Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas [1 ed.] 9781613242360, 9781607418764

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved. Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

NEUROLOGY – LABORATORY AND CLINICAL RESEARCH DEVELOPMENTS SERIES

SOMATOSENSORY CORTEX: ROLES, INTERVENTIONS AND TRAUMAS

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

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NEUROLOGY – LABORATORY AND CLINICAL RESEARCH DEVELOPMENTS SERIES Intracranial Hypertension Stefan Mircea Iencean and Alexandru Vladimir Ciurea 2009 ISBN: 978-1-60741-862-7 Cerebral Blood Flow Regulation Nodar P. Mitagvaria and Haim (James) I. Bicher 2009 ISBN: 978-1-60692-163-0 Cerebral Ischemia in Young Adults: Pathogenic and Clinical Perspectives Alessandro Pezzini and Alessandro Padovani (Editors) 2009 ISBN: 978-1-60741-627-2

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Dizziness: Vertigo, Disequilibrium and Lightheadedness Agnes Lindqvist and Gjord Nyman (Editors) 2009: ISBN 978-1-60741-847-4 Somatosensory Cortex: Roles, Interventions and Traumas Niels Johnsen and Rolf Agerskov (Editors) 2009. ISBN: 978-1-60741-876-4

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

NEUROLOGY – LABORATORY AND CLINICAL RESEARCH DEVELOPMENTS SERIES

SOMATOSENSORY CORTEX: ROLES, INTERVENTIONS AND TRAUMAS

NIELS JOHNSEN AND Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

ROLF AGERSKOV EDITORS

Nova Science Publishers, Inc. New York

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Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works.

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Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Library of Congress Cataloging-in-Publication Data Somatosensory cortex : roles, interventions, and traumas / editors, Niels Johnsen and Rolf Agerskov. p. ; cm. Includes bibliographical references and index. ISBN 978-1-61324-236-0 (eBook) 1. Sensorimotor cortex. 2. Somesthesia. I. Johnsen, Niels. II. Agerskov, Rolf. [DNLM: 1. Somatosensory Cortex--injuries. 2. Somatosensory Cortex--physiology. 3. Brain Mapping. 4. Diagnostic Imaging. 5. Somatosensory Cortex--physiopathology. WL 307 S6892 2009] QP383.15.S66 2009 612.8'2--dc22 2009027483

Published by Nova Science Publishers, Inc.  New York

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Contents Preface Chapter 1

NeuroImaging of Somatotopy in Primary Somatosensory Cortex U.N. Sboto-Frankenstein, J. Lawrence and B. Tomanek

Chapter 2

The Role of the Somatosensory Cortex in Pain Processing Jennifer Kornelsen and Boguslaw Tomanek

Chapter 3

Cortical Representation of Cutaneous Receptors in Primary Somatic Sensory Cortex of Man: A Functional Imaging Study Polonara Gabriele, Mascioli Giulia, Salvolini Ugo, Manzoni Tullio and Fabri Mara

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Chapter 5

Chapter 6

Chapter 7

Chapter 8

From Physical Representation to Social Perception: A New Role for the Primary Somatosensory Cortex (Review Article) Michael Schaefer Rehabilitation After Stroke Using Brain-Computer-Interfaces and Neurostimulation Surjo R. Soekadar, Andrea Caria, Ander Ramos Murguialday and Niels Birbaumer

1 31

51

79

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Mechanisms of Epileptogenesis in the Somatosensory Cortex in Rats with Genetic Absence Epilepsy Evgenia Yu. Sitnikova

121

Thermo-nociceptive Responses Evoked by Laser Pulses in the Primary Somatosensory Cortex Bai Chuang Shyu

141

Regulation of the Critical Period for Whisker Lesion-Induced Barrel Structural Plasticity in the Mouse Somatosensory Cortex Tomohisa Toda and Hiroshi Kawasaki

157

Index Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

177

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Preface The somatosensory system is a diverse sensory system comprising the receptors and processing centers to produce the sensory modalities such as touch, temperature, proprioception (body position), and nociception (pain). This book gives an overview of the methodology for investigation of pain in neuroimaging studies and the relevant structures of the lateral pain system. Furthermore, classic studies understand the body map representation in primary somatosensory cortex (SI) as fix and reflecting the physical location of peripheral stimulation in the form of the famous somatosensory homunculus. This book reports the results of recent studies that challenge this view and suggest a more complex role of SI. Also dealt with in this book is the current state and perspective of neurotechnology, particular the use of brain computer interfaces (BCI) and neurostimulation in the rehabilitation of stroke. Future developments and prospects such as the combination of BCI systems with noninvasive form of neurostimulation and functional electric stimulation (FES) is examined as well. Other chapters include a review of research done in the primary somatosensory cortex implicated in the pathogenesis of absence epilepsy, an analysis of the development of noninvasive neuroimaging techniques that have enabled the study of S1 more widely, and an electrophysiological investigation of central neuronal responses evoked by CO2 laser pulses to study evoked responses and thermal pain sensation. Chapter 1 - Our current understanding of somatotopy in primary somatosensory cortex (S1) largely derives from the pioneering work of Penfield and Rasmussen, who used invasive intraoperative cortical stimulation to elicit sensation, and on occasion movement, from corresponding body regions. Since then, the invasiveness of the technique has initiated the development of noninvasive neuroimaging techniques that have enabled the study of S1 more widely. These noninvasive techniques can be classified according to the type of information they reveal: structural, biochemical, or functional. Functional techniques can be further classified based on the source of the collected signal. Direct methods, such as EEG, MEG and TMS record or disrupt a signal directly related to neuronal electrical activity. Indirect methods including PET, NIRS and fMRI detect signals caused by physiological changes in, for example, glucose metabolism or hemodynamics due to neuronal activity. Each technique with its inherent advantages and disadvantages is briefly reviewed. Contrary to other neuroimaging techniques, its availability, the high spatial resolution and the ability to noninvasively

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Niels Johnsen and Rolf Agerskov

perform repeated measures using the endogenous BOLD contrast have made fMRI a popular tool to investigate the detailed somatotopy of S1. FMRI has provided insight into S1 hand representation including individual finger somatotopy. FMRI research has also suggested revisions and refinements of the still controversial somatotopy of the face, genitals and feet. Although not commonly used in the clinic, S1 fMRI has several presurgical and intraoperative advantages that can increase the precision of neuronavigation and thus minimize surgical trauma and avoid postoperative neurological deficits. Chapter 2 - The role of the somatosensory cortex in pain perception has not yet been precisely identified. Numerous studies using various techniques and stimuli have provided contradictory results. This chapter presents an overview of the recent neuroimaging research examining the role of somatosensory cortex in pain processing. First, methodologies for the investigation of pain in neuroimaging studies are reviewed. Next, the relevant structures of the lateral pain system are identified along with a discussion of the fibres that mediate first and second pain. The somatotopic organization of the somatosensory cortex for pain, laterality of pain processing, and cortical reorganization in pain conditions are then reviewed. Finally, the role of the lateral pain system in the modulation of pain and a section on antinociception end the chapter. Chapter 3 - This study describes the cortical representation of the cutaneous periphery in human first somatic sensory area (SI). The aim of the investigation was to: 1. reconsider the somatosensory homunculus using a widely available, non-invasive technique, and 2. establish whether medium-strength (1.5 Tesla) fMRI imaging can be used to map reliably somatosensory cortical areas in man. A General Electric Signa LX NV/i magnet normally employed for diagnostic purposes was used to study 19 healthy volunteers by acquiring 10 contiguous 5-mm-thick brain sections parallel to the bicommissural plane using 50mT/m gradients and an echo planar sequence. Unilateral tactile stimulation was applied to 10 different body regions by rubbing the skin with a soft cotton pad at a frequency of about 1 Hz. The stimulation paradigm, consisting of alternating periods of rest and stimulation, lasted 5 min. Stimulation of different body regions evoked activation foci in the post-central gyrus of the anterior parietal cortex, where SI is located. Activated cortical regions followed a precise topographical organization: foci evoked by foot, lower leg, trunk, arm, hand and face stimulation were arranged medial to lateral throughout the contralateral post-central gyrus. Stimulation of proximal body regions (face, trunk, proximal limbs) and of the hand also elicited consistent activation in area SI of the ipsilateral hemisphere. The resulting somatotopic map agrees with previous human and monkey functional studies. The present data confirm that in man, as in non-human primates, the cutaneous periphery is represented in a somatotopically organized fashion in contralateral area SI. As demonstrated in monkeys, some body regions are represented bilaterally in the anterior parietal cortex. The possible mechanisms underpinning such bilateral representation are discussed, also analyzing the interhemispheric connections between homologous SI regions. Chapter 4 - Classic studies understand the body map representation in primary somatosensory cortex (SI) as fix and reflecting the physical location of peripheral stimulation in the form of the famous somatosensory homunculus. This review reports results of recent studies that challenge this view and suggest a more complex role of SI. For example, animal

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Preface

ix

studies used simple tactile illusions to demonstrate that the topographic representation in SI adapts dynamically to different situational requirements. Moreover, they showed that SI reflects the perceived rather than the physical location of peripheral stimulation. Using similar illusions, in particular by manipulating visuo-tactile integration processes, human studies confirmed those findings. Furthermore, even simple ‘disguising’ of the body seems to be sufficient to affect the perception of the body, along with corresponding changes in the topography of SI. Recent research has also demonstrated that SI responds differentially when observed touch is attributed to the own body compared to another body (in both cases in absence of any real touch). Thus, it was proposed that the somatosensory cortices may be involved in social perception processes. These new insights about the functions of SI may contribute to our understanding of body perception and encourage approaches focusing on dynamic aspects of the body image for future therapeutic interventions. Chapter 5 - This chapter deals with the current state and perspective of neurotechnology, particular the use of brain computer interfaces (BCI) and neurostimulation in the rehabilitation of stroke. While 20 years ago brain-computer-interfaces that utilize neurophysiologic or metabolic signals originating in the brain to activate or deactivate external devices or computers have been used by a handful of research groups only, there are now - after the decade of the brain - several hundred groups world-wide working in this field. Additionally, the modulation of brain activity by non-invasive cortical stimulation undergoes a renaissance. New and innovative techniques to modulate or even enhance brain functions have emerged. After a short introduction of the BCI-systems that have been developed and successfully used in patients with intractable epilepsy, attention deficit disorder, ALS and chronic pain since 1979 by the University of Tuebingen group, recent developments in the use of BCI technology and neurostimulation for stroke survivors will be sketched and exemplified by our latest results. Limits and current challenges in the use of BCI technology and brain stimulation will be highlighted and discussed. The chapter closes with an outlook on future developments and prospects introducing promising developments such as the combination of BCI systems with non-invasive forms of neurostimulation and e.g. functional electric stimulation (FES). Chapter 6 - The primary somatosensory cortex (SmI) is known to be implicated in the pathogenesis of absence epilepsy, as it has been demonstrated in rodent strains with a genetic predisposition to this disease. The current Chapter provides some data in favor to the ‘cortical focus theory’ of absence epilepsy [Meeren et al., 2002; Meeren et al., 2005], that considers the area of perioral projections in the SmI as a trigger zone of absence seizures (epileptic focus). Our study focuses onto the neuronal mechanisms which are responsible for involvement of the SmI in the pathogenesis of absence epilepsy. Electroencephalographic investigations in vivo and histological (microscopic) analysis of cortical tissue were performed in a WAG/Rij rat genetic model of absence epilepsy. It is found that epileptic discharges appear in the cortex as a result of functional disorder, i.e., due to too strong synchronization between neurons in the SmI and surrounding areas. Our data confirm that some microanatomical disorder in the neocortex (such as a cellular disorganization and changes in neuron-glia ratio) can lead to cortical dysfunction and thus promote development of epileptic activity. In general, a complex functional and microstructural impairment of the SmI may result in a serious neurological disorder, namely, absence epilepsy.

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Niels Johnsen and Rolf Agerskov

Chapter 7 - Pain is a multidimensional experience which involves sensorydiscriminative, affective, motivational, and evaluative components. Recent neuroimaging studies in humans have identified multiple cortical and subcortical structures involved in pain processing. The primary somatosensory cortex (S1) receives information mainly from the ventral posterior lateral nucleus of the thalamus and is thought to mediate sensory discrimination of stimulus localization and intensity. Brief CO2 laser pulses have been used to study evoked responses and thermal pain sensation, and evoked cortical potentials may be objective correlates of pain sensation. We performed an electrophysiological investigation of central neuronal responses evoked by CO2 laser pulses in anesthetized and freely moving rats. We found that maximum dorsal column potentials with positive polarity were evoked in lumbar segment 4. Most of the dorsal horn units activated by laser pulse stimuli were widedynamic-range neurons and the C-fibers were the most likely conduction system for this response. The laser-evoked dorsal column potentials and dorsal horn units were suppressed by fentanyl or morphine, and this effect was fully reversed by naloxone. In the thalamus, the latency of laser-evoked responses suggested that nociceptive responses were mediated by C fiber input. All nociceptive units recorded from the lateral thalamus were wide-dynamicrange nociceptive neurons. Two distinct laser-evoked negative potentials (early and late components) were evoked by brief laser pulses in the contralateral S1 of freely moving rats and were correlated with nocifensive behavioral responses such as limb withdrawal, head-turning, and paw-licking. Current source density analysis of extracellular cortical field potentials in S1 revealed a distinct spatial-temporal pattern of intracortical sink source currents evoked by laser stimuli. These current flows showed that synaptic activation occurred initially in cortical layers IV and VI separately and was then relayed transynaptically to more superficial and deeper layers. Our results suggest that large and small diameter thermal nociceptive afferents generate laminar-specific intracortical synaptic currents in S1 and that these excitatory synaptic currents are conveyed separately by lateral and medial thalamic nuclei. Chapter 8 - Neuronal circuits in the developing brain are refined by natural sensory inputs during critical periods of early postnatal life, and each critical period ends at a specific time point in development. An interesting question at hand is what regulates the termination of critical periods. Recently, the molecular mechanisms underlying the termination of critical periods have been investigated using thalamocortical circuits in the somatosensory system and the visual system. One attractive hypothesis that has been proposed is that the termination is regulated by oligodendrocyte-derived signaling molecules. To test this hypothesis, we have examined whisker lesion-induced barrel structural plasticity in the mouse somatosensory cortex using several lines of mutant mice. In this chapter, we will discuss recent findings regarding the molecular mechanisms underlying the termination of critical periods. We will also compare these molecular mechanisms in several different systems. Recent studies support the idea that the somatosensory system and the visual system employ distinct molecular mechanisms to control the termination of critical periods.

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Chapter 1

NeuroImaging of Somatotopy in Primary Somatosensory Cortex U.N. Sboto-Frankenstein,1 J. Lawrence2 and B. Tomanek 1 1

MR Technology, Institute of Biodiagnostics, National Research Council Canada, Winnipeg, Manitoba, Canada 2 Department of Psychology, University of Manitoba, Winnipeg, Manitoba; Canada

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Abstract Our current understanding of somatotopy in primary somatosensory cortex (S1) largely derives from the pioneering work of Penfield and Rasmussen, who used invasive intraoperative cortical stimulation to elicit sensation, and on occasion movement, from corresponding body regions. Since then, the invasiveness of the technique has initiated the development of noninvasive neuroimaging techniques that have enabled the study of S1 more widely. These noninvasive techniques can be classified according to the type of information they reveal: structural, biochemical, or functional. Functional techniques can be further classified based on the source of the collected signal. Direct methods, such as EEG, MEG and TMS record or disrupt a signal directly related to neuronal electrical activity. Indirect methods including PET, NIRS and fMRI detect signals caused by physiological changes in, for example, glucose metabolism or hemodynamics due to neuronal activity. Each technique with its inherent advantages and disadvantages is briefly reviewed. Contrary to other neuroimaging techniques, its availability, the high spatial resolution and the ability to noninvasively perform repeated measures using the endogenous BOLD contrast have made fMRI a popular tool to investigate the detailed somatotopy of S1. FMRI has provided insight into S1 hand representation including individual finger somatotopy. FMRI research has also suggested revisions and refinements of the still controversial somatotopy of the face, genitals and feet. Although not commonly used in the clinic, S1 fMRI has several presurgical and intraoperative advantages that can

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U.N. Sboto-Frankenstein, J. Lawrence and B. Tomanek increase the precision of neuronavigation and thus minimize surgical trauma and avoid postoperative neurological deficits.

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1. Introduction The primary somatosensory cortex (S1) is a parietal cortical region that is known for its somatotopic representation of the body. Over the past two decades there have been exciting neuroimaging advances that have challenged, confirmed or refined early concepts of S1 somatotopy. Mapping S1 somatotopy correlates anatomical regions of interest with brain function. The information obtained by such brain mapping efforts goes beyond basic research designed to learn about S1 functional anatomy but has wide applications in the areas of pain, pre-and intraoperative brain mapping and neuronal plasticity. While Otfried Foerster produced the first cortical map of the entire cerebral cortex, published together with Penfield (1), the foundations of human S1 mapping were greatly extended by Canadian neurosurgeons Wilder Penfield and Theodore Rasmussen who used invasive intraoperative cortical stimulation to examine S1 topography (2). Although still used as a gold standard in intraoperative mapping today, the invasiveness of this procedure has initiated the development of noninvasive neuroimaging techniques such as positron emission tomography (PET), magnetoencephalograhy (MEG), near infrared spectroscopy (NIRS) and Blood Oxygen Level Dependent functional Magnetic Resonance Imaging (BOLD fMRI) in an effort to identify eloquent cortex from expendable brain tissue. These efforts were complemented by neuroimaging investigations of the specific somatotopy of primary motor and somatosensory cortices. Due to its high spatial resolution in contrast to other indirect neuroimaging techniques such as PET and NIRS, fMRI has been able to provide insights into the spatial details of S1 somatotopy including the hand, face, foot and genitals. Although not used as a standard in neurosurgery, S1 topographical mapping has several important pre- and intraoperative applications that have not been fully realized in the clinic.

2. Somatosensory Cortex Mapping: Foundations The brain is composed of twenty-seven separate organs dedicated to different sexual, moral and intellectual traits. The exact brain regions involved in these traits can be determined by manually examining “bumps” upon an individual’s head. This historic approach to brain mapping was termed phrenology (3) by Johann Gaspar Spurzheim, a German physician and assistant to Franz Joseph Gall. Even though Gall’s theories were not well accepted in Germany or France, phrenology did have strong followers in England and the United States. Although later discredited, Gall’s work was an attempt to map particular traits or functions to the brain. However, it wasn’t until the mid 19th century that scientists like John Hughlings Jackson or Pierre Paul Broca made significant contributions in the area of mapping function to specific brain regions by studying compromised brain function in patients with epilepsy or stroke (4,5). Jackson proposed separate motor systems in the brain while Broca discovered that focal lesions in the frontal cortex of the dominant hemisphere

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produced aphasia. In 1870, Fritsch and Hitzig applied electrical current to the frontal cortex of a lightly anesthetized dog which in turn started moving the contralateral leg. Wilder Penfield and Theodore Rasmussen (2) whose names synonymously go with the somatosensory and motor homunculi, refer to Broca’s and Jackson’s initial work as a starting point of localization of function within the cerebral cortex. Human brain mapping has not always been as non-invasive as afforded by today’s neuroimaging techniques. Localization of function in the human somatosensory cortex was achieved by Penfield in his pioneering work on intraoperative brain mapping. In the book “The Cerebral Cortex of Man” Penfield and Rasmussen report on a review of 400 patient case studies who have undergone intraoperative cortical stimulation (ICS) at the Royal Victoria Hospital and Montreal Neurological Institute over a period of 19 years. Many of these patients had epileptic seizures due to tumors or lesions in the region of the central sulcus. One of Penfield’s challenges was to remove a tumor without damage to non-affected regions, a challenge that persists for neurosurgeons today. Depending on the location of the tumor, cortical motor and sensory regions had to be mapped carefully by using either thyratron or Rahm and Scarff stimulation. Electrical pulses shorter than a millisecond were used to stimulate the exposed cortex and Penfield elicited sensory responses largely from the postcentral gyrus but also to a smaller extent from the precentral gyrus. These stimulations resulted in tingling sensations, feelings of electricity or numbness of different contralateral body regions and were carefully mapped in individual sensory sequence charts. In their book the authors report the following general somatotopic organization of somatosensory cortex as a constant finding in their subjects (also see Figure 1). The representation of the lower extremity, such as toes, foot and genitalia is located on the top and medial surface of the brain hemisphere. Adjacent to the representation of the lower extremity is the upper extremity with a large area devoted to the hand representation. The face, tongue, pharynx and abdomen’s representations are located in the lateral and inferior portions of the hemisphere. Overall the tongue and lips have the largest postcentral representation followed by the hand. Penfield and Rasmussen also observed that the relative length of cortex devoted to any one structure showed variation from one person to another, thus it was impossible to identify a particular body region with measurements of well defined anatomical landmarks. This painstaking work resulted in the drawing of the sensory homunculus as ”the little man in the brain”, and provided the foundation for present day somatosensory cortical mapping. Penfield and Rasmussen’s work did not go without criticism. They were criticized for rigorous textual descriptions of the effects of stimulation of the brain which were rendered into a simplified drawing of “the little man in the brain”. By some this effort was considered an extraordinary conceptual leap (6). Furthermore later renditions of homunculi were considered less and less topographically accurate (6) minimizing the precision of earlier mapping efforts. Nevertheless, the work by Wilder Penfield and colleagues revolutionized our understanding of cortical localization in somatosensory cortex and other brain regions. Today Penfield’s intraoperative cortical stimulation (ICS) and somatosensory evoked potentials (SSEPs) are still widely used to localize function in the primary motor and somatosensory cortices.

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Courtesy of MacMillan Publishing.

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Figure 1. Somatosensory homunculus showing the somatotopic map of the human body in postcentral gyrus. The length of the lines underneath the cortical drawings indicate a comparative extent of each individual representation. (Penfield and Rasmussen, 1950).

3. Invasive Intraoperative Methods Intraoperative mapping of brain function is necessary to avoid surgical removal of functional brain tissue. It is a tool that increases the precision of neuronavigation and decreases neurological deficits after surgery. Until recently functional localization for surgical purposes has solely relied on invasive intraoperative cortical stimulation (ICS) and/ or somatosensory evoked potentials (SSEPs). Both ICS and intraoperative SSEPs are considered invasive because they involve the surgically exposed cortex and, in the former, require that the patient is awake and interactive for the mapping procedure. Although originally developed to treat patients with severe epilepsy (1,2) ICS was also used to explore the functional anatomy of the brain and identify somatosensory and somatomotor cortical areas to be excluded from surgical removal. Prior to ICS an additional craniotomy is required to implant an electrode grid. For ICS electrodes are placed directly on the exposed surface of the brain and electrical stimulating currents between 2 to 4 mA are applied to the cortex for somatosensory or motor stimulation (7). This electrical stimulation can be used to elicit sensations and/or interfere with a voluntary response or stimulate a

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voluntary response. Therefore it assesses the necessity of a particular brain region for a given task directly. Compared to noninvasive presurgical neuroimaging techniques such as fMRI, ICS is still considered the current “gold standard” in identifying eloquent brain tissue. The rationale for this approach is discussed in the section on presurgical mapping of the somatosensory cortex with fMRI. The SSEP method can be used to evaluate both the central and peripheral nervous systems (8). SSEPs are more commonly used to assess sensory pathway dysfunction and demyelinating diseases such as multiple sclerosis but have also played a role in intraoperative monitoring and central sulcus localization. SSEPs consist of a series of waves that reflect sequential activation of neural structures along the somatosensory pathways (9). Typically a patient is stimulated with electrical current at various sites of the body including the median nerve at the wrist, the peroneal nerve at the knee and/ or the tibial nerve at the ankle and recording electrodes are placed on the cortical surface. The recorded potentials called evoked potentials are the electrical signals generated by the nervous system in response to these electrical stimuli. The SSEP waveform has different components, for example a negativity 20 milliseconds after median nerve stimulation (the so-called N20) localizes to the lateral parietal area whereas lower limb stimulation results in maximal responses near the midline. A benefit of using SSEPs is that the central sulcus can be localized under general anesthesia (10) which is beneficial for brain surgery. Although accurate, invasive measures such as ICS and intraoperative SSEPs suffer from several disadvantages that make the development and validation of alternative methods important (11). Noninvasive neuroimaging techniques such as positron emission tomography (PET), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are considered complementary techniques to ICS. Currently, experiments are conducted to validate these methods against the current “gold standard” ICS (12-17). Apart from the invasiveness of ICS and intraoperative SSEPs, functional and anatomical information is obtained intra-operatively and cannot be used to extensively evaluate and plan the surgical approach ahead of time. These shortcomings have opened the doors for noninvasive presurgical neuroimaging techniques.

4. Noninvasive Methods of Somatosensory Cortex Mapping While invasive methods provide direct measures of neuronal activity, they are not very suitable for studying S1 function in human subjects. Therefore neuroimaging methods have rapidly advanced to allow noninvasive study of the brain. Neuroimaging techniques can be classified according to the type of information they reveal: structural, biochemical, or functional. Structural techniques can provide anatomical information regarding shape, size and tissue density. Biochemical techniques can reveal information about the local chemical environment of tissue such as the relative concentrations of metabolites, amino acids and neurotransmitters. This type of information can provide insight into the physiology of the tissue and signal revealing if there is likely potential tumor development or necrosis. Functional techniques can reveal information on the location and time of neuronal activity

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associated with a related task or stimulus. These techniques can provide direct (EEG, MEG) or indirect (BOLD fMRI, PET) information about neuronal activity. Below we will briefly review these techniques and provide some examples of how they have been applied to the study of S1.

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4.1. Structural Neuroimaging Several magnetic resonance imaging (MRI) methods are employed in both research and clinic to study not only structure, but also to obtain information about the biochemical environment and function. All these techniques are based on the same principles and require the same equipment. The MR imaging technique requires a static external magnetic field, a variable magnetic field and radiofrequency (RF) pulses. When a sample, containing protons is placed in a strong magnetic field, the majority of protons align with the main magnetic field. Since water contains hydrogen and is found in abundance in the human body, this phenomenon can be applied to study living organisms. Along with the external magnetic field a radio-frequency (RF) pulse is applied to excite protons. Once the RF pulse is removed, the energy gradually dissipates causing the protons to relax and realign with the main magnetic field (18). Time-variable magnetic fields are applied to spatially encode the proton signals. Proton relaxation, which depends on tissue properties, can be exploited to achieve the contrast in MR images. Readers interested in details of MRI are referred to: (18). Most human MR systems allow images with a resolution of about 0.5mm in plane and a slice thickness of about 2mm. The higher the magnetic field the better resolution can be obtained within the same time. High resolution anatomical MR images can be used for measurements of structural dimensions, volume, and thickness in S1. For example, using cortical thickness analysis, Schaechter and co-authors demonstrated increased cortical thickness and functional reorganization in S1 of chronic hemiparetic stroke patients (19). Diffusion tensor imaging (DTI) is a relatively novel structural tool that allows for the assessment of white matter fiber tract integrity. Ultimately the combination of anatomical and functional imaging with DTI will provide a powerful means not only to assess S1 grey matter anatomy and function, but also its underlying white matter fiber tract architecture.

4.2. Biochemical Neuroimaging Biochemical neuroimaging can be obtained by using so called magnetic resonance spectroscopy imaging (MRSI). This technique is used for observing the local chemical environment within a region of interest (ROI). Specific metabolites can be used as markers of a disease. For example, the presence of N-acetyl aspartate (NAA) is considered a marker of neuronal health as it associated with functioning mature neurons. Other metabolites of interest include lactate (LAC), choline (Cho), creatine and phosphocreatine (CR/PCr), myoinositol, glutamate, glutamines, GABA are markers of cellular energy, status of cellular membranes or integrity of myelination.

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The advantage of this technique, in comparison to MRI, is that it offers additional insight into the integrity and state of the neural tissue rather than structural information alone. However, the sensitivity of MRSI is limited. Voxels of interest are usually 1 x 1 x 1 mm or larger. MRSI has been applied to research of S1 to observe biomarkers of neuronal and axonal health. Ertem et al. (2005) evaluated NAA and Cho/Cr in S1 of amputees who have undergone a limb replantation or revascularization (20) and found no significant degeneration of the myelin sheaths in S1 as there were no significant differences in Cho/Cr compared to the control group. MRSI has also been used to relate the level of functional activity in S1 with the level of NAA in multiple sclerosis patients (21). Thus the analysis of specific neuronal markers and metabolites can serve as an indicator of the state of S1 tissue in health and disease.

4.3. Functional Neuroimaging

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Functional neuroimaging techniques can be classified based on the source of the collected signal. Direct methods, such as EEG and MEG, record a signal directly related to the neuronal electrical activity. Similarly, TMS disrupts neuronal activity directly to observe a behavioral outcome. We will describe the most common direct methods: EEG, MEG and TMS. Indirect methods detect signals caused by physiological changes in, for example, glucose metabolism or hemodynamics due to neuronal activity. Indirect methods reviewed include PET, NIRS and fMRI. Although a discussion of multimodal imaging is beyond the scope of this chapter, it is noteworthy that research efforts designed to integrate the different techniques can overcome the limitations inherent to each technique on its own. 4.3.1. Electroencephalography Electroencephalography (EEG) detects changes in the electrical currents in the brain through recording electrodes placed on the scalp. Because the electrodes are placed remotely to the brain and collect a population response, the detected signal is a sum of both excitatory postsynaptic potentials and inhibitory postsynaptic potentials. The metal electrodes are placed on the scalp in a standard montage. Good contact must be made between the scalp and electrode in order to obtain good signal. An electrolyte or conductive jelly is sometimes used to increase conductivity and electrodes are secured in a tight cap worn by the subject. To investigate brain function in response to a task or stimulus, the analysis of the EEG signal is time locked to the experimental paradigm. Commonly this type of technique is called an event related potential (ERP). Since this technique measures neuronal activity directly, it is able to achieve high temporal resolution, on the order of milliseconds (22). However, the distance between electrodes determines the spatial resolution which is typically lower than some other methods discussed in this chapter. Approaches have been taken to improve the spatial resolution obtainable by EEG including mathematical modeling of the propagation of potentials using MRI and using a large number, between 64 and 128 electrodes (23). Since these electrodes are placed topically, the depth of recording is limited to the superficial layers of the cortex.

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EEG is a tool that has been extensively used to learn about S1. Its applications have ranged from investigations of somatotopy to presurgical planning and the neuronal basis of pain perception. Within pain research, EEG has aided in elucidating the temporal response of pain perception in S1. Jensen (2008) provides some evidence that links the subjectivity of the pain response with smaller amplitudes of slower wave activity (delta, theta, and alpha) and higher amplitudes of faster wave activity (beta) (24). The examination of S1 with EEG also has clinical applications. The high temporal resolution of EEG has been used to identify seizure activity in the primary (25) and secondary somatosensory cortices of epileptic patients (26,27). Despite the advantage of the high temporal resolution, additional investigations with methods that offer greater spatial resolution will be of benefit to the study of S1. 4.3.2. Magneto encephalography (MEG) Similar to EEG, Magneto encephalography (MEG) utilizes the electrical signals of neuronal activity. However, MEG detects small magnetic field oscillations that are generated by the extracellular electrical currents. As this technique relies on the electrical signals, it possesses some of the same advantages as EEG including high temporal resolution, but is also limited in depth of recording. The spatial resolution of MEG is better compared to EEG as it is unaffected by skull irregularities. However it is lower than that of other methods discussed in this chapter. MEG has been applied to investigate several dimensions of sensory processing including somatotopic organization, pain perception and analgesia. While the somatosensory homunculus may seem quite established, recent research has revealed interesting influences on the way in which regions of S1 become active. For example, Schaefer and authors (2008) used MEG to investigate S1 topography of the neuronal response during touch while manipulating the visibility of the stimulation (28). When participants viewed the stimulation, the authors found a significant shift in the location of S1 activity compared to a control condition. Furthermore, adjusting the view by magnification also resulted in changes in the location of S1 activity. The authors suggest that these alterations in S1 topography are reflective of the influence from visual brain regions (28). MEG has also been used to study S1 in the fields of pain and acupuncture. In healthy individuals, observed field oscillations in S1 have been related to the intensity of an evoked noxious stimulus and perceived pain ratings (29). The group shows that gamma oscillations correlate with the subjective perception of pain. Another application involves the use of MEG to reveal modulation of S1 activity during acupuncture (30). Together these studies illustrate the ability of MEG to reveal behavioral modulations of S1 activity as reflected by changes in the location and amplitude of the MEG signal. 4.3.3. Transcranial Magnetic Stimulation (TMS) Transcranial magnetic stimulation (TMS) maps the function of brain areas by inducing a temporary disturbance in a localized, targeted area. A TMS device consists of a hand-held simulator coil that is connected to a charging unit. A brief (one millisecond) electric current is circulated through the coil when it is applied to the scalp creating a perpendicular magnetic field. The magnetic field induces an electric field that lasts tens of milliseconds. The electric field causes depolarization of the underlying neurons creating a temporary "virtual" lesion (31). The spatial resolution of TMS is approximately 0.5-1 cm (32) and the penetration depth

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is 2 cm (33)). For a comprehensive review of the details involved in TMS methodology see Sack and Linden (34). An advantage of this technique is that it allows delineation of the relationship between brain and behavior by modifying activity of specific brain regions. Secondly, the temporary "virtual" lesion can be replicated across healthy subjects and individuals can be used as their own "normal" control, offering an advantage over typical lesion studies which have inherent variations of location and severity. Finally, by applying the pulse at different times of a task, one can delineate whether the brain region plays a critical role at a particular phase of the task. In contrast to functional neuroimaging techniques that observe brain activity widely, TMS can determine the involvement of a specific region by temporarily disrupting its function and evaluating the subsequent effects. During the use of other neuroimaging techniques it is often assumed that the areas that are observed to be active are task related, which may not be the case. They could be active coincidentally or caused by factors not related to the task. TMS is limited, even though the response of the area of interest is mapped, it is not known what effects may exist in other regions of the brain that are influenced by the targeted area. There are also some safety concerns that have been raised as there are some reports of seizures following repetitive TMS (rTMS). However, to address this, safety guidelines have been published (35); (36). TMS has been used to investigate the influence of sensory information on other motor and perceptual tasks. Applying repetitive TMS (rTMS) to the region of the somatosensory cortex representing eye proprioception elicits errors in eye position, a behavior used in locating a visual target (37). As this area has previously only been studied in non-human primates, TMS offers a unique tool for revealing similar systems in healthy humans noninvasively (37). Also, application of TMS to the face region of the somatosensory cortex resulted in difficulties in perceiving facial expression while application to the finger area of the somatosensory cortex had no significant impact (38). TMS may not be as widely used as other neuroimaging techniques but its application has revealed interesting roles for S1 in sensory feedback for motor control and perception. 4.3.4. Positron Emission Tomography (PET) PET imaging uses the hemodynamic response to identify an area of activity by observing the temporal and spatial distribution of a radioactive contrast agent. In PET imaging, radiolabeled oxygen and glucose are commonly used. 2 deoxy-1-18F-D-glucose (FDG) PET identifies regional cerebral metabolic rate of glucose and offers good spatial resolution. The advantage of using a radiolabeled contrast agent is that the amount injected is precisely measured and it can be sampled by taking a blood sample to quantify the metabolism of the tracer. However, both administering contrast agent and blood sampling make these techniques more invasive than some other functional neuroimaging techniques. The requirement of radioactive tracer is limiting in other respects. First, there are restrictions in the amount of tracer a subject can be exposed to. This limits the number of times a person can be scanned or the length of time a person can be scanned. Finally, the available scan time is also restricted by the half-life of the contrast agent.

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Since these techniques rely on the hemodynamic response for distribution of the tracer, rather than measuring neuronal activity directly, the temporal resolution is lower than that of EEG and MEG. However, the spatial resolution of these techniques, especially FDG PET, is higher than that of electrophysiological methods. As PET imaging is an established technique and offers good spatial resolution, many aspects of S1 function have been investigated including S1 somatotopy, functional plasticity and pain. Details of this work will not be discussed, however some interesting applications are introduced below and the reader is referred to Chapter 2 by Kornelsen and Tomanek (2009) in this book to read more about some S1 PET studies in the area of pain. The use of PET imaging has been integrated with rTMS to investigate the role of S1 in crossmodal plasticity in subjects with blindness (39). In crossmodal plasticity one sensation is lost and the corresponding brain region is reorganized and then performs another function. For example, in subjects with congenital blindness, somatosensory stimuli also activate the visual cortex. Wittenberg and authors applied rTMS to stimulate S1 and used PET to map the resulting functional network in blind subjects. RTMS stimulation of S1 resulted in visual cortex activity only in subjects who became blind early in life and not in those who became blind later in life (39). The use of rTMS with PET emphasizes the benefit of combining neuroimaging techniques to more fully characterize the involvement of S1 in particular diseases or disorders. Recently, PET imaging has also offered a window into S1 function in patients who are minimally conscious (40). Patients who are minimally conscious demonstrate some awareness of themselves and their surroundings (41) in contrast to patients who are in a persistent vegetative state and are without this awareness (42). Boly and others used PET to examine S1 and other neuronal responses to a noxious stimulus in patients of both classifications. (40). The authors demonstrate that minimally conscious individuals show similar S1 activation to healthy controls and significantly more than patients in a persistent vegetative state. These results suggest that S1 function is preserved in patients who are minimally conscious and emphasize the clinical utility of PET. 4.3.5. Near Infrared Spectroscopy (NIRS) Near infrared spectroscopy (NIRS) takes advantage of an endogenous contrast agent: regional changes in blood oxygenation. NIRS is an optical method which transmits two specific near-infrared wavelengths of light (650-950 nm) and is sensitive to the differential light absorption and reflection of oxygenated and deoxygenated blood (43). A distinct advantage of this technique over some of the other methods discussed is the portability of the device. As a result NIRS may be able to study responses in a more natural setting. The spatial resolution is also limited, approximately three centimeters or more (44). Because this technique relies on the absorption of light, skull thickness restricts the depth of recording to a few centimeters (45). NIRS has primarily been used to investigate motor and visual responses (46). However, recently there has been one study that has demonstrated that NIRS can be applied to study S1 function (46). Using median nerve stimulation, the group was successful in eliciting an observable response in contralateral S1. As NIRS has not been

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widely used to investigate S1, its potential as a research tool for this brain region has not been fully realized. 4.3.6. Functional Magnetic Resonance Imaging (fMRI) MR techniques can also be used to investigate regions of brain activity. Functional MRI (fMRI) detects areas of activity based on changes in blood flow, volume, and oxygenation. The most widely used method of fMRI is based upon the Blood Oxygenation Level Dependent (BOLD) effect (47). Deoxygenated blood is paramagnetic which results in field inhomogenities and therefore signal loss. Oxygenated blood is diamagnetic. This difference in magnetic susceptibility can be used as a source of image contrast. Neuronal activation causes local increased blood flow and decrease in the ratio of deoxygenated and oxygenated blood observed as signal intensity increase with MRI (see Logothesis and Pfeffer for review, (48)). By analyzing the time course of changes in signal change, one can identify regions that are task or stimulus related. As the fMRI signal relies on the hemodynamic response the temporal resolution is lower (in the matter of seconds) than the electrophysiological techniques discussed earlier. FMRI is also much more expensive than some of the other methods discussed in this chapter. There are additional difficulties in the complexity of the study design and the unnatural setting of the scanner as the experimenter must consider all variables that may influence the subject’s attention during the study. However, these issues are not unique to fMRI, and must also be considered during the application of the other methods discussed in this chapter. FMRI is an ideal tool to study function in the primary somatosensory cortex. In contrast to PET the endogenous BOLD contrast allows for repeated measures. Although limited in temporal resolution, the spatial resolution of fMRI is also superior to that of other noninvasive imaging techniques and allows for more detailed investigation of functional architecture. This is crucial in studies of S1 somatotopy, where the distinction of small somatosensory regions such as individual fingers for example, require high spatial resolution imaging. High spatial resolution has also made fMRI the tool of choice for presurgical mapping. The use of fMRI for investigating S1 somatotopy and the application for pre and intra- operative mapping are the topics of the next sections.

5. FMRI of Somatotopy in Primary Somatosensory Cortex 5.1. Brief Anatomy of the Primary Somatosensory Cortex The primary somatosensory cortex (S1) is located in the anterior parietal cortex, in the posterior bank of the central sulcus and encompasses four Brodmann Areas (BA). Human somatosensory areas BA1, 2 and 3 are depicted in Figure 2. BA 3 is further divided into BA 3a and b.

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http://en.wikipedia.org/wiki/Postcentral_gyrus

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Figure 2. The primary somatosensory cortex (S1) in the anterior parietal cortex of the posterior bank of the central sulcus. This image depicts somatosensory cortex encompassing BA1 (green) BA2 (yellow) and BA3 (red).

A complete map of the body surface exists in each of the four areas of S1 in old world monkeys and thus it is assumed that four homunculi exist in human S1 (49). The various regions of the body are represented somatotopically in specific portions of the postcentral gyrus. As such the face area lies in the most ventral part while above it are the sensory areas for the hand, arm, trunk and leg and foot (see Figure 1). Each brain area has specific connections to skin, joint and muscle receptors with body representations reflecting sensory receptor densities and not size of different body parts. Cortical areas representing the hand, face and mouth regions are disproportionately large. For the hand, thumb and index fingers are particularly well represented. Although the face occupies a large part of the lower postcentral gyrus there is still some disagreement about its exact topography. Similar controversies exist in regards to foot and genital S1 topography. The high spatial resolution of fMRI provides new opportunities to explore the details of S1 somatotopy including the representation of the hands, fingers, face, feet and genitals.

5.2. FMRI of S1 Hand Representation Somatosensory mapping of the hand and more precisely of the finger areas in S1 has several interesting and important applications beyond its application as a presurgical tool. An understanding of the functional brain changes after hand injury or loss can contribute to the optimization of rehabilitation strategies. Somatosensory mapping of the hand can also provide crucial information about brain-hand neural networks involved in the field of intelligent hand prosthesis (50). Therefore there are a relatively large number of fMRI studies that have investigated the somatotopy of the hand and fingers in S1. The hand representation in S1 is not limited to one, but multiple areas. Using intraoperative cortical mapping Penfield found evidence of two separate representations of the hand (2). Furthermore studies of nonhuman primates have revealed that each cytoarchitectonic subdivision of S1 (areas 3a, b, 1 and 2) has its own fairly complete representation of the body surface (51). The representation of the hand down to individual

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fingers in S1 has been assessed using a variety of stimuli including electrical, mechanical, vibratory, air puffs, manual rubbing, piezoceramic stimulation and brushing (50,52-61). A generally consistent finding among these studies is that sensory stimuli on the hand and finger regions result in the activation of contralateral area 3b. A more recent finding using fMRI showed that the steady activation in contralateral S1 is accompanied by a more transient deactivation in ipsilateral S1 (see Figure 3) (62).

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Figure 3. Group-level analysis of activations to stimulation of right-hand fingertips. In the colour scale, yellow and red refer to activations, and blue and green refer to deactivations. L, Left; R, Right; Contra, contralateral; Ipsi, ipsilateral. Red, green and blue in the graph refer to the different tactile stimulation frequencies used.

In addition to the well known activation in contralateral S1, a small activation cluster appeared in ipsilateral area 2 and a deactivation in ipsilateral area 3b and primary motor cortex. The authors suggest that this deactivation can be explained by decreased neuronal activity as a result of interhemispheric inhibition and may play a role in improving left versus right differentiation of touch during cooperative bilateral hand actions. These results were corroborated by Eickhoff et al., (2008) who report that tactile stimulation of either hand resulted in deactivation of ipsilateral areas 3b and 1 (52). Eickhoff et al. (2008) furthermore provide evidence for ipsilateral processing of information from the right hand in area 2. Both studies detail activation and deactivation patterns in S1 due to sensory stimulation of the hands or fingers, but do not report on the somatotopy of individual fingers. The effort to image individual fingers using fMRI started in the mid 90s. Using a textured surface to rub the fingertips Lin et al. (1996) reported multiple activation foci in S1 (58). In a comparison of stimulating one versus three digits the activation extent differentiated the two suggesting that the spatial resolution of fMRI is adequate to differentiate between digits in S1. Then Kurth et al. (1998) showed that electrical stimulation of single fingers can be detected using fMRI (59). The group reports separate somatotopic S1 locations of digits 2 and 5 in five out of fourteen subjects demonstrating that the differentiation between single fingers is possible in at least a subgroup of subjects. Gelnar et al (1998) followed up on these observations and used higher spatial resolution to study the

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representation of individual fingers in S1 (54). Using vibratory stimulation on digits 1, 2 and 5 did not result in any major differences in individual digit representation however the authors report significant differences in incidence of activity across all four S1 subregions corresponding to 3a, b, 2, and 1. The authors do not report a medial to lateral digit representation in individual subjects but do comment that the spatial distance differences between the center-of-mass coordinates for the activated regions of interest (ROIs) were the greatest between digit 1 and 5, with the latter being located more medially on the postcentral gyrus. To improve upon demonstrating somatotopic organization of individual digits Maldjian et al. (1999) used a 4 Tesla MRI which provides high spatial resolution and high signal change for fMRI studies (60). Using a low frequency vibratory stimulus on the pad of each finger of the left hand, the group was able to show that the thumb to fifth digit were organized somatotopically in a lateral to medial, inferior to superior, and anterior to posterior relationship in three out of five subjects. The authors comment that the resolution wasn’t sufficient to explore separate activation foci in areas 3a, b, 2, and 1. Francis et al (2000) observed separation of digits 2 and 5 at 3T and also advise the reader that “hotspots” appearing in areas 3a, b, 2, and 1 should be interpreted at best as premature findings since it is often unclear with what confidence a given activation cluster can be assigned to a specific S1 subarea (53). Another study at 3T (61) using larger subject numbers showed activation in area 3b for all fingers in 17 out of 18 subjects. At the individual level a somatotopic relationship was present for the thumb and little finger, with a higher variability for the fingers in between. Most recently, Weilbull et al. (2008) compared low (3 mm3) and high (2 mm3) resolution fMRI of finger somatotopy at 3T (50). At 2 mm3 voxel volume, activation of the thumb, middle finger and little finger areas was seen in 89%, 67% and 50% of volunteers compared to 78%, 61% and 33% at 3 mm3. In the group analysis significant activation for the little finger was absent at 3 mm3, however all three fingers showed significant S1 activation at 2 mm3. The authors also suggest that the use of a large smoothing kernel is disadvantageous when investigating small, localized and highly detailed functional regions such as the finger areas in S1. In contrast to using a 4 mm smoothing kernel with the high resolution data, using an 8 mm smoothing kernel width resulted in the absence of activation. FMRI offers a unique view of the somatosensory hand and finger regions. However, fMRI studies differ considerably in regards to numbers of subjects, magnetic field strength and accompanying differences in signal to noise ratio and spatial resolution, paradigm design, as well as anatomical considerations and data analysis. Recent studies (50,61) have used larger subject numbers (≥ 20) optimizing statistical interpretation in comparison to relatively low subject numbers in earlier fMRI studies. High field strength (≥ 3T) acquisitions have enabled voxel sizes of 2 mm3 allowing investigations of more detailed somatotopic cortical architecture of the hand and finger regions (50). Low spatial resolution can limit the interpretation of highly detailed somatotopic fMRI data. In addition to the lack of high resolution data to assess detailed finger somatotopy, there is an absence of fMRI studies assessing S1 subregional responses to stimulation of different subclasses of peripheral somatosensory receptors. Such studies could provide some insight into the functional distinctions between areas 3a, b, 2 and 1 (63).

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5.3. FMRI of S1 Face Representation Due to their behavioral relevance, somatosensory mapping of the hands has been the main focus of neuroimaging research. Therefore there are a more limited number of fMRI studies examining the S1 cortical representation of the face and trigeminal system. The clear geometry of the trigeminal system with its three divisions (ophthalmic-V1; maxillary-V2 and mandibular-V3) provides unique advantages for investigating the somatotopic representation of the face region in S1. Mapping the S1 face region has applications in investigations of cortical reorganization and plasticity after injury or disease as well as a number of painrelated diseases that affect the trigeminal system including neuropathic pain and migraine (64). Using intraoperative cortical stimulation Penfield and Rasmussen (1950) have shown that the contralateral face is represented in an upright manner in S1, such that the region of the forehead (V1) for example, is located superiorly to the region of the chin (V3). In contrast to several neuroimaging studies that have supported this observation, there are also fMRI reports of an inverted face representation (65) a representation involving spatial overlap between trigeminal divisions V1 and 3 (66) and most recently a face representation in human S1 that is mapped in a segmental pattern (67). Using a most sophisticated MR-compatible dodecapus device to study S1 somatotopy to multiple (12) facial stimulation sites Huang and Sereno (68) demonstrated that the contralateral face is organized upright in S1. The authors discuss multiple representations of the contralateral face, lips and fingers in areas 3a, 3b, 1 and 2, and suggest, although they were not able to positively distinguish the representations in the separate sub-regions, that the repeated representations of particular face, lip and finger activation locations strongly support multiple representations in S1. On the contrary, in an earlier study, Servos et al (1999) presented fMRI data on five subjects that provided support for the hypothesis that the representation of the face in human S1 is upside down (65) and not upright as demonstrated by others (2,68). The authors suggest that Penfield’s map should be revised to include an inverted face orientation. FMRI studies using noxious heat to stimulate the face support these observations (69,70). It is worth to mention that there are very interesting fMRI studies on phantom limb pain supporting an upside down topography of the face (71,72). Patients with phantom limb pain showed a shift of the lip representation into the deafferented primary motor and somatosensory hand areas during lip movements. This displacement of lip representation positively correlated with the amount of phantom limb pain and also suggests that the lip and hand are located in close proximity to one another. In another effort to investigate the controversial results regarding facial somatotopy, Iannetti et al. (2003) examined activations in response to stimulated areas on the forehead (ophthalmic trigeminal division V1) and lip (mandibular trigeminal division, V3) and did not find an upright or inverted S1 face representation but instead report an overlap of V1 and V3 activations in S1(66). Iannetti et al., (2003) point towards converging evidence that the face representation within S1 is far more complex and also different than described in the initial homunculus. Supporting this theory are microelectrode recordings in monkeys that show that cortical fields responding to stimulation of different facial territories have an irregular shape and lie intermingled (73). Moulton et al., (67) also propose a more complex, but segmental

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organization of face representation in S1. Sensory processing in the trigeminal nucleus is represented in a segmental rostro-caudal manner (ophthalmic, maxillary, mandibular) and the information conveyed by the trigeminal nerve divisions appears to converge and reorganize in the trigeminal nucleus conforming to a dermatome “onion-skin” model (69,74). Using five separate stimulation sites on the right face, Moulton et al. (2007) were able to obtain topographical activation foci in S1 in support of this model. Based on the fMRI studies cited above, there is still a lot of controversy about the exact nature of the topographical representation of the face in S1. FMRI studies using multiple facial stimulation sites are few, underlining that the recent effort by Sereno and Huang (2007) using their dodecapus device is a step in the right direction. Since the majority of fMRI studies have used block designs to study S1facial somatotopy, Dresel et al. (2008) tested an event-related paradigm as many studies have shown a top-down-modulation of stimulus-induced activations by subject-inherent factors such as anticipation, habituation and attention(75). In their study Dresel et al. (2008) used a novel device that employs von Frey filaments to deliver punctate tactile stimuli to the face and other body surfaces. Two different experimental paradigms were tested a block and an event related fMRI design. Even though punctate tactile stimulation of the upper lip and thenar eminence of the hand activated S1 and S2 during both experimental designs, no significant S1 activation was detected during the block-wise stimulation of the face in three subjects. S1 face representation could be identified in all individual subjects during the eventrelated design. The authors suggest that block designs are generally more susceptible to the confounding modulatory effects of anticipation and habituation (76,77). They also advocate that event-related designs are more sensitive to detection of S1 activation in certain subjects as they are known to better control for such modulatory factors. There is only one fMRI study that has investigated the mouth region including the tongue, lip and teeth (78). The authors report that tooth representation is located superior to that of the tongue and inferior to that of the lip in the rostral portion of S1. Compared to rostral portions of S1, the somatotopic organization of these structures was less distinct and showed more activation overlap in middle and caudal portions of S1 providing support for the theory that the input from oral structures converges hierarchically across the primary somatosensory cortex. Aside from the somatotopic representation of the oral region in S1, Guest et al. (2007) provide fMRI results that show that oral temperature is represented in human primary taste cortex in the anterior insula as well as primary somatosensory cortex (areas 1, 2 and 3)(79). The authors show activation foci to oral temperature, but not taste, in S1, demonstrating that not all temperature representations are in the insula but also include S1. The ability to precisely characterize the topography of the facial region in primary somatosensory cortex shall benefit from some of the advances cited above. Some of these advances have focused on optimizing experimental design: The ability to stimulate multiple regions of the face will allow for better characterization of the face region including its trigeminal branches V1, 2 and 3. Using multiple facial stimulation sites may also contribute to our understanding of an upright versus upside down or segmental S1 face representation. The increased sensitivity of event-related designs can provide better detection of activations

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by controlling for individual modulatory responses such as anticipation or habituation which is particularly important in individual subject analyses.

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5.4. S1 FMRI of Foot and Genital Representation Combining foot and genital somatotopy in S1 into one section may seem like a misfit, however there are two reasons for that. The first reason is the limited fMRI literature on foot and genital somatotopy in S1 and the second reason is the proximity of the two areas in Penfield’s somatosensory homunculus with the genitals located below the foot in the mesial wall of the interhemispheric fissure. The interest in mapping the genitals has largely been in relation to sexual arousal and penile erection (80,81) to explore the central nervous system as a potential site for erectile pathology and as a therapeutic target. Neuroimaging studies of sexual stimulation or watching erotic movies (81-83) show increased activity in regions associated with emotion and motivation components as well as endocrine/autonomic components of the response. In these neuroimaging studies of sexual arousal S1 did not figure prominently. In terms of somatotopy of the penis in S1 there are neuroscience studies that report some conflicting results either assigning the penile representation to the mesial wall or to the convexity of the contralateral hemisphere. An fMRI study (84) has re-examined the cortical representation of the penis in human S1 and studied its topographical relationship to that of adjacent body parts. The authors questioned the violation of somatotopic continuity and ask the same question as Foerster (1936) in terms of why the genitals should be represented below the toes (see Figure 1) (85). They furthermore note that only three out of the 400 patients examined by Penfield and Rasmussen (1950) reported genital sensation when receiving electrical stimulation of the cortex adjacent to the central fissure. In Kell et al.’s (2005) study brushing the skin of the penis, big toe and lower abdominal wall evoked significant focal activations in contralateral S1(84). Responses to toe stimulation observed with fMRI were located on the contralateral postcentral gyrus at the medial edge of the convexity but did not descend along the mesial wall. The sensory representation of the penis co-localized to an area about 1cm lateral of the toe representation and overlapped with that of the lower abdominal wall. The authors conclude that the lower half of the body is confined to the convexity of the hemisphere along the postcentral gyrus and does not extend into the mesial interhemispheric fissure and propose a refined version of Penfield and Rasmussen’s somatosensory homunculus where the male genitals are represented between the legs and trunk. These findings should be observed with caution since they can have implications for the interpretation of neuroimaging studies that have used genital or foot S1 representation in the mesial interhemispheric fissure in the context of sensation and/or pain.

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6. Presurgical Mapping of Somatosensory Cortex with fMRI A variety of fMRI stimulation protocols are routinely used for presurgical brain mapping in patients with tumors. The paradigm used depends on the location of the tumor and most often involves finger tapping to map the central sulcus region and motor cortex, verbal tasks to identify Broca’s and Wernicke’s areas for language lateralization and a visual checkerboard-type stimulus to identify eloquent visual cortical areas. Sensory paradigms designed to identify the primary somatosensory cortex are less frequently used. However, the identification of the central sulcus which is sandwiched between the primary motor cortex and the primary somatosensory cortex is crucial for neurosurgical procedures involving the central sulcus region. Stippich et al. (2007) provide selection criteria of candidates for presurgical motor and somatosensory fMRI when neurological symptoms indicate an involvement of the sensorimotor cortex and when insufficient information is yielded from morphological imaging (86). The first involves the inability to identify the MR-morphologic central sulcus landmarks due to tumor growth. In these patients both pre- and postcentral gyri are impossible to localize based on morphological criteria alone and fMRI can provide somatotopic motor and sensory mapping. For the second criterion the central sulcus region is morphologically localizable but the precentral “motor-knob” is no longer clearly identifiable because of shift or compression by the tumor. In this case somatotopic mapping of the postcentral gyrus can increase the precision of localization. Thirdly, if the tumor lies directly above or below the motor hand area, somatotopic mapping will allow for better estimation of surgery-related neurological deficits. And finally if there is a discrepancy between morphological findings and the clinical status of the patient, such that there is no neurological deficit despite verifiable tumor growth into the central sulcus region, mapping motor and somatosensory cortex can provide additional information about eloquent brain tissue. Thus the addition of a somatosensory task can add to the precision of central sulcus localization. Yetkin et al. (1995) were the first group to demonstrate that passive tactile stimulation can be a useful adjunct to motor tasks when mapping sensorimotor cortex(87). In this work the authors report that the activated regions identified by somatosensory and motor tasks coincide in the majority of patients. Indeed, recently Overduin and Servos (2008) observed that cutaeneous stimulation of the thumb and index fingers resulted in symmetrically distributed somatosensory and motor cortex BOLD responses (88). Penfield and Rasmussen’s (1950) early brain mapping efforts also showed that motor responses may be elicited by stimulating somatosensory cortex and vice versa. It is also likely that the task used by Yetkin et al (1995), a finger – thumb tapping task, has sensory/touch and movement components and therefore activates pre- and postcentral gyri. This possibility is highlighted in Figure 4 in a subject performing a bilateral finger – thumb tapping task where both pre and postcentral gyri are activated.

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Images were obtained with a 3T Siemens clinical scanner at the National Research Council Institute for Biodiagnostics.

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Figure 4. Bilateral finger-thumb tapping activations are displayed on a single subject T1-weighted anatomical image. Red to white colour scale activations are motor and sensory activations in response to right hand finger tapping and blue-green colour scale activations are motor and sensory activations in response to left hand finger tapping.

This work suggests that in surgical mapping both motor and sensory tasks may be employed to optimize the detection of the sensorimotor region and minimize the risk of technical failure (17). In a more recent effort to provide an integrated battery of preoperative fMRI tasks Hirsch et al. (2000) evaluated, among other tasks, active motor and passive sensory tasks in healthy volunteers and surgical candidates (89). While both tasks were 100% effective in the healthy control population, the tactile stimulation task revealed activity in the primary somatosensory cortex in 94% of patients with lesions in or close to the motor strip, whereas the finger-thumb tapping task predominantly demonstrated function in the area of the precentral gyrus in 89% of patients. When central sulcus localization was based on combining the motor and sensory tasks, the central sulcus was identified in 97% of cases. The authors suggest that using more than one task allows isolation of eloquent cortical areas with improved confidence and sensitivity. As such the addition of a sensory task translates into a greater likelihood of a successful map for patients undergoing surgery near the central sulcus. Somatosensory fMRI is also useful in patients with moderate to severe motor-deficits. These deficits may arise when the tumor invades primary motor cortex and/or the patients suffer from a moderate to severe paresis involving the hand (or other limb) rendering them unable to perform a motor task appropriately (90). Patients may also suffer from musculoskeletal, language, or attention problems that limit their ability to perform the motor tasks precisely as instructed (17). In such situations alternative mapping strategies are needed. Many presurgical brain mapping studies report cases in which motor tasks (such as thumb-finger opposition, fist clenching, sponge-squeezing) can not be used to identify the central sulcus region (90-93). For example, in 18% of patients in which a hand motor task was used to identify the central sulcus region presurgical fMRI was unsuccessful (90). The

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authors report that the failure to obtain a selective and reproducible activation focus was closely related to relevant sensorimotor deficits. Indeed the presence of moderate to severe motor deficits such as a paresis of the involved hand was the main clinical factor associated with poor functional results. These results were corroborated by Dymarkowski et al. (1998) who reported that poor activation quality was related to the patients’ relative inability to perform the motor tasks (93). In one patient who was unable to perform the hand motor task the authors used a sensory stimulus (stroking the hand with a rigid brush) to successfully produce activation in the primary somatosensory cortex. In a more recent large scale study using fMRI for presurgical mapping of the central sulcus region, Krings et al. (2001) report on 103 patients, 68 of which had some kind of motor deficit including paresis, loss of dexterity or ataxia (92). Again, the authors report that failure to obtain functional information was closely related to motor deficits. In 26 of the 30 failed fMRI studies the patient had a paresis of the investigated limb. Moreover the authors report that the degree of paresis was positively correlated with the frequency of motion related artefacts. This literature emphasizes the importance of alternative mapping strategies that do not require movement or “active” tasks involving the hands or other limbs to achieve functional activation and central sulcus localization. Therefore one group in particular (94,95) has been developing and implementing “passive” somatosensory fMRI paradigms involving electrical stimulation of the median and tibial nerves. With this passive paradigm the authors succeeded in identifying the somatosensory cortex and present it as a feasible paradigm for the generation of pre- and intraoperative fMRI (95) which will be discussed below. Although the addition of a somatosensory task in presurgical fMRI has some clear advantages, there are some disadvantages of presurgical fMRI in general that involve the lower spatial resolution when compared to the current gold standard ICS. The weakness of fMRI is due to the origin of the BOLD contrast mechanism. The hemodynamic changes associated with the BOLD contrast occur in the venous side of capillary networks and therefore the detected localization of activation does not exactly overlap with active neurons (15). Furthermore the spatial resolution of MRI and thus fMRI is limited to about 0.5-1mm. On the contrary, ICS directly tests the necessity of a particular brain region for a given task by electrical stimulation and is therefore spatially more accurate. Moreover, it has been shown that the relationship between lesion margin and viable brain tissue is crucial in minimizing neurological deficit due to surgery. The rate of neurological deficit increases the closer the functional activation is to the lesion. A distance of 2cm between the functional activation and lesion border is considered sufficient to avoid neurological deficit after surgery (17). With shorter distances and activations that are immediately adjacent to, or intertwined with the lesion, ICS is the tool to localize function and minimize neurological deficit (15). Thus fMRI is a sufficient presurgical tool when the activation is at least 2 cm distant from the lesion, however when activation and lesion boundaries are closer, the presurgical role of fMRI is to select patients for ICS (15). Another noteworthy drawback of presurgical fMRI involves the occurrence of brain shift during surgery. Correcting for these tissue shifts is a fundamental issue for those involved in stereotactically guided surgical procedures. Image guided surgery systems register presurgical fMRI images to the intraoperative coordinate system of the patient. The resulting maps are used to display the position and orientation of tracked surgical instruments on

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reformatted anatomical and functional image slices and renderings of the brain and anatomical structures of interest (96). The neurosurgeon uses this information to plan a minimally invasive but sufficient surgical approach. The drawback of these image guided surgery systems is that they make the assumption that a patient’s head and brain are fixed in space and time. Several recent studies have shown that this assumption is false (96,97). There is a significant amount of brain shift after the skull is opened and before the neurosurgical procedure starts. Mean shifts of the cortex of 5–10 mm have been reported with maximum shifts of up to 20 mm (96,98). If the brain shift is large enough relative to the amount of surgical precision required, then the overall accuracy of the surgery can be substantially reduced compromising surgical outcome and rendering presurgical fMRI a suboptimal neurosurgical tool. Although efforts are underway to predict brain shift prior to surgery, brain deformation patterns can be extremely complex not only involving the brain surface but also deeper structures that make accurate predictions via simple computational algorithms difficult (96). Furthermore mathematical methods of nonlinear registration and brain shift modeling for localizing functional eloquent brain areas are not yet time-efficient and robust enough to be applied in a routine intraoperative clinical setting (97). Rather than predicting brain shift prior to surgery there are some exciting advances that have concentrated on bringing fMRI into the operating room where images can be acquired post-brain shift and thereby increase the accuracy of neuronavigation.

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7. Intraoperative Mapping of Somatosensory Cortex with fMRI There are several research developments that have contributed to bringing somatosensory fMRI into the operating room. Bringing fMRI into the operating room is not a trivial task and necessitates research into the technical and mechanical aspects of bringing MRI into the operating room or alternatively moving the patient out of the operating room to the MRI suite, the design of fMRI paradigms that can be used in anesthetized patients and the effects of anesthetics on the BOLD response. Although developments of MRI technology have resulted in the introduction of low field open MRI systems into neurosurgical operating theaters, interventional MR scanners often limit the access of the surgeon to the operative field (98) and may involve transporting the patient during surgery. Such transport may affect anesthesia line connections, the sterility of the operating field, increase overall surgery time and potentially cause patient blood pressure changes due to the movement (99). The recent development of a movable 1.5T and very recently 3T MRI magnet placed directly in the neurosurgical operating room makes it possible to successfully obtain pre-, intra- and postsurgical fMRI head and spine images without moving the patient (99,100) Intraoperative fMRI not only avoids the issues associated with brain shift (see section 5), but intraoperative fMRI without patient movement increases patient safety and the ability to obtain functional and anatomical data in real time which increases the precision of neuronavigation. The first effort of moving fMRI into the operating room was provided by Gering and Weber (1998)(101). The authors modified a 0.5T MRI scanner and its real-time controller

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software to obtain real time fMRI finger tapping data in two healthy volunteers. These first attempts were largely followed by German research investigating the feasibility of intraoperative fMRI (102,103). This group in particular has worked on implementing fMRI intraoperatively in patients with centrally located pathology (94,95,102). Initially Gasser et al. (2004) developed a passive sensory paradigm by using simultaneous electrical stimulation of the median and tibial nerves to identify somatosensory cortex in healthy volunteers. This paradigm was effective in 93% of the analyses with activation observed in the contralateral primary somatosensory cortex. The authors concluded that this paradigm is a valuable and effective tool for the identification of somatosensory cortex and can easily be implemented and standardized as a clinical routine. As a next step toward real-time intraoperative fMRI the applicability of the passive paradigm was assessed in anesthetized patients (94,95). Apart from technical issues such as susceptibility artifacts at the air-tissue boundaries of exposed cortical surface impacting image quality, fMRI of anesthetized patients brings its own challenges. As fMRI relies on the coupling between neuronal activity and the hemodynamic response, the type of anesthetic used and its effects on cerebral vasoreactivity all have important implications for the observed signal change (104). Nevertheless using a block design of four alternating rest and stimulation conditions of the median and tibial nerves the group was able to identify sensorimotor cortex in three out of four anesthetized patients with activations in primary somatosensory cortex (BA 3) and primary motor cortex (BA4). Gasser et al. (2005) note a reduced BOLD response under neuroanesthesia with propofol that resulted in less activation of the somatosensory network (95). Compared to their previous study in which nonanesthetized awake volunteers were assessed with the passive paradigm, the mean intensity of the electrical stimuli for the median and tibial nerves had to be increased by 7.1 and 6.2 mA in mean amplitude, respectively to obtain an equally strong blood oxygen level dependent signal in somatosensory cortex (94). Overall the results obtained with intraoperative fMRI look promising. Gasser et al. (2005) were able to deal with susceptibility artifacts originating from air/tissue boundaries by filling the resection cavity with saline resulting in a reduction of field inhomogeneities. Contrary to presurgical paradigms such as motor, verbal or visual tasks, the passive sensory paradigm is more easily adapted intraoperatively in anesthetized patients. Sensory stimulation successfully elicits activations in primary somatosenory cortex and allows for the identification of central sulcus in anesthetized patients. The literature on anesthetics and the BOLD response has been discussed in animal work showing certain analogies (105). Investigations of the human BOLD response under anesthesia, as well as intraoperative studies including larger subject numbers will further validate the use of somatosensory fMRI in the operating room.

8. Conclusion The development of noninvasive neuroimaging methods has opened the door to a variety of techniques that can be applied to the study of S1. While some have been widely used to study S1 anatomy and function, others such as rTMS and NIRS have only recently

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contributed to our understanding of S1 somatotopy. FMRI has been extensively used to investigate the somatotopy of different body part representations in S1. This work has highlighted the complexity of S1 face representation and the necessity of high resolution imaging for detailing the somatotopy of individual fingers. It has also brought to light revisions of the original somatosensory homunculus placing the male genitals and feet somatotopically continuous on the convexity of the contralateral hemisphere. Since Penfield and Rasmussen’s early intraoperative cortical stimulation efforts, S1 brain mapping is back in the operating room. This time invasive measures are replaced by intraoperative fMRI using sensory stimulation paradigms in anesthetized patients to identify the central sulcus. This advance is possible because of research into a) the technical and mechanical aspects of bringing MRI into the operating, b) the design of sensory fMRI paradigms that can be used under anesthesia and c) the effects of anesthesia on the BOLD response. Intraoperative fMRI using a sensory paradigm avoids the presurgical challenges of brain shift during surgery, increases surgical precision and minimizes the distress of a patient who does not have to remain conscious for functional brain assessments. In many patients with pathology in the central sulcus region precise identification of this region is crucial and can be achieved with a motor or a sensory task on its own. However, the combination of both tasks increases the precision of localization and prevents technical failure when one task is unsuccessful in delineating the central sulcus. This can be the case in patients with moderate to severe motor-deficits due to tumor invasion or other reasons who are unable to perform an fMRI task involving movement of the hands. While only mentioned briefly in this chapter with few examples, the combination of different neuroimaging techniques is an exciting branch of neuroscience that will offer further insights into the complexity of the anatomy and function of S1.

References [1] [2] [3] [4] [5] [6] [7]

Foerster O, Penfield W. The structural basis of traumatic epilepsy and results of radical operations. Brain, 1930;53:99-119. Penfield W, Rasmussen T. The Cerebral Cortex of Man. A Clinical Study of Localization of Function. New York, NY: MacMillan; 1950. Gall FJ, Spurzheim JC. Anatomie und Physiologie des Nervensystemes im Allgemeinen und des Gehirns insbesondere. Paris: F.Schoell; 1810. Broca P. Sur le siège de la faculté du langage articulé. Bull. Soc. Anat. De Paris, 1861;6(2):355. Jackson JH. Selected writings of John Hughlings Jackson. London: Hodder and Stoughton; 1931. p. 500. Schott GD. Penfield's homunculus: A note on cerebral cartography. Journal of Neurology Neurosurgery and Psychiatry, 1993;56(4):329-333. Schuh L, Drury I. Intraoperative electrocorticography and direct cortical electrical stimulation Seminars in anesthesia, Preoperative Medicine and Pain, 1997;16(1).

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

24 [8]

[9]

[10]

[11]

[12]

[13]

[14]

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

[15] [16] [17]

[18]

[19]

[20]

[21]

U.N. Sboto-Frankenstein, J. Lawrence and B. Tomanek Cruccu G, Aminoff MJ, Curio G, Guerit JM, Kakigi R, Mauguiere F, et al. Recommendations for the clinical use of somatosensory-evoked potentials. Clinical Neurophysiology, 2008;119(8):1705-1719. Legatt AD, Soliman E. Somatosensory evoked potentials: General Principles. 2006; Available at: http://emedicine.medscape.com/article/1139906-media. Accessed 03/05/2009, 2009. Štetkárová I, Stejskal L, Kofler M. Tumors localized near the central sulcus may cause increased somatosensory evoked potentials. Clinical Neurophysiology, 2006;117(6):1359-1366. Bittar RG, Olivier A, Sadikot AF, Andermann F, Comeau RM, Cyr M, et al. Localization of somatosensory function by using positron emission tomography scanning: A comparison with intraoperative cortical stimulation. Journal of Neurosurgery, 1999;90(3):478-483. Korvenoja A, Kirveskari E, Aronen HJ, Avikainen S, Brander A, Huttunen J, et al. Sensorimotor cortex localization: Comparison of magnetoencephalography, functional MR imaging, and intraoperative cortical mapping. Radiology, 2006;241(1):213-222. Pirotte B, Neugroschl C, Metens T, Wikler D, Denolin V, Voordecker P, et al. Comparison of functional MR imaging guidance to electrical cortical mapping for targeting selective motor cortex areas in neuropathic pain: A study based on intraoperative stereotactic navigation. American Journal of Neuroradiology, 2005;26(9):2256-2266. Roberts TP, Zusman E, McDermott M, Barbaro N, Rowley HA. Correlation of functional magnetic source imaging with intraoperative cortical stimulation in neurosurgical patients. Journal of image guided surgery, 1995;1(6):339-347. Sunaert S. Presurgical planning for tumor resectioning. Journal of Magnetic Resonance Imaging, 2006;23(6):887-905. Tharin S, Golby A. Functional brain mapping and its applications to neurosurgery. Neurosurgery, 2007;60(4 SUPPL. 2). Yetkin FZ, Mueller WM, Morris GL, McAuliffe TL, Ulmer JL, Cox RW, et al. Functional MR activation correlated with intraoperative cortical mapping. American Journal of Neuroradiology, 1997;18(7):1311-1315. Huettel SA, Song AW, McCarthy G. Basic Principles of MR Signal Generation. Functional Magnetic Resonance Imaging. 2nd ed. Sunderland, Massachusetts: Sinauer Associates, Inc; 2009. p. 57--88. Schaechter JD, Moore CI, Connell BD, Rosen BR, Dijkhuizen RM. Structural and functional plasticity in the somatosensory cortex of chronic stroke patients. Brain, 2006 Oct;129(Pt 10):2722-2733. Ertem K, Alkan A, Sarac K, Onal C, Bostan H, Yologlu S, et al. Magnetic resonance spectroscopy study of proton metabolite level changes in sensorimotor cortex after upper limb replantation-revascularization. Magn.Reson.Imaging, 2005 Jan;23(1):105109. Rocca MA, Mezzapesa DM, Falini A, Ghezzi A, Martinelli V, Scotti G, et al. Evidence for axonal pathology and adaptive cortical reorganization in patients at presentation

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

NeuroImaging of Somatotopy in Primary Somatosensory Cortex

[22] [23]

[24] [25]

[26]

[27]

[28] [29]

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

[30]

[31]

[32]

[33] [34]

[35]

[36]

25

with clinically isolated syndromes suggestive of multiple sclerosis. Neuroimage, 2003 Apr;18(4):847-855. Epstein CM, Andriola MR. Evoked Potentials. Introduction to EEG and Evoked Potentials Philadelphia: J.B. Lippincott Company; 1983. p. 227. Babiloni F, Mattia D, Babiloni C, Astolfi L, Salinari S, Basilisco A, et al. Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle. Magn.Reson.Imaging, 2004 Dec;22(10):1471-1476. Jensen MP, Hakimian S, Sherlin LH, Fregni F. New insights into neuromodulatory approaches for the treatment of pain. J.Pain, 2008 Mar;9(3):193-199. Koubeissi MZ, Maciunas RJ, Tanner A, Luders HO. Medically intractable seizures originating from the primary somatosensory hand area. Epileptic Disord. 2008 Dec;10(4):339-348. Morris HH, Estes ML, Gilmore R, Van Ness PC, Barnett GH, Turnbull J. Chronic intractable epilepsy as the only symptom of primary brain tumor. Epilepsia, 1993 NovDec;34(6):1038-1043. Morris HH, Matkovic Z, Estes ML, Prayson RA, Comair YG, Turnbull J, et al. Ganglioglioma and intractable epilepsy: clinical and neurophysiologic features and predictors of outcome after surgery. Epilepsia, 1998 Mar;39(3):307-313. Schaefer M, Heinze HJ, Rotte M. Observing the touched body magnified alters somatosensory homunculus. Neuroreport, 2008 Jun 11;19(9):901-905. Gross J, Schnitzler A, Timmermann L, Ploner M. Gamma oscillations in human primary somatosensory cortex reflect pain perception. PLoS Biol. 2007 May;5(5):e133. Dhond RP, Witzel T, Hamalainen M, Kettner N, Napadow V. Spatiotemporal mapping the neural correlates of acupuncture with MEG. J.Altern.Complement.Med. 2008 Jul;14(6):679-688. Pascual-Leone A, Bartres-Faz D, Keenan JP. Transcranial magnetic stimulation: studying the brain-behaviour relationship by induction of 'virtual lesions'. Philos.Trans.R.Soc.Lond.B.Biol.Sci. 1999 Jul 29;354(1387):1229-1238. Brasil-Neto JP, Cohen LG, Panizza M, Nilsson J, Roth BJ, Hallett M. Optimal focal transcranial magnetic activation of the human motor cortex: effects of coil orientation, shape of the induced current pulse, and stimulus intensity. J.Clin.Neurophysiol. 1992 Jan;9(1):132-136. Rudiak D, Marg E. Finding the depth of magnetic brain stimulation: a re-evaluation. Electroencephalogr.Clin.Neurophysiol. 1994 Oct;93(5):358-371. Sack AT, Linden DE. Combining transcranial magnetic stimulation and functional imaging in cognitive brain research: possibilities and limitations. Brain Res.Brain Res.Rev. 2003 Sep;43(1):41-56. Chen R, Gerloff C, Classen J, Wassermann EM, Hallett M, Cohen LG. Safety of different inter-train intervals for repetitive transcranial magnetic stimulation and recommendations for safe ranges of stimulation parameters. Electroencephalogr.Clin.Neurophysiol. 1997 Dec;105(6):415-421. Wassermann EM. Risk and safety of repetitive transcranial magnetic stimulation: report and suggested guidelines from the International Workshop on the Safety of Repetitive

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

26

[37] [38]

[39]

[40]

[41]

[42] [43]

[44]

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

[45]

[46]

[47]

[48] [49]

[50]

[51]

U.N. Sboto-Frankenstein, J. Lawrence and B. Tomanek Transcranial Magnetic Stimulation, June 5-7, 1996. Electroencephalogr.Clin.Neurophysiol. 1998 Jan;108(1):1-16. Balslev D, Miall RC. Eye position representation in human anterior parietal cortex. J.Neurosci. 2008 Sep 3;28(36):8968-8972. Pitcher D, Garrido L, Walsh V, Duchaine BC. Transcranial magnetic stimulation disrupts the perception and embodiment of facial expressions. J.Neurosci. 2008 Sep 3;28(36):8929-8933. Wittenberg GF, Werhahn KJ, Wassermann EM, Herscovitch P, Cohen LG. Functional connectivity between somatosensory and visual cortex in early blind humans. Eur.J.Neurosci. 2004 Oct;20(7):1923-1927. Boly M, Faymonville ME, Schnakers C, Peigneux P, Lambermont B, Phillips C, et al. Perception of pain in the minimally conscious state with PET activation: an observational study. Lancet Neurol. 2008 Nov;7(11):1013-1020. Giacino JT, Ashwal S, Childs N, Cranford R, Jennett B, Katz DI, et al. The minimally conscious state: definition and diagnostic criteria. Neurology 2002 Feb 12;58(3):349353. Bernat JL. Chronic disorders of consciousness. Lancet, 2006 Apr 8;367(9517):11811192. Strangman G, Culver JP, Thompson JH, Boas DA. A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. Neuroimage, 2002 Oct;17(2):719-731. Eliassen JC, Boespflug EL, Lamy M, Allendorfer J, Chu WJ, Szaflarski JP. Brainmapping techniques for evaluating poststroke recovery and rehabilitation: a review. Top.Stroke Rehabil. 2008 Sep-Oct;15(5):427-450. Boas DA, Dale AM, Franceschini MA. Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy. Neuroimage, 2004;23 Suppl 1:S275-88. Niederhauser BD, Rosenbaum BP, Gore JC, Jarquin-Valdivia AA. A functional nearinfrared spectroscopy study to detect activation of somatosensory cortex by peripheral nerve stimulation. Neurocrit Care. 2008;9(1):31-36. Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc.Natl.Acad.Sci.U.S.A. 1990 Dec;87(24):9868-9872. Logothetis NK, Pfeuffer J. On the nature of the BOLD fMRI contrast mechanism. Magn.Reson.Imaging, 2004 Dec;22(10):1517-1531. Hendry SHC, Hsiao SS, Bushnell MC. Somatic Sensation. In: Zigmond MJ, Bloom FE, Landia SC, Roberts LR, Squire LR, editors. Fundamentals of Neuroscience San Diego: Academic Press; 1999. p. 761-789. Weibull A, Björkman A, Hall H, Rosén B, Lundborg G, Svensson J. Optimizing the mapping of finger areas in primary somatosensory cortex using functional MRI. Magnetic Resonance Imaging, 2008;26(10):1342-1351. Kaas JH, Nelson RJ, Sur M. Multiple representations of the body within the primary somatosensory cortex of primates. Science, 1979;204(4392):521-523.

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[52] Eickhoff SB, Grefkes C, Fink GR, Zilles K. Functional lateralization of face, hand, and trunk representation in anatomically defined human somatosensory areas. Cerebral Cortex, 2008;18(12):2820-2830. [53] Francis ST, Kelly EF, Bowtell R, Dunseath WJR, Folger SE, McGlone F. fMRI of the responses to vibratory stimulation of digit tips. NeuroImage, 2000;11(3):188-202. [54] Gelnar PA, Krauss BR, Szeverenyi NM, Apkarian AV. Fingertip representation in the human somatosensory cortex: An fMRI study. NeuroImage, 1998;7(4 I):261-283. [55] Hammeke TA, Yetkin FZ, Mueller WM, Morris GL, Haughton VM, Rao SM, et al. Functional magnetic resonance imaging of somatosensory stimulation. Neurosurgery, 1994;35(4):677-681. [56] Hansson T, Brismar T. Tactile stimulation of the hand causes bilateral cortical activation: A functional magnetic resonance study in humans. Neuroscience Letters, 1999;271(1):29-32. [57] Hodge Jr. CJ, Huckins SC, Szeverenyi NM, Fonte MM, Dubroff JG, Davuluri K. Patterns of lateral sensory cortical activation determined using functional magnetic resonance imaging. Journal of Neurosurgery, 1998;89(5):769-779. [58] Lin W, Kuppusamy K, Haacke EM, Burton H. Functional MRI in human somatosensory cortex activated by touching textured surfaces. Journal of Magnetic Resonance Imaging, 1996;6(4):565-572. [59] Kurth R, Villringer K, Mackert B-, Schwiemann J, Braun J, Curio G, et al. fMRI assessment of somatotopy in human Brodmann area 3b by electrical finger stimulation. NeuroReport, 1998;9(2):207-212. [60] Maldjian JA, Gottschalk A, Patel RS, Detre JA, Alsop DC. The sensory somatotopic map of the human hand demonstrated at 4 Tesla. NeuroImage, 1999;10(1):55-62. [61] van Westen D, Fransson P, Olsrud J, Rosén B, Lundborg G, Larsson E-. Fingersomatotopy in area 3b: An fMRI-study. BMC Neuroscience, 2004;5. [62] Hlushchuk Y, Hari R. Transient suppression of ipsilateral primary somatosensory cortex during tactile finger stimulation. Journal of Neuroscience, 2006;26(21):58195824. [63] Burton H. cerebral cortical regions devoted to the somatosensory system: results from brain imaging studies in humans. In: Randall NJ, editor. The somatosensory system. Deciphering the brain’s own body image: CRC Press; 2002. p. 27--72. [64] Borsook D, Burstein R, Becerra L. Functional imaging of the human trigeminal system: Opportunities for new insights into pain processing in health and disease. Journal of Neurobiology, 2004;61(1):107-125. [65] Servos P, Engel SA, Gati J, Menon R. fMRI evidence for an inverted face representation in human somatosensory cortex. NeuroReport, 1999;10(7):1393-1395. [66] Iannetti GD, Porro CA, Pantano P, Romanelli PL, Galeotti F, Cruccu G. Representation of different trigeminal divisions within the primary and secondary human somatosensory cortex. NeuroImage, 2003;19(3):906-912. [67] Moulton EA, Pendse G, Morris S, Strassman A, Aiello-Lammens M, Becerra L, et al. Capsaicin-induced thermal hyperalgesia and sensitization in the human trigeminal nociceptive pathway: an fMRI study. Neuroimage, 2007 May 1;35(4):1586-1600.

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28

U.N. Sboto-Frankenstein, J. Lawrence and B. Tomanek

[68] Huang R-, Sereno MI. Dodecapus: An MR-compatible system for somatosensory stimulation. NeuroImage, 2007;34(3):1060-1073. [69] DaSilva AFM, Becerra.L. L, Makris N, Strassman AM, Gonzalez RG, Geatrakis N, et al. Somatotopic activation in the human trigeminal pain pathway. Journal of Neuroscience, 2002;22(18):8183-8192. [70] Borsook D, DaSilva AFM, Ploghaus A, Becerra L. Specific and somatotopic functional magnetic resonance imaging activation in the trigeminal ganglion by brush and noxious heat. Journal of Neuroscience, 2003;23(21):7897-7903. [71] Lotze M, Flor H, Grodd W, Larbig W, Birbaumer N. Phantom movements and pain an fMRI study in upper limb amputees. Brain, 2001;124(11):2268-2277. [72] MacIver K, Lloyd DM, Kelly S, Roberts N, Nurmikko T. Phantom limb pain, cortical reorganization and the therapeutic effect of mental imagery. Brain, 2008;131(8):21812191. [73] Manger PR, Woods TM, Jones EG. Representation of face and intra-oral structures in area 3b of macaque monkey somatosensory cortex. Journal of Comparative Neurology, 1996;371(4):513-521. [74] Kunc Z. Significant factors pertaining to the results of trigeminal tractotomy. In: Hassler R, Walker A, editors. Trigeminal neuralgia, pathogenesis and pathophysiology Stuttgart: Thieme; 1970. [75] Dresel C, Parzinger A, Rimpau C, Zimmer C, Ceballos-Baumann AO, Haslinger B. A new device for tactile stimulation during fMRI. NeuroImage, 2008;39(3):1094-1103. [76] Friston KJ, Zarahn E, Josephs O, Henson RNA, Dale AM. Stochastic designs in eventrelated fMRI. NeuroImage, 1999;10(5):607-619. [77] Porro CA, Lui F, Facchin P, Maieron M, Baraldi P. Percept-related activity in the human somatosensory system: Functional magnetic resonance imaging studies. Magnetic Resonance Imaging, 2004;22(10 SPEC. ISS.):1539-1548. [78] Miyamoto JJ, Honda M, Saito DN, Okada T, Ono T, Ohyama K, et al. The representation of the human oral area in the somatosensory cortex: A functional MRI study. Cerebral Cortex, 2006;16(5):669-675. [79] Guest S, Grabenhorst F, Essick G, Chen Y, Young M, McGlone F, et al. Human cortical representation of oral temperature. Physiology and Behavior, 2007;92(5):975984. [80] Komisaruk BR, Whipple B. Functional MRI of the brain during orgasm in women. Annual Review of Sex Research, 2005;16:62-86. [81] Park K, Seo JJ, Kang HK, Ryu SB, Kim HJ, Jeong GW. A new potential of blood oxygenation level dependent (bold) functional MRI for evaluating cerebral centers of penile erection. International Journal of Impotence Research, 2001;13(2):73-81. [82] Georgiadis JR, Holstege G. Human brain activation during sexual stimulation of the penis. Journal of Comparative Neurology, 2005;493(1):33-38. [83] Stoléru S, Grégoire M-, Gérard D, Decety J, Lafarge E, Cinotti L, et al. Neuroanatomical correlates of visually evoked sexual arousal in human males. Archives of Sexual Behavior, 1999;28(1):1-21.

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NeuroImaging of Somatotopy in Primary Somatosensory Cortex

29

[84] Kell CA, Von Kriegstein K, Rösler A, Kleinschmidt A, Laufs H. The sensory cortical representation of the human penis: Revisiting somatotopy in the male homunculus. Journal of Neuroscience, 2005;25(25):5984-5987. [85] Foerster O. The motor cortex in man in the light of Hughlings Jackson’s Doctrines. Brain, 1936;2(59):135-159. [86] Stippich C, Blatow M, Krakow K. Presurgical Functional MRI in Patients with Brain Tumors. In: Stippich C, editor. Clinical Functional MRI. Presurgical Functional Neuroimaging Berlin: Springer-Verlag; 2007. [87] Yetkin FZ, Mueller WM, Hammeke TA, Morris III GL, Haughton VM, Berger MS, et al. Functional magnetic resonance imaging mapping of the sensorimotor cortex with tactile stimulation. Neurosurgery, 1995;36(5):921-925. [88] Overduin SA, Servos P. Distributed digit somatotopy in primary somatosensory cortex. NeuroImage 2004;23(2):462-472. [89] Hirsch J, Ruge MI, Kim KHS, Correa DD, Victor JD, Relkin NR, et al. An integrated functional magnetic resonance imaging procedure for preoperative mapping of cortical areas associated with tactile, motor,language, and visual functions. Neurosurgery, 2000;47(3):711-722. [90] Pujol J, Conesa G, Deus J, López-Obarrio L, Isamat F, Capdevila A. Clinical application of functional magnetic resonance imaging in presurgical identification of the central sulcus. Journal of Neurosurgery, 1998;88(5):863-869. [91] Pujol J, Deus J, Acebes JJ, Villanueva A, Aparicio A, Soriano-Mas C, et al. Identification of the sensorimotor cortex with functional MRI: Frequency and actual contribution in a neurosurgical context. Journal of Neuroimaging, 2008;18(1):28-33. [92] Krings T, Reinges MHT, Erberich S, Kemeny S, Rohde V, Spetzger U, et al. Functional MRI for presurgical planning: Problems, artefacts, and solution strategies. Journal of Neurology Neurosurgery and Psychiatry, 2001;70(6):749-760. [93] Dymarkowski S, Sunaert S, Van Oostende S, Van Hecke P, Wilms G, Demaerel P, et al. Functional MRI of the brain: Localisation of eloquent cortex in focal brain lesion therapy. European Radiology, 1998;8(9):1573-1580. [94] Gasser TG, Sandalcioglu EI, Wiedemayer H, Hans V, Gizewski E, Forsting M, et al. A novel passive functional MRI paradigm for preoperative identification of the somatosensory cortex. Neurosurgical Review, 2004;27(2):106-112. [95] Gasser T, Sandalcioglu E, Schoch B, Gizewski E, Forsting M, Stolke D, et al. Functional magnetic resonance imaging in anesthetized patients: A relevant step toward real-time intraoperative functional neuroimaging. Neurosurgery, 2005;57(1 SUPPL.). [96] Hartkens T, Hill DLG, Castellano-Smith AD, Hawkes DJ, Maurer Jr. CR, Martin AJ, et al. Measurement and analysis of brain deformation during neurosurgery. IEEE Transactions on Medical Imaging, 2003;22(1):82-92. [97] Nimsky C, Ganslandt O, Hastreiter P, Fahlbusch R. Intraoperative compensation for brain shift. Surgical Neurology, 2001;56(6):357-364. [98] Letteboer MMJ, Willems PWA, Viergever MA, Niessen WJ. Brain shift estimation in image-guided neurosurgery using 3-D ultrasound. IEEE Transactions on Biomedical Engineering, 2005;52(2):268-276.

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[99] (99) Hoult DI, Saunders JK, Sutherland GR, Sharp J, Gervin M, Glen Kolansky H, et al. The engineering of an interventional MRI with a movable 1.5 Tesla magnet. Journal of Magnetic Resonance Imaging, 2001;13(1):78-86. [100] Sutherland GR, Kaibara T, Louw D, Hoult DI, Tomanek B, Saunders J. A mobile highfield magnetic resonance system for neurosurgery. Journal of Neurosurgery, 1999;91(5):804-813. [101] Gering DT, Weber DM. Intraoperative, real-time, functional MRI. Journal of Magnetic Resonance Imaging, 1998;8(1):254-257. [102] Gasser T, Ganslandt O, Sandalcioglu E, Stolke D, Fahlbusch R, Nimsky C. Intraoperative functional MRI: Implementation and preliminary experience. NeuroImage, 2005;26(3):685-693. [103] Nimsky C, Ganslandt O, Von Keller B, Romstöck J, Fahlbusch R. Intraoperative highfield-strength MR imaging: Implementation and experience in 200 patients. Radiology, 2004;233(1):67-78. [104] Qiu M, Ramani R, Swetye M, Rajeevan N, Constable RT. Anesthetic effects on regional CBF, BOLD, and the coupling between task-induced changes in CBF and BOLD: an fMRI study in normal human subjects. Magn.Reson.Med. 2008 Oct;60(4):987-996. [105] Lahti KM, Ferris CF, Li F, Sotak CH, King JA. Comparison of evoked cortical activity in conscious and propofol-anesthetized rats using functional MRI. Magn.Reson.Med. 1999 Feb;41(2):412-416.

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Chapter 2

The Role of the Somatosensory Cortex in Pain Processing Jennifer Kornelsen and Boguslaw Tomanek National Research Council of Canada, Institute for Biodiagnostics, Winnipeg, Manitoba, Canada

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Abstract The role of the somatosensory cortex in pain perception has not yet been precisely identified. Numerous studies using various techniques and stimuli have provided contradictory results. This chapter presents an overview of the recent neuroimaging research examining the role of somatosensory cortex in pain processing. First, methodologies for the investigation of pain in neuroimaging studies are reviewed. Next, the relevant structures of the lateral pain system are identified along with a discussion of the fibres that mediate first and second pain. The somatotopic organization of the somatosensory cortex for pain, laterality of pain processing, and cortical reorganization in pain conditions are then reviewed. Finally, the role of the lateral pain system in the modulation of pain and a section on anti-nociception end the chapter.

Introduction The role of somatosensory cortex in pain perception has not been easily identifiable. Although numerous studies using various techniques and stimuli have been employed, the results have been contradictory. Early imaging studies in this area produced varied results. Using positron emission tomography (PET) and a heat stimulus to the arm, Talbot et al. (1991) found significant activity in the contralateral primary somatosensory cortex (SI), whereas with a similar stimulus Jones et al. (1991) did not observe significant SI activation, although both studies were in agreement on the activation of anterior cingulate cortex (ACC). To further confuse the issue, a single photon-emission computed tomography (SPECT) study

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that involved submersing fingers in hot water elicited a decrease in SI activity (Apkarian et al., 1992). Since these early conflicting results, many imaging studies have been conducted with the aim of identifying the role of the somatosensory cortex in pain processing. The somatosensory cortex, as part of the lateral pain system, is thought to be involved in the sensory-discriminative aspect of pain processing. Sensory-discriminative processing of pain information involves stimulus localization, intensity discrimination, and quality discrimination. The goal of numerous recent imaging studies has been to determine how each of the somatosensory cortex regions contributes to these specific functions. This chapter presents an overview of the recent neuroimaging research examining the role of the somatosensory cortex in pain processing.

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Methods for the Investigation of Pain in the Somatosensory Cortex Many types of imaging techniques are available, and each has inherent advantages and disadvantages (see chapter 1 for a review). Likely, the converging evidence produced by each of these imaging methods will bring to light a cohesive explanation of the role the somatosensory cortex plays in the processing of pain information. Just as there are many imaging techniques, there are many forms of painful stimuli typically used in imaging studies. These include, but are not limited to, phasic or tonic noxious thermal stimuli, chemical irritants, electric stimulation, ischemia, and visceral distention as types of experimentally induced noxious stimuli. Furthermore, naturally occurring pain conditions can be used as stimuli, such as headache, migraine, fibromyalgia, and neuropathic pain. These conditions can also be induced or exacerbated through experimental manipulation. There appears to be little consistency with regard to the primary somatosensory cortex involvement in these various imaging techniques and forms of noxious stimulation (Bushnell et al., 1999). Bushnell et al. (1999) have addressed the issue of this inconsistency in the research findings and has provided four potential explanations of the variable results concerning the SI involvement in pain processing. First, cognitive modulation has an influence on SI activity. This explanation could account for the different results in the early imaging work by Jones et al. (1991) and Talbot et al. (1991). Whereas Talbot et al. applied the heat stimulus to six different locations on the arm of their subjects, Jones et al. presented their heat stimulus to a single location on the arm. It is therefore possible that the SI activity seen in the Talbot et al. study is an effect of the attention toward the pain stimulus rather than the cortical processing of the pain stimulus itself. This type of cognitive modulation of SI activity has also been reported for other sensory modalities (Meyer et al., 1991). A second potential explanation for the inconsistency in SI activation during presentation of pain stimuli is the variability in the sulcal anatomy of SI (Bushnell et al., 1999). With PET, Andersson et al. (1997) were able to provide evidence for a somatotopic organization of SI. Distinct activation sites were detected for the foot and hand representation of pain, consistent with known topographic organization of cutaneous representation. Bushnell et al. (1999) reported SI activation in response to a noxious heat stimulus on the posterior bank of the central sulcus, however these sites varied

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in their stereotaxic coordinates among subjects. This intersubject variability in the pain related activity could contribute to a focal signal degradation when averaged across subjects, making it difficult to identify regions consistently activated in SI during pain processing (Bushnell et al., 1999). A third potential explanation of the decrease in SI activity in response to noxious heat stimulation provided by Apkarian et al. (1992) indicated that noxious stimulation produces inhibitory effects in SI. This idea was supported later by the same authors (Apkarian et al. 1994) in a study which illustrated reduced tactile perception in the presence of a pain stimulus. It was proposed that the net effect of exciting neurons while inhibiting the spontaneous activity of others with the presentation of a pain stimulus could have resulted in differential effects on regional cerebral blood flow, furthermore dependent on the timing, duration, location, and intensity of the noxious stimulus (Bushnell et al., 1999). A fourth potential explanation for the variable results in SI activity is the differences in procedure and analysis between the studies. Bushnell et al. (1999) note numerous areas where differences between the way a study's methodology can affect the outcome, including different approaches for comparison of stimulation conditions such as subtraction and regression, how instructions to subjects can influence cognitive states, and the timing of the stimulus variables. In addition, differences in statistical analysis, such as methods for calculating variance, the assumptions about the data, the criteria for significance in the data, and the power of the statistical tests, can all affect the outcome. Bushnell et al. (1999) pointed out, however, that when many studies are considered, a trend may appear which may elucidate the SI involvement in pain processing.

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Structures of the Lateral Pain System The participation of the cerebral cortex in pain perception is no longer in question. However, the specific function of each of the cerebral regions is now under investigation. The International Association for the Study of Pain has provided a definition of pain: “Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage or described in terms of such damage” (Merskey, 1986). This definition clearly outlines that pain has both a sensory and emotional component, a construct replicated in the segregation of the medial and lateral pain systems. The medial pain system is considered to be the affective-motivational component of the pain system, whereas the lateral pain system is considered to be the sensory-discriminative component. These pain systems have been identified (and named) based on their projection pathways originating in nociceptive areas of lamina I and V of the dorsal horns of the spinal cord and projecting to nuclei of the thalamus. Simply put, projection pathways from the spinal cord to the nuclei of the lateral thalamus project to the primary and secondary somatosensory cortices, thus forming the lateral pain system, whereas projection pathways from the spinal cord to the nuclei of the medial thalamus project to the anterior cingulate cortex forming the medial pain system. The categorization of the insula is less clear, as it receives input from the lateral system but projects to the limbic system. Recent studies have shown the insular cortex to consist of separate sections with distinct functions, such as somatotopic organization (Brooks et al., 2005; 2007). In this chapter, the insular cortex is considered part of the lateral pain system,

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based on its cortico-cortical input and the proximity to the SII, which both necessitates the study of, and elucidates the subtle functional differences between, the insular cortex and secondary somatosensory cortex in the processing of pain information (Frot et al., 2007). The medial pain system and cingulate cortex, and the parallel processing of nociceptive information in these cortical regions will not be covered here (for the role of the medial pain system in pain processing, see Sewards and Sewards, 2002; Vogt and Sikes, 2000; Xie et al., 2009). Nociceptive neurons in SI are arranged in the deep layers III-V (Kenshalo and Douglass, 1995), and have small receptive fields arranged in a somatotopic pattern along the postcentral gyrus (Lamour et al., 1983). The encoding of graded stimulus intensities and plasticity of response properties following injury consistent with hyperalgesia, support that this area is well equipped for the sensory-discriminative aspects of pain processing (Treede et al., 1999). The secondary somatosensory cortex (SII) area has few nociceptive neurons, which suggests this area is less well suited for sensory-discriminative functions (Treede et al., 1999) although this is inconsistent with imaging findings of SII activation. Single cell recordings in the monkey have shown the nociceptive pathway in the somatosensory system project to area 3b and 1 of SI (Kenshalo and Isensee, 1983) and to SII and posterior parietal cortex (Dong et al., 1989). This is consistent with the pathways reported by Sewards and Sewards (2002) who propose that separate sensory and hedonic representations exist at each level of the primary structures of the somatosensory system, including the spinal cord, brainstem, thalamus and cortex. In the dorsal horn of the spinal cord the hedonistic representation consisting of nociceptive-specific, wide dynamic range, and thermoreceptive neurons located in lamina I and II, while sensory representation composed primarily of low threshold and wide dynamic range neurons is found in lamina III-V. They further report that in primates, no hedonic representation exists in SI and SII and the activities of neurons in both areas represent the sensory aspect exclusively. SI is often found active, while SII has consistently been shown active, following noxious stimuli in imaging studies, and therefore SI and SII are considered primarily sensory and without hedonic representation (for a thorough review of the separate sensory and hedonic pathways in mammals, see Sewards and Sewards, 2002). This is in agreement with a PET study involving manipulation of the rated unpleasantness of a pain stimulus while maintaining the perceived pain intensity with hypnosis. Modulation of the pain related activity in the anterior cingulate cortex closely paralleled a selective change in the perceived unpleasantness of the pain stimulus, whereas the absence of changes in the sensory component of the pain perception and absence of modulation within SI, SII and the insular cortex indicates a significant involvement of the anterior cingulate cortex in the processing of pain affect, and further, argues against the involvement of the lateral pain system structures in this function (Rainville et al., 1997). However, the anatomical connections between SI, SII, the insular cortex, and the anterior cingulate cortex suggest that these structures do not function in isolation but are highly interactive in the encoding of the different aspects of pain information (Rainville et al., 1997). The pain experience is understood as a combination and integration of sensation, cognition and emotion. It makes sense, therefore, that the neurobiology of pain would involve an integration of numerous neuronal networks (Derbyshire et al., 2002).

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Pain Fibres Mediating First and Second Pain Sensory-discriminative pain processing involves stimulus localization, intensity discrimination, and quality discrimination. This processing functions to determine where the pain is, how strong the pain is, and what kind of pain it is. These sensory-discriminative features are in part mediated by Aδ and C fibres. Pain is mediated by small thinly myelinated fibres that conduct impulses at 5-30 m/s (Aδ fibres) and by small diameter unmyelinated fibres that conduct impulses at 0.5-2 m/s (C fibres). The two fibre types are associated with two successive and qualitatively different pain perceptions (Ploner, 2002). The Aδ fibre mediates first pain, which is described as a sharp, pin prick-like, well localized pain. In contrast, the C fibre mediates second pain, which is a dull, longer lasting and burning pain, that is not well localized. It has been suggested that the function of first pain is an immediate avoidance reaction to the harmful stimulus, whereas the second pain is involved in longer lasting processes such as tissue inflammation (Forss, 2005; Ploner, 2002). As the two pain fibre types differ in their function, it is reasonable to expect they may be differentially involved in pain disorders (Forss, 2005). Ploner et al., (2002) investigated the cortical representation of first and second pain sensation in humans. Using continuous pain ratings and magnetoencephalography (MEG), they demonstrated that a brief laser noxious stimulus elicits sustained pain perception and cortical activity. The cortical activity was evoked by Aδ fibre stimulation, mediating first pain, and C fibre stimulation, mediating second pain. Activity was localized in contralateral SI, bilateral SII and anterior cingulate cortex. The time course data for the activity revealed differential temporal activity patterns. Ratios of activation strengths indicated strong SI activity during the early time window, SII activity during both the early and late windows, and anterior cingulate cortex activity during the late time window. Therefore, the SI region showed a strong predominance of first pain related activation whereas the anterior cingulate cortex showed a strong predominance of second pain related activation. SII was revealed to be equally active during first and second pain related activity. Ploner et al. (2002) suggest that the differences in cortical representation likely reflect the perceptual and functional differences between first and second pain. Ploner et al. (2002) had proposed an interesting argument to the controversy regarding SI activation, and lack of SI activation, in imaging studies. The results of their MEG study on the cortical representation of first and second pain sensation show that first pain activates SI in a strong but short manner, whereas second pain elicits a longer lasting activation in SII and anterior cingulate cortex. The SI activation is therefore less likely than the SII or anterior cingulate cortex to be detected by imaging methods such as single photon emission computed tomography, positron emission tomography or functional magnetic resonance imaging. This may account for the inconsistent findings of significant SI activation in imaging studies. With the aim of clarifying the cortical network involved in pain processing, Forss et al., (2005) compared activation patterns, temporal behaviour, and recovery profiles of cortical areas responding to Aδ and C fibre stimuli with whole scalp MEG recordings. Using thuliumlaser stimulation on the dorsum of the hand, selective nociceptive nerve fibre stimulation was accomplished. Bilateral activity of the SII cortices was detected in all 10 of the study subjects for Aδ stimulation and in 8 of the 10 subjects for C fibre stimulation. Activity in the SI cortex

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was not observed with stimulation of either fibre type. Their results indicated that the nociceptive input mediated by the first and second fibre types is processed in a common cortical network, but in different time windows. The authors noted that the reliable temporospatial characterizations of the first and second pain cortical responses provide a useful tool for neuroscience to study the two distinct fibre systems at the cortical level. The study by Forss et al. (2005) provides two additional major findings to the earlier studies in this area. First, their findings show a strong and consistent activation of the SII cortex, which emphasizes the important role that this region plays in pain processing. Second, they show that Aδ and C fibre stimulation elicits similar source locations in the SII response, which is taken to imply that either the same or largely overlapping neuronal populations are responding to peripheral noxious stimulation in the SII region regardless of the mediating fibre type (Forss et al., 2005). Separate stimulation of the Aδ and C fibres in the Forss et al study did not reveal a functional division between the cortical regions. Rather, a common cortical network with different time windows was implicated. For patients referred for epilepsy surgery whose seizures are suspected to originate in the perisylvian or insular cortex, intracerebral recordings of electrical potentials evoked by painful stimuli can be measured. Intracerebral recording of electrical potentials evoked by noxious and innocuous skin stimulations in these regions has shown that SII and insular cortex respond to the stimulation with different latencies (Frot et al., 2001). Mazzola et al. (2006) directly stimulated, through transopercular electrode contacts, the SII region of 14 epilepsy surgery patients with the aim of comparing SII, SI, and insular responses along a single track. SII responses were compared to those from the adjacent SI and insular cortex in order to show distinct somatosensory maps and pain representations within these regions. Regardless of the regions stimulated, somatosensory responses were evoked, including paresthesia, temperature, and pain sensation. However, percentages of responses in SI and SII were significantly higher than in the insular cortex. The rate of the elicited pain sensation was similar for the SII and insula and no pain sensation was elicited in SI. The distribution of the somatosensory responses in the regions of interest was observed as follows. Sensations of cutaneous paresthesia, described as a neutral or unpleasant sensation of tingling light touch or a slight electric current, were reported for stimulation of the anterior part of the postcentral opercular cortex (SII) but were more widely distributed in the insula and SI. The highest rate of temperature responses were shown in SII when areas caudal and lateral to the areas producing cutaneous paresthesia were stimulated, although this finding was not statistically significant. Sensations of mild to intolerable pain intensity were elicited by SII stimulation of the right hemisphere in three of the epilepsy patients. The descriptions of the pain perception included tingling pain in the superior part of the face (bilaterally but predominantly left), a painful cramping and electrical current sensation of the left half of the body, and a painful tingling and cramping in the left cheek quickly spreading to the left half of the body. The degree of pain reported was independent of the stimulation intensity. The pain response was evoked after stimulation to areas of SII deeper and more superior to those evoking the paresthesia and temperature responses, although this difference in contact location was not statistically significant, possibly due to the small number of pain responses. A recent meta-analysis of PET and fMRI studies of hand somatosensory stimulation suggested that pain responses in SII were localized in the OP1 cytoarchetectonic

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subdivision located in the caudal and lateral part of this area (Eickhoff et al., 2006), in agreement with the results reported by Mazzola et al. (2006). Stimulation of SI did not elicit any pain responses. Stimulation of the upper posterior portion of the insular cortex evoked pain responses of equal frequency but the pain was described as qualitatively different, primarily as burning sensations, electrical discharges, and stinging sensations.

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Somatotopy in SI/SII Whereas the somatotopy of tactile perception is well established in SI, the somatotopy of pain perception is largely unknown. In addition to the controversy surrounding the involvement of SI in pain processing, additional factors play in this paucity of knowledge regarding pain somatotopy. An investigation of the somatotopic organization requires techniques providing high spatial and temporal resolution while selectively applying painful stimulation and recording cortical activity non-invasively (Ogino et al., 2005). Multichannel MEG has the advantages of non-invasively detecting cortical activity at higher spatial resolution than somatosensory-evoked potentials, functional magnetic resonance imaging (fMRI), or positron emission tomography (Ogino et al., 2005). While a few MEG studies have demonstrated SI activity in response to painful stimulation (Ploner et al., 1999; Kanda et al., 2000; Inui et al., 2002) it has been noted that the early SI components are weak and are likely to be overlooked (Kakigi et al., 2005; Ploner et al., 2002). Thus, using a combination of MEG and noxious intraepidermal electrical stimulation to selectively provide Aδ fibre nociceptive stimuli without tactile sensation, Ogino et al. (2005) recorded pain-evoked somatosensory-evoked magnetic fields along the central gyrus. The dorsum of the left hand and left foot was stimulated in healthy human subjects producing a well-defined pricking pain. For both the hand and foot stimulation, clear, consistently evoked magnetic fields were detected in three regions; that of the right centroparietal area and the right and left frontotemporal areas, corresponding to right SI and bilateral SII, respectively. The authors report a significant difference in the location of the hand and foot activity in the SI cortex. The contralateral source location under the foot stimulation condition was significantly medial and significantly posterior to that of the hand stimulation condition. Specifically, the SI activity was located in the anterior crown of the postcentral gyrus in the Brodmann's area 1 or 2. The preferential Aδ fibre stimulation employed in this study ensured that a brief, pricking, and well localized first pain was elicited in the absence of Aβ or Aα fibre stimulation mediating innocuous, tactile information. Direct comparison of noxious to tactile stimulation in the SI cortex has been conducted with MEG studies, where the location of noxious stimulus-evoked SI activation in area 1 was found to be slightly more medial and superior to that of early SI activation in area 3b evoked by tactile stimulation (Kanda et al., 2000; Inui et al., 2003), in agreement with the results presented by Ogino et al. (2005). In contrast to the strong somatotopic organization reported for SI, the source locations of contralateral and ipsilateral SII activation did not significantly differ for hand and foot stimulation. The authors thus report this to be the first MEG study to show SI somatotopy in the human pain system and report less somatotopy in bilateral SII. The lack of topographic organization in SII for pain perception is consistent with PET results (Xu et al., 1997). Based

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on their findings, Ogino et al. (2005) suggest that the SI involvement in pain perception serves to localize the site of stimulation whereas SII is associated with a cognitive-evaluative role of pain processing. In agreement with this, significant gradients in the size of the sensations evoked on the skin by the stimulation of SI, SII, and the insular cortex was shown (Mazzola et al., 2006). Based on the sizes of the receptive fields, a decreasing spatial resolution from SI to SII to insula, suggesting SII is less well equipped for spatial discrimination than SI. Recently, an optical imaging study investigating the area-specific representation of nociceptive versus tactile stimuli within SI, has shown that nociceptive inputs are preferentially represented in areas 3a and 1 while non-nociceptive input are preferentially represented in areas 3b and 1 of SI cortex (Chen et al., 2008). Using optical imaging of intrinsic signal (OIS) and single unit electrophysiology with non-human primates, Chen et al. studied cortical activation patterns within Brodmann's areas 3a, 3b, and 1 and recorded signal amplitude changes during non-nociceptive, thermal nociceptive, and mechanical nociceptive stimulation of the fingerpads. In addition to the differential representation for type of stimuli within the SI cortex areas, topographic organization was revealed for nociceptive activation in areas 3a and 1, providing evidence for somatotopy in SI for pain processing. Mechanical nociceptive stimuli elicited somatotopically organized activation spatially colocalized with tactile responses in the same areas, suggesting that, although nociception is topographically represented in SI, it is overlapping with tactile maps. With increasing intensity of mechanical nociceptive stimulation, an enhancement of signal amplitude was shown for areas 3a, 3b, and 1, suggesting that this area plays a role in intensity discrimination (Chen et al., 2009).

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Laterality Using a whole head magnetometer, somatosensory evoked magnetic fields were recorded from SI of 12 healthy human subjects, following painful CO2 laser stimulation of the dorsum of the left hand (Kanda et al., 2000). In 7 of the 12 subjects, three spatially segregated cortical areas were simultaneously activated, that of the contralateral SI and bilateral SII, providing evidence for parallel processing of pain information in these regions. The evoked magnetic field over the contralateral SI in response to painful stimulation by CO2 laser is consistent with the results reported in Ploner et al. (1999). Both studies reported no significant difference in the peak latency of the SI source and bilateral SII sources, indicating that pain processing occurs in a non-serial, parallel manner (Ploner, 1999; Kanda, 2000). The early PET study by Talbot et al. (1991) revealed SI and SII activity, contralateral to the stimulated arm, and they suggest that the strong SII activity indicates that these regions may be more important for processing pain than for processing of tactile information. This was one of the first imaging studies to show that the processing of painful stimuli is restricted to three major structures, that of the anterior cingulate cortex, the primary somatosensory cortex, and the secondary somatosensory cortex. The authors proposed that information regarding pain intensity and laterality is received by both the parietal and frontal cortices. More recently, a left hemisphere bias was reported for the early sensory component of pain perception using brain electrical source analysis of laser-evoked potentials (Shleretha et

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al., 2003). During laser heat stimulation to the dorsum of the hands, subjects were asked to perform either a spatial or intensity discrimination task contrasted with a mental arithmetic task. Distraction by mental math was shown to have a significant analgesic effect. The most pronounced enhancement during the spatial and intensity discrimination task compared to the distraction task was for the source in the operculoinsular cortex. Further, this source activity was significantly stronger in the left hemisphere independent of the side stimulated, suggesting a dominant role of the left frontal operculum and adjacent dorsal insula in the early sensory-discriminative dimensions of pain processing (Shleretha et al., 2003). By applying a painful CO2 laser stimulus to the left and right lower legs, Youell et al. (2004) were able to investigate the lateralization of pain processing. Their aim was to clarify the functional division between the lateral and medial pain system with fMRI. SI, SII, the insula, and the thalamus were identified as volumes of interest, and lateralization was quantified by comparing the level of activity between the hemispheres within each volume of interest. In both the SI and the thalamus, activity was significantly greater in the contralateral hemisphere. Activity was greater in the left than in the right hemisphere in the insular cortex, whereas in SII there was no significant difference in lateralization. The greater activity in the contralateral hemisphere for SI and the thalamus is consistent with their roles in the sensory discriminative aspect of pain processing and its associated somatotopy. A recent event related fMRI study revealed different laterality in cerebral activity based on the subjects' skin sensitivity. Querleux et al. (2008) used a lactic acid and saline solution simultaneously applied split-face to either side of the naso-labial fold in a sensitive skin group and a nonsensitive skin group. In both groups, skin discomfort increased activity in SI on the side contralateral to noxious stimulation. The SI activity was significantly greater in the sensitive skin group. While the activity remained contralateral in the non-sensitive group, activity was also detected in the ipsilateral SI and bilateral peri-insular SII region. In a study by Mazzola et al. (2006) lateralization of evoked sensory responses following stimulation of SII, SI, and the insular cortex revealed that the affected limbs were exclusively contralateral to hemisphere stimulated in SI but could also occur bilaterally or ipsilaterally during stimulation of either SII or the insula. The highest percentage of ipsilateral or bilateral responses was elicited after stimulation of SII. Evoked sensations involving the midline body were predominantly bilateral regardless of the side of the stimulated region. Response lateralization was the same regardless of left or right side stimulation (Mazzola et al., 2006).

Reorganization of SI in Pain Conditions Lesions of the afferent nerves may lead to extensive reorganization of the cortex associated with the deafferented body region (Yang et al., 1994; Elbert et al., 1995; Flor et al., 1995). In upper extremity amputation, the cortical representation of the face spread to the neighboring representation of the upper limb zone (Yang et al., 1994; Elbert et al., 1995). For phantom limb pain, the extent of the reorganization was observed to be proportional to the magnitude of the pain experienced (Flor et al., 1995). This cortical plasticity is consistent with the increased cortical representation observed with training (Elbert et al., 1995). Flor et al. (1997) hypothesized that ongoing painful stimulation would result in cortical

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reorganization of SI and that this expansion should be specific to the site of pain and should elicit an exaggerated cortical response, specific to the tactile modality. Using magnetic source imaging (MSI) (Flor et al., 1997), 10 chronic low back pain patients were studied. The data revealed an enhanced cortical reactivity to the tactile stimulation, the magnitude of which was positively related to the chronicity of pain. Significant increases in cortical activity were present in the patients with longer pain duration compared to controls, and were greater than the activity seen with shorter pain duration patients, although this was not significant. Electromagnetic source localization revealed the source of the early peak at 70 ms located in the primary somatosensory cortex, confirming earlier findings with healthy controls suggesting strong involvement of SI in pain processing (Howland et al., 1995). The maximum activity elicited in SI indicated that cortical representation of the back was shifted medially in the chronic back pain patient group, suggesting that chronic pain is accompanied by cortical reorganization. In addition to the enhanced reactivity, the shifting of the representation may indicate an expansion of back representation into the neighboring leg and foot area, in accordance to the shift in upper extremity to face reorganization seen in earlier work (Flor et al., 1995). This cortical reorganization may serve an important role in the persistence of chronic pain experience (Flor et al., 1997). In line with this reasoning is the idea that a re-reorganization, or reversal of reorganization, might occur for patients whose neuropathic pain conditions have been treated successfully, as shown by MEG studies following effective spinal cord stimulation pain treatment (Maihofner et al., 2004). Since this early work by Flor et al. (1995), numerous other studies have shown evidence of cortical reorganization in chronic pain conditions, such as fibromyalgia (Gracely et al., 2004), stroke (Schaechter et al., 2006), complex regional pain syndrome (Maihofner et al., 2006), as well as changes in cortical thickness in SI in chronic back pain patients (Apkarian et al., 2004) and migraine sufferers (DaSilva et al., 2007). A recent study by DaSilva et al. (2008) investigated multiple cortical regions for structural and functional changes in a chronic trigeminal neuropathic pain. It was hypothesized that regions of somatosensory input (SI, SII) would show cortical thickening while areas involved in emotional processing (anterior cingulate cortex, anterior insula) would show cortical thinning, based on previous work by others (Schmidt-Wilcke et al., 2006). Their results revealed that cortical thickness of the most caudal section of SI, representing the craniofacial region, was significantly thinner in the contralateral and ipsilateral sides to the patients' pain when compared to healthy controls. Cortical thinning in the craniofacial region of SI and an observed extension to SII was correlated with functional blood oxygenation level dependent activity elicited by allodynic brush stimulation of the contralateral facial area. In contrast to the thinning of the facial region, bilateral thickening of the rostral neighboring hand and trunk somatosensory areas in SI were observed. Bilateral thickening of the posterior insula with colocalized BOLD activation was also observed. DaSilva et al. (2008) discuss physiological mechanisms potentially underlying the findings in their study. The integrity of the somatosensory map in a healthy system is maintained by an axonal bias at representational body sections of SI, by strength and number of synapses, and by inhibitory and excitatory mechanisms that are increased within sections and decreased near the borders of sections (Steen et al., 2007). In pathological conditions there is dendritic reorganization and resultant somatotopic reshaping (Hickmott and Ethell,

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2006). The somatotopic plasticity in SI can then be explained by either the active neighbouring region to a denervated section as in phantom limb pain (Flor et al., 2006) or by a decrease in functional distance between the affected cortical pain area and neighbouring non-affected sections of SI, as in Maihofner et al. (2003). DaSilva et al. (2008) propose that this latter finding can account for the thickening of the rostral regions of SI, related either to increased axonal sprouting to the neighboring region, or by the activation of previously dormant cortico-cortical connections between the regions. They suggest that the close spatial relationship in healthy subjects may change in chronic pain conditions, that these changes may be related to functional plasticity, and that structural reorganization in SI may occur concomitantly in other non-neighboring regions involved in pain perception such as the insula, as indicated by the high positive correlation for cortical thickening in their study. In addition, as they hypothesized, the overstimulation induced by the evoked and spontaneous components of the neuropathic pain in their study may be a possible cause of the subsequent structural changes in the somatotopic facial region of SI in a manner similar to that observed in the sensorimotor cortex of animal models of deafferentation (Hickmott and Steen, 2005). See Melzack (1999) for a light but informative account of the development of the gate control theory of pain and the neuromatrix. Melzack also presents his thoughts on phantom limb pain, chronic pain, pain and stress, and the multiple determinants of pain.

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Pain Modulation in the Somatosensory Cortex Although the anatomical structures involved in pain transmission are recognized, the cerebral mechanisms involved in pain modulation remain unclear (Valet et al., 2004). While distraction from a pain stimulus is known to reduce the perception of the pain intensity, the mechanism is not understood. Neuroimaging studies aimed at resolving this issue have identified regions of interest in the pain network that may be involved in pain modulation. For example, it has been shown that by focusing attention toward a noxious stimulus, the prefrontal areas, the anterior cingulate cortex, and the thalamus are activated (Peyron et al., 1999), whereas distracting attention away from a noxious stimulus shifts the area of activation from the anterior insular cortex to the posterior insular cortex (Brooks et al., 2002). Numerous studies have provided evidence that distraction from a noxious stimulus reduces the subjective pain experience and the associated cortical activation (Petrovic et al., 2000; Tracey et al., 2002; Lorenz et al., 2003). An fMRI study by Valet et al. (2004) aimed to characterize the mechanisms responsible for the pain modulation. They found that during noxious stimulation without distraction, activation was seen in the lateral parts of the thalamus, and the contralateral SI, SII, and the dorsal-posterior part of the insular cortex, all regions of the lateral pain system. In addition, the medial thalamus, the midcingulate, anterior-ventral parts of the insular cortex, and the lateral prefrontal cortex were activated, as structures that comprise the medial pain system. Valet et al. noted that during noxious stimulation with distraction, activity was significantly reduced in the entire cerebrum.

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DaSilva et al., 2008. Figure 1. Somatosensory (SI & SII) and Motor (MI) Cortices. Panels A and B - SI and MI in this study were defined as the central sulcus including its posterior wall, and the precentral gyrus, respectively. SII was defined was the subcentral section lateroventral to the postcentral gyrus. In the hemispheres contralateral and ipsilateral to the TNP, regions of the sensorimotor cortex were segmented in ten equal vertical sections labeled from bottom to top in an ascendant manner, being section 1 located in the lowest portion, and section ten in the highest.; Panel C - Average BOLD deactivations (dark-light blue) and activations (red-yellow) in the sensorimotor cortex during allodynic brush of the affected V2 of the six TNP patients. The functional clusters were located in the most caudal region of SI and MI where the face and the neighboring regions are somatotopically represented; Panel D – Differences in cortical thickness between TNP and HC along sections of the sensorimotor cortex (pink = TNP,HC; green = TNP.HC). There is bilateral thinning in the most caudal region of the somatosensory cortex, where the face is represented, which was colocalized with functional clusters during allodynic pain.

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Activation was seen in the contralateral dorsal-posterior insular cortex and the SI, whereas no significant activation was seen in the thalamus and SII.The effects of distraction during noxious stimulation led to an increased activity in the posterior thalamus, the perigenual anterior cingulate cortex, the orbitofrontal cortex, and the periaqueductal grey matter. Given that these structures were associated with the reduced pain sensation, and that a covariation analysis of the blood-oxygenation level dependent (BOLD) fMRI pattern revealed a functional interaction with the periaqueductal grey and the posterior thalamus, the authors put forth that these structures are key in the modulation of pain during distraction.

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Mechanisms of Anti-Nociception SI is considered to be the prototypical cortical area of the lateral pain system. PET studies have been used to show that SI has one of the lowest opiate receptor densities and that opiate receptors are primarily associated with the medial pain system (Jones et al., 1991; Vogt et al., 1995). Surrounding the sylvian fissure are several nociceptive regions, including SII in the parietal operculum and the insula, and these regions are also part of the lateral pain system (Treede et al., 2000; Frot and Maguiere, 2003). The insula was originally considered part of the medial pain system based on its output to the limbic system, but it may also be considered part of the lateral pain system based on it receiving direct nociceptive input from the lateral thalamic nuclei (Craig, 1995) as discussed above. Baumgartner et al (2006) used PET to determine the opiate receptor distribution in this operculo-insular region. A main finding of their study was the high opiate receptor availability in the frontal operculum and SII. Baumgartner et al (2006) used PET with the subtype nonselective opioidergic radioligand 18F under resting conditions, to determine how opiate receptor distribution is colocalized with the distribution of nociceptive areas in the human brain. They found that nociceptive areas of the lateral pain system, which included the frontoparietal operculum and the insula, have opiate receptor binding potentials significantly higher than in the primary somatosensory/primary motor cortex (SI/MI) region, and comparable to the cingulate cortices of the medial pain system. In fact, the frontal operculum exhibited higher binding potential than the midcingulate cortex. This supports the hypothesis of Treede et al (2000) that the frontal operculum, including SII, is more important in processing nociception and pain sensation than SI. In addition, the Baumgartner et al. study revealed a higher opiate receptor binding potential in the insular cortex than the opercular cortex. While traditionally this would be interpreted as evidence for the opiate receptor modulation of the medial pain system, it could otherwise be interpreted as evidence for the opiate receptor modulation of the lateral pain system, given the nociceptive input from the thalamic nuclei. Regardless of the classification, their findings suggest that the cortical anti-nociceptive effects of opiates are mediated by the opercular-insular cortex in addition to the cingulate cortex. The findings here nicely parallel those of Frot et al. (2007) with intracranial recordings of the insula, showing increasing amplitudes with increasing stimulus energies, while recording of the SII regions. They also showed intensity coding below pain threshold only, with a plateau at higher intensity, whereas Ostrowsky et al. (2002) showed direct stimulation of the insula produces a painful sensation. These studies support the ideas that pain intensity

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encoding is a function of the insular cortex, and that opiate effects on sensory pain involve the operculo-insular component of the lateral pain system (Baumgartner et al., 2006). Stimulation of the primary motor cortex has been used for many years as a non-invasive treatment for chronic pain (Lefaucheur et al., 2001; Pleger et al., 2004; Johnson et al., 2006). Recently, repetitive transcranial magnetic stimulation (rTMS) of the secondary somatosensory cortex has also been shown effective for reducing chronic pain of pancreatitis (Fregni et al., 2005). It is proposed that rTMS of the SII cortex may be effective for the treatment of visceral pain, although more research is required (Fregni et al., 2007). Somatosensory cortex stimulation has also proven effective for deafferentation pain (De Ridder et al., 2007). Lesions along the somatosensory tract can cause deafferentation pain, such as phantom limb pain, where cortical plasticity occurs and leads to somatosensory cortex reorganization (De Ridder et al., 2007). The rationale behind the strategy of using rTMS, as outlined in De Ridder et al. (2007) is as follows. The phantom pain is caused by cortical hyperactivity and reorganization, which can be demonstrated by functional neuroimaging techniques such as PET, fMRI or MSI. The area of hyperactivity and reorganization can be influenced by neuronavigated TMS and, given a successful suppression of pain by TMS, a stimulating electrode can be implanted epidurally over the area identified. In this way, a target was located on the somatosensory cortex at a site corresponding to an area of hyperactivity for 8 patients (De Ridder et al., 2007). Neuronavigation-guided TMS was able to suppress the deafferentation pain in 5 of the 8 patients. While the underlying mechanism is unclear, it is proposed by De Ridder et al. (2007) that activation of descending corticofugal axons may be responsible for increased synaptic activity in the thalamus rather than at the dendrites in the cortex. Cortical stimulation activates and increases firing rates of deafferented neurons, resulting in more lateral inhibition, and deactivates the neural substrate responsible for the deafferentation pain. In animal research, it has also been shown that stimulation of SII facilitates the anti-nociception effect of a neuronal NO synthase inhibitor in rats (Kuroda et al., 2001). SII stimulation in combination with 7-nitro-indazole worked synergistically to reduce the expression of c-Fos following formalin injection to the fourth and fifth lumbar spinal dorsal horn. The synergistic anti-nociception was resistant to both the opiate antagonist naloxone and the alpha-adrenoceptor antagonist phentolamine, but was reduced by the serotonin receptor antagonist methysergide. The authors suggest that SII stimulation, in combination with inhibition of neuronal NO synthase, may suppress spinal nociceptive neurons through a descending spinal serotonergic pathway resulting in antinociception. Although the mechanism is unknown, it is clear that stimulation of somatosensory cortex has the advantage over the conventional motor cortex stimulation in the immediate effect it produces allowing for easier and less time-consuming programming of parameters. Although very new, this technique shows promise for alleviating pain and reversing reorganization thought to be responsible for the neuropathic pain conditions, and warrants further investigation with other sites of stimulation and other patient populations (De Ridder et al., 2007).

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Conclusion The research presented here supports the claim that the somatosensory cortex is involved in the sensory-discriminative aspect of pain processing. The three components of sensorydiscriminative processing, that of stimulus localization, intensity discrimination, and quality discrimination, were shown to occur in the somatosensory cortex. Evidence for stimulus localization as a function of SI is strong. Somatotopic representation of the hand and foot were seen in SI, whereas SII showed bilateral activity without significant differences in hand and foot representation. This indicates that SI is well equipped to serve stimulus localization (Ogino et al., 2005). The work by Chen et al. (2009) revealed in more detail the topography of this representation of noxious and innocuous stimuli, showing that nociceptive input to SI is processed in areas 3a and 1 while innocuous input is processed in areas 3b and 1. Further, evidence for topography for nociceptive input within areas 3a and 1 was presented, overlapping with the tactile somatotopy maps. The work by Mazzola et al. (2006) revealed lower spatial resolution as indicated by decreasing size of receptive fields from SI, SII, and the insula, again supporting the premise that SI is equipped for stimulus localization. The strong lateralization of SI activity as compared to the bilateral activity in SII in response to a lateralized stimulus presentation provides further support (Youell et al., 2004). Taken together, this evidence supports the role of SI in stimulus localization. Evidence for intensity discrimination as a function of the somatosensory cortex has also been provided by recent imaging studies. Frot et al. (2007) have shown that the insula and SII are involved in intensity encoding of thermal stimuli. Whereas the SII was shown to gradually encode increasing thermal stimuli in the range of the sensory threshold to the pain threshold, the insula encoded stimulus intensities above the pain threshold. It has also been shown that with an increasing mechanical noxious stimulus, increasing signal amplitudes are recorded in SI (Chen et al., 2009) suggesting an intensity discriminative function of this region. The role of the somatosensory cortex in qualitative discrimination of nociceptive input has been supported by recent imaging studies. Selective stimulation of Aδ and C fibres has revealed that SI is involved in the processing of first pain, which is qualitatively described as pricking, sharp and well localized pain, whereas SII is involved in processing both first and second pain, described as a dull, burning, diffuse pain. SII is strongly and equally activated by both first and second pain, and there appears to be a processing of these two pain types in different time windows. These differences in cortical representation may contribute to the differences in quality perception (Ploner et al., 2002; Forss et al., 2005). Additional evidence for this role is provided by stimulation of somatosensory cortex and the resultant pain sensations. Whereas stimulation of SI cortex does not elicit any pain sensation, stimulation of SII elicits a pain sensation, described as tingling or cramping, and stimulation of the insula elicits a painful sensation described as burning or stinging (Mazzola et al., 2006). The ability of the somatosensory cortex to discriminate qualitatively is therefore supported by this recent work. The imaging studies of the past decade have provided evidence for the role of the somatosensory cortex in the processing of pain. To date, the evidence points to the SI region as a primary source of noxious stimulus localization, the SII region as involved in the

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qualitative discrimination of noxious stimuli, and the insular cortex as involved in the intensity coding of stimuli in the noxious range. Although there does appear to be some overlap in these functions, there is strong evidence to support the role of the somatosensory cortex in pain processing and more recent work has begun to tease apart the specific functions of the somatosensory regions. As proposed by Treede et al. (1999) it is not an improvement in imaging techniques that is required to answer these questions but rather the development of new experimental paradigms that carefully delineate the multiple dimensions of pain, as outlined in the IASP definition.

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References Andersson, J. L., A. Lilja, et al. (1997). Somatotopic organization along the central sulcus, for pain localization in humans, as revealed by positron emission tomography. Exp Brain Res. 117(2): 192-9. Apkarian, A. V., Y. Sosa, et al. (2004). Chronic back pain is associated with decreased prefrontal and thalamic gray matter density. J Neurosci. 24(46): 10410-5. Apkarian, A. V., R. A. Stea, et al. (1994). Heat-induced pain diminishes vibrotactile perception: a touch gate. Somatosens Mot Res. 11(3): 259-67. Apkarian, A. V., R. A. Stea, et al. (1992). Persistent pain inhibits contralateral somatosensory cortical activity in humans. Neurosci Lett. 140(2): 141-7. Baumgartner, U., H. G. Buchholz, et al. (2006). High opiate receptor binding potential in the human lateral pain system. Neuroimage, 30(3): 692-9. Brooks, J. C., T. J. Nurmikko, et al. (2002). fMRI of thermal pain: effects of stimulus laterality and attention. Neuroimage, 15(2): 293-301. Brooks, J. C. and I. Tracey (2007). The insula: a multidimensional integration site for pain. Pain, 128(1-2): 1-2. Brooks, J. C., L. Zambreanu, et al. (2005). Somatotopic organisation of the human insula to painful heat studied with high resolution functional imaging. Neuroimage, 27(1): 201-9. Bushnell, M. C., G. H. Duncan, et al. (1999). Pain perception: is there a role for primary somatosensory cortex? Proc Natl Acad Sci U S A. 96(14): 7705-9. Chen, L. M., R. M. Friedman, et al. (2008). Optical imaging of nociception in primary somatosensory cortex of non-human primates. Acta Physiologica Sinica, 60(5): 664-8. Chen, L. M., R. M. Friedman, et al. (2009). Area-specific representation of mechanical nociceptive stimuli within SI cortex of squirrel monkeys. Pain, 141: 258-68. Craig, A.D (1995). Supraspinal projections of lamina I neurons. In: Besson, J.M., Guilbaud, G., Ollat, H. (Eds.), Forebrain Areas Involved in Pain Processing. John Libbey Eurotext, Paris, pp. 13-25. DaSilva, A. F., L. Becerra, et al. (2008). Colocalized structural and functional changes in the cortex of patients with trigeminal neuropathic pain. PLoS ONE, 3(10): e3396. DaSilva, A. F., C. Granziera, et al. (2007). Thickening in the somatosensory cortex of patients with migraine. Neurology, 69(21): 1990-5. De Ridder, D., G. De Mulder, et al. (2007). Somatosensory cortex stimulation for deafferentation pain. Acta Neurochir Suppl. 97(Pt 2): 67-74.

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Derbyshire, S. W., A. K. Jones, et al. (2002). Cerebral responses to noxious thermal stimulation in chronic low back pain patients and normal controls. Neuroimage, 16(1): 158-68. Dong, W. K., L. D. Salonen, et al. (1989). Nociceptive responses of trigeminal neurons in SII-7b cortex of awake monkeys. Brain Res. 484(1-2): 314-24. Eickhoff, S., Amunts, K., Mohlberg, H., Zilles, K. (2006). The human parietal operculum. II. Stereotaxic maps and correlation with functional imaging results. Cerebral Cortex, 16:268-79. Elbert, T., C. Pantev, et al. (1995). Increased cortical representation of the fingers of the left hand in string players. Science, 270(5234): 305-7. Flor, H., C. Braun, et al. (1997). Extensive reorganization of primary somatosensory cortex in chronic back pain patients. Neurosci Let.t 224(1): 5-8. Flor, H., T. Elbert, et al. (1995). Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation. Nature, 375(6531): 482-4. Flor, H., L. Nikolajsen, et al. (2006). Phantom limb pain: a case of maladaptive CNS plasticity? Nat Rev Neurosci. 7(11): 873-81. Forss, N., T. T. Raij, et al. (2005). Common cortical network for first and second pain. Neuroimage, 24(1): 132-42. Fregni, F., D. DaSilva, et al. (2005). Treatment of chronic visceral pain with brain stimulation. Ann Neurol. 58(6): 971-2. Fregni, F., S. Freedman, et al. (2007). Recent advances in the treatment of chronic pain with non-invasive brain stimulation techniques. Lancet Neurol. 6(2): 188-91. Frot, M., L. Garcia-Larrea, et al. (2001). Responses of the supra-sylvian (SII) cortex in humans to painful and innocuous stimuli. A study using intra-cerebral recordings. Pain, 94(1): 65-73. Frot, M., M. Magnin, et al. (2007). Human SII and posterior insula differently encode thermal laser stimuli. Cereb Cortex, 17(3): 610-20. Frot, M. and F. Mauguiere (2003). Dual representation of pain in the operculo-insular cortex in humans. Brain, 126(Pt 2): 438-50. Gracely, R. H., M. E. Geisser, et al. (2004). Pain catastrophizing and neural responses to pain among persons with fibromyalgia. Brain, 127(Pt 4): 835-43. Hickmott, P. W. and I. M. Ethell (2006). Dendritic plasticity in the adult neocortex. Neuroscientist, 12(1): 16-28. Hickmott, P. W. and P. A. Steen (2005). Large-scale changes in dendritic structure during reorganization of adult somatosensory cortex. Nat Neurosci. 8(2): 140-2. Howland, E. W., R. T. Wakai, et al. (1995). Whole head mapping of magnetic fields following painful electric finger shock. Brain Res Cogn Brain Res. 2(3): 165-72. Inui, K., T. D. Tran, et al. (2002). Pain-related magnetic fields evoked by intra-epidermal electrical stimulation in humans. Clin Neurophysiol. 113(2): 298-304. Inui, K., T. D. Tran, et al. (2003). A comparative magnetoencephalographic study of cortical activations evoked by noxious and innocuous somatosensory stimulations. Neuroscience, 120(1): 235-48.

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Jennifer Kornelsen and Boguslaw Tomanek

Johnson, S., J. Summers, et al. (2006). Changes to somatosensory detection and pain thresholds following high frequency repetitive TMS of the motor cortex in individuals suffering from chronic pain. Pain, 123(1-2): 187-92. Jones, A. K., W. D. Brown, et al. (1991). Cortical and subcortical localization of response to pain in man using positron emission tomography. Proc Biol Sci. 244(1309): 39-44. Kakigi, R., K. Inui, et al. (2005). Electrophysiological studies on human pain perception. Clin Neurophysiol. 116(4): 743-63. Kanda, M., T. Nagamine, et al. (2000). Primary somatosensory cortex is actively involved in pain processing in human. Brain Res. 853(2): 282-9. Kenshalo, D. R., and Douglass, D. K. (1995) The role of the cerebral cortex in the experience of pain. In: B. Bromm and J.E. Desmedt (Eds.), Pain and the Brain: From Nociception to Cognition, Raven Press, New York, pp. 21-34. Kenshalo, D. R., and O. Isensee (1983). Responses of primate SI cortical neurons to noxious stimuli. J Neurophysiol. 50(6): 1479-96. Kuroda, R., N. Kawao, et al. (2001). Secondary somatosensory cortex stimulation facilitates the antinociceptive effect of the NO synthase inhibitor through suppression of spinal nociceptive neurons in the rat. Brain Res. 903(1-2): 110-6. Lamour, Y., G. Guilbaud, et al. (1983). Rat somatosensory (SmI) cortex: II. Laminar and columnar organization of noxious and non-noxious inputs. Exp Brain Res. 49(1): 46-54. Lefaucheur, J. P., X. Drouot, et al. (2001). Interventional neurophysiology for pain control: duration of pain relief following repetitive transcranial magnetic stimulation of the motor cortex. Neurophysiol Clin. 31(4): 247-52. Lorenz, J., S. Minoshima, et al. (2003). Keeping pain out of mind: the role of the dorsolateral prefrontal cortex in pain modulation. Brain, 126(Pt 5): 1079-91. Maihofner, C., H. O. Handwerker, et al. (2006). Functional imaging of allodynia in complex regional pain syndrome. Neurology, 66(5): 711-7. Maihofner, C., H. O. Handwerker, et al. (2003). Patterns of cortical reorganization in complex regional pain syndrome. Neurology, 61(12): 1707-15. Maihofner, C., H. O. Handwerker, et al. (2004). Cortical reorganization during recovery from complex regional pain syndrome. Neurology, 63(4): 693-701. Mazzola, L., J. Isnard, et al. (2006). Somatosensory and pain responses to stimulation of the second somatosensory area (SII) in humans. A comparison with SI and insular responses. Cereb Cortex, 16(7): 960-8. Melzack, R. (1999). From the gate to the neuromatrix. Pain Supp.l 6: S121-6. Merskey, H. (1986). Classification of chronic pain. Descriptions of chronic pain syndromes and definitions of pain terms. Pain Suppl., 3 S1-S225. Meyer, E., S. S. Ferguson, et al. (1991). Attention modulates somatosensory cerebral blood flow response to vibrotactile stimulation as measured by positron emission tomography. Ann Neurol. 29(4): 440-3. Ogino, Y., H. Nemoto, et al. (2005). Somatotopy in human primary somatosensory cortex in pain system. Anesthesiology, 103(4): 821-7. Ostrowsky, K., M. Magnin, et al. (2002). Representation of pain and somatic sensation in the human insula: a study of responses to direct electrical cortical stimulation. Cereb Cortex, 12(4): 376-85.

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49

Petrovic, P., K. M. Petersson, et al. (2000). Pain-related cerebral activation is altered by a distracting cognitive task. Pain, 85(1-2): 19-30. Peyron, R., L. Garcia-Larrea, et al. (1999). Haemodynamic brain responses to acute pain in humans: sensory and attentional networks. Brain, 122 ( Pt 9): 1765-80. Pleger, B., F. Janssen, et al. (2004). Repetitive transcranial magnetic stimulation of the motor cortex attenuates pain perception in complex regional pain syndrome type I. Neurosci Lett. 356(2): 87-90. Ploner, M., J. Gross, et al. (2002). Cortical representation of first and second pain sensation in humans. Proc Natl Acad Sci U S A. 99(19): 12444-8. Ploner, M., F. Schmitz, et al. (1999). Parallel activation of primary and secondary somatosensory cortices in human pain processing. J Neurophysiol. 81(6): 3100-4. Querleux, B., K. Dauchot, et al. (2008). Neural basis of sensitive skin: an fMRI study. Skin Res Technol. 14(4): 454-61. Rainville, P., G. H. Duncan, et al. (1997). Pain affect encoded in human anterior cingulate but not somatosensory cortex. Science, 277(5328): 968-71. Schaechter, J. D., C. I. Moore, et al. (2006). Structural and functional plasticity in the somatosensory cortex of chronic stroke patients. Brain, 129(Pt 10): 2722-33. Schlereth, T., U. Baumgartner, et al. (2003). Left-hemisphere dominance in early nociceptive processing in the human parasylvian cortex. Neuroimage, 20(1): 441-54. Schmidt-Wilcke, T., E. Leinisch, et al. (2006). Affective components and intensity of pain correlate with structural differences in gray matter in chronic back pain patients. Pain, 125(1-2): 89-97. Sewards, T. V. and M. Sewards (2002). Separate, parallel sensory and hedonic pathways in the mammalian somatosensory system. Brain Res Bull. 58(3): 243-60. Steen, P. A., M. Mason, et al. (2007). Axonal bias at a representational border in adult rat somatosensory cortex (S1). J Comp Neurol. 500(4): 634-45. Talbot, J. D., S. Marrett, et al. (1991). Multiple representations of pain in human cerebral cortex. Science, 251(4999): 1355-8. Tracey, I., A. Ploghaus, et al. (2002). Imaging attentional modulation of pain in the periaqueductal gray in humans. J Neurosci. 22(7): 2748-52. Treede, R. D., A. V. Apkarian, et al. (2000). Cortical representation of pain: functional characterization of nociceptive areas near the lateral sulcus. Pain, 87(2): 113-9. Treede, R. D., D. R. Kenshalo, et al. (1999). The cortical representation of pain. Pain, 79(23): 105-11. Valet, M., T. Sprenger, et al. (2004). Distraction modulates connectivity of the cingulofrontal cortex and the midbrain during pain--an fMRI analysis. Pain, 109(3): 399-408. Vogt, B. A. and R. W. Sikes (2000). The medial pain system, cingulate cortex, and parallel processing of nociceptive information. Prog Brain Res. 122: 223-35. Vogt, B.A., Watanabe, J., Grootoonk, S., Jones, A.K.P. (1995) Topography of deprenorphine binding in human cingulate gyrus and adjacent cortex derived from coregistered PET and MR images. Hum Brain Mapp. 3, 1-12. Xie, Y. F., F. Q. Huo, et al. (2009). Cerebral cortex modulation of pain. Acta Pharmacol Sin. 30(1): 31-41.

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Xu, X., H. Fukuyama, et al. (1997). Functional localization of pain perception in the human brain studied by PET. Neuroreport, 8(2): 555-9. Yang, T.T., C. C. Gallen, et al. (1994). Noninvasive detection of cerebral plasticity in adult human somatosensory cortex. Neuroreport, 5(6): 701-4. Youell, P. D., R. G. Wise, et al. (2004). Lateralisation of nociceptive processing in the human brain: a functional magnetic resonance imaging study. Neuroimage, 23(3): 1068-77.

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In: Somatosensory Cortex: Roles, Interventions and Traumas ISBN 978-1-60741-876-4 Editor: Niels Johnsen and Rolf Agerskov © 2008 Nova Science Publishers, Inc.

Chapter 3

Cortical Representation of Cutaneous Receptors in Primary Somatic Sensory Cortex of Man: A Functional Imaging Study Polonara Gabriele1, Mascioli Giulia1, Salvolini Ugo1, Manzoni Tullio2 and Fabri Mara2* 1

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2

Istituto di Radiologia; Università Politecnica delle Marche, Ancona, Italy; Dipartimento di Neuroscienze, Sezione di Fisiologia; Università Politecnica delle Marche, Ancona, Italy

Abstract This study describes the cortical representation of the cutaneous periphery in human first somatic sensory area (SI). The aim of the investigation was to: 1. reconsider the somatosensory homunculus using a widely available, non-invasive technique, and 2. establish whether medium-strength (1.5 Tesla) fMRI imaging can be used to map reliably somatosensory cortical areas in man. A General Electric Signa LX NV/i magnet normally employed for diagnostic purposes was used to study 19 healthy volunteers by acquiring 10 contiguous 5-mmthick brain sections parallel to the bicommissural plane using 50mT/m gradients and an echo planar sequence. Unilateral tactile stimulation was applied to 10 different body * Address for correspondence: Mara Fabri Dipartimento di Neuroscienze, Sezione di Fisiologia; Università Politecnica delle Marche Via Tronto 10/A, 60020 Ancona - Torrette, Italy Phone: +39 071 220 6193 Fax: +39 071 220 6052 E-mail: [email protected]

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Polonara Gabriele, Mascioli Giulia, Salvolini Ugo, et al. regions by rubbing the skin with a soft cotton pad at a frequency of about 1 Hz. The stimulation paradigm, consisting of alternating periods of rest and stimulation, lasted 5 min. Stimulation of different body regions evoked activation foci in the post-central gyrus of the anterior parietal cortex, where SI is located. Activated cortical regions followed a precise topographical organization: foci evoked by foot, lower leg, trunk, arm, hand and face stimulation were arranged medial to lateral throughout the contralateral post-central gyrus. Stimulation of proximal body regions (face, trunk, proximal limbs) and of the hand also elicited consistent activation in area SI of the ipsilateral hemisphere. The resulting somatotopic map agrees with previous human and monkey functional studies. The present data confirm that in man, as in non-human primates, the cutaneous periphery is represented in a somatotopically organized fashion in contralateral area SI. As demonstrated in monkeys, some body regions are represented bilaterally in the anterior parietal cortex. The possible mechanisms underpinning such bilateral representation are discussed, also analyzing the interhemispheric connections between homologous SI regions.

Keywords: body map, somatosensory cortex, somatotopy, brain imaging, fMRI.

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Introduction The cortical representation of the cutaneous periphery in human parietal cortex has been studied since Penfield (Penfield and Boldrey, 1937; Penfield and Rasmussen, 1950; Woolsey et al., 1979). The area containing the representation of the skin and the deep receptors in the opposite hemibody has been designated as the first somatic sensory cortex (SI), although for some authors the term refers only to area 3b (see Kaas, 1983, Kaas et al., 2002, for a review). In this work, as in most imaging studies, SI is taken to encompass all four anterior parietal fields. Many papers have explored the topographic organization of SI in mammals, which in non-human primates has been localized in the anterior parietal cortex (APC) just behind the central sulcus (CS), in the post-rolandic gyrus. Area SI is made up of four distinct cytoarchitectonic regions, 3a, 3b, 1 and 2 from anterior to posterior, each having a different functional role and containing a complete representation, usually of the contralateral half of the body periphery (Kaas et al., 1979; Nelson et al., 1980; see Kaas et al., 2002 for data and literature). Four distinct architectonic areas have also been described in human SI (Geyer et al, 1997, 1999, 2000), while data about the representation of peripheral cutaneous receptors are still fragmentary (Moore et al., 2000; Young et al., 2004). Penfield’s early description of the cortical representation was a “homunculus” oriented medio-laterally in the contralateral hemisphere, with the head regions lying laterally and the lower limbs and feet medially (Penfield and Boldrey, 1937). Although subsequent studies have largely confirmed this organization, most have investigated the representation of parts of the sensory periphery that are set wide apart, like hand, foot, and lips, thus failing to sketch a comprehensive picture (see Burton, 2002, for a review). The one study providing a complete description is reported in a magnetoencephalography (MEG) work analyzing the

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Cortical Representation of Cutaneous Receptors…

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cortical activation elicited in SI by stimulation of cutaneous receptors over the entire body surface (Nakamura et al., 1998). This functional magnetic resonance imaging (fMRI) investigation used a mediumstrength (1.5 Tesla; T) magnet to study the cortical representation of tactile skin receptors in human contralateral area SI, to establish whether this widely used non-invasive technique, often employed in the preoperative work-up of brain surgery patients, is a useful and reliable tool to define cortical areas activated by tactile stimulation. We also investigated the cortical representation of some body regions in ispilateral area SI. Previous studies of the ipsilateral representation of skin regions in the human brain have addressed hand (Polonara et al., 1999; Fabri et al., 1999, 2001, 2002), trunk (Fabri et al., 2005, 2006) and head midline receptors (Disbrow et al., 2003).

Methods Subjects

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Nineteen healthy volunteers (aged 22 to 49 years; 11 females, 8 males; Table 1) gave their informed consent to participate in the study. The experimental protocol was approved by the institutional Ethics Committee. All but three subjects were right-handed as determined by the Edinburgh handedness inventory (Oldfield, 1971; Table 1). Imaging Protocols Subjects were placed in a 1.5 T scanner (Signa LX NV/i, General Electric Medical System, Milwaukee, WI, USA) equipped with 50 mT/m gradients, with the head restrained within a circularly polarized head coil. They were instructed to keep their eyes closed, find a comfortable position and relax, avoiding even minimal movement; their ears were plugged. Subjects due to receive tactile stimulation of the tongue were asked to keep the tongue out of their closed lips. The experimental procedure consisted of four steps. In the first step, an anatomic sagittal localizer (SPGR, 2D, TR 120 ms, TE 15 ms, Flip Angle 70°, Field of View 23 x 23 cm, slice thickness 5 mm, Matrix 256 x 256, 1 Nex, scan time 31 s) was acquired to select section levels. Ten contiguous 5 mm thick oblique axial sections parallel to the bicommissural plane were selected. The second step involved acquisition of a 3D data set (IR Prep Fast SPGR 3D; TR 15.2 ms, TE 6.9 ms, TI 500 ms, Flip Angle 15°, Field of View 29 x 29 cm, slice thickness 1 mm, matrix 288 x 288, 1 Nex, scan time 8:20 min). These data were not obtained in the first volunteer (L.B.) because the relevant sequence became available during the investigation. The data were then processed with the BrainVoyager software (BV; QX version, BrainInnovation, Maastricht, The Netherlands), which uses the 3D data sets to co-register and align functional activation maps onto volume images of the brain. The third step involved the acquisition of high-resolution axial anatomic images (SPGR, 2D, TR 100 ms, TE 12 ms, Flip Angle 70°, Field of View 28 x 21 cm, thickness 5 mm, Matrix 256 x 256, 1 Nex, scan time 3:17 min for 10 images), on which the functional activation images were superimposed. The anatomic images allow to visualize blood vessels, which are possible sources of signal.

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Table 1. Subjects studied and stimulation sites

Subject

Age (years )

Gender

Body region stimulated Handedness (Oldfield score) tongue face hand

L.B.

29

M

right (12)

L.A.

23

M

right (26)

I.P.

22

F

right (18)

E.P.

24

F

right (19)

L

A.I.

35

M

right (12)

R

R

F.F.

23

F

right (13)

L

L

C.C.

30

M

right (19)

L*

L

E.G.

24

F

right (10)

L*

A.M.

24

M

right (16)

G.M.

33

F

left (46)

Al.M.

28

F

right (10)

L, R

A.V.

24

M

right (16)

L, R

M.S.

28

F

left (41)

L, R

Lu.A.

38

F

right (10)

L, R

E.B.

27

F

right (14)

L

A.S.

43

F

right (10)

L, R L

L

forearm

arm

shoulder

trunk

R

R

L

L

L

L

thigh

L

leg

foot

L

L

L

L

R

R L

L L

L L

L

L, R L, R

L

L L L

L

L

R

L

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Table 1. (Continued)

Subject

Age (years )

Gender

Body region stimulated Handedness (Oldfield score) tongue face hand

M.D.

42

F

left (40)

E.A.

36

M

right (13)

M.A.

49

M

right (10)

*hand dorsum

forearm

arm

shoulder

trunk

thigh

L L

L L

foot L

L L

leg

L

56

Polonara Gabriele, Mascioli Giulia, Salvolini Ugo, et al.

In the fourth step fMRI scans were acquired in the same axial planes with a single-shot T2*weighted gradient-echo EPI sequence (TR 3,000 ms, TE 60 ms, Flip Angle 90°, Field of View 28 x 21 cm, Matrix 96 x 64, 1 Nex, scan time 5:12 min). During the stimulation cycle 1000 axial functional images (100/section, 1 image/3 s) were acquired from the 10 contiguous axial sections selected in the second step. Consecutive images from each section were examined in cine mode to detect any head movements (see Kim and Urgubil 1997, for a review). Cycles in which head motion was detected were discarded. Functional images were obtained with the blood oxygenation level-dependent contrast (BOLD) method. Axial planes were orthogonal to both sagittal and coronal planes and allowed to identify the CS and the post-central gyrus (PCG).

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Stimulation Unilateral tactile stimulation was applied by rubbing skin regions with a soft cotton pad (trunk regions), a soft sponge (mandibular region of the face) or a rough sponge (hand, foot, and limbs) at a frequency of about 1 Hz (Figure 1). Tongue stimulation using cotton buds was applied to one side of the tongue, carefully avoiding the lips. Stimulation was applied to right hemibody regions in 2 subjects, to left hemibody regions in 12, and to either side of tongue and face in 5 and 2 subjects, respectively (Table 1). We used three block-design stimulation paradigms, all lasting 5 min. The first, applied for tactile stimulation of a single body region (L.B., L.A., I.P., C.C., E.G., A.M., G.M., Al.M., A.V., M.S., Lu.A., E.B.), consisted of five 30-s periods of rest alternating with five 30-s periods of stimulation. The second, used for tactile stimulation of two body regions in the same session (subjects E.P., A.I., F.F., A.S., M.D., E.A. and M.A.), was composed of ten 15-s periods of rest alternating with ten 15-s periods of stimulation. During each stimulation period, two regions (e.g. hand/foot, or trunk/face) were alternately stimulated, enabling a larger number of body regions to be studied in a smaller number of sessions. Subjects Al.M., G.M., Lu.A., E.B., A.V., and M.S. also participated in a study of the cortical representation of gustatory sensitivity using a paradigm made up of 60 s rest, 30 s stimulation, 90 s rest, 30 s stimulation, and 90 s rest. A similar paradigm was applied for tactile stimulation of the tongue to compare the two sets of findings. Subjects received 2-4 scans, depending on whether two or more body regions were being stimulated (Table 1). Two subjects, I.P. and E.A., were studied in two different sessions. During rest periods the experimenter made the same movements 10-15 cm above the subject's hand as a control for stimulus-related signal intensity changes (Yetkin et al., 1996). Data Analysis After the experimental session, images were transferred to a Unix workstation (General Electric Advantage Windows 4.2) and then to a personal computer. Data from all subjects were analyzed with the BV software and the Statistical Parametric Mapping software (SPM2; The Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College, London, UK), as follows.

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Figure 1. Illustration of the left hemibody regions that received tactile stimulation in different subjects during different scans. The right side regions were symmetric to those shown in color in the figurine.

The first two images of each functional series were discarded. Data from each subject were processed to remove noise and artifacts. In BV analysis, the functional images of each patient were overlaid on the 2D anatomic images and incorporated into their 3D data sets through trilinear interpolation. Data were then transformed into Talairach space (Talairach and Tournoux, 1988). Preprocessing of functional scans included 3D motion correction. SPM2 analysis included preprocessing of functional scans to remove motion artifacts (spatial realignment of images), to co-register coplanar and echoplanar images to the high-resolution image. Data were then resampled into 2-mm isotropic voxels and warped into a standardized atlas space (normalization; Talairach and Tournoux, 1988). Each scan was adjusted to the Talairach coordinate system to identify the position of activated areas. Rest and stimulation conditions were modeled using a General Linear Model (GLM) statistical analysis that accounted for the delayed cerebral blood flow change after stimulus presentation. Activated volumes are clusters of at least 8 voxels (1 voxel = 1 mm x 1 mm x 1 mm) in which the signal change was significantly different from the baseline (P < 0.05). When the signal increase in selected regions of interest (ROIs) - lying in areas corresponding anatomically to SI (in PCG) - correlated temporally with the stimulation pattern, the activation was assumed to be evoked by the tactile stimulus. Averaged time courses were calculated within each ROI in order to show the mean BOLD signal change due to the stimulus. BOLD signal changes were expressed as a percentage of the baseline signal.

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Area SI was identified by analyzing its location according to standard anatomic landmarks (e.g. the omega-shaped CS in axial views) and a reference atlas (Mai et al., 1997). A paired t test was applied to the mean signal increases and mean activation volume sizes obtained in the contralateral and ipsilateral hemisphere. A P value of 0.05 was significant.

Results Left Side Stimulation Left side stimulation was applied on tongue, hand and thigh (n=6 subjects), trunk (n=5), face, lower leg, foot, forearm and arm (n=4), and shoulder (n=3) (Table 1). Activation was consistently elicited in contralateral SI; ipsilateral activation was also noted for some body parts, as detailed below. Signal increases (Table 2) and activated cortical volumes (Table 3) in the ipsilateral hemisphere, where present, were not significantly different from those observed in the contralateral hemisphere (P > 0.05).

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Table 2. Percent signal increase evoked by tactile stimulation of left hemibody Body region stimulated

Mean signal increase (%) ± SD contralateral SI

ipsilateral SI

p value

Tongue (n=6)

1.6 ± 0.6

1.7 ± 0.5

0.43

Face (n=4)

1.5 ± 0.4

1.4 ± 0.2

0.73

Hand (n=5)

1.9 ± 0.9

1.6 ± 0.3

0.54

Forearm (n=4)

0.8 ± 0.5

-

-

Arm (n=4)

0.7 ± 0.1

0.6 ± 0.0

0,08

Shoulder (n=3)

1.0 ± 0.8

0.6 ± 0.5

0.44

Trunk (n=4)

1.0 ± 0.6

0.9 ± 0.6

0.82

Thigh (n=6)

0.8 ± 0.4

0.7 ± 0.2

0.41

Lower leg (n=4)

0.8 ± 0.3

-

-

Foot (n=3)

1.3 ± 0.6

-

-

Head

Tongue and Face Stimulation Tactile stimulation of the left hemitongue and the mandibular region of the face (see Figure 1) caused bilateral activation in SI in the more lateral part of the PCG (Figure 2A, B). The contralateral and ipsilateral activation foci had similar Talairach coordinates in the two Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

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hemispheres (Table 4). In both hemispheres the tactile representation of the tongue occupied a more posterior and medial cortical region than that of the face tactile receptors stimulated in the present study (Figure 8).

Figure 2. Cortical activation in PCG, elicited in different subjects and scans during tactile stimulation of left head regions and left hand. Activated regions (visualized using GE T2* single-shot EPI sequences [3000/60/1]) were superimposed on axial (A1, B1, C1), coronal (A2, B2, C2), and sagittal images from the contralateral (A3, B3, C3) and ipsilateral hemisphere (A4, B4, C4) obtained with an SPGR T1-weighted sequence (100/12/1 [repetition time/echo time/excitations]). Left hemisphere on the right. A: activation evoked by left tongue stimulation (subject E.B.). Activation foci were found both in the right, contralateral hemisphere (1) and in the left, ipsilateral hemisphere (2), as shown in the axial (A1), coronal (A2), and sagittal images (A3, contralateral, and A4, ipsilateral). B: activation evoked by left face stimulation (subject G.M.). Activation foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral cortex (2), as shown in axial (B1), coronal (B2), and sagittal images (A3, contralateral, and B4, ipsilateral). C: activation elicited by left hand stimulation (subject E.G.). Foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral hemisphere (2), as shown in axial (C1), coronal (C2), and sagittal images (C3, contralateral, and C4, ipsilateral). CS, central sulcus.

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Hand Stimulation The functional data showed that unilateral tactile stimulation of the hand (palm and fingers) activated several foci in both hemispheres. Strong activation was detected in the contralateral PCG during left hand stimulation. Sometimes two foci were evoked. One was along the posterior bank of the omega-shaped CS and in the hand representation zone of SI (Figure 2C, focus 1); this focus partially extended rostrally into the anterior bank of the CS, in the motor cortex, which is frequently co-activated during passive tactile stimulation (see also Polonara et al., 1999). The other focus was in the posterior parietal cortex (PPC), around and in the depth of the PCS (Figure 2C, focus 1’). Since in most cases it was difficult to distinguish the anterior from the posterior focus within SI, to the purpose of quantitative analysis they were considered as a single activation area (Tabs. II-IV). In the left (ipsilateral) hemisphere, somatosensory activation was observed in the PCG, in a region corresponding to the PPC (Figure 2C, focus 2), but not in the APC, which forms the posterior bank of the CS. The difference between mean contralateral and ipsilateral activation volumes (959 and 484, respectively; Table 3; Figure 5B), though not significant (P > 0.05), may partially be ascribed to an additional activated region in the contralateral APC.

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Table 3. SI cortical volumes activated by tactile stimulation of left hemibody Body region stimulated

Mean activation volumes (Voxels* ± SD) contralateral SI

ipsilateral SI

P value

Tongue (n=6)

617 ± 253

610 ± 227

0.83

Face (n=4)

633 ± 100

600 ± 292

0.84

Hand (n=5)

959 ± 422

484 ± 110

0.07

Forearm (n=4)

305 ± 178

-

-

Arm (n=4)

399 ± 272

154 ± 137

0.31

Shoulder (n=3)

670 ± 148

293 ± 233

0.08

Trunk (n=4)

529 ± 341

194 ± 178

0.13

Thigh (n=6)

417 ± 265

100 ± 87

0.19

Lower leg (n=4)

208 ± 119

-

-

Foot (n=4)

323 ± 72

-

-

*one voxel corresponds to 1 mm3

Tactile stimulation of skin receptors on the back of the hand, performed in two subjects (C.C. and E.G.), elicited contralateral foci in similar SI regions in both subjects, while ipsilateral activation was observed in a single case (Table 4).

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Table 4. Mean Talairach coordinates (±SD) of activation foci evoked in the first somatic sensory cortex by tactile stimulation of various left hemibody regions Body region stimulated

contralateral SI

ipsilateral SI

x

y

z

x

y

z

Tongue (n=6)

50.4 ± 2.88

-24.8 ± 3.96

25.6 ± 3.51

-49.00 ± 6.03

-24.67 ± 3.93

24.17 ± 3.19

Face (n=4)

53.25 ± 3.2

-17.25 ± 1.26

33.75 ± 4.27

-48.00 ± 2.45

-19.25 ± 5.91

33.75 ± 4.27

Hand (n=5)

32.8 ± 5.76

-35.8 ± 7.66

52.8 ± 3.49

-37.5 ± 6.4

-34.5 ± 8.43

46.75 ± 2.87

Forearm (n=4)

24.50 ± 2.65

-45.0 ± 2.83

47.0 ± 7.79

-

-

-

Arm (n=4)

25.0 ± 4.55

-39.0 ± 5.85

44.50 ± 2.08

-26.0 ± 5.66

-43.0 ± 1.41

46.5 ± 0.71

Shoulder (n=3)

19.33 ± 0.71

-43.50 ± 4.95

51.50 ± 6.36

-26.5 ± 7.78

-45.5 ± 2.12

44.5 ± 2.12

Trunk (n=4)

22.25 ± 2.50

-45.75 ± 5.32

51.25 ± 7.54

-21.50 ± 5.0

-46.25 ± 5.86

50.75 ± 6.80

Thigh (n=6)

17.17 ± 3.71

-45.83 ± 3.06

53.33 ± 4.72

-21.00 ± 4.64

-47.00 ± 4.0

49.4 ± 5.86

Lower leg (n=4)

17.25 ± 1.71

-43.75 ± 3.20

51.75 ± 4.65

-

-

-

Foot (n=3)

8.25 ± 3.20

-40.67 ± 6.38

56.25 ± 2.63

-

-

-

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Proximal Limbs and Trunk

Shoulder, Arm, Thigh Tactile stimulation of these peripheral regions yielded activation patterns characterized by fairly strong activation in the contralateral hemisphere (Table 3; Figures 3A, B, D and 5B), in the posterior part of the PCG (Figure 7A-D; Table 4). Stimulation of the arm elicited activation at lateral and ventral sites, thigh stimulation at more medial and dorsal sites, and shoulder stimulation activated an intermediate zone (Figure 3; Table 4). Ipsilateral foci, though smaller than the corresponding contralateral foci (Table 3; Figure 5B), were consistently detected.

Ventromedial Trunk Surface Unilateral stimulation of the left ventral trunk close to the midline caused an increased blood flow both in the contralateral and in the ipsilateral PCG, as described previously (Figure 3C; see Fabri et al., 2005). In most subjects such foci were in the posterior part of the PCG (Table 4). Sometimes a more anterior focus, again bilateral, was also observed, likely corresponding to the second trunk midline representation zone on the border between cytoarchitectonic areas 3a and 3b (Fabri et al., 2005). Contralateral and ipsilateral signal increases were similar in all subjects, whereas the contralateral foci were larger than the ipsilateral ones (529 vs 194 voxels; Table 3; Figure 5B; Fabri et al., 2005). Distal Limbs

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Forearm, Lower Leg Unilateral tactile stimulation of these regions produced similar activation patterns, with a fairly large focus (Table 3; Figure 5B) in the contralateral hemisphere and lack of ipsilateral activation (Figure 4A, B). In all cases, foci were in the posterior part of the PCG (Figure 4A, B), the one elicited by forearm stimulation occupying a more lateral position and the one evoked by leg stimulation a more medial position (Table 4).

Foot Left foot stimulation involved both plantar and dorsal skin receptors. There were two contralateral foci (Figure 4C), one in the medial part of the APC and the other in the frontal cortex. The former was in a region in the medial aspect of the PCG likely corresponding to the SI foot representation (Table 4). The frontal focus likely corresponded to the foot representation in the motor cortex. The signal change and activated volume of the somatosensory focus are reported in Tables 2 and 3, respectively, and in Figure 5A, B. There was no evidence of ipsilateral activation.

Right Side Stimulation Right side stimulation was applied on tongue (n=5 subjects), face (n=2), hand (n=2), and forearm, shoulder, lower leg and foot (n=1) (Table 1). Given the small sample, statistical analysis could be performed only for tongue representation.

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Figure 3. Cortical activation in PCG, elicited in different subjects and scans by tactile stimulation of left arm, shoulder, trunk, and thigh. Activated regions (visualized as described in Fig. 2) were superimposed on axial (A1, B1, C1, D1), coronal (A2, B2, C2, D2), and sagittal images from the contralateral (A3, B3, C3, D3) and ipsilateral hemisphere (A4, B4, C4, D4) obtained using an SPGR T1-weighted sequence (as described in Fig. 2). Left hemisphere on the right. A: activation evoked by left arm stimulation (subject E.G.). Activation foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral hemisphere (2), as shown in axial (A1), coronal (A2), and sagittal images (A3, contralateral, and A4, ipsilateral). B: activation evoked by left shoulder stimulation (subject E.A.). Activation foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral cortex (2), as shown in axial (B1), coronal (B2), and sagittal images (A3, contralateral, and B4, ipsilateral). C: activation evoked by left medial trunk stimulation (subject I.P.). Activation foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral hemisphere (2), as shown in axial (C1), coronal (C2), and sagittal images (C3, contralateral, and C4, ipsilateral). D: activation elicited by left thigh stimulation (subject A.M.). Foci were seen both in the right, contralateral hemisphere (1) and in the left, ipsilateral cortex (2), as shown in axial (C1), coronal (C2), and sagittal images (C3, contralateral, and C4, ipsilateral). CS, central sulcus.

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Figure 4. Cortical activation in PCG elicited in different subjects and scans by tactile stimulation of left forearm, lower leg, and foot. Activated regions (visualized as described in Fig. 2) were superimposed on axial (A1, B1, C1), coronal (A2, B2, C2), and sagittal images from the contralateral hemisphere (A3, B3, C3), obtained with an SPGR T1-weighted sequence (described in Fig. 2). Left hemisphere on the right. A: activation evoked by left forearm stimulation (subject A.S.). Activation foci were seen only in the right, contralateral hemisphere (black arrow), as shown in axial (A1), coronal (A2), and sagittal images (A3). B: activation evoked by left lower leg stimulation (subject E.G.). Activation foci were only in the right, contralateral hemisphere (black arrow), as shown in axial (B1), coronal (B2), and sagittal images (A3). C: activation evoked by left foot stimulation (subject E.P.). Foci were seen only in the right, contralateral hemisphere (black arrow), as shown in axial (C1), coronal (C2), and sagittal images (C3). CS, central sulcus (white arrows).

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Figure 5. Graphic representation of activated signal increases and volume sizes evoked bilaterally by stimulation of different left (A and B, respectively) and right (C and D) hemibody regions.

The topographic pattern of cortical activation was the mirror image of that elicited by stimulation of the homologous body regions on the left side. Foci activated in different subjects are shown in Figure 6. The mean Talairach coordinates of the regions activated by right hemibody stimulation are reported in Table 5. Signal increases and activated region volume sizes are shown in Figure 5C and D, respectively, and in Table 6. Activated volumes and signal increases in the ipsilateral hemisphere, where detected, were not significantly different from those in the contralateral cortex.

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Figure 6. Cortical activation in PCG elicited in different subjects and scans by tactile stimulation of different right hemibody regions. Activated regions (visualized as described in Fig. 2) were superimposed on axial images obtained with an SPGR T1-weighted sequence, as described in Fig. 2. Left hemisphere on the right. A: activation evoked by right tongue stimulation (subject E.B.). Activation foci were seen both in the left, contralateral hemisphere (1) and in the right, ipsilateral cortex (2). B: activation evoked by right face stimulation (subject G.M.). Activation foci were both in the left, contralateral hemisphere (1) and in the right, ipsilateral cortex (2). C-F (subject A.I.). C: activation evoked by right hand stimulation. Activation foci were found in both hemispheres and occupied the entire contralateral PCG (1), but only the posterior part of the ipsilateral PCG (2). D: activation evoked by right forearm stimulation. An activation focus was seen only in the contralateral hemisphere (1). E: activation evoked by right shoulder stimulation. Foci were seen in the posterior part of the PCG both on the contralateral (1) and the ipsilateral (2) side. F: activation evoked by right foot stimulation. Activation was seen only in the contralateral hemisphere (1). CS, central sulcus.

Summary Maps Stimulation of cutaneous tactile receptors in various regions of the left hemibody produced contralateral activation patterns according to a clear topographic organization. The contralateral activation maps obtained by stimulating different left hemibody regions in four subjects are shown on “inflated” right hemispheres in Figure 7A-D. Stimulation of different right hemibody regions gave rise to contralateral cortical foci that mirrored the topographic pattern evoked by left side stimulation in the right hemisphere. Stimulation of left proximal regions and hand also evoked ipsilateral foci in the left SI, whose topographic organization was similar to that seen in the contralateral cortex. Figure 7E, F shows the activation evoked by stimulation of different ipsilateral body regions in the “inflated” left hemispheres of two subjects. Also in this case, stimulation of different right hemibody regions gave rise to ipsilateral cortical foci that mirrored the topographic pattern evoked in the left hemisphere by left side stimulation.

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Table 5. Mean Talairach coordinates (±SD) of activation foci evoked in SI by tactilestimulation of various right hemibody regions contralateral SI

Body region stimulated

ipsilateral SI

x

y

z

x

y

z

Tongue (n=5)

-49.2 ± 3.7

-23.8 ± 3.35

25.60 ± 3.58

44.4 ± 2.07

-21.0 ± 6.12

25.2 ± 5.4

Face (n=2)

-52.0 ± 5.66

-20.5 ± 3.54

27.0 ± 0.0

52.0 ± 2.83

-17.0 ± 8.49

27.5 ± 0.71

Hand (n=1)

-37.00

-39.00

44.00

40.00

-45.00

44.00

Forearm (n=1)

-25.00

-55.00

40.00

-

-

-

Shoulder (n=1)

-30.00

-53.00

44.00

27.00

-48.00

44.00

Lower leg (n=1)

-17.00

-43.00

53.00

-

-

-

Foot (n=1)

-8.00

-51.00

53.00

-

-

-

Table 6. Percent of signal increase and size of cortical volumes evoked by right hemibody stimulation Body region stimulated

Mean signal increase (%) ± SD

Mean activation volumes (Voxels* ± SD)

contralateral SI

ipsilateral SI

contralateral SI

ipsilateral SI

Tongue (n=5)

1.34 ± 0.5

1.1 ± 0.4

596 ± 359

401 ± 257

Face (n=2)

1.4 ± 0.14

1.2 ± 0.28

611 ± 190

389 ± 289

Hand (n=1)

1.2

0.9

1205

772

Forearm (n=1)

0.7

-

123

-

Shoulder (n=1)

0.7

0.7

446

80

Lower leg (n=1)

1.6

-

132

-

Foot (n=1)

1.4

-

514

-

*one voxel cooresponds to one mm3.

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Figure 7. A-D: right cortical areas activated by stimulation of different contralateral body regions. E, F: left cortical areas activated by stimulation of different ipsilateral body regions. Activation foci were superimposed on inflated, unfolded brains reconstructed by BV processing, which allows to visualize cortical areas hidden in the sulcal depth in normal brain. In each brain, light grey regions represent superficial cortical areas; dark grey zones are cortical zones buried in the sulci. Activation foci are shown in colors matching those of the body regions illustrated in Fig. 1. The Talairach coordinates refer to the point with the highest statistical significance (not indicated) within each activated zone in each subject. A: data from subject C.C. showing activation evoked by stimulation of contralateral proximal body regions. Foci lie in the posterior part of the PCG and in the anterior bank of the PCS (area 1). B: data from subject E.G. C: data from subject E.P. D: data from subject I.P. E: data from subject E.G. showing activation evoked by stimulation of left proximal ipsilateral body regions and hand. Foci lie in the posterior part of the PCG and in the anterior bank of the PCS. F: data from subject I.P. Colors of coordinates match those indicating corresponding activated cortical regions. Arrows indicate the CS, central sulcus; PCS, post-central sulcus.

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Figure 8. Schematic somatosensory maps in the contralateral (right; A) and ipsilateral (left; B) flattened hemisphere after left hemibody stimulation. A: representation of cortical regions activated in the right hemisphere by stimulation of different left hemibody regions. Activation foci were superimposed on the flattened BV-reconstructed brain, where cortical areas hidden in the sulcal depth in the normal brain can be viewed as 2D representations. Light grey regions are superficial cortical areas, dark grey ones are cortical zones buried in the sulci. Activation foci are shown in colors matching those corresponding to different body regions (inset). Foci lie in the posterior part of the PCG and in the anterior bank of the PCS. B: representation of cortical regions activated in the left hemisphere by stimulation of different ipsilateral body regions. CS, central sulcus; PCS, post-central sulcus; SS, Sylvian sulcus.

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Comparison of the signal increases and activation volumes elicited in the contralateral and ipsilateral maps shows very similar signal changes in homologous regions of the two hemispheres (Tabs. II and VI for left and right side stimulation, respectively). Contralateral activated volumes were generally larger, except those recorded in head regions (Tabs. III and VI, for left and right side stimulation, respectively). However, the difference was not significant, probably because of the small sample size and of interindividual variability (Table 3). Schematic summary maps based on the mean Talairach coordinates and activated volumes in the contralateral (A) and ipsilateral (B) flattened cortex are shown in Figure 8.

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Discussion The present fMRI study explored the cortical representation of the body tactile receptor surface and is the most exhaustive mapping study of the human SI cortex performed with a medium-strength magnetic field to date. For technical reasons, only frontal body regions were stimulated. Data obtained from 19 healthy volunteers confirmed the topographic organization of area SI described in electrophysiologic (Nelson et al., 1980; Iwamura et al., 1998; Taoka et al., 1998) and neuroanatomic (Burton and Fabri, 1995; for a review see Kaas et al., 2002) studies of non-human primates and partial data obtained in humans with invasive (Penfield and Boldrey, 1937; Woolsey et al., 1979) and non-invasive methods (Nakamura, 1998; Rothemund et al., 2005; for a review see Burton 2002). Monkey studies have shown that fMRI and microelectrode mapping do not provide perfectly overlapping data (Disbrow et al., 2000); it is therefore important that the discrepancy be taken into account when comparing human fMRI data with microelectrode data from other species. In spite of this limitation, fMRI can nonetheless provide an iportant contribution to the knowledge of human brain organization. Activation was consistently evoked in the contralateral hemisphere. Tactile stimulation of proximal body regions (shoulder, arm, thigh, trunk) and the hand also activated ipsilateral foci. In both hemispheres the upper body was represented in the lateral part of the APC and the lower body in its medial part. These general organization features agree with previous descriptions of the representation of peripheral skin receptors in SI (Nakamura et al., 1998). The head regions stimulated in the study, i.e. tongue and mandibular regions of the face, activated cortical areas in the lateral part of the PCG, in line with previous human studies performed with MEG (Yang et al., 1993; Suzuki et al., 2004; for a review see Kagiki et al., 2000), positron emission tomography (PET; Boling et al., 2002), fMRI (Sakai et al., 1995; Iannetti et al., 2003; Miyamoto et al., 2005), and intrinsic optical imaging (IOI; Sato et al., 2005), and with data from non-human primates (Nelson et al. 1980; Toda and Taoka, 2002, 2004; see also data and literature in Disbrow et al., 2003). In this study, the foci evoked by tongue stimulation were more posterior and medial than those evoked by face stimulation (Figures 7, 8). No other studies have compared directly the tongue and mandibular regions, except the one by Penfield and Rasmussen (1950), where the jaws were represented above the tongue. In every other human study, ours included, the tongue and mandibular representation zones were found in both hemispheres. A non-activated cortical area (gap) was

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detected between the representation of the mandibular region and that of the hand, paralleling a similar arrangement observed in MEG studies of the topography of the face in SI using electrical stimulation (Yang et al., 1993; Suzuki et al., 2004): somatosensory evoked field (SEF) potentials elicited by stimulation of different face regions originated in continuous cortical zones, while SEFs evoked by medial nerve stimulation were not continuous. The gap region probably contains the representation of intraoral structures (i.e., gingival, Murayama et al., 2005; dental pulp, Kubo et al., 2008), orbital skin and/or eye structure (Balslev and Miall, 2008) , and nose (Schwartz et al., 2004). The hand representation is the most extensively studied cortical region. Our data agree with results from previous MEG (Nakamura et al., 1998), PET (Bodegård et al., 2000; Burton et al., 1997), fMRI (Lin et al., 1996; Polonara et al., 1999; Moore et al., 2000) and IOI (Sato et al., 2005) studies showing contralateral activation in the APC, corresponding to cytoarchitectonic area 1, and bilateral foci in the PPC, where area 2 is located (for a review, see Burton, 2002). The hand representation in ipsilateral SI has been described in monkey area 2-5 (Iwamura et al., 1994) and recently also in area 3b (Lipton et al., 2006). In the present study, simultaneous stimulation of palm and fingers prevented identification of the digit representation sequence. The distal limbs, i.e., forearm and lower leg, have seldom been explored in mapping studies. Some MEG investigations have addressed the cortical representation of the lower leg evoked by electrical stimulation of various lower limb nerves (Kagiki et al., 1995; Shimojo et al., 1996) or by tactile stimulation of the leg surface (Nakamura et al., 1998). The results of the former two studies have been defined as “compatible with the homunculus” (see Kagiki et al., 2000, for a review). In the third, a clear origin of the cortical dipole evoked by leg stimulation could not be demonstrated. The representation of forearm tactile receptors, investigated in two MEG studies (Yang et al., 1993; Nakamura et al., 1998), found contralateral locations from inferior to superior and lateral to medial for forearm, elbow and upper arm representations. Our data agree with the topographic organization described in non-human primates: the forearm representation in SI was found in the PCG just medial to the hand and lateral to the arm representation, and that of the lower leg was in the upper (medial) part of the PCG, between areas containing the thigh representation laterally and the foot representation medially (Kaas et al. 1979; Nelson et al., 1980). Mapping data regarding proximal limbs (arm, shoulder, thigh) and trunk are also scarce. Some MEG and fMRI reports describe contralateral activation evoked by nerve electrical or tactile stimulation of upper leg (Nakamura et al., 1998 ), arm (Nakamura et al., 1998; Servos et al., 1998), shoulder (Itomi et al., 2001) and trunk (Nakamura et al., 1998; Itomi et al., 2000). According to these studies, the proximal limb representations are close to that of the trunk. In the present work ipsilateral activation was also evoked, and had a similar topographic organization (see also Fabri et al., 2005). Similar results have been obtained in non-human primates (Conti et al., 1986; Manzoni et al., 1989; Iwamura, 1998; Taoka et al., 1998, 2000). The foot representation was found medially, in the interhemispheric sulcus, in line with previous MEG (Nakamura et al., 1998; Del Gratta et al., 2002), PET (Del Gratta et al., 2002; Hagen and Pardo, 2002) and fMRI (Sakai et al., 1995) reports describing similar coordinates for foci activated by toe tactile stimulation, and with data obtained from electrophysiologic

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recording experiments in non-human primates (Nelson et al., 1980). The ipsilateral representation of the foot has never been described in humans. In monkeys, sparse neurons with bilateral receptive fields on the foot have been found in the medial part of the PCG (Taoka et al., 2000; Iwamura et al., 2002).

Multiple Representations Activation foci were prevalently noted in the posterior part of the APC, in the exposed part of the cortex, in a region likely containing cytoarchitectonic area 1 (Geyer et al., 1997, 1999, 2000); sometimes, activation was observed in the posterior bank of the CS, where area 3b is located. The inconsistent detection of area 3b activation is probably due to the type of stimulus used: moving stimuli, like those employed in this study, have been shown to be more effective in recruiting area 1 compared with 3b neurons (Bodegård et al., 2000); in addition, or alternatively, our data were obtained from awake subjects: similar stimulation conditions evoked greater activation of area 1 compared with area 3b in awake monkeys than in their anaesthetized counterparts (Chen et al., 2005).

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Bilateral Representation Stimulation of head regions, proximal limb and trunk, and hand induced ipsilateral SI activation. A human MEG study of the complete cortical representation of skin receptors (Nakamura et al., 1998) using a natural stimulus, similar to the one employed in our study (light, superficial stimulus applied on skin) produced similar results, but did not investigate ipsilateral representation. Ipsilateral activation has been described for the hand (see data and literature in Polonara et al., 1999, Fabri et al., 1999, 2001), trunk (Fabri et al., 2005) and head regions (Disbrow et al., 2003). Tactile activation of ipsilateral cortical regions occurs via two pathways: from contralateral SI through callosal fibers, and/or through extracallosal, likely thalamo-cortical ipsilateral inputs (Manzoni 1997); whether one or both are involved, and to what extent, remains to be elucidated. In a previous paper we showed that ipsilateral PPC activation after unilateral tactile stimulation of the hand is subserved by the corpus callosum (Fabri et al., 1999, 2001). However, it has recently been shown that the ipsilateral representation of ventromedial trunk regions and oral structures is at least partially independent of the commissure. In fact, in patients with complete callosal resection SI is still bilaterally activated by ventral trunk stimulation (Fabri et al., 2006). The bilateral foci, signal increase and activated volumes evoked by tactile stimulation of head structures in our healthy volunteers were quite similar in the contralateral and ipsilateral hemispheres. In addition, activation in cortical head representations has been described without significant differences in latency between the hemispheres (Disbrow et al., 2003). The data collected to date suggest that anatomically adjacent cutaneous territories, e.g. regions lying close to the body midline, may be represented in both hemispheres in a manner that is largely independent of the corpus callosum and joins the two side of the body,

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ensuring anatomic continuity (anatomic midline; see Fabri et al., 2006); in contrast, functional continuity (functional midline; see Fabri et al., 2006) in anatomically non-adjacent cutaneous territories often working together, like the hands, would be ensured by bilateral representation via a mechanism that is largely dependent on the commissure, which would thus be responsible for the integrated and coordinated behavior of distant structures.

Conclusion In conclusion, the data presented in this study demonstrate that 1.5 T fMRI is a valuable and reliable tool to map the somatosensory cortex. Exploring the cortical maps with a machine normally used for diagnostic purposes can help assess the functional importance of cortical areas adjacent to focal brain lesions in preoperative functional studies, so as to prevent or circumscribe damage by neurosurgical procedures. The high individual variation found in the human motor-sensory cortex reinforces the need for continuing brain mapping studies (Farrell et al., 2007). The degree of correspondence between an fMRI-defined region and the “true” area could be investigated in future studies of neurosurgical patients. This paper presents preliminary evidence of the feasibility of this approach.

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Acknowledgments The research has been supported by grants from MIUR (Ministero Istruzione, Università e Ricerca, 2005). The authors are grateful to the volunteers, to the technical staff of Radiology Institute, particularly to Mr Gianrico Conti and Mr Luigi Imperiale for assistance during scan sessions and data transfer. We also thank Ms Silvia Modena for editing the English.

References Balslev D, Miall RC (2008): Eye position representation in human anterior parietal cortex. J Neurosci. 28: 8968-8972. Bodegård A, Geyer S, Naito E, Zilles K, Roland PE (2000): Somatosensory area in man activated by moving stimuli: cytoarchitectonic mapping and PET. Neuroreport, 11: 187190. Boling W, Reutens DC, Olivier A (2002): Functional topography of the low postcentral area. J Neurosurg. 97: 388-395. Burton H (2002): Cerebral cortex regions devoted to somatosensory system: results from brain imaging studies in humans. In: Nelson R editor. The Somatosensory System: Deciphering the Brain’s Own Body Image. Boca Raton: CRC p 27-72.

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74

Polonara Gabriele, Mascioli Giulia, Salvolini Ugo, et al.

Burton H, Fabri M (1995): Ipsilateral intracortical connections of physiologically defined cutaneous representations in areas 3b and 1 of macaque monkeys: projections in the vicinity of the central sulcus. J Comp Neurol. 355: 508-538. Burton H, Mac Leod AMK, Videen TO, Raichle ME (1997): Multiple foci in parietal and frontal cortex by rubbing embossed grating pattern across fingerpads: a positron emission tomography study in humans. Cereb Cortex, 7: 3-17. Chen LM, Friedman RM, Roe AW (2005): Optical imaging of SI topography in anesthetized awake squirrel monkey. J Neurosci. 25: 7648-7659. Conti F, Fabri M, Manzoni T (1986): Bilateral receptive fields and callosal connectivity of the body midline representation in the first somatosensory area of Primates. Somatosensory Res. 3: 273-289. Del Gratta C, Della Penna S, Ferretti A, Franciotti R, Pizzella V, Tartaro A, Torquati K, Bonomo L, Romani GL, Rossini PM (2002): Topographic organization of the human primary and secondary somatosensory cortices: comparison of fMRI and MEG findings. Neuroimage, 17: 1373-1383. Disbrow EA, Hinkley LBN, Roberts TPL (2003): Ipsilateral representation of oral structures in human anterior parietal somatosensory cortex and integration of inputs across the midline. J Comp Neurol. 467: 487-497. Disbrow EA, Slutsky DA, Roberts TPL, Krubitzer LA (2000): Functional MRI at 1.5 tesla: a comparison of the blood oxygenation level-dependent signal and electrophysiology. Proc Natl Acad Sci USA, 97: 9718-9723. Fabri M, Polonara G, Quattrini A, Salvolini U, Del Pesce M, Manzoni T (1999): Role of the corpus callosum in the somatosensory activation of the ipsilateral cerebral cortex: an fMRI study of callosotomized patients. Eur J Neurosci. 11: 3983-3994. Fabri M, Polonara G, Del Pesce M, Quattrini A, Salvolini U, Manzoni T (2001): Posterior corpus callosum and interhemispheric transfer of somatosensory information: an fMRI study of a partially callosotomized patient. J Cogn Neurosci. 13: 1071-1079. Fabri M, Polonara G, Quattrini A, Salvolini U (2002): Mechanical noxious stimuli cause bilateral activation of parietal operculum in callosotomized subjects. Cereb Cortex, 12: 446-451. Fabri M, Polonara G, Mabiglia C, Salvolini U, Manzoni T (2004): Cortical representation of body cutaneous receptors in the first somatic sensory area of human brain studied with functional magnetic resonance imaging. 4th Forum of the Federation of European Neuroscience Societies, Lisbon 10-14-July. Fabri M, Polonara G, Salvolini U, Manzoni T (2005): Bilateral cortical representation of the trunk midline in the human first somatic sensory area. Hum Brain Mapp. 25: 287-296. Fabri M, Polonara G, Mascioli G, Paggi A, Salvolini U, Manzoni T (2006): Contribution f the corpus callosum to bilateral representation of the trunk midline in the human brain: an fMRI study of callosotomized patients. Eur J Neurosci. 23: 3139-3148.

Farrell DF, Burbank N, Lettich E, Ojemann GA (2007): Individual variation in motor-sensory (rolandic) cortex. J Clin Neurophysiol. 24: 286-293. Geyer S, Schleicher A, Zilles K (1997): The somatosensory cortex of humans: cytoarchitecture and regional distributions of receptor-binding sites. Neuroimage, 6: 2745.

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

Cortical Representation of Cutaneous Receptors…

75

Geyer S, Schleicher A, Zilles K (1999): Areas 3a, 3b and 1 of human primary somatosensory cortex 1. Microstructural organization and interindividual variability. Neuroimage, 10: 63-83. Geyer S, Schormann T, Mohlberg H, Zilles K (2000): Areas 3a, 3b and 1 of human primary somatosensory cortex 2. Spatial normalization to standard anatomical space. Neuroimage, 11: 684-696. Hagen MC, Pardo JV (2002): PET studies of somatosensory processing of light touch. Behav Brain Res. 135: 133-140. Iannetti GD, Porro CA, Pantano P, Romanelli PL, Galeotti F, Cruccu G (2003): Representation of different trigeminal divisions within the primary and secondary human somatosensory cortex. Neuroimage, 19: 906-912. Itomi K, Kagiki R, Hoshiyama M, Watanabe K (2001): A unique area of the homunculus: the topography of the primary somatosensory cortex in human following posterior scalp and shoulder stimulation. Brain Topogr. 14: 15-23. Itomi K, Kagiki R, Maeda K, Hoshiyama M (2000): Dermatome versus homunculus; detailed topography of the primary somatosensory cortex following trunk stimulation. Clin Neurophysiol. 111: 405-412. Iwamura Y (1998): Hierarchical somatosensory processing. Curr Opin Neurobiol. 8: 522528. Iwamura Y, Iriki A, Tanaka M (1994): Bilateral hand representation in the postcentral somatosensory cortex. Nature, 369: 554-556. Iwamura Y, Tanaka M, Iriki A, Taoka M, Toda T (2002): processing of tactile and kinaesthetic signals from bilateral sides of the body in the postcentral gyrus of the awake monkeys. Behav Brain Res. 135: 185-190. Kaas JH (1983): What, if anything, is SI? Organization of first somatosensory area of cortex. Physiol Rev. 63: 206-230. Kaas JH, Jain N, Qi H-X (2002): The organization of somatosensory system in Primates. In: Nelson R editor. The Somatosensory System: Deciphering the Brain’s Own Body Image. Boca Raton: CRC. p 1-25. Kaas, JH, Nelson RJ, Sur M, Lin CS, Merzenich MM (1979): Multiple representations of the body within the primary somatosensory cortex of primates. Science, 204: 521-523. Kagiki R, Koyama S, Hoshiyama M, Shimojo M, Kitamura Y, Watanabe S (1995): Topography of somatosensory evoked magnetic fields following posterior tibial nerve stimulation. Electroencephalogr Clin Neurophysiol. 95: 127-134. Kagiki R, Hoshiyama M, Shimojo M, Naka D, Yamasaki H, Watanabe S, Xiang J, Maeda K, Lam K, Itomi K, Nakamura A (2000): The somatosensory evoked magnetic fields. Progr Neurobiol. 61: 495-523. Kim S-G, Urgubil K (1997): Functional magnetic resonance imaging of the human brain. J Neurosci Methods, 15: 3821-3839. Kubo K, Shibukawa Y, Shintani M, Suzuki T, Ichinohe T, Kaneko Y (2008): Cortical representation area of human dental pulp. J Dent Res. 87: 358-362. Lin W, Kuppusamy K, Haacke EM, Burton H (1996): Functional MRI in human somatosensory cortex activated by touching textured surfaces. J Magn Res Imag. 6: 565572.

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

76

Polonara Gabriele, Mascioli Giulia, Salvolini Ugo, et al.

Lipton ML, Fu K-MG, Branch CA, Schroeder CE (2006): Ipsilateral hand input to area 3b revealed by converging hemodynamic and electrophysiological analysis in macaque monkeys. J Neurosci. 26: 180-165. Mai JK, Assheuer J, Paxinos G (1997): Atlas of the Human Brain. San Diego: Academic Press. 328 p. Manzoni T (1997): The callosal connections of the hierarchically organized somatosensory areas of primates. J Neurosurg Sci. 41: 1-22. Manzoni T, Barbaresi P, Conti F, Fabri M (1989): The callosal connections of the primary somatosensory cortex and the neural bases of midline fusion. Exp Brain Res. 76: 251266. Miyamoto JJ, Honda M, Saito DN, Okada T, Ono T, Ohyama K, Sadato N (2005): The representation of the human oral area in the somatosensory cortex: a functional MRI study. Cereb Cortex, 16: 669-675. Moore CI, Stern CE, Corkin S, Fischl B, Gray AC, Rosen BR, Dale AM (2000): Segregation of somatosensory activation in the human rolandic cortex using fMRI. J Neurophysiol. 84: 558-569. Murayama S, Nakasato N, Nakahara H, Kanno A (2005): Neuromagnetic evidence that gingival area is adjacent to tongue area in human primary somatosensory cortex. Tohoku J Exp Med. 207: 191-196. Nakamura A, Yamada T, Goto A, Kato T, Ito K, Abe Y, Kachi T, Kakigi R (1998): Somatosensory homunculus drawn by MEG. Neuroimage, 7: 377-386. Nelson RJ, Sur M, Felleman DJ, Kaas JH (1980): Representations of the body surface in postcentral parietal cortex of Macaca fascicularis. J Comp Neurol. 192: 611-643. Oldfield RC (1971): The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 9: 97-113. Penfield W, Boldrey E (1937): Somatic motor and sensory representation in the cerebral cortex of man studied by electrical stimulation. Brain, 60: 389. Penfield W, Rasmussen T (1950): The Cerebral Cortex of Man. New York: Macmillan. 248 p. Polonara G, Fabri M, Manzoni T, Salvolini U (1999): Localization of the first and second somatosensory areas in the human cerebral cortex with functional MR imaging. Am J Neuroradiol. 20: 199-205. Polonara G, Fabri M, Mabiglia C., Manzoni T, Salvolini U (2005a): Body representation in the first somatic sensory area of human brain: an fMRI study. European Congress of Radiology, Wien, 4-8 March. Polonara G, Fabri M, Mascioli G, Mabiglia C., Manzoni T, Salvolini U (2005b): Cortical activation map evoked in the first somatic sensory area of the human brain by tactile stimulation of different body regions: an fMRI study. XXX Annual Meeting of the European Society of Neuroradiology (ESNR), Barcelona 15-18 September. Rothemund Y, Schaefer M, Grüsser SM, Flor H (2005): Localization of the human female breast in primary somatosensory cortex. Exp Brain Res. 164: 357–364. Sakay K, Watanabe E, Onodera Y, Itagaki H, Yamamoto E, Koizumi H, Miyashita Y (1995): Functional mapping of the human somatosensory cortex with echo-planar MRI. Magn Res Med. 33: 736-743.

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77

Sato K, Nariai T, Tanaka Y, Maehara T, Miyakawa N, Sasaki S, Momose-Sato Y, Ohno K (2005): Functional representation of the finger and face in the human somatosensory cortex: intraoperative intrinsic optical imaging. Neuroimage, 25: 1292-1301. Schwartz TH, Chen LM, Friedman RM, Spencer DD, Roe AW (2004): Intraoperative optical imaging of human face cortical topography: a case study. NeuroReport, 15: 1527-1531. Servos P, Zacks J, Rumelhart DE, Glover GH (1998): Somatotopy of human arm using fMRI. Neuroreport, 9: 605-609. Shimojo M, Kagiki R, Hoshiyama M, Koyama S, Kitamura Y, Watanabe S (1996): Differentiation of receptive fields in the sensory cortex following stimulation of various nerves of the lower limb I man. Magnetoencephalography study. J Neurosurg. 85: 255262. Suzuki T, Shibukawa Y, Kumai T, Shintani M (2004): Face area representation of primary somatosensory cortex in humans identified by whole-head magnetoencephalography. Jap J Physiol. 54: 161-169. Talairach J, Tournoux P. (1988): Co-Planar Stereotaxic Atlas of the Human Brain. Stuttgart: Thieme, 122 p. Taoka M, Toda T, Iriki A, Tanaka M, Iwamura I (2000): Bilateral receptive field in the hindlimb region of the postcentral somatosensory cortex in awake macaque monkey. Exp Brain Res. 134: 139-146. Taoka M, Toda T, Iwamura I (1998): Representation of the midline trunk, bilateral arms, and shoulders in the monkey postcentral somatosensory cortex. Exp Brain Res. 123: 315-322. Toda T, Taoka M (2002): Hierarchical somesthetic processing of tongue inputs in the postcentral somatosensory cortex of conscious macaque monkeys. Exp Brain Res. 147: 243-251. Toda T, Taoka M (2004): Converging patterns of inputs from oral structures in the postcentral somatosensory cortex of conscious macaque monkeys. Exp Brain Res. 158: 43-49. Woolsey CN, Erickson TC, Gilson WE (1979): Localization in somatic sensory and motor areas of human cerebral cortex as determined by direct recording of evoked potentials and electrical stimulation. J Neurosurg. 51: 476. Yang TT, Gallen CC, Schwartz BJ, Bloom FE (1993): Noninvasive somatosensory homunculus mappings in humans by using a large-array biomagnetometer. Proc. Natl. Acad Sci USA, 90: 3098-3102. Yetkin FZ, Haughton V, Cox RW, Hyde J, Birn RM, Wong EC, Prost R (1996): Effect of motion outside the field of view on functional MR. Am J Neuroradiol. 17: 1005-1009. Young JP, Herath P, Eickhoff S, Choi J, Grefkes C. Zilles K, Roland PE (2004): Somatotpy and attentional modulation of the human parietal and opercular regions. J Neurosci. 24: 5391-5399.

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In: Somatosensory Cortex: Roles, Interventions and Traumas ISBN 978-1-60741-876-4 Editor: Niels Johnsen and Rolf Agerskov © 2008 Nova Science Publishers, Inc.

Chapter 4

From Physical Representation to Social Perception: A New Role for the Primary Somatosensory Cortex (Review Article) Michael Schaefer* Department of Neurology, Otto-von-Guericke Universität Magdeburg, 39120 Magdeburg, Germany

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Abstract Classic studies understand the body map representation in primary somatosensory cortex (SI) as fix and reflecting the physical location of peripheral stimulation in the form of the famous somatosensory homunculus. This review reports results of recent studies that challenge this view and suggest a more complex role of SI. For example, animal studies used simple tactile illusions to demonstrate that the topographic representation in SI adapts dynamically to different situational requirements. Moreover, they showed that SI reflects the perceived rather than the physical location of peripheral stimulation. Using similar illusions, in particular by manipulating visuo-tactile integration processes, human studies confirmed those findings. Furthermore, even simple ‘disguising’ of the body seems to be sufficient to affect the perception of the body, along with corresponding changes in the topography of SI. Recent research has also demonstrated that SI responds differentially when observed touch is attributed to the own body compared to another body (in both cases in absence of any real touch). Thus, it was proposed that the somatosensory cortices may be involved in social perception processes. These new insights about the functions of SI may contribute to our understanding of body perception and encourage approaches focusing on dynamic aspects of the body image for future therapeutic interventions. *

*Correspondence to: Michael Schaefer, PhD Department of Neurology Otto-von-Guericke Universität Magdeburg 39120 Magdeburg, Germany Tel.: +49(0) 391-6717542 Fax: +49(0) 391-6715233 Email: [email protected]

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1. Introduction: The New Hands of a Pianist In the German expressionistic movie “The hands of Orlac” by Robert Wiene, a pianist has a transplant operation that gives him new hands. Unfortunately, the hands belonged to a murderer, and Orlac suddenly finds himself in a situation in which his new hands commit crimes and start to take over his life. Although today this idea sounds bizarre, we are still fascinated when we hear that not only hands but also even parts of faces have been transplanted. Thus, in contrast to contemporary views, which describe the location of the sense of self somewhere in the brain, we often still seem to think that also body parts somehow represent parts of our self. This review reports recent results referring to a new and a more complex role for the primary somatosensory cortex (SI), the first cortical site contributing to the processing of tactile information. Previously, it has been demonstrated that SI seems to code the perceived image of the body rather than solely representing physical information on the body surface. Hence, this research points to a new role for SI in forming an early image of the body. Furthermore, recent studies suggest that this early concept of our own body may also include important dimensions of our self. Thus, the tactile sense and its first major processing area in SI seem to be essential for building a representation of our body and self. This is also supported by expressions like “let’s keep in touch” or movies like “The hands of Orlac”. Below we will trace how studies based on neuroimaging data have contributed to this new view about SI.

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2. Long-Term Plasticity in SI 1937 Penfield and Boldrey were the first ones who discovered that a region on the human postcentral gyrus represents the surface of our body in a topographic map. Any physical stimulation of the body surface is represented in SI. Moreover, this map shows systematically the tactile sensitivity of each body area. Body parts with low receptor densities (e.g., the back) are represented by small areas in SI and body parts with a high sensitivity to tactile stimulation (e.g., the tongue) are represented by relatively big areas. Thus, the resulting body image in SI is distorted in the form of the famous somatosensory homunculus. For decades researchers believed that the topography in SI is fixed already in early childhood. The traditional view of an unchangeable body map representation in SI was questioned by studies with upper limb amputees. Amputees who have lost an extremity often vividly feel their phantom limb. For example, a British study with war veterans who have lost a limb reported that 55% of them felt phantom limb pain (Wartan et al., 1997). Some upper limb amputees also report referred sensations (Ramachandran, 1998; Ramachandran and Hirstein, 1998), meaning that they experience their phantom limb when stimulating specific intact parts of the body, which is then referred to the phantom limb. It has been discussed that these phantom limb phenomena might result from distortions in the body map topography in SI (Ramachandran, 1998; Ramachandran and Hirstein, 1998). Since upper limb amputees have lost an arm and a hand, there is ‘empty space’ in the functional topography in SI. No sensory information is coming to the region that has been formerly innervated by the hand

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and arm. Thus, many researchers speculated that the distorted body image might be responsible for phantom limb phenomena. In 1994 Yang et al. used neuromagnetic source imaging to map the topography in SI in upper limb amputees. They found that the cortical representation of the mouth region invaded the region that formerly represented the amputated limb. This cortical reorganization was a prominent example of plastic changes in the brain. Thus, even the adult brain seems to be able to change after injuries. Subsequent research extended these reports by showing that these plastic changes are not related to all phantom limb phenomena, but are strongly correlated with the degree of phantom limb pain (Flor et al., 1995). While these results point to a maladaptive plasticity in SI, there are also examples for beneficial plasticity. By using neuromagnetic source imaging, Elbert et al. (1995) demonstrated that the cortical representation of the digits of the left hand of string players was larger than that of a control group. Moreover, the amount of cortical reorganization in the representation of the finger digits was correlated with the age at which the person started to play strings. The authors concluded that the topographic organization in SI depends on use and it adapts to current needs and experiences of the individual.

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3. Short-Term Modulations: Influences of Motor and Prefrontal Areas on the Topography in Somatosensory Cortex In contrast to those long-term changes, recent studies also report that the topography in SI can be altered in a very fast way. Whereas plastic long-term changes (e.g., in musicians) need years to establish, short-term changes of SI, in dependency of the task (Braun et al., 2001; Schaefer et al., 2005a) or as an effect of attention (Noppeney et al., 1999), evolve in a very fast way. For example, short-term modulations within SI can be generated by tool-use as we demonstrated earlier (Schaefer et al., 2004b). In this study subjects had the task to manipulate a small object with a pair of tongs (as a tool) or with their hand (control condition). Neuromagnetic source imaging revealed that cortical representations of the first digit (D1) and the fifth digit (D5) were further apart during tool use compared with non-tool use and baseline (Figure 1). These results suggest that maps in SI are parts of the neural network representing the modified schema of the hand during tool use. Moreover, the results demonstrate that the functional topography of SI can be modulated without preceding longlasting sensory training or deafferentation. Other studies demonstrated rapid task-specific changes of the organization of SI as a result of motor activity. Braun et al. (2001) reported that the cortical representations of D1 and D5 were more distant during handwriting compared with rest in healthy humans. However, the results of the study were unable to distinguish whether these changes represented the consequence of altered reafferent input from joints, muscles and skin during the execution of the motor task or of a task-related influence of motor and premotor areas upon the organization of the somatosensory cortex.

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Figure 1. A: Dipole localizations of the somatosensory evoked fields (SEFs) of D1 and D5. Displayed are the results of one representative subject overlaid onto a coronal MRI slice through the somatosensory cortex. The positions of the cortical representations of D5 and D1 are specified in polar coordinates. Note the differences between rest or hand condition and tool use condition. B: Mean differences of the cortical distance between the cortical representations of D1 and D5 during rest, hand and tool condition. Asterisks indicate the significance differences between tool condition and rest (p < .001), and tool condition and hand condition (p < .01), respectively.

To test this hypothesis of a task-related influence of motor and premotor areas, we studied the functional topography of SI by examining coupling effects in a bimanual movement task (Schaefer et al., 2005a). Bimanual coupling is known to be related to an activation of the premotor cortex and the supplementary motor area (Sadato et al., 1997; Steyvers et al., 2003). The functional organization of the somatosensory cortex for known bimanual coupling effects was compared to the organization of the somatosensory cortex during the same movements but only with a small effort in coupling. More in detail, subjects were required to produce cyclically trajectories with both hands. The direction of these trajectories was varied to be either the same (parallel) or the different (orthogonal). In the parallel condition, the trajectories drawn by each hand were minimally affected in comparison to the performance of the hand alone. When they performed the movements in

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orthogonal direction (bimanual coupling task), trajectories deviated from their target paths (Franz et al., 1991; Franz, 1997, see also Figure 2). Results of neuromagnetic source imaging revealed that the neural sources of D1 and D5 moved further apart during the bimanual coupling task in comparison to the same task without coupling, suggesting dynamic modulations of SI as a result of a task-related influence of motor or premotor areas (see Figure 3.)

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Figure 2. Typical displacement during the line task of the dominant hand when the other hand also produced lines (parallel condition, left side), and when the other hand produced circles (orthogonal condition, right side).

Figure 3. Dipole localizations of the SEFs of D1 and D5. Displayed are the results of one representative subject overlaid onto an axial MRI slice. Note the differences between rest or parallel condition (PARA) and orthogonal (ORTHO) condition.

How could neurons in the somatosensory cortex be affected by motor actions? Since SI has dense reciprocal connections with the motor cortex, Braun et al. (2001) as well as Schaefer et al. (2004b, 2005a) suggested that feedback loops from these areas may explain this short-term plastic changes in SI. Moreover, it has been proposed that a prefrontal-cortical sensory gating system may alter SI depending on the requirements of different tasks (Staines

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et al., 2002). Staines et al. (2002) demonstrated that task-relevant somatosensory information leads to facilitation within the contralateral SI and to suppression of the ipsilateral SI. The authors showed that this modulation was associated with activation of the right prefrontal cortex, thereby demonstrating top-down influences of frontal areas on SI. Similar results have been reported by Chapman et al. (1988). Staines et al. (2002) concluded that there may be a prefrontal-cortical sensory gating system altering sensory information at the cortical level of SI to suit task-dependent needs for sensory inflow. In a neuromagnetic study we aimed to test this theory (Schaefer et al., 2005b). Ten subjects participated in a task, which is known to rely on activation of frontal or prefrontal areas, and compared it with a task involving the same movements but with no or only small contributions of frontal or prefrontal areas. The Tower of Hanoi task is a prototype task to study high-level cognition such as planning and problem-solving behavior (Simon, 1975). Studies with patients as well as imaging studies with healthy participants have shown that the neural mechanisms of the Tower of Hanoi task can be related to activation of frontal or prefrontal areas (Shallice, 1982; Anderson and Douglas, 2002). For the control task subjects were asked to perform the same movements but with no specific task. Thus, subjects had to stockpile the rings in any type of order and to any cylinder, but with the same frequency of hand movements as in the Tower of Hanoi task. During these tasks we examined the functional topography of SI with a pneumatical tactile stimulation device. The stimulation device consisted of a diaphragm with a 10 mm diameter causing a distinct tactile sensation when inflated toward the skin by a pulse of pressed air of 2.5 atm for 20 ms (Figure 4).

Figure 4. Picture of the pneumatically driven stimulation device. The device consisted of a diaphragm with a 10 mm diameter causing a distinct tactile sensation when inflated toward the skin by a pulse of pressed air.

The stimulation devices were taped on D1 and D5 allowing the participants to perform the task with almost no restrictions. Methodological studies have revealed that this approach allows valid and reliable mapping of SI (e.g., Schaefer et al., 2004a). Participants were instructed to ignore all tactile stimuli and not to move their head. Based on the theory of a prefrontal-cortical sensory gating system (Staines et al., 2002), we hypothesized that the

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pattern of activation of SI changes during the Tower of Hanoi task compared to the simple manual motor task, suggesting rapid modulation of cortical maps in SI.

Figure 5. A: Topographic map and waveform of magnetic activity evoked by stimulation of the right D1 (rest condition, single subject). Time courses of magnetic activity from 148 sensors are superimposed. Isocontour maps show the magnetic potential pattern elicited by stimulation of the right D1 at the first prominent peak after stimulus onset (nasion up, right side displays the right hemisphere, left side the left hemisphere). B: Source localization results of the somatosensory evoked fields of D1 (squares) and D5 (circles). Displayed are the results of one single representative subject overlaid onto a coronal MRI slice. Note the differences between rest, control task and Tower of Hanoi task.

The resulting somatosensory magnetic fields revealed a clear dipolar topographic field pattern in the region over the central sulcus contralateral to the stimulated side (Figure 5). Neuromagnetic source imaging of these dipolar fields showed dipoles for the stimulated digits on the postcentral gyrus (SI). Further analysis revealed effects of the task on the functional topography in SI. When subjects performed the Tower of Hanoi task, the cortical representations of D1 and D5 moved further apart compared to the control task containing the same movements but without the cognitive characteristic (see Figure 5).Thus, performing motor tasks with different cognitive demands results in a dynamic modulation of SI. The results provide support for the theory that the functional topography in SI may be modulated by a prefrontal-cortical sensory gating system.

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What is the implication of these shifts in SI? It seems to be unlikely that a new sensory map is always acquired whenever this motor task is performed. Braun et al. (2001) suggested that specific representational maps may be activated by dynamically switching between stable maps established earlier, depending on actual task requirements. This dynamic switching of somatosensory maps might be related to sub-threshold synaptic activities (Moore and Nelson, 1998). The task-specific activations of concurrently preexisting maps within a certain representational zone may represent a general principle to optimize stimulus processing (Braun et al., 2001; Nicolelis and Fanselow, 2002).

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4. SI Represents the Perceived Rather than the Physical Image of the Body When Penfield and Boldrey (1937) described the somatosensory homunculus, they proposed a body map that was not only supposed to be fixed, but also was considered as representing the physical image of the body in a relatively mechanical way. Recent research has questioned this view and suggests a much more complex role for SI in establishing and maintaining a first image of the body. In an intriguing animal study Chen et al. (2003) investigated the role of the somatosensory cortex during the tactile funneling illusion. The funneling illusion consists of a simultaneous stimulation of two points on the skin, which produces a single focal sensation at the center of the stimulus pattern, even when no physical stimulus occurs at that site. Chen et al. (2003) used the technique of optical imaging to examine the role of SI (Area 3b) during this illusion. They reported that simultaneous stimulation of two fingertips produced a single focal cortical activation located between the expected regions for each single fingertip activation. Thus, the authors concluded that the topographic organization in SI reflects the perceived rather than the physical location of peripheral stimulation. Further evidence came from human studies. Using fMRI, Blankenburg et al. (2006) similarly examined a somatosensory illusion that can dissociate tactile perception from physical stimulation. The so-called cutaneous rabbit illusion consists of repeated rapid stimulation at the wrist followed by the skin near the elbow. This procedure evokes the illusion of touches at intervening locations along the arm, as if a rabbit hopped along it. FMRI results revealed that illusory sequences activated contralateral SI at a somatotopic location corresponding to the filled-in illusory perception on the forearm (compared with a control condition). The authors concluded that illusory somatosensory perception affected SI and that this activation was somatotopically organized. The understanding that the functional topography in SI may reflect the perceived shape of the body rather than physical aspects of peripheral stimulation was further supported by neuromagnetic studies on multisensory integration. It has been long established that vision often dominates the tactile modality (Rock and Victor, 1964). Thus, simple manipulations of multisensory integration may result in tactile illusions (e.g., Ramachandran and RogersRamachandran, 1996; Ramachandran, 1998). In order to test the hypothesis that brain activity at early stages of sensory processing is susceptible for tactile illusions, we created a simple illusion of a referred sensation while examining neuromagnetic activity in SI (Schaefer et al.,

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2006a). Subjects watched a video that showed a hand that was stroked by a stick on D1 while actually receiving real tactile stimuli on D5. The video was presented in the peripersonal space of the subject at a distance where the real hand would be expected. Thus, we created an experimental conflict between tactile and visual senses. Due to the known dominance of the visual modality over somatosensation (Rock and Victor, 1964) we hypothesized that the participants would feel the stroking on D1 instead of D5. We described this tactile illusion as an artificially induced referred sensation. Moreover, we hypothesized that SI is prone to this kind of tactile illusions.

Figure 6. Dipole sources of the SEFs of D1 (squares) and D5 (circles). Differences between D1 and D5 in the in-phase condition and the out-of-phase condition and rest, demonstrating an increase of source extent of the dipole source of D5, are clearly visible.

Results revealed that subjects felt the illusion of being touched on D1 instead of D5. This tactile illusion was accompanied by changes in the topography of the functional organization of SI (Figure 6). Moreover, the amount of the referred sensation was significantly correlated with the modulations in SI. Thus, the results confirmed that in contrast to traditional views of the body map, topographic representation in SI reflects the perceived rather than the physical location of peripheral stimulation. These findings further demonstrate that not only tactile illusions based on modulations in the tactile modality may alter the somatosensory topography, but also tactile illusions based on manipulations of multisensory integration. Hence, the results point to multisensory processing in SI; an area of the brain that long has been regarded as being strictly unimodal.

5. Morphing the Body When watching an exhibition by the American artist Cindy Sherman the visitor often is warned that the presented pictures might be offending for some people. Considering that those potentially offending pictures only display puppets, the warning seems to be almost ridiculous. However, when we actually see those pictures of puppets in different situations,

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we really feel touched by them, although we know and easily can see that these images depict puppets and not humans. So why are we affected so easily even by anthropomorphic depictions? The above-mentioned studies have shown that the body map in SI seems to adapt dynamically to different situational requirements. In particular, they have shown that the functional topography in SI reflects the perceived rather than the physical location of peripheral stimulation. The experiments that led to this conclusion were based on tactile illusions, for example on manipulations of multisensory integration (Schaefer et al., 2006a). However, recent studies also suggest that we do not necessarily need to create an illusion to affect the functional organization in SI. It seems sufficient to change the visual appearance or shape of our body to modestly distort our feeling of our own body, accompanied with corresponding modulations in the topography of SI. Thus, simply viewing the own body “disguised” may elicit feelings of a morphed body, associated with modulations in SI topography. Two studies provided evidence for this view.

Figure 7. Experimental condition of elongated arm. The artificial hand and arm in front is attached to the subject’s body by the use of a special shirt. The subject is seeing his arm elongated about a length of 20 cm.

In a first study we manipulated the visual information about the subject’s body to elicit the appearance of an elongated arm (Schaefer et al., 2007). For this purpose we used an artificial hand and arm, which were attached in an anatomically correct way over the subject’s real hand and arm and connected to the body of the participant. Thus, subjects viewed their arm as extended by about 20 cm (Figure 7). Since it is known that the visual sense often dominates the tactile modality (Rock and Victor, 1964), we hypothesized that subjects would modestly feel the elongated arm when the artificial arm was connected to their body compared with control conditions. The results showed that during the illusion condition the participants felt that their arm was elongated. Neuromagnetic source imaging of the functional organization in SI revealed that the illusion was accompanied by shifts in the cortical distance between D1 and D5 (see Figure 8). These modulations were significantly correlated with the feeling of an extended arm, thus suggesting an involvement of SI in perceived changes in the size of body parts.

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Figure 8. Dipole solutions of the SEFs of D5 (circles) and D1 (squares) overlaid onto a coronal MRI slice. Note the differences for the cortical representations between rest or control condition and elongated arm condition.

Figure 9. Attachment of the artificial third hand and arm to the body of the subject in the illusion condition. The “third” arm was attached between the middle of the body and the left arm.

A second study used even more dramatic manipulations of the visual appearance of the participants. The experiment aimed to extend the hypothesis that the somatosensory homunculus mirrors the phenomenally perceived shape of the body by investigating if even artificial supernumerary body parts may be represented in the somatosensory homunculus when the illusion is adopted. In order to test this, subjects were given the visual impression that they had a supernumerary third arm and hand (Schaefer et al., 2008b). Participants were asked to wear a special shirt with an artificial third arm between both own arms. This third artificial rubbery arm was ending in front of the subjects. Hence, the participants viewed this artificial hand and arm connected to their body between the left arm and the middle of their body (see Figure 9).

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Figure 10. Dipole sources of the SEFs of D1 (squares) and D5 (circles, here always rest state for picture purposes) for one representative subject. Differences of the distances for the cortical representations between rest or control condition and illusion condition (three arms) are visible.

Due to the known dominance of the visual modality (Rock and Victor, 1964; Schaefer et al., 2007), we hypothesized that the subjects would not only view the third arm but more or less would feel this third arm and transiently believe that this hand and arm belong to their own body. Furthermore, since we assumed that even artificial body parts that were illusory felt might be represented in the somatosensory homunculus, we expected alterations in SI related to this illusory feeling. Results revealed that most of the participants reported the sensation of feeling the third arm. This feeling was associated with modulations in SI (Figure 10). The cortical representation of D1 was shifting to a more medial and superior position on the somatosensory cortex when subjects felt the illusion. Moreover, the amount of this shift predicted the strength of the illusion. Thus, the somatosensory homunculus seems to mirror the perceived shape of the body rather than physical aspects of peripheral stimulation even when feeling an artificial additional body part. The reason for this shift may be that the “new” third hand might be located directly below the cortical representation of D1, resulting in a shift towards a more medial and superior position of the representation for D1. It seems remarkable that just viewing the own body morphed or disguised is sufficient to influence the perception of the body. We suggest that SI may provide a first dynamic and transient coherent body image by using tactile and also visual information (from other cortical areas via feedback loops, e.g., Rockland and Ojima [2003]). Subsequent cortical processing may then stabilize and enrich this body image with information derived from other modalities. Whereas the body image at this early stage seems to be easily influenced by simple tactile illusions (Chen et al., 2001; Blankenburg et al., 2006, Schaefer et al., 2007, 2008b), later stages of forming the body image might be more influenced by cognitive variables (e.g., in patients with anorexia nervosa).

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6. Viewing the Own Body Magnified

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The traditional understanding of the role of SI is to be a first major unimodal area processing somatosensory input. However, as shown above, recent studies demonstrate that in SI multisensory integration may also take place. An important finding has been reported by Kennett et al. (2001). Using behavioral experiments they revealed that subjects were more accurate in detecting invisible tactile stimuli when they were looking at their stimulated body part compared to viewing a neutral object presented at the same location. Hence, viewing the body can improve tactile acuity. Moreover, this visual enhancement of touch was best when the visual appearance of the arm was magnified. Kennett et al. (2001) suggested that the neural correlates for these effects correspond to modulations in SI, probably induced by back projections from multimodal cortical areas. In 2002 Taylor-Clarke et al. used electroencephalography (EEG) to examine activity in SI in a visuo-tactile enhancement experiment. They showed altered somatosensory potentials associated with the visual enhancement of touch. Although this study successfully linked the behavioral improvements with modulations in SI when seeing the body being touched, it remains unclear if the effects for seeing a magnified body part are similarly based on alterations in SI.

Figure 11. Group means and standard error for the cortical distance between D2 and D5. Asterisks indicate significant differences between the conditions “observe hand magnified” and “observe hand in real size” and rest, respectively.

To further examine the role of SI while seeing the own stimulated body part in different ways we employed an MEG study (Schaefer et al., 2008a). According to the original experiment of Kennett et al. (2001) we compared the topography of SI in a resting state, while seeing the stimulated hand, and while viewing a neutral object of comparable size. Furthermore, we varied the size of the seen body part and presented it in real size or strongly

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magnified. Results confirmed the hypothesis of Kennett et al. (2001) and Taylor-Clarke et al. (2002) by demonstrating modulations in SI when seeing the own hand being touched compared with control conditions. In addition, we found that the magnification of the seen stimulated hand similarly resulted in dynamic alterations of the somatosensory homunculus (Figure 11). Thus, integration of visual and tactile information, necessary to form a representation of peripersonal space, seems to engage brain areas like SI, which was previously thought to be strictly unimodal.

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7. Is this My Body Or Your Body? Peripersonal Space and Social Perception The studies reported above have demonstrated that in contrast to traditional views SI has a more complex role than previously assumed. SI is not only prone to influences from motor or premotor areas; even prefrontal areas seem to have an impact on this brain region. Further, SI reflects the perceived body image rather than the actual physical stimulation. Moreover, recent studies also relate the somatosensory cortices to higher cognitive functions, e.g. the representation of peripersonal space and even social perception, which is shown in the following section. In general, healthy subjects know very well what belongs to their own body. However, as discussed above, simple manipulations in multisensory integration can induce profound tactile illusions. Based on these simple manipulations Botvinick and Cohen (1998) reported an intriguing finding. They instructed participants to watch a rubber hand placed on a table in front of them. Their real right hand was hidden. Now the experimenter touched both, the real right hand as well as the rubber hand, with a small paintbrush. Subjects perceived touch sensations as arising from the rubber hand when both the rubber hand and their own real hidden hand were repeatedly tapped in synchrony (Botvinick and Cohen, 1998; Armel and Ramachandran, 2003). Thus, subjects had the feeling as if the rubber hand belongs to their own body. This illusion disappears when a small asynchrony is introduced between the stroking of the rubber and the real hand. The effect of the rubber hand illusion was replicated in many studies (e.g., Makin et al. 2008; Ehrsson et al. 2004; Ehrsson et al. 2005). For example, in a study by Ehrsson et al. (2008) the rubber hand illusion was used in upper limb amputees to evoke feelings of ownership for the rubber hand replacing their lost hand. This was accomplished by simultaneously touching the stump of the amputees and the finger of the rubber hand. Furthermore, Durgin et al. (2007) reported that touching a rubber hand with a bright beam of light from a laser pointer generated tactile and thermal sensations when the rubber hand was seen as one’s own hand. What are the neural correlates for this manipulation of ownership of an alien body part? Animal data suggest an involvement of the posterior parietal cortex in this projection of sensations to external limbs (Graziano et al., 2000). Further, fMRI data revealed an involvement of the premotor cortex and areas in the posterior parietal cortex when feeling the rubber hand illusion (Ehrsson et al., 2004, 2005). Additionally, Peled et al. (2003) found altered somatosensory evoked potentials in schizophrenic patients during the rubber hand

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illusion, suggesting a role of the somatosensory cortices when subjects report feelings of ownership regarding the rubber hand.

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Figure 12. Dipole localizations of the SEFs. Note the differences between rest or asynchronous condition (asynchro) and synchronous (synchro) condition.

To further test whether the rubber hand illusion also engages SI, we conducted an MEG study (Schaefer et al., 2006b). We recorded neuromagnetic fields while subjects watched a video, showing a hand that was stroked by a stick on D1. At the same time subjects were stimulated on D1 synchronously or asynchronously to the stimulated hand in the video. The video was displayed in peripersonal space of the subjects. Based on the findings of Botvinick and Cohen (1998) we assumed that during synchronous stimulation the subjects would experience an illusion of feeling the touch on the hand in the video. We further hypothesized that the cortical representation of D1 would be modulated, suggesting dynamic short-term modulation of cortical maps related to this illusion (Figures 12 and 13). Behavioral results showed that in the synchronous stimulation condition subjects reported an illusion in which they seemed to feel being touched on the hand in the video. Results of the neuromagnetic source imaging revealed that the cortical representation of D1 changed to a more inferior location during synchronous in comparison to asynchronous stimulation and baseline. Moreover, this change was significantly positively correlated with the feeling of the touch on the video hand. The data suggest that somatosensory cortical maps contribute to the experienced illusion in which the subjects seemed to feel the touching of the hand on the video hand. Only if the seen touch was attributed to the own body, SI seems to be modulated. Hence, the results demonstrate that viewing touch in peripersonal space can change somatosensory processing in SI when it is believed to occur on the own body part, but not when it is believed to be on the body of someone else. To further examine the role of SI for seen touch on the own vs. the body of someone else we conducted an fMRI study (Schaefer et al., 2009).

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Figure 13. Mean differences (group data) between D1 and D5 dipoles during rest, asynchronous and synchronous condition (D5 always rest state). Asterisks indicate the significant differences between the synchronous (synchro) and asynchronous (asynchro) condition and rest, respectively.

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Subjects viewed a touched hand either in an allocentric view or in an egocentric perspective (in the absence of any real touch). As a control condition, participants watched video clips displaying a hand that was not touched, but with touch close to this hand, thus including the same motion aspects as in the experimental conditions (Figure 14).

Figure 14. Types of stimuli used in the experiment: On the right the touch-condition; on the left the nontouch condition. The upper panel depicts the hand in egocentric perspective, the lower the allocentric perspective. Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

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The results revealed activation of somatosensory cortices when observing the hand being touched in egocentric as well as in the allocentric perspective. Furthermore, somatosensory responses differed depending on the perspective of the observed touch. Whereas the egocentric perspective showed activation in the anterior part of SI (BA 3a, 3b), the allocentric perspective involved significant activation of the posterior part of SI (BA 2) (Figure 15). BA 2 has multimodal receptive fields and connections to the rostral part of the posterior parietal cortex, which in turn receives visual input from more caudal parts of the posterior parietal cortex (Iwamura, 1998). Thus, the connectivity between these regions may be related to the activation in BA2. Viewing touch in an egocentric condition may have induced selfattribution/imagination of being touched on one’s own hand, which is different from observing touch on another hand and might require less multimodal activation in BA2. Results of another recent study support these results. Ebisch et al. (2008) reported a significant difference between the sight of an intentional touch compared to an accidental touch in left SI/BA2. Taken together, SI seems to be differentially engaged depending on whether observed touch is attributed to the own body or to someone else. Moreover, different parts of SI seem to provide different functions regarding the differentiation of self and others and also depending on the perceived intentionality of the seen touch. Hence, we conclude that SI is involved in perceptional processes of the social environment.

Figure 15. Brain response for observed touch (relative to nontouch) in egocentric perspective compared with neural activations for allocentric perspective, superimposed on the MNI reference brain. Results show significant posterior activation of SI for the allocentric perspective (BA 2) relative to the egocentric perspective (BA 3a, 3b). Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

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The results of this study showing activation of somatosensory areas when observing touch are also discussed in terms of a possible mirror neuron system for observed and experienced touch (e.g., Keysers et al., 2004; Blakemore et al., 2005). Whereas the mirror neuron system of action observation seems to be crucial for the understanding and imitation of actions (Rizzolatti et al., 2001) and for the understanding of intentions (Iacoboni et al., 2005; Iacoboni and Dapretto, 2006), a mirror neuron system for observation of touch may be important for the recognition and understanding of touch. This may be crucial to form an internal representation of a somatosensory event and to estimate consequences necessary for action preparation. Thus, a mirror neuron system for tactile observation analogous to action observation may exist that might be necessary for rapid assessment and evaluation of how other people may feel or a situation that may be consequential to the observer.

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8. Conclusion: Consequences For the Image of Our Self Since the early observations of Head and Holmes (1911) it has been well known that there is a stable mental construct of the body or a unitary corporeal self that endures in space and in time. The somatosensory cortices play an important role in maintaining this corporeal self. The above discussed studies have demonstrated that the functions of SI are much more complex than previously thought. Thus, SI seems to be influenced by higher order cortical sites like prefrontal areas, by tactile illusions or even by simple disguises of the body, by manipulations of the visibility of body parts and also by social perceptions. The mental construct of our body is supposed to be based on a network of different brain areas, but research discussed above suggests that a corporeal self at a very early stage seems to be established. Later stages in forming the body image might be more influenced by cognitive variables (e.g., in patients with anorexia nervosa). This new understanding of the functions of SI may encourage approaches of using the dynamic facet of this body image as a tool in rehabilitation. For example, recent studies demonstrated that the manipulation of visual feedback can be used to successfully influence phantom sensations in amputees. Studies using the virtual reality box (or mirror-box), which utilizes visual feedback (the mirror image of the intact hand) to pretend the physical occurrence of the phantom limb, report intriguing results (Ramachandran and RogersRamachandran, 1996; Hunter et al., 2003). Future approaches may also include other patients with distorted body images, e.g., with anorexia nervosa. However, the major conclusion of the presented results is more fundamental. These studies show that even at a very early stage in cortical processing complex perceptions are being processed in SI that probably even include social aspects. When SI perceives social dimensions, it also needs to maintain a sense of self. Thus, in contrast to traditional views, central aspects of our self are not only based on frontal brain regions, but also on areas previously thought to be important for peripheral processing, the somatosensory cortices. We conclude that our self seems to be based on a very broad network of brain regions.

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Acknowledgments MS was supported by the Deutsche Forschungsgemeinschaft.

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References Anderson, J.R., Douglas, S., 2002. Tower of Hanoi: evidence for the cost of goal retrieval. J. Exp. Psychol. Learn. Mem. Cogn. 27, 1331-1346. Armel, K.C., Ramachandran, V.S., 2003. Projecting sensations to external objects. Evidence from skin conductance response. Proced. Roy. Soc. Biol. Sci. 270, 1499-1506 Blakemore, S.-J., Bristow, D., Bird, G., Frith, C., Ward, J., 2005. Somatosensory activations during the observation of touch and a case of vision-touch synaesthesia. Brain, 128, 1571-1583. Blankenburg, F., Ruff, C.C., Deichmann, R., Rees, G., Driver, J., 2006. The cutaneous rabbit illusion affects human primary sensory cortex somatotopically. PloS Biol. 4, e69. Botvinick, M., Cohen, J., 1998. Rubber hand ‘feel’ touch that eyes can see. Nature 391, 756. Braun, C., Heinz, U., Schweizer, R., Wiech, K., Birbaumer, N., Topka, H., 2001. Dynamic organization of the somatosensory cortex induced by motor activity. Brain, 124, 22592267. Chapman, C.E., Jiang, W., Lamarre, Y., 1988. Modulation of lemniscal input during conditioned arm movements in the monkey. Exp. Brain Res. 72, 316-334. Chen, L.M., Friedman, R.M., Roe, A.W., 2003. Optical imaging of a tactile illusion in area 3b of the primary somatosensry cortex. Science, 302, 881-885. Durgin, F.H., Evans, L., Dunphy, N., Klostermann, S., Simmons, K., 2007. Rubber hands feel the touch of light. Psychol. Sci. 18, 152-157. Ebisch, S.J., Perruci, M.G., Ferretti, A., Del Gratta, C., Romani, G.L., Gallese, V., 2008. The sense of touch: Embodied simulation in a visuotactile mirroring mechanism for observed animate or inanimate touch. J. Cogn. Neuroci. 20, 1-13. Ehrsson, H.H., Spence, C., Passingham, R.E., 2004. That’s my hand! Activity in premotor cortex reflects feeling of ownership of a limb. Science, 305, 875-877. Ehrsson, H.H., Holmes, N.P. Passingham, R.E., 2005. Touching a rubber hand: feeling of body ownership is associated with activity in multisensory brain areas. J. Neurosci. 9, 10564-10573. Ehrsson, H.H., Rosen, B., Stockselius, A., Ragnoe, Ch., Koehler, P., Lundborg, G., 2008. Upper limb amputees can be induced to experience a rubber hand as their own. Brain, 131, 3443-3452. Elbert, T., Pantev, C., Wienbruch, C., Rockstroh, B., Taub, E., 1995. Increased cortical representation of the fingers of the left hand in string players. Science, 270, 305-307. Flor, H., Elbert, T., Knecht, S., Wienbruch, C., Pantev, C., Birbaumer, N., Larbig, W., Taub, E., 1995. Phantom limb pain as a perceptual correlate of massive reorganization in upper limp amputees. Nature, 375, 482-484. Franz, E.A., Zelaznik, H.N., McCabe, G., 1991. Spatial topologixal constraints in a bimanual task. Acta Psychol. 77, 137-151.

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

98

Michael Schaefer

Franz, E.A., 1997. Spatial coupling in the coordination of complex actions. Q. J. Exp. Psychol. 50, 684-704. Graziano, M.S.A., Cooke, D.F., Taylor, C.S.R., 2000. Coding the location of the arm by sight. Science, 290, 1782-1786. Head, H., Holmes, G., 1911. Sensory disturbances from cerebral lesions. Brain, 34, 102-254. Hunter, J.P., Katz, J., Davis, K.D., 2003. The effect of tactile and visual sensory inputs on phantom limb awareness. Brain, 126, 579-589. Iacoboni, M., Molnar-Szakacs, I., Gallese, V., Buccino, G., Mazziotta, J.C., Rizzolatti, G., 2005. Grasping the intentions of others with one's own mirror neuron system. PLoS Biology, 3, 529-535. Iacoboni, M., Dapretto, M., 2006. The mirror neuron system and the consequences of its dysfunction. Nature Rev. Neurosci. 7, 942-951. Iwamura, Y., 1998. Hierarchical somatosensory processing. Curr. Opin. Neurobiol. 8, 522528. Keysers, C., Wicker, B., Gazzola, V., Anton, J.-L., Fogassi, L., Gallese, V., 2004. A touching sight: SII/PV activation during the observation and experience of touch. Neuron, 42, 335-346. Kennett, S., Taylor-Clarke, M., Haggard, P., 2001. Noninformative vision improves the spatial resolution of touch in humans. Curr. Biol. 11, 1188-1191. Makin, T.R., Holmes, N.P., Ehrsson, H.H., 2008. On the other hand: Dummy hands and peripersonal Space. Behav. Brain Res. 191, 1-10. Moore, C.I., Nelson, S.B., 1998. Spatio-temporal subthreshold receptive fields in the vibrissa representation of rat primary somatosensory cortex. J. Neurophysiol. 80, 2882-2892. Noppeney, U., Waberski, T.D., Gobbelé, R., Buchner, H., 1999. Spatial attention modulates the cortical somatosensory representation of the digits in humans. NeuroReport, 10, 3137-3141. Nicolelis, M.A., Fanselow, E.E., 2002. Thalamocortical optimization of tactile processing according to behavioral state. Nat. Neurosci. 5, 517-523. Peled, A., Pressman, A., Geva, A.B., Modai, I., 2003. Somatosensory evoked potentials during a rubber-hand illusion in schizophrenia. Schizoph. Res. 64, 157-163. Penfield, W., Boldrey, E., 1937. Somatic motor and sensory representation in cerebral cortex of man as studied by electrical stimulation. Brain, 60, 389-443. Ramachandran, V.S., Rogers-Ramachandran, D., 1996. Synaesthesia in phantom limbs induced with mirrors. Proc. R. Soc. Lond. B Biol. Sci. 263, 377-386. Ramachandran, V.S., 1998. Consciousness and body image, lessons from phantom limbs, Capgras syndrome and pain asymbolia. Phil. Trans. R. Soc. Lond. B, 353, 1851-1859. Ramachandran, V.S., Hirstein, W., 1998. The perception of phantom limbs: The D.O. Hebb lecture. Brain, 121, 1603-1630. Rizzolatti, G., Fogassi, L., Gallese, V., 2001. Neurophysiological mechanisms underlying the understanding and imitation of action. Nat. Rev. Neurosci. 2, 661-670. Rock, I., Victor, J., 1964. Vision and touch: An experimentally created conflict between the two senses. Science, 143, 594-596. Rockland, K.S., Ojima, H., 2003. Multisensory convergence in calcarine viusal areas in macaque monkey. Intern. J. Psychophysiol. 50, 19-26.

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Sadato, N., Yonekura, Y., Waki, A., Yamada, H., Ishii, Y., 1997. Role of the supplementary motor area and the right premotor cortex in the coordination of bimanual finger movements. J. Neurosci. 17, 9667-9674. Schaefer, M., Noennig, N., Karl, A., Heinze, H.-J., Rotte, M., 2004a. Reproducibility and stability of neuromagnetic source imaging in primary somatosensory cortex. Brain Topogr. 17, 47-53. Schaefer, M., Rothemund, Y., Heinze, H.-J., Rotte, M., 2004b. Short time plasticity of the primary somatosensory cortex during tool use: a MEG study. NeuroReport, 15, 12931297. Schaefer, M., Flor, H., Heinze, H.-J., Rotte M., 2005a. Dynamic shifts in the organization of primary somatosensory cortex induced by bimanual spatial coupling of motor activity. Neuroimage 25, 395-400. Schaefer, M., Heinze, H.-J., Rotte, M., 2005b. Task-relevant modulation of primary somatosensory cortex suggests a prefrontal-cortical sensory gating system. Neuroimage, 17, 130-135. Schaefer, M., Noennig, N., Heinze, H.-J., Rotte, M., 2006a. Fooling your feelings: Artificially induced referred sensations are linked to a modulation of the primary somatosensory cortex. Neuroimage, 29, 67-73. Schaefer, M., Flor, H., Heinze, H.-J., Rotte, M., 2006b. Dynamic modulation of the primary somatosensory cortex during seeing and feeling a touched hand. Neuroimage, 29, 587592. Schaefer, M., Flor, H., Heinze, H.-J., Rotte, M., 2007. Morphing the body: illusory feeling of an elongated arm affects somatosensory homunculus. Neuroimage, 36, 700-705. Schaefer, M., Heinze, H.-J., Rotte, M., 2008a. Seeing the hand bigger than it is: Observing the touched body magnified alters somatosensory homunculus. NeuroReport, 19, 901905. Schaefer, M., Heinze, H.-J., Rotte, M., 2008b. My third arm: feeling an artificial supernumerary arm changes topography of the homunculus. Human Brain Mapping, 30, 1413-1420. Schaefer, M., Xu, B., Flor, H., Cohen, L.G., 2009. Effects of different viewing perspectives on somatosensory activations during observation of touch, Human Brain Mapping, in press. Shallice, T., 1982. Specific impairments of planning. Philos. Trans. R. Soc. Lond. B Biol. Sci. 98, 199-209. Simon, H.A., 1975. The functional equivalence of problem solving skill. Cogn. Psychol. 7, 268-288. Staines, W.R., Graham, S.J., Black, S.E., McIlroy, W.E., 2002. Task-relevant modulation of contralateral and ipsilateral primary somatosensory cortex and the role of a prefrontalcortical sensory gating system. Neuroimage, 15, 190-199. Steyvers, M., Etoh, S., Sauner, D., Levin, O., Siebner, H.R., Swinnen, S.P., Rothwell, J.C., 2003. High-frequency transcranial magnetic stimulation of the supplementary motor area reduces bimanual coupling during anti-phase but not in-phase movements. Exp. Brain Res. 151, 309-317.

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Taylor-Clarke, M., Kennett, S., Haggard, P., 2002. Vision modulates somatosensory cortical processing. Curr. Biol. 12, 233-236. Wartan, S.W., Hamann, W., Wedley, J.R. , McColl, I., 1997. Phantom pain and sensation among British veteran amputees. British J. Anaesth. 78, 652-659. Yang, T.T., Gallen, C., Schwartz, B., Bloom, F.E., Ramachandran, V.S., Cobb, S., 1994. Sensory maps in the human brain. Nature, 36, 592-593.

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In: Somatosensory Cortex: Roles, Interventions and Traumas ISBN 978-1-60741-876-4 Editor: Niels Johnsen and Rolf Agerskov © 2008 Nova Science Publishers, Inc.

Chapter 5

Rehabilitation After Stroke Using Brain-Computer-Interfaces and Neurostimulation Surjo R. Soekadar1,2, Andrea Caria3, Ander Ramos Murguialday3 and Niels Birbaumer3

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1

Neurostimulation Unit, Department of Psychiatry and Psychotherapy, University of Tübingen, Germany 2 National Institutes of Health (NIH), NINDS, Human Cortical Physiology and Stroke Neurorehabilitation Section, Bethesda, USA 3 Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany

Abstract This chapter deals with the current state and perspective of neurotechnology, particular the use of brain computer interfaces (BCI) and neurostimulation in the rehabilitation of stroke. While 20 years ago brain-computer-interfaces that utilize neurophysiologic or metabolic signals originating in the brain to activate or deactivate external devices or computers have been used by a handful of research groups only, there are now - after the decade of the brain - several hundred groups world-wide working in this field. Additionally, the modulation of brain activity by non-invasive cortical stimulation undergoes a renaissance. New and innovative techniques to modulate or even enhance brain functions have emerged. After a short introduction of the BCI-systems that have been developed and successfully used in patients with intractable epilepsy, attention deficit disorder, ALS and chronic pain since 1979 by the University of Tuebingen group, recent developments in the use of BCI technology and neurostimulation for stroke survivors will be sketched and exemplified by our latest results. Limits and current challenges in the use of BCI technology and brain stimulation will be highlighted and discussed. The chapter closes with an outlook on future developments and prospects

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introducing promising developments such as the combination of BCI systems with noninvasive forms of neurostimulation and e.g. functional electric stimulation (FES). Keywords: neurotechnology, brain-computer-interface, neurostimulation, neuro-rehabilitation, stroke.

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Introduction Driven by enormous growth of computational capacities over the last two decades, an unprecedented progress in the field of neurotechnology has been made. Based on innovations in sensor technology, signal transmission and processing, scientific interest in Brain Computer Interfaces (BCI) or Brain Machine Interfaces (BMI) that utilize electric, magnetic or metabolic brain activity to drive external devices has experienced significant growth. While before 1990 only a handful research groups worked on BCI, there was an exponential growth in research activity that accelerated after the turn of the century. Since the discovery of electric brain oscillations by Hans Berger in 1929 many scientists strived for finding the underlying code of brain oscillations that would allow them to read thoughts and reveal the fundaments of human behaviour. The idea to bypass peripheral nerves and muscles using a direct access to the brain is closely related to the hope that people with compromised communication abilities or loss of motor control will substantially benefit from such technology. Stroke is already the leading cause for long-term disability worldwide and the number of affected people increases substantially every year due to demographic change and increasing survival rates (WHO, 2003). About 30% of all stroke victims suffer from very limited motor recovery and cannot manage their daily needs unassisted (Kwakkel et al., 2003; Rosamond et al., 2008). For those patients restoration of movement would substantially improve their quality of life. But despite remarkable progress, BCI technology for restoration of movement is still in its infancy. There are enormous unsolved problems that limit the practicability and success of BCI-devices for daily use in a normal environment. The average communication rate achieved with BCI technology in humans is currently in the range of 0.4 - 0.5 bit / sec (Wolpaw et al., 2000). It was shown that patients that are otherwise incapable to communicate, i.e. locked-in-patients suffering from amyotrophic lateral sclerosis (ALS), a disease characterized by a combined degradation of upper and lower motor neurons, can significantly benefit from BCI use (Birbaumer et al., 1999; Kübler et al., 2001; Birbaumer et al., 2006). In patients with severe motor deficits, for example after stroke, the required information density for complete substitution of lost motor functions is by far higher. While theoretical considerations to reach such information rates by multiple invasive single-neuron recordings are promising (Koepsell et al., 2008), speed and accuracy of currently available intracortical BCI for humans is comparable with non-invasive methods (Wolpaw et al., 2004; Hochberg et al., 2006).

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However, recent findings implicate that use of non-invasive BCI might entail another groundbreaking quality for rehabilitation of stroke patients: the selective induction of usedependent neuroplastic changes that specifically facilitates motor recovery. The chapter focuses on this particular quality of BCI use and draws perspectives based on combined application of neurotechnology in rehabilitation of stroke. Prima facie, according to Skinner’s proposal (1953) on operant (instrumental) and classical (Pavlovian) conditioning, voluntary control of brain activity shouldn’t be possible at all as there is no neuromuscular system involved. Later Neal E. Miller’s suggested that instrumental (“voluntary”) control of the autonomous nerve system (ANS) was possible (Miller, 1969) leading to an extensive body of experiments that aimed to influence visceral parameters such as blood pressure (Engel, 1981; McGrady et al., 1995), heart rate (Cuthbert et al., 1981) and gastric motility (Hoelzl & Whitehead, 1983) by instrumental control. While the most impressive clinical results using classical conditioning were achieved with electromyographic feedback in neuromuscular rehabilitation of various neurological conditions (Birbaumer & Kimmel, 1979), chronic neuromuscular pain (Flor & Birbaumer, 1993), and posture control in kyphosis and scoliosis (Dworkin et al., 1985; Birbaumer et al., 1994), those studies on “voluntary” control of the ANS without inclusion of the musculoskeletal system showed only very limited success of biofeedback. However there was one exception: self-regulation of brain activity (Elbert et al., 1984).

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Brain-Computer-Interfaces The origin of non-invasive BCI-systems can be seen in early works done on operant training of brain response in the context of neuro-feedback. In neuro-feedback, subjects receive visual or auditory on-line feedback of their brain activity and are asked to voluntarily modify a particular type of brainwave. The feedback signals contain the information on the degree of success in controlling the signal and the reward. It has been suggested that neuro-feedback might offer treatment strategies for conditions associated with abnormal oscillatory brain activity. In this context, over the last three decades Birbaumer and colleagues developed several non-invasive systems for various scientific and clinical questions such as therapy-resistant epilepsy (Kotchoubey et al., 2001), children with attention deficit disorder (Birbaumer et al., 1986; Strehl et al., 2006; Fuchs et al., 2003) and chronic pain syndrome (Lotze et al., 1999). In general, depending on where neurophysiological signals or metabolic changes are recorded, two forms of BCI can be distinguished: invasive BCI and non-invasive BCI. Semiinvasive approaches are based on epi- or subdural electrode arrays to record local field potentials (LFP). In non-invasive BCI-research four types of neurophysiologic signals have been tested so far. Three based on EEG-activity and one based on MEG-activity: 1. Slow Cortical Potentials (SCP-BCI), 2. Brain-oscillations measured by EEG ranging from 4 to 40 Hz (primarily μ- or sensorimotor rhythm range, SMR, and its harmonics; EEG-BCI), 3. Event-related brain potentials (ERPs), primarily the P300 (P300-BCI) and 4. Brain-oscillations measured by MEG in the range of SMRs (MEG-BCI).

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The operant control of SCPs (defined as slow event-related direct-current shifts of the EEG in the range of 300ms to several seconds) reaches back to the late 70ies when Birbaumer and co-workers demonstrated by numerous publications that strong and anatomically specific effects of self-induced changes in cortical activity on behaviour and cognition occur (Birbaumer et al., 1990; 1992; 1995 and 1999b). Studies that simultaneously investigated voluntary SCPs and blood-oxygen-level dependent signals (BOLD) revealed that central SCPs are particularly associated with BOLD variations in the anterior basal ganglia and premotor cortex (Hinterberger et al., 2005) suggesting a critical role of basal-gangliathalamo-frontal networks. SMRs, in contrast to SCP’s, are recorded over the sensori-motor cortex within the frequency of 8-15 Hz. During actual or imagined movements SMR disappear (Howe and Sterman, 1972). There seems to be a close association with functional motor inhibition of thalamo-cortical loops. Depending on the context, the SMR is also called μ-rhythm following a suggestion of Gastaut (1952) and Gastaut et al. (1952). SMRs have been extensively investigated by the Pfurtscheller group in Graz (Pfurtscheller et al., 2005) and the Wolpaw group in Albany (Wolpaw et al., 2004; Wolpaw et al., 2007). The focality and accessibility by cognitive manipulation makes SMR an ideal candidate to drive BCI systems. Pfurtscheller’s BCI-group in Graz, Austria, was the first to apply a SMR-based BCI to a quadriplegic patient with high spinal cord lesion. Induced by imagination of movements, voluntary modulation of SMR enabled the paralyzed patient to control electrical stimulation of his hand and arm muscles. With this apparatus he could for example grasp (Pfurtscheller et al., 2003). Another extensively tested BCI controller is the P300-BCI based on event-related brain potentials (ERP) by Donchin (Farwell & Donchin, 1988). While SCP- and SMR-control is learned through visual and auditory feedback often requiring up to ten training sessions before reliable control is achieved, the P300-BCI needs no training at all. Information rates of P300-BCI can reach 20-30 bits/min (Lenhard et al., 2008). Finally, a magnetoencephalography (MEG-) BCI developed by Niels Birbaumer and Leonardo Cohen at NINDS, National Institutes of Health, USA, was extensively tested and then applied in stroke survivors (Birbaumer & Cohen, 2007). In contrast to EEG-based BCIsystems, the MEG-BCI allows recording of a much broader frequency range and allows the gradual distinction of anatomically specific cortical activation. Based on the MEG-BCI, Buch et al. (2008) showed that 6 of 8 stroke patients could learn to control their SMR to control a hand orthosis affixed to their paralyzed hand. Most recently also a BOLD-signal based fMRI-BCI has been introduced (Weiskopf et al., 2003; Yoo et al., 2004; DeCharms 2005; Caria et al., 2007). In 2003 Weiskopf & Birbaumer et al. proposed that the development of fMRI-BCIs might be a powerful tool in the treatment of various disorders and diseases. It was shown that intracortical activity is highly correlated with local blood flow change and the BOLD signal (Logothetis et al., 2001). Based on that concept, it became evident that volitional regulation of BOLD activity in cortical and sub-cortical areas such as amygdala, anterior cingulate, insula and parahippocampal gyrus was associated with changes of connectivity between those areas (Caria et al., 2007). DeCharms et al. demonstrated that use of a real-time fMRI-BCI can affect pain perception (DeCharms et al., 2005).

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In addition to the fMRI-BCI approach, near infrared spectroscopy (NIRS) or functional near-infrared imaging (fNIR) is also a non-invasive technique based on metabolic changes of the brain. Using multiple pairs or channels of light sources and light detectors operating at two or more discrete wavelengths at near infrared range (700–1000 nm) cerebral oxygenation and blood flow of localized regions of the brain can be determined. Typically the depth of brain tissue that can be measured is between 1cm and 3cm. The degree of increases in regional cerebral blood flow (rCBF) exceeds that of increases in regional cerebral oxygen metabolic rate (rCMRO2) resulting in a decrease in deoxygenated haemoglobin in venous blood during higher oxygen demand. Therefore, increase in total haemoglobin and oxygenated haemoglobin with a decrease in deoxygenated haemoglobin is expected to be observed in activated areas during NIRS measurement. Compared to other BCI-approaches the advantage of functional near-infrared imaging (fNIR) lies in its simplicity, flexibility and high signal to noise ratio (Sitaram et al., 2007). Taken together the following properties of non-invasive BCI-control should be emphasized:

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(1) Voluntary control of circumscribed brain areas is possible (2) Learned regulation of brain oscillations may influence activity of sub-cortical sites but is highly specific and does not co-activate other unrelated brain sites (3) Cognitive activity such as imagery for desynchronization of SMR may assist the acquisition of brain control but is not a necessary condition to modulate brain oscillations (4) Behavioural effects of self-induced local brain changes seem to be functionally specific for the respective brain region Besides the described non-invasive BCI-approaches several invasive and semi-invasive techniques have been developed during the last years. Whereas there is only little risk in applying non-invasive BCI-systems, implantation of electrodes or microelectrode arrays require scull opening. Incision of the dura mater is obligatory for epicortical grids or intracortical recordings. In semi-invasive and invasive BCI-research, mainly three signals have been tested: 1. electrocorticogram (ECoG), 2. action potential spike trains from implanted microelectrodes and 3. synaptic field potentials from implanted electrodes. Pilot studies on an ECoG based BCI using motor imagery showed that control over cursor movements can be learned with only a few minutes of training (Schalk et al., 2008; Hinterberger et al., 2008). Besides a better topographical resolution than non-invasive approaches, ECoG-based BCI have a better signal-to-noise ratio due to absence of electromyographic contaminations and other artefacts. The reconstruction of movements from firing patterns of single cells of the motor cortex (Nicolelis, 2003) or parietal neuronal pools (Scherberger et al., 2005) in animals were remarkably successful and induced notable enthusiasm. Monkeys learned to move cursors into moving goals on a computer screen in a predetermined sequence by successively activating neurons in motor, premotor and parietal motor areas. In a particularly successful preparation 32 cells were sufficient to move an artificial arm and perform skillful reaching movements after extensive training (Schwartz, 2007). This technique enabled a monkey to

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feed himself (Velliste et al., 2008). The plasticity of the cortical circuits allowed learned control of movements directly from the cellular activity even outside the primary or secondary homuncular representations of the motor cortex (Taylor et al., 2002). In an encouraging experiment Hochberg (2006) implanted extremely densely packed microelectrode arrays of up to several hundred microelectrodes (Donoghue et al., 2002) in two quadriplegic human patients. Within a few training sessions, the patients learned to use neuronal activity from field potentials to move a computer cursor in several directions comparable to the tasks used for multidimensional cursor movements in the non-invasive SMR-BCI reported by Wolpaw & McFarland (2004). However, in contrast to the studies in healthy animals none of the invasive procedures allowed restoration of skillful movement in paralyzed humans. It is not clear why so far the human preparations have achieved only limited results in terms of application to activities of daily living (Hochberg et al., 2006). There are a couple of major problems that are unsolved so far. Some of them are related to the fact that the motor cortex contributes only about 40% of the whole cortical input to the corticospinal tract indicating that complex motor behaviour is not exclusively represented in the motor cortex. This would indicate that multiple recording sites all over the brain, even in deeper brain sites, might be necessary to further increase the precision of BCI control. Another problem is often referred to as the decoding problem meaning that spike firing patterns are ambiguous. Nevertheless, results of invasive BCI-systems are impressive. Generalization from invasive animal BCI-approaches to human beings with neurological disorders is unfortunately premature. The limited results of invasive BCI-techniques in patients with neurotrauma or stroke might be closely related to continuous neuroplastic changes making it hard to predict which area is optimal for signal recording. Practicability, reliability and safety-issues are further limitations.

Neurostimulation In his “Essai théorique et experimental sur le galvanisme” Giovanni Aldini (1762-1834) described facial muscle contractions during electric brain stimulation of recently decapitated prisoners (Aldini, 1804). Later, in 1874, Bartholow, one of the founding members of the American Neurological Association, described the effects of electrical stimulation in conscious humans (Bartholow, 1874). Stimulation of the left postcentral gyrus was associated with distinct muscular contractions of the right arms and legs. Accompanied by studies on animals by Fritsch and Hitzig (1870) this led to systematic studies on motor and sensory representations in humans (e.g. Penfield, 1937). The idea was born that by electrical stimulation of the brain specific behavioural changes, eventually even complex behaviour, can be induced. About five decades ago stimulation of the peripheral nerves or peripheral nerve stimulation became the first form of “neurostimulation” to be developed. It was supplemented by an invasive technique which directly stimulated the spinal cord (SCS). Besides spinal cord stimulation and peripheral nerve stimulation, invasive and non-invasive forms of stimulation directly applied to the brain became established. Whereas the term neurostimulation includes both, stimulation of the peripheral or central nervous system, the term brain stimulation is used only for the latter and includes non-invasive and invasive

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approaches. The most prominent invasive brain stimulation methods include deep brain stimulation (DBS) and motor cortex stimulation (MCS). DBS has been successfully used in Parkinson disease (Anderson & Lenz, 2006) and lately also in mental disorders, such as depression (Giacobbe & Kennedy, 2006) and obsessive-compulsive disorders (Greenberg et al., 2006). MCS showed to be effective in neuropathic pain (Henderson & Lad, 2006). Whereas use of invasive neurostimulation entails the risk of complications, i.e. infections, bleedings and accidentally brain injury, non-invasive forms of brain stimulation represent a promising alternative. For a long time, quantification of beneficial effects of non-invasive methods (particularly on neurophysiology and cognition) was difficult so that those methods were widely neglected compared to neuro-pharmacological approaches. It is the merit of Paulus and Nietsche (University of Göttingen, Germany) that direct-current stimulation (tDCS) was re-discovered for specific modulation of brain function (Nitsche & Paulus, 2000). Intensified research substantiated that anodal tDCS, normally applied at 1 to 2 mA over periods of up to 30 minutes, affects cortical plasticity and learning in healthy subjects (Antal et al., 2004; Lang et al., 2003; Marshall et al., 2004; Reis et al., 2009). Recently developed techniques based on non-invasive electrical stimulation, such as transcranial alternating current stimulation (tACS) (Antal et al., 2008) or random noise stimulation (RNS) (Terney et al., 2008) might be valuable new forms of brain stimulation, but need to be further tested. Another technique, transcranial magnetic stimulation (TMS), based on magnetic pulses, can focally induce electric currents and belong to the best established non-invasive forms of brain stimulation. Depending on the intensity and frequency of stimulation, TMS can have lasting effects on the excitability of the brain. Starting from the observation that repetitive TMS (rTMS) elicits either excitatory or inhibitory effects that outlast the stimulation, attempts to use TMS as a therapeutic tool in neurological and psychiatric disorders emerged. They include depression (Miniussi et al., 2005), tinnitus (Khedr et al., 2009; Plewnia et al., 2007), posttraumatic stress disorder (Cohen et al., 2004), auditory hallucinations (Hoffmann et al., 2005), chronic pain (Lefaucher et al., 2004), epilepsy (Theodore et al., 2003) and movement disorders (Fregni et al., 2005). Whereas effects of tDCS and rTMS on brain excitability seem to be comparable, underlying mechanisms might differ. In both techniques influence on remote brain areas via trans-synaptic transmission have been shown (Lang et al., 2005; Denslow et al., 2005). Both, tDCS and rTMS are well tolerated and safe if used within safety limits (Wassermann, 1998; Nitsche et al., 2003). In stroke, modulation of motor areas of the affected hemisphere with anodal tDCS was associated with motor improvements of the paretic hand (Hummel et al., 2005). Amelioration of stroke related aphasia was repeatedly described (Monti et al., 2008; Hesse et al., 2007). A pilot study on combined tDCS and robot-assisted arm training by Hesse et al. (2007) showed beneficial effects on motor function (assessed by Fugl-Meyer-Motor-Score) and aphasia in several participants. Also, recent reports have suggested that rTMS in acute stages of stroke might improve clinical outcome (Khedr et al., 2005; Mansur et al., 2005). In summary, improvements after non-invasive neurostimulation in stroke patients ranged between 10% and 30%. The reported findings are encouraging and trendsetting. However, underlying mechanisms of neurostimulation need to be better understood. Still, there is lack of knowledge about effect duration and it became clear that the context of stimulation (i.e. the

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state of the brain during and after neurostimulation) and factors such as BDNF polymorphism (Cheeran et al., 2008) might play a role for the brain’s susceptibility to neuroplastic changes induced by brain stimulation. For evaluating the clinical relevance of brain stimulation in the treatment of stroke patients, larger studies in less selected patient groups that identify the influence of lesion location, degree of disability and time since stroke are clearly needed.

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BCI-Systems to Augment Neuroplasticity in Stroke Numerous studies indicate extensive neuroplastic changes after stroke. On the synaptic, neuronal and circuit level, the following mechanisms have been described: new synapses strengthening and rewiring (Chklovskii et al., 2004) following long-term potentiation (LTP) or long-term depression (LTD), dendritic sprouting modulated by neurotrophic factors, such as BDNF, extensive peri-infarct reorganization that might include unaffected areas taking over the function of the lesioned site (vicarious reorganization; Jaillard et al., 2005) and finally changes of activity patterns in remote cortical regions (Frost et al., 2003) including interhemispheric inhibition (Murase et al., 2004). Characterized by dynamic recursive interactions between those levels, the complexity of neuroplastic changes after stroke becomes daunting. Interpretation of longitudinal studies looking at neuroplastic changes during the course of stroke recovery is difficult as it is unclear whether certain neuronal reorganization processes reflect or lead to motor recovery. However, findings on beneficial effects of various interventions, such as reduction of somatosensory input from the intact hand (Floel et al., 2004) or increase from the affected hand (Conforto et al., 2002), neuropharmacologic strategies influencing dopaminergic or adrenergic modulation (Scheidmann et al., 2004), and last but not least studies on the effects of non-invasive brain stimulation (Hummel et al., 2005; Hesse et al., 2007; Takeuchi et al., 2008) implicate that modulation of neuroplasticity might be functionally relevant for stroke recovery. While BCI use in motor recovery can be categorized in two strategies: one, based on the finding that abnormal brain activity can be remarkably improved by the use of BCI technology, and one, aiming at activation of devices that assist in motor function. In 2007 Niels Birbaumer (University of Tübingen, Germany) and Leonardo Cohen (NINDS, NIH, USA) introduced a MEG-based BCI that combines both: by either increasing or decreasing SMR activity, an orthosis affixed to the participant’s arm opens or closes their hand (fig.1). A great advantage of the MEG-BCI is the high spatial and temporal resolution that additionally allows precise examination of cortical reorganization processes during and after BCI-training. In a subsequent study, eight patients with chronic hand plegia resulting from stroke participated in 13 to 22 BCI training sessions to learn voluntary control of their μ-rhythm (or its harmonics’) amplitude originating in the sensorimotor areas of the cortex (Buch et al., 2008). Diagnostic MRIs revealed single, unilateral subcortical, cortical or mixed lesions in the participating patients. Patients had no residual finger extension function. Before the actual training, the patients had to imagine several distinct movements of the upper and lower extremity as well as the tongue. While doing this, the ipsilesional area with the strongest oscillatory MEG response was selected.

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Figure 1. MEG-BCI. The subject sits upright in the MEG, while his arm and his fingers are afixed to an orthosis controlled by voluntary regulation of SMR.

This area was represented by three MEG-sensors. Frequencies for BCI-control ranged between 9 and 25 Hz. Depending on the sensors’ activity a cursor was moved on a screen. For the training only these frequencies were selected that allowed optimal distinction between imagined hand opening and closing. During training online-feedback was then given by showing a raised or lowered screen cursor. After approximately 4 seconds of either up or down regulation, the affected hand was either opened or closed. SMR control was associated with increased range and specificity of μ-rhythm modulation as recorded from sensors overlying central ipsilesional (4 patients) or contralesional (2 patients) regions of the array. However in the course of the training most patients significantly increased neuroelectric activity over central motor brain areas (t(18) =5,49 P < .001, paired t-test 2-tailed). Two patients were unable to gain BCI control (see fig. 2, subjects BW & GH). One patient (WF) started with high success rates of BCI control (approximately 85%) at the beginning of the training and did not improve much further. This study demonstrated for the first time that most patients with chronic stroke, even with complete hand paralysis, can learn to control SMR-based BCI-systems. However, BCI training was not associated with notable clinical improvement. Studies to investigate the reasons are underway. Possible explanations include: 1. insufficient BCI training duration. Up to one hour of BCI training per day for 2-3 weeks might be too little to induce relevant motor recovery in patients with chronic paralysis after stroke. Also inadequate measures to investigate motor function recovery might have been used. 2. limited translation of BCIassociated movements into daily-life activities (“transfer package”; Taub et al., 2006). 3. shift of activation during BCI training. All patients were instructed to use some sort of motor imagery to initiate SMR-control. However, in the course of BCI training most patients did not use motor imagery to control SMR anymore and neuroelectric activity increased over the central motor areas. 4. delay of BCI driven somatosensory input. BCI systems that translate SMR-regulation online into BCI driven motor execution that lead to a contingent somatosensory feedback might improve impact of BCI training on motor recovery.

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Figure 2. shows the course of training and brain activity changes of each patient. On the left side, structural MRs of all participating stroke patients are shown. On the right side percentage of correct trials for each session is given (with the regression line and the regression coefficients in the top right corner of each graph). The central part of the figure depicts the amplitude differences for the two targets (opening and closing the hand, upper and lower goal) in the selected frequency band during the last training session and the R2 for target trials during the last session: R2 denotes the correlation of the SMR-amplitude of particular MEG sensors (black circles) with the target indicating those sensors with the most frequent correct responses for both types of trials.

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In this context, BCI-controlled functional electric stimulation (FES) of the affected hand muscles might offer an optimal approach leading to contingent somatosensory feedback and increased experience of self-efficacy. Still it is unclear why some stroke patients did not gain control over the BCI. Studies on lesion location and functional connectivity during BCI control might further elucidate the underlying mechanisms of BCI control.

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Figure 3. shows the average success rate averaged over all stroke patients across sessions. The average success rate for the last training session is 72%.

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Outlook on the Future It was shown that in patients with stroke, BCI application based on SMR-control is possible and accompanied by neuroplastic changes that yield the potential for facilitating motor recovery even in completely paralyzed people. While over the past years, new strategies in stroke rehabilitation such as constrained-induced therapy (CIT) (Taub et al., 1993; Wolf et al., 2006), bilateral arm training with auditory cueing (BATRAC) (Whitall et al., 2000; Luft et al., 2004), body-weight-supported treadmill training (Sullivan et al., 2002) and robot assisted approaches (Hesse et al., 2007) emerged, they require at least a minimum of rest movement and motor control in the affected limb. Use of BCI combined with other strategies offer a perspective for the 30-50% of stroke patients with permanent motor deficits, particularly with complete paralysis. Sufficient training time, combination with brain stimulation techniques, neuropharmacologic augmentation (Ziemann et al., 2006), improved BCI-coupled somato sensory input (e.g. using functional electric stimulation, FES) and last but not least efficient “transfer packages” that translate BCI driven movements into daily-life actions might potentiate effects of BCI on motor recovery in rehabilitation of severely affected stroke survivors. Efforts to understand effects of BCI use on activity-dependent neuroplasticity in patients with neurological disorders or stroke have just begun. The relation between brain activity or

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voluntary control of brain oscillations and restoration of motor function is yet a widely unexplored field. Semi-invasive approaches using epicortical grids for bidirectional BCI systems that combine brain signal recording and stimulation are currently under development. In this context wireless ECoG-grids are a prerequisite to extent the current limitation of 30-day use of cable-based systems that are presently available for temporary ECoG recordings in humans. Their potential and importance will substantially depend on their reliability, safety and provided gain of function. Looking at the translation of newly invented strategies for stroke rehabilitation into clinically useful treatments over the last decade that are mildly spoken ‘disappointing’, new concerted action is needed to overcome the obstacles between research and optimal patient care. Consortia that facilitate interactions between patients, front-line-clinicians and basic scientists, not to mention improved conditions for multidisciplinary efforts in science, coevally creating frameworks for an across-the-board agreement on common methods, outcome measures and clinical implementation are crucial to master the challenges ahead in stroke rehabilitation that include implementation of up-to-date research finding into clinical routine.

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Conclusion Brain-Computer-Interface technology and neurostimulation are powerful tools to modulate brain activity. As neuroplastic changes after stroke and their functional relevance become better understood, facilitation of motor recovery by BCI technology and neurostimulation represent promising resources to improve motor function and quality-of-life in severely affected stroke survivors.

Acknowledgments This work was supported by the Federal Ministry of Education and Research (BMBF; Bernstein Focus: Neurotechnology, Germany), the NIH/DFG Research Career Transition Award to Surjo R. Soekadar, the Werner Reichardt Centre for Integrative Neuroscience (CIN) at the University of Tübingen (pool project 06-2008) and the Sonderforschungsbereich 550 at the University of Tübingen, Germany.

References Aldini J. Essai théorique et experimental sur le galvanisme, avec une série d’expériences faites devant des commissaires de l’Institut nationale de France, et en divers amphithéâtres anatomiques de Londres. Fournier Fils, Paris 1804.

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

Rehabilitation After Stroke Using Brain-Computer-Interfaces…

113

Anderson WS, Lenz FA. Surgery insight: Deep brain stimulation for movement disorders. Nat Clin Pract Neurol, 2006;2:310-320. Antal A, Boros K, Poreisz C, Chaieb L, Terney D, and Paulus W. Comparatively weak aftereffects of transcranial alternating current stimulation (tACS) on cortical excitability in humans. Brain Stimulation, 2008;1:97–105. Bartholow R. Experimental investigations into the functions of the human brain. Am J Med Sci, 1874;134:305–313. Berger, H. Ueber das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten, 1929;87:527-570. Birbaumer, N., & Kimmel, H. (Eds.). Biofeedback and Self-Regulation. Hillsdale: Erlbaum. 1979. Birbaumer N, Elbert T, Rockstroh B & Lutzenberger W. Biofeedback of slow cortical potentials in attentional disorders. In W.C. McCallum, R. Zappoli, & F. Denoth (Eds.), Cerebral Psychophysiology: Studies in Event-Related Potentials. Amsterdam: Elsevier, 1986. Birbaumer N, Elbert T, Canavan A & Rockstroh B. Slow Potentials of the Cerebral Cortex and Behavior. Physiological Reviews, 1990;70:1-41. Birbaumer N, Roberts L, Lutzenberger W, Rockstroh B & Elbert T. Area-specific selfregulation of slow cortical potentials on the sagittal midline and its effects on behavior. Electroencephalography and Clinical Neurophysiology, 1992;84:353-361. Birbaumer N, Flor H, Cevey B, Dworkin B & Miller NE. Behavioral treatment of scoliosis and kyphosis. Journal of Psychosomatic Research, 1994;6:623-628. Birbaumer N, Flor H, Lutzenberger W & Elbert T. Chaos and order in the human brain. In G. Karmos & M. Molnar (Eds.), Perspectives of Event-Related Potentials Research, Amsterdam: Elsevier. 1995; 450-459. Birbaumer N, Ghanayim N, Hinterberger T, Iversen I, Kotchoubey B, Kübler A, Perelmouter J, Taub E, & Flor H. A spelling device for the paralysed. Nature, 1999;398:297-298. Birbaumer N. Slow cortical potentials: Plasticity, operant control, and behavioral effects. The Neuroscientist, 1999b;5:74-78. Birbaumer N. Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology, 2006;43:517-532 Birbaumer N, Cohen LG. Brain-computer interfaces: communication and restoration of movement in paralysis. J Physiol, 2007;579:621-636. Buch E, Weber C, Cohen LG, Braun C, Dimyan MA, Ard T, Mellinger J, Caria A, Soekadar S, Fourkas A, Birbaumer N. Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke. 2008;39:910-917. Caria A, Veit R, Sitaram R, Lotze M, Weiskopf N, Grodd W, Birbaumer N. Regulation of anterior insular cortex activity using real-time fMRI. NeuroImage, 2007;35:1238-1246. Cheeran B, Talelli P, Mori F, Koch G, Suppa A, Edwards M, Houlden H, Bhatia K, Greenwood R, Rothwell JC. A common polymorphism in the brain-derived neurotrophic factor gene (BDNF) modulates human cortical plasticity and the response to rTMS. J Physiol. 2008;586:5717-5725.

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Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

114

Surjo R. Soekadar, Andrea Caria, Ander Ramos Murguialday, et al.

Chklovskii DB, Mel BW, Svoboda K. Cortical rewiring and information storage. Nature, 2004;431:782-788. Cohen H, Kaplan Z, Kotler M, et al. Repetitive transcranial magnetic stimulation of the right dorsolateral prefrontal cortex in posttraumatic stress disorder: a double-blind, placebocontrolled study. Am J Psychiatr, 2004;161:515–524. Conforto AB, Kaelin-Lang A, Cohen LG. Increase in hand muscle strength of stroke patients after somatosensory stimulation. Ann Neurol, 2002;51:122-125. Cuthbert B, Kristeller J, Simons R, Hodes R, & Lang PJ. Strategies of arousal control: biofeedback, meditation, and motivation. Journal of Experimental Psychology, 1981;110:518-546. DeCharms RC, Maeda F, Glover GH, Ludlow D, Pauly JM, Soneji D, Gabrieli JD & Mackey SC. Control over brain activation and pain learned by using real-time functional MRI. Proceedings of the National Academy of Sciencey, 2005;102:18626-18631. Denslow S, Lomarev M, George MS, Bohning DE. Cortical and subcortical brain effects of transcranial magnetic stimulation (TMS)-induced movement: an interleaved TMS/functional magnetic resonance imaging study. Biol Psychiatry, 2005;57:752-760. Donoghue JP. Connecting cortex to machines: recent advances in brain interfaces. Nature, Neuroscience, 2002;5:1085-1088. Dworkin B, Miller NE, Dworkin S, Birbaumer N, Brines M, Jonas S, Schwentker E & Graham J. Behavioral method for the treatment of idiopathic scoliosis. Proceedings of the National Academy of Science, USA, 1985;82:2493-2497. Elbert, T., Rockstroh, B., Lutzenberger, W., & Birbaumer, N. (Eds.). Self-Regulation of the Brain and Behavior. New York: Springer. 1984. Engel BT. Clinical biofeedback: a behavioral analysis. Neuroscience and biobehavioral reviews, 1981;5:397-400. Farwell LA & Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology, 1988;70:510-523. Floel A, Nagorsen U, Werhahn KJ, Ravindran S, Birbaumer N, Knecht S, Cohen LG. Influence of somatosensory input on motor function in patients with chronic stroke. Ann Neurol, 2004;56:206-212. Flor H, & Birbaumer N. Comparison of the efficacy of EMG biofeedback, cognitive behavior therapy, and conservative medical interventions in the treatment of chronic musculoskeletal pain. Journal of Consulting & Clinical Psychology, 1993;61:653-658. Fregni F, Simon DK, Wu A, Pascual-Leone A. Non-invasive brain stimulation for Parkinson’s disease: a systematic review and meta-analysis of the literature. J Neurol Neurosurg Psychiatry, 2005;76:1614–1623. Fritsch GT, Hitzig E. Über die elektrische Erregbarkeit des Grosshirns. Arch Anat Physiol (wiss. Med), 1870;37:300–302. Frost SB, Barbay S, Friel KM, Plautz EJ, Nudo RJ. Reorganization of remote cortical regions after ischemic brain injury: a potential substrate for stroke recovery. J Neurophysiol, 2003;89:3205-3214.

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

Rehabilitation After Stroke Using Brain-Computer-Interfaces…

115

Fuchs T, Birbaumer N, Lutzenberger W, Gruzelier JH, Kaiser J. Neurofeedback training for attention-deficit/hyperactivity disorder in children: a comparison with methylphenidate. Applied Psychophysiology and Biofeedback, 2003;28:1-12. Gastaut H. Electrocorticographic study of the reactivity of rolandic rhythm. Review neurologique (Paris), 1952;87:176-182. Gastaut H, Terzian H & Gastaut Y. Study of a little electroencephalographic activity: rolandic arched rhythm. Marseille medical, 1952;89:296-310. Giacobbe P, Kennedy SH.. Deep brain stimulation for treatment-resistant depression: a psychiatric perspective. Curr Psychiatry Rep, 2006;8:437-444. Greenberg BD, Malone DA, Friehs GM, Rezai AR, Kubu CS, Malloy PF, Salloway SP, Okun MS, Goodman WK, Rasmussen SA. Three-year outcomes in deep brain stimulation for highly resistant obsessive-compulsive disorder. Neuropsychopharmacology, 2006;31:2384-2393. Henderson JM, Lad SP. Motor cortex stimulation and neuropathic facial pain. Neurosurg Focus. 2006;21:E6. Hesse S, Werner C, Schonhardt EM, Bardeleben A, Jenrich W, Kirker SG. Combined transcranial direct current stimulation and robot-assisted arm training in subacute stroke patients: a pilot study. Restor Neurol Neurosci, 2007;25:9-15. Hinterberger T, Veit R, Wilhelm B, Weiskopf N, Vatine JJ & Birbaumer N. Neuronal Mechanisms underlying control of a brain-computer-interface. European Journal of Neuroscience, 2005;21:3169-3181. Hinterberger T, Widman G, Lal TN, Hill J, Tangermann M, Rosenstiel W, Schölkopf B, Elger C, Birbaumer N. Voluntary brain regulation and communication with electrocorticogram signals. Epilepsy Behav. 2008;13:300-306. Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A., Chen D, Penn RD & Donoghue JP. Neural ensemble control of prosthetic devices by a human with tetraplegia. Nature, 2006;442:164-171 Hoelzl R & Whitehead W.(eds). Psychophysiology of the Gastrointestinal Tract. 1983. Plenum Press, N.Y. Hoffman RE, Gueorguieva R, Hawkins KA, et al. Temporoparietal transcranial magnetic stimulation for auditory hallucinations: safety, efficacy and moderators in a fifty patient sample. Biol Psychiatry, 2005; 58:97–104. Howe RC & Sterman MB. Cortical-subcortical EEG correlates of suppressed motor behavior during sleep and waking in the cat. J. Electroencephalography and Clinical Neurophysiology, 1972;32, 681-695. Hummel F, Celnik P, Giraux P, Floel A, Wu WH, Gerloff C, Cohen LG. Effects of noninvasive cortical stimulation on skilled motor function in chronic stroke. Brain. 2005;128:490-499. Jaillard A, Martin CD, Garambois K, Lebas JF, Hommel M. Vicarious function within the human primary motor cortex? A longitudinal fMRI stroke study. Brain, 2005;128:11221138. Khedr EM, Ahmed MA, Fathy N, Rothwell JC. Therapeutic trial of repetitive transcranial magnetic stimulation after acute ischemic stroke. Neurology, 2005;65:466–468.

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

116

Surjo R. Soekadar, Andrea Caria, Ander Ramos Murguialday, et al.

Koepsell K, Sommer FT. Information transmission in oscillatory neural activity. Biol Cybern, 2008;99:403-416. Kotchoubey B, Strehl U, Uhlmann C, Holzapfel S, König M, Fröscher W, Blankenhorn V, Birbaumer N. Modification of slow cortical potentials in patients with refractory epilepsy: a controlled outcome study. Epilepsia, 2001;42:406-416. Kübler A, Kotchoubey B, Kaiser J, Wolpaw J & Birbaumer N. Brain-computer communication: unlocking the locked-in. Psychological Bulletin, 2001;127:358-375. Kwakkel G, Kollen BJ, van der Grond J & Prevo AJ. Probability of regaining dexterity in the flaccid upper limb: impact of severity of paresis and time since onset in acute stroke. Stroke, 2003:34;2181-2186. Lang N, Siebner HR, Ward NS, Lee L, Nitsche MA, Paulus W, Rothwell JC, Lemon RN, Frackowiak RS. How does transcranial DC stimulation of the primary motor cortex alter regional neuronal activity in the human brain? Eur J Neurosci, 2005;22:495-504. Lefaucheur JP. Transcranial magnetic stimulation in the management of pain. Clin Neurophysiol (Suppl), 2004;57:737–748. Lenhardt A, Kaper M, Ritter HJ. An adaptive P300-based online brain-computer interface. IEEE Trans Neural Syst Rehabil Eng, 2008;16:121–130. Logothetis N, Pauls J, Augath M, Trinath T, Oeltermann A. Neurophysiological investigation of the basis of the fMRI signal. Nature, 2001;412:150-157. Lotze M, Grodd W, Birbaumer N, Erb M, Huse E, Flor H. Does use of a myoelectric prosthesis prevent cortical reorganization and phantom limb pain? Nat Neurosci., 1999;2:501-502. Luft AR, McCombe-Waller S, Whitall J, Forrester LW, Macko R, Sorkin JD, Schulz JB, Goldberg AP, Hanley DF. Repetitive bilateral arm training and motor cortex activation in chronic stroke: a randomized controlled trial. JAMA, 2004;292:1853-1861. Mansur CG, Fregni F, Boggio PS, Riberto M, Gallucci-Neto J, Santos CM, Wagner T, Rigonatti SP, Marcolin MA, Pascual-Leone A. A sham stimulation-controlled trial of rTMS of the unaffected hemisphere in stroke patients. Neurology, 2005;64:1802-1804. Marshall L, Mölle M, Hallschmid M, Born J. Transcranial direct current stimulation during sleep improves declarative memory. J Neurosci. 2004 Nov 3;24(44):9985-9992. McGrady A, Olson P & Kroon J. Biobehavioral treatment of essential hypertension. In M. Schwartz (ed.) Biofeedback. (2nd ed) ,New York: Guilford. 1995. Miller N. Learning of visceral and glandular responses. Science, 1969;163:434-445 Miniussi C, Bonato C, Bignotti S, et al. Repetitive transcranial magnetic simulation (rTMS) at high and low frequency: an efficacious therapy for major drug-resistant depression? Clin Neurophysiol, 2005;116:1062–1071. Monti A, Cogiamanian F, Marceglia S, Ferrucci R, Mameli F, Mrakic-Sposta S, Vergari M, Zago S, Priori A. Improved naming after transcranial direct current stimulation in aphasia. J Neurol Neurosurg Psychiatry, 2008;79:451-453. Murase N, Duque J, Mazzocchio R, Cohen LG. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol, 2004;55:400-409.

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

Rehabilitation After Stroke Using Brain-Computer-Interfaces…

117

Nicolelis MA. Brain-machine interfaces to restore motor function and probe neural circuits. Nature Reviews Neuroscience, 2003;4:417-422. Nitsche MA, Paulus W. Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiol, 2000;527:633-639. Nitsