1991). For methods to induce cortical malformations see Luhmann (2016). Interestingly many neurophysiological properties of the microgyric cortex were preserved (Innocenti et al., 1993). This was also the case in a human case of microgyria (Innocenti et al., 2001) and in a monkey case of spontaneous microgyria in the motor cortex (Schmidlin et al., 2009). However abnormal excitability and auditory perceptions were described in animal work (Luhmann, 1998; Escabí et al., 2007).

System-wide changes in development Many, perhaps most of the changes in the developmental events mentioned above are not restricted to the topical modifications identified but are rather the expression of more widespread changes in brain structure. This is due to the fact that different brain parts influence each other’s development via trophic interactions and/or activity. The late Bertram Payne reviewed several years of work in his laboratory on the consequences of lesions of areas 17 and 18 in the cat at birth, 30 days and adulthood (Payne, 1999). In summary, the anatomical consequences of the lesion differed at each age. They involved differential degeneration of retinal ganglion cells classes, maintenance or elimination of geniculocortical projections, reorganization of projections among peristriate visual areas and enhanced projections from extrastriate visual areas to superior colliculus. The lesions, therefore, caused a complete rewiring of visual areas, accompanied by some degree of sparing of visuomotor behavior. We investigated two cases of patients with early lesions of primary visual areas (MS and FJ; Kiper et al., 2002; Knyazeva et al., 2002). The patient with the earliest lesion (MS) improved with age in some visual tests but both patients remained impaired in tasks of figure-ground discrimination. The patients were studied with fMRI and EEG but the answers obtained with these methods were insufficient. Therefore, we developed an animal model consisting of early lesion of primary visual areas in the ferret (Restrepo et al., 2003). In this model the residual visually responsive portion of cortex showed scrambled retinotopy and the visual callosal connections were altered. It remains to be investigated if the patients MS and FJ mentioned above had scrambled retinotopy in their visually responsive cortical regions and if this was the cause for their impaired figure ground discrimination. Scrambled retinotopy was also reported in a case of early cortical lesion (Mikellidou et al., 2019), who however, was apparently not tested for figure-ground discrimination.

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A particularly dramatic re-routing of visual projections to the auditory and somatosensory thalamus was obtained in the hamster with early lesions (Frost, 1981). Consequent to the lesion visual responses could be obtained in auditory cortex, (Ptito et al., 2001). Comparable results were obtained in the ferret (Sharma et al., 2000). Magrou et al. (2019) reported, in the monkey, changes in the thalamic projection to the cortex abnormally developed between areas 17 and 18 after early enucleation (above). Joint reduction of excitatory-inhibitory balance is expected to cause circuit-wide changes in an animal model of Rett syndrome (Banerjee et al., 2016). Conversely, multiple factors impact the development of prefrontal cortex in rodents (Kolb et al., 2012). Studies on the consequences of early, or congenital visual deprivation have revealed widespread changes in connections including, in humans, atrophy of the geniculostriate system, pulvinar and corticocortical pathways including, as expected from the animal work (above), the posterior sectors of the Corpus Callosum (Ptito et al., 2008; Reislev et al., 2016; Cavaliere et al., 2020). The same deprivations in animals and in humans have provided evidence of cross-modal plasticity with the visual cortex becoming activated by somatosensory or auditory stimuli (Rauschecker, 1995; Watkins et al., 2013). Which pathways might be responsible for crossmodal plasticity is unclear. In development, exuberant, transient projections are formed from auditory and somatosensory areas to visual areas in the cat (Innocenti and Clarke, 1984; Dehay et al., 1988; Innocenti et al., 1988). Some of these projections remain in the adult cat and monkey (Innocenti et al., 1988; Falchier et al., 2002; Rockland and Ojima, 2003) and could be responsible for the cross-modal plasticity. In addition, somatosensory information could be carried by thalamocortical afferents (M€uller et al., 2019). In congenitally deaf cats different sectors of the auditory cortex were found to improve visual localization and visual motion detection (Lomber et al., 2010). Butler and Lomber (2013) have reviewed the system-wide changes caused by early deafness.

Language learning Provides a fascinating example of functional plasticity in development probably exploiting some of the mechanisms above, in particular, the selection and functional validation of juvenile, labile cortical connections. The best explored feature is the development of phonemic boundaries (Kuhl, 2010) (e.g., the l/r contrast) which characterizes Indo-European languages but is absent in Japanese. Initially Japanese children can discriminate both phonemes but their subsequent exposure to their native language erases the boundary. Phonetic learning

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occurs within the first year while syntactic learning, between 18 and 36 months (Kuhl, 2010). Phonemic learning is enhanced by social interaction as if a “social gating” exists for language learning. Top-down language processing occurs between 3 and over 10 years (Skeide and Friederici 2016). Word learning revealed changes in Fractional Anisotropy (FA) in the left precentral gyrus, postcentral gyrus and middle-temporal white matter of preschool children, suggestive of some kind of white matter plasticity (Ekerdt et al., 2020). A critical period might exist for the later developing aspects of language acquisition since children raised in isolation seem to have acquired, at best, rudimentary language, a striking similarity with the consequences of visual deprivation in animals (reviewed in Innocenti, 2007).

MYELIN PLASTICITY The view that axons are cables faithfully conducting information between neurons has been superseded by the evidence that they participate in information processing by performing three kinds of computational operations: mapping, differential amplification and temporal transformations (Innocenti et al., 1994, 2016). The latter operation depends on axonal conduction velocity which in turn depends on axon diameter. These two parameters and axon length determine the conduction time (delay) between neurons. Myelin thickness keeps a nearly stable relation with axon diameter whereby the g ratio, the ratio between inner and outer axon diameter, stabilizes around 0.6–0.7, for optimal axonal conduction (Rushton, 1953; Smith and Koles, 1970; Drakesmith and Jones, 2018). It follows that myelin thickness tracks whichever changes in axon diameter are imposed by axonal plasticity in development. The existence of neurotransmitter receptors on oligodendrocytes and neurotransmitter release from axons are attractive conditions for the existence of direct coupling between axonal spiking and myelination (reviewed by Micu et al., 2018). This evidence probably clarifies how axonal conduction can be adjusted to pathway length in development in order to obtain synchronous activation of targets as in the auditory system (Seidl et al., 2010; Seidl and Rubel, 2016) or in visual callosal connections (Innocenti et al., 1994). In the auditory system axons of the trapezoid body remain thinner and less myelinated in animals raised with ear plugs (Sinclair et al., 2017) a finding resampling the consequences of binocular deprivation on visual callosal connections (Box 1.1). In development, myelination is also under the control of thyroid hormones and is seriously impaired by hypothyroidism (Lucia et al., 2018 and references therein).

Social interaction within a critical period is required for the development of normal myelination in medial prefrontal cortex axons (Makinodan et al., 2012) and for the development of normal social interactions, an effect which recalls that of visual experience on the development of visual callosal connections (Box 1.1). In recent years the relations between axons and oligodendrocytes or oligodendrocytes precursor cells (OPCs) have revealed high degrees of complexity. Oligodendrocytes are not only involved in producing myelin, but also in supporting axonal metabolism, probably via transport of lactate (F€unfschilling et al., 2012; Lee et al., 2012). An impressive body of evidence has documented the occurrence of myelin plasticity in the adult rodent, linked to the continuous production of OPCs (Rivers et al., 2008; Kang et al., 2010; Emery, 2010; Hill et al., 2018; Hughes et al., 2018; see Chang et al., 2016, for review). Fields (2015) has collected over several years evidence that myelination is modifiable by activity, hence might provide a basis for plasticity (memory) in addition to synaptic modifications (reviewed in Fields and Bukalo, 2020). Not only OPCs might be involved in adult myelin plasticity, but perinodal astrocytes as well (Dutta et al., 2018). Myelin plasticity in the adult is required for the acquisition of motor skills in mice (Xiao et al., 2017) and neuronal activity is required for oligodendrogenesis and adaptive myelination (Gibson et al., 2014). However, Yeung et al. (2014) have excluded adult genesis of oligodendrocytes in the adult human brain by studying the incorporation of 14C. Some degree of remyelination may occur in MS patients (Kipp et al., 2012) and in some severe cases production of oligodendrocytes has been documented as well (Yeung et al., 2019). It is unclear what enhanced myelination might achieve in the normal adult brain since the g ratio in most axons is close to the optimal 0.7 value (above). An increase in myelin could occur in two situations (i) myelination of unmyelinated or incompletely myelinated axons (Tomassy et al., 2014), of which a large number exists in the rodent brain, where most experiments have been performed and (ii) increased axon diameter which causes an increase in myelin thickness keeping the axon in the g ¼ 0.7 range. In this second case myelination would rather be an epiphenomenon of the increased radial dimension of axons. In truth, the evidence for increased myelination in humans is scanty (Scholz et al., 2009; SampaioBaptista et al., 2018).

ADULT PLASTICITY There seems to be a limited amount of neurogenesis in the adult brain and, particularly in humans, the concept is controversial (Lucassen et al., 2019). Axonal growth

DEFINING NEUROPLASTICITY in also limited in the adult brain and the expression of plasticity has been restricted to changes in response properties, whose nature is in general unknown. This is not to say that the adult brain is devoid of plasticity. Although some mechanisms supporting brain plasticity may continue through life, for example myelination (Wang and Young, 2014 and above), and synaptogenesis, the basis of adult plasticity is different and largely discussed in this volume. Changes in synaptic strength, including both increase and decrease, based on Hebbian-like rules or other principles (Magee and Grienberger, 2020), are clearly possible at any age (Merzenich et al., 2014) and also provide the basis for memory (Kandel, 2001; see Chapter 2 by Mancini et al.). This kind of plasticity is typically reversible. Local axonal sprouting and changes in dendritic spines and synapses which might alter excitatory-inhibitory balance are another mechanism of adult plasticity (Knott et al., 2002, 2006; El-Boustani et al., 2018). Ketamine administration was found to increase synapses in the adult brain (Pryazhnikov et al., 2018 and references therein) with therapeutic perspectives for the treatment of depression. The role of astrocytes in synaptic plasticity has been advocated (Singh and Abraham, 2017). Changes in neural network whose structural and functional complexity might escape us for a long time (Innocenti, 2017) can lead to unpredictable shifts in processing simulating a holistic behavior of brain function. Kaas et al. (1983) and Merzenich et al. (1984) were probably the first to report that in the adult animal “When a restricted sector of somatosensory cortex is deprived of its normal pattern of activation in adult mammals by sectioning peripheral nerves or dorsal roots, or by amputation of a body part, the affected cortex rapidly becomes largely or completely reactivated by inputs from adjoining and nearby skin fields.” The result was ascribed to unmasking and potentiation of pre-existing sub-threshold afferents as well as to sprouting of local connections. The first mechanism was supported by the finding that in the adult monkey which underwent lesion of the primary motor cortex improved function was sustained by enhanced activity in premotor cortex, supplementary motor and cingulate motor cortex (Rouiller and Olivier, 2004). The second mechanism was validated by work in the visual system where a cortical site corresponding to an artificial scotoma caused by retinal lesion was found to be invaded by axons sprouting from the surrounding intact cortex (Darian-Smith and Gilbert, 1994). Remodeling of intrinsic axons in V1 was reported in monkeys trained to identify collinear contours; changes consisted in addition as well as elimination of axonal segments imaged in-vivo (Van Kerkoerle et al., 2018).

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Caleo (2018) has reviewed several studies demonstrating either enhanced or decreased callosal input after adult cortical lesions in animals and in humans. Several studies aimed at exploring the potential of adult plasticity in regenerating long projections, in particular the corticospinal projections were initiated by the finding that myelin associated proteins impair the regeneration long projections in the adult and the inhibition can be overcome by anti-myelin antibody (Caroni and Schwab, 1988; Schwab 1990). These efforts have met with some success (Freund et al., 2009) although they still encounter some unknown obstacles (Beaud et al., 2020) as documented also by preliminary clinical trials (Kucher et al., 2018). Other attempts to repristinate growth of long connections in the adult included the use of peripheral nerve grafts (David and Aguayo, 1981) bulbar olfactory ensheathing cells (Tabakow et al., 2014) and other means (Endo et al., 2009). It is probable that attempt to repristinate growth of long axons in the adult by local action on the adult axons will not be able to repristinate the conditions which have allowed the precisely orchestrated axonal growth to target in development.

ADAPTIVE VS MALADAPTIVE PLASTICITY Although, as mentioned in the introduction, the evolutionary goal of neuroplasticity may be that of favoring adaptation of the animal to the environment, evidence of neuroplasticity in pathological cases, including, autism, schizophrenia and Alzheimer disease have been reported (Oberman and Pascual-Leone, 2013). Some of the changes may be caused by abnormal developmental trajectories including neuronal migration (Ayoub and Rakic, 2015), maintenance of projections which should have been eliminated or other developmentally based abnormalities in connections (e.g., Innocenti et al., 2003; Herbert et al., 2004; Zikopoulos and Barbas, 2010). Transcranial Magnetic Stimulation can alleviate the symptomatology in some cases (Oberman and Pascual-Leone, 2013; see for instance Chapter 5). Behavioral training successfully recovered cortical network dysfunctions in a rodent model of autism (Zhou et al., 2015). Attentional training has been found to improve working memory (reviewed in SpencerSmith and Klingberg, 2015).

CONCLUSIONS I have suggested that neuroplasticity is at the roots of why the nervous system exists at all. That is, the nervous system exists so that an input from the environment is transformed into an output by the animal. In a cursory way, I have described many aspects of neuroplasticity which support this view. Changes in the brain, particularly striking in development, are caused by sensory

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inputs, through the eyes, ears, skin, and probably muscles. Other aspects of neuroplasticity seem to be related to the adaptation of the brain to its body. The survival of neuron number in development depends on the size of the periphery, and cytoarchitectonic modifications are related to the structure of sensory organs, were they skin or retina. These adaptations might assist the brain to implement the sense of body ownership, a non-trivial operation which can be manipulated in adulthood (Ehrsson et al., 2004; Blanke et al., 2015). But is the response to the environment the only cause of neuroplasticity? Or, is it because the manipulation of sensory inputs are the only conditions easily amenable to experiment and observation? Can one think of instances of neuroplasticity other than those driven by peripheral inputs? Perhaps one can, if one considers the brain a machine whose overall performance can be improved by tinkering. Therefore, one could consider changes in the brain which decrease energy costs and/or improve speed of information transfer (Wang et al., 2008). Also, neuron number increases along the mammalian radiation (Gabi et al., 2016) as does the number of cortical areas (Kaas, 2013; Halley and Krubitzer, 2019). Finally, it can be seen that morphological and functional hemispheric lateralization are distinctive features of the human brain. All these changes occur along the lines of increased differentiation and improve brain performance; but this kind of neuroplasticity is in the hands of evolution and of its fiddling with developmental mechanisms (Innocenti, 2011; Finlay and Uchiyama, 2015; Finlay and Huang, 2020), and fall beyond the scope of the present chapter. It is in no way clear that the kind and degree of neuroplasticity should remain the same across the mammalian radiation. The case of myelin, in particular, seems to show decreased plasticity in the human vs the rodent brain. This calls for the emergence of a new discipline comparing the various aspects of neuroplasticity across fila. What can be said by now is that the far more robust neuroplasticity of the developing compared to the adult brain imposes the search and implementation of strategies that might protect the brain of the child.

ACKNOWLEDGMENTS GMI is very grateful for the generous hospitality of Prof Jean-Philippe Thiran in his department at the Federal Institute of Technology in Lausanne (EPFL), and for the wonderful, stimulating companionship of its members.

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Section II Neuroplasticity: Basic mechanism and assessment at system level

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Handbook of Clinical Neurology, Vol. 184 (3rd series) Neuroplasticity: From Bench to Bedside A. Quartarone, M.F. Ghilardi, and F. Boller, Editors https://doi.org/10.1016/B978-0-12-819410-2.00002-3 Copyright © 2022 Elsevier B.V. All rights reserved

Chapter 2

Basic mechanisms of plasticity and learning ANDREA MANCINI1*, ANTONIO DE IURE2, AND BARBARA PICCONI2,3* 1

Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy 2

IRCCS San Raffaele Roma, Laboratory of Experimental Neurophysiology, Rome, Italy 3

University San Raffaele, Rome, Italy

Abstract The last century was characterized by a significant scientific effort aimed at unveiling the neurobiological basis of learning and memory. Thanks to the characterization of the mechanisms regulating the long-term changes of neuronal synaptic connections, it was possible to understand how specific neural networks shape themselves during the acquisition of memory traces or complex motor tasks. In this chapter, we will summarize the mechanisms underlying the main forms of synaptic plasticity taking advantage of the studies performed in the hippocampus and in the nucleus striatum, key brain structures that play a crucial role in cognition. Moreover, we will discuss how the molecular pathways involved in the induction of physiologic synaptic long-term changes could be disrupted during neurodegenerative and neuroinflammatory disorders, highlighting the translational relevance of this intriguing research field.

INTRODUCTION Learning resides on the ability of shaping ourselves upon the experiences we have lived. The memory processes fill our everyday life, allowing the possibility to remember the day in which we were happy to have reached a specific goal, as well as the ability to type quickly on a standard computer keyboard. During the last decades, the scientific community has reached significant milestones in understanding the biologic and molecular basis of learning, unveiling potential pathogenetic pathways that could be affected during the development of different neurological disorders. In this chapter, we will summarize the proposed mechanisms by which the experiences can shape our neural network in brain areas considered crucial for learning and memory, such as the hippocampus and the nucleus striatum. Finally, we will discuss how neural plastic abilities could be disrupted during pathologic conditions, taking advantage of the pre-clinic, and clinic studies performed in neurodegenerative and neuroinflammatory disorders of the central nervous system (CNS).

SYNAPTIC AND NEURONAL BASIS OF LEARNING AND MEMORY At the end of the 19th century, Santiago Ramon y Cajal suggested that a modification of the existing neuronal connections could play a crucial role in the consolidation of a specific memory trace (Ramón y Cajal, 1894). His intuition required decades to be confirmed, but nowadays the long-term changes in synaptic strength are considered the neurophysiologic basis of learning (Fig. 2.1.). Donald Hebb, in his book “The organization of behavior”, refined the Cajal theory postulating a coincidence detection model in which the connection between two neuronal cells is strengthened by the simultaneous activation of both of them (Morris, 1999). The concept that synapses could undergo activitydependent changes was further investigated by Terje Lomo in 1966, who highlighted a long-lasting increase in synaptic efficacy depending on the repetitive activation of neuronal network (Lømo, 1966). This was probably the beginning of the era of the long-term potentiation

*Correspondence to: Andrea Mancini, Section of Neurology, University of Perugia, 06132, Perugia, Italy. Tel: +39-075-5784228; E-mail: [email protected]; Barbara Picconi, University San Raffaele, Rome, Italy and IRCCS San Raffaele Roma, Laboratory of Experimental Neurophysiology, via di Val Cannuta 247, Rome, Italy. Tel: +39-06-5225-2258, E-mail: barbara. [email protected]

Fig. 2.1. Schematic representation of the mechanisms underlying synaptic plastic changes (LTD and LTP) at striatal and hippocampal connections. (A–C) Description of the three main forms of synaptic plasticity in a generic synapse. (B) In a control condition before high frequency stimulation (HFS), the postsynaptic site contains an NMDA receptor closed by the Mg2+ blockage and the AMPA receptor physiologically open. (A) LTP induction after HFS protocol induced by the increase of Ca2+/Na2+ entrance through the AMPA receptors and the consequential opening of NMDA receptors. (C) LTD induction after stimulation protocol in AMPAR-dependent condition; in this condition, the NMDA receptor is closed. (D) Striatal nuclei with the main innervation fibers (see abbreviations below). (E) Representation of striatum and hippocampus localization within the human brain. (F) Hippocampus with the main innervation fibers and the main areas (CA1, CA3, DG) (see abbreviations below). Main Abbreviations: AMPA, a-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid; CA, cornu ammonis; Ca2 +, calcium; CC, corpus callosum; ChI, cholinergic interneurons; DA, dopamine; DG, dentate gyrus; HFS, high frequency stimulation; LFS, low frequency stimulation; LTD, long term depression; LTP, long term potentiation; MF, mossy fibers; Na2 +, sodium; NMDA, N-methyl-D-aspartate; PP, perforant path; SC, Schaffer collaterals; SPN GABA, gabaergic striatal projection neurons.

BASIC MECHANISMS OF PLASTICITY AND LEARNING (LTP), that was expanded a few years later with the brilliant work of Lomo and Tim Bliss, a psychologist interested in the mechanisms behind memory processes (Nicoll, 2017). In their work, Bliss and Lomo demonstrated that the repetitive activation, named high frequency stimulation (HFS), of the perforant path (PP) fibers projecting to hippocampal dentate gyrus (DG) induced a persistent increase in the amplitude of excitatory postsynaptic potentials (EPSPs) (Fig. 2.1.F) in the same area (Bliss and Lomo, 1973), that could last for several days (Bliss and Gardner-Medwin, 1973). This work is a landmark in the neuroscience field, inspiring the future research efforts aimed at the characterization of the neurobiological basis of learning and memory. Indeed, a few years later, key properties of the LTP were described, such as its “associativity” (a weak input fails to induce LTP on its own but could succeed if tetanized together with a strong input), “cooperativity”, and “input specificity” (a strong input, recruiting numerous synapses can induce LTP but only in the stimulated pathway) (McNaughton et al., 1978; Levy and Steward, 1979). These properties led to consider LTP as a Hebbian phenomenon, requiring the presence of simultaneous post-synaptic cell depolarization and synaptic activation (Kelso et al., 1986; Malinow and Miller, 1986; Wigstrom et al., 1986; Gustafsson et al., 1987). In the same years, the proper characterization of glutamate-based neurotransmission and N-methyl-Daspartate glutamate receptor (NMDAR) properties helped in the understanding of the molecular pathways underlying LTP induction and maintenance (Malenka and Bear, 2004; Bliss and Collingridge, 2013; Nicoll, 2017) (see Fig. 2.1.A and B). Overall, the discovery and investigation of hippocampal LTP significantly contributed to the understanding of the biological mechanisms through which neural networks can be functionally and structurally shaped in relation to experience (Bliss and Collingridge, 1993). To date, this form of synaptic plasticity has been characterized in several brain areas and represents the best known activity-dependent form of synaptic plasticity (Malenka and Bear, 2004), but other types of synaptic and neuronal plastic changes have been described. Indeed, Ito and colleagues described another form of long-term synaptic change represented by a weakening of the connection at the parallel fiber-Purkinje neuron synapses in the cerebellum (Ito et al., 1982). This form of plasticity was named long-term depression (LTD) and during the last decades it has been extensively characterized in different brain areas, suggesting a cooperation between LTP (Fig. 2.1.A) and LTD (Fig. 2.1.C) in the learning processes (Malenka and Bear, 2004). The property of the synaptic connection to undergo long-term changes seems to fulfill the major requirement for a putative biological basis of learning and memory, allowing a long-lasting

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bidirectional modulation of neuronal connections. Moreover, the discovery that it is possible to induce an input-specific and associative LTP at the hippocampal synapses led to the creation of computational hippocampal models underlying the encoding and the retrieval of memory traces (Rebola et al., 2017). It has to be considered that such LTP/LTD-based computational models have been hypothesized not only for the retrieval of the so called “declarative” memory, characterized by a conscious recalling of facts and events previously stored and interconnected, but also for the “non-declarative” memories mainly involved in motor learning and skilled behavior. Indeed, a coordinated potentiation and/or depression of synaptic strength in the basal ganglia network, modulating and filtering the thalamo-cortical connections, has been hypothesized to play a crucial role during the execution and acquisition of a specific motor task (Calabresi et al., 2014). In the next sections, the main forms of synaptic plasticity will be discussed. However, we need to mention some of the latest findings obtained in the field of neuroplasticity. The development of new techniques, such as optogenetics recordings, has allowed to study the activity and the functional changes of a single neuron during the storage and retrieval of the memory traces. The process of learning has been linked to the formation of a specific neuronal ensemble or memory engram which activation enables the recall of the conditioning event (Tonegawa et al., 2015, 2018; Holtmaat and Caroni, 2016; Titley et al., 2017). In this context, the recruitment of specific neurons seems to rely not only on synaptic long-term changes, but also on neuron-centered plastic mechanisms that enhance or weaken synaptic efficiency and ultimately define the neuron’s contribution in a memory engram (Titley et al., 2017). Indeed, plastic changes of neuronal intrinsic membrane excitability have been extensively investigated as potential mechanisms of neuronal-based learning processes complementary to synaptic plasticity (Titley et al., 2017). This form of plasticity is thought to involve neuronal voltage- or calcium-dependent ion channels that could modify neuronal membrane excitability, the threshold for the generation of action potential, the spontaneous, and/or evoked spike frequency and the afterhyperpolarization amplitude (Titley et al., 2017). The presence of specific neurons that are more prone or more resistant to be activated in a network could act as a stimulus filter for synaptic connections, integrating the wellknown changes in synaptic strength. The presence of neuronal intrinsic plastic changes was found in vivo in the neocortex (Paz et al., 2009; Mahon and Charpier, 2012) and in the cerebellum (Belmeguenai et al., 2010), while its possible contribution to learning processes was suggested by different pharmacologic studies

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targeting neuronal channels involved in membrane excitability changes (Titley et al., 2017). The possibility that not only synapses, but also neuronal membrane intrinsic properties could contribute to memory processes maintains the study of the neurobiological basis of learning one of the more fascinating field in neuroscience, even after one century from its beginning.

MOLECULAR MECHANISMS OF SYNAPTIC LONG-TERM CHANGES: LESSONS FROM THE HIPPOCAMPUS NMDAR-dependent LTP The first molecular insights into the mechanisms of long-term synaptic changes were obtained thanks to the study of hippocampal CA1 area (Fig. 2.1.F), leading to the description of an NMDAR-dependent type of LTP that is considered the prototypic form of synaptic plasticity (Malenka and Bear, 2004). The study of synaptic excitatory transmission led to identify different types of glutamate receptors, such as the NMDAR and a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPAR) (Watkins and Jane, 2006) (Fig. 2.1.B). Both of them are ionotropic receptors, allowing a glutamate-induced entrance of positive ions (such as Na+ and Ca2+) at the post-synaptic site (excitatory post-synaptic currents, EPSCs) with a subsequent depolarization of the neuronal membrane (Watkins and Jane, 2006). The application of pharmacological antagonists of these receptors highlighted that, while AMPA receptors are required for the basal synaptic transmission (Watkins and Jane, 2006), the blockade of NMDA receptors had no effect on basal EPSCs, but blocked the induction of LTP in the hippocampal area CA1 (Collingridge et al., 1983). Moreover, in the same years, it was shown that the induction of LTP was also blocked by chelating post-synaptic Ca2+, suggesting that the LTP-dependent modifications of the postsynaptic neuron are dependent on the level of free Ca2+ (Lynch et al., 1983). The picture became to be more clear after the discovery that NMDAR is characterized by a voltage-dependent Mg2+ block, meaning a low current conductance at resting membrane potentials (Mayer et al., 1984; Nowak et al., 1984) which turns into high Ca2+ conductance once the cell is depolarized (Macdermott et al., 1986; Ascher and Nowak, 1988) (Fig. 2.1.A). These peculiar characteristics of the NMDAR fit with the hypothesized properties of hippocampal LTP. Indeed, the necessity of a specific stimulation of the NMDAR when the post-synaptic cell is already depolarized reflects the input specificity and the associativity of the LTP. The mechanisms leading to LTP were expanded and better understood during the successive decades, with

the deciphering of NMDAR-dependent LTP. It is well accepted that the induction of this form of synaptic plasticity is dependent on Ca2+ influx through the NMDAR and a rise of its concentration at the post-synaptic site (Malenka and Bear, 2004; Nicoll and Roche, 2013). Nevertheless, it has been long debated which subsequent molecular pathways are triggered by this Ca2+ influx, since there may be multiple intracellular cascades triggered by the different induction protocols (Malenka and Bear, 2004). Many different proteins have been suggested to play a role, such as the cAMP-dependent protein kinase (PKA), especially during early post-natal life (Yasuda et al., 2003), the protein kinase C (PKC) and its atypical isozyme protein kinase M zeta (PKMz), the mitogenactivated protein kinase cascade (MAPK) and the extracellular signal-regulated kinases (ERKs) (Malenka and Bear, 2004). Overall, the process leading to synaptic LTP seems to involve many different actors, but it is established that the activation of calcium/calmodulindependent protein kinase II (CaMKII) is a key event, being both necessary and sufficient for LTP induction (Pettit et al., 1994; Lledo et al., 1995; Giese et al., 1998; Lisman and Raghavachari, 2015). Specifically, the activation of CaMKII can induce a potentiation of the synaptic transmission, increasing the number of AMPARs expressed at the post-synaptic density (PSD) through activity-dependent exocytosis of intracellular vesicular pools of these receptors and through the lateral diffusion of extra-synaptic receptors into the PSD (Lledo et al., 1995; Choquet and Triller, 2003; Makino and Malinow, 2009; Kennedy and Ehlers, 2011; Patterson and Yasuda, 2011; Opazo et al., 2012; Jurado et al., 2013) (Fig. 2.1.A). The specific mechanisms underlying the recruitment of AMPARs are still under investigation, but it has been hypothesized a role for protein-protein interactions among their cytoplasmic tails or auxiliary subunits (Bredt and Nicoll, 2003; Collingridge et al., 2004; Shepherd and Huganir, 2007; Coombs and Cull-Candy, 2009; Kato et al., 2010), in parallel with the CaMKII-dependent phosphorylation of the subunit GluR1 of the AMPAR (Roche et al., 1996; Barria et al., 1997; Mammen et al., 1997) which could also increase the single channel conductance (Kristensen et al., 2011). Moreover, an interaction between the CaMKII and the GluN2B subunit of the NMDAR seems to be relevant for LTP induction, leading to the recruitment and activation of CaMKII at the PSD (Barria and Malinow, 2005). To complete the picture of NMDAR-dependent LTP, it should be noted that also pre-synaptic changes may contribute to this form of synaptic plasticity, with many possible candidates acting as retrograde messengers (Malenka and Bear, 2004). After its induction, the subsequent maintenance of LTP requires protein synthesis and gene transcription,

BASIC MECHANISMS OF PLASTICITY AND LEARNING processes involving the recruitment of different signaling molecules such as PKA, MAPK, CaMKII, PKMz and the key transcription factor CREB (Abraham and Williams, 2003, Pittenger and Kandel, 2003, Lynch, 2004). LTPrelated morphologic changes represent a link between functional and structural potentiation of neuronal connections and these processes include dendritic spine enlargement, new spines growth and the split of enlarged PSDs in two distinct synapses (Yuste and Bonhoeffer, 2001; Abraham and Williams, 2003). Finally, during last years, based on the studies performed in Aplysia and Drosophila, it has been proposed a role for prion-like synaptic proteins, such as cytoplasmic polyadenylation element-binding protein (CPEB), which could modulate protein synthesis and the subsequent structural synaptic changes underlying the maintenance of long-term memories (Si and Kandel, 2016; Rayman and Kandel, 2017; Asok et al., 2019).

NMDAR-independent LTP Another prototype of LTP was discovered and characterized in the hippocampus, specifically at the mossy fiber (MF) synapses connecting dentate gyrus (DG) granule cells and CA3 pyramidal neurons (Malenka and Bear, 2004; Nicoll and Schmitz, 2005; Rebola et al., 2017) (Fig. 2.1.F). This form of synaptic plasticity received a lot of attention because it is mechanistically different from the NMDAR-dependent LTP described in the hippocampal CA1 area and similar synaptic plastic changes have been described at corticothalamic and cerebellar synapses (Salin et al., 1996; Linden, 1997; Castro-Alamancos and Calcagnotto, 1999). Mossy fiber–CA3 neuron synapses are represented by giant boutons with many release sites expressing different forms of short-term and long-term synaptic plasticity (Nicoll and Schmitz, 2005, Rebola et al., 2017). A peculiar characteristic of these synapses is the presence of a low release probability of neurotransmitter vesicles when the frequency of activation is low (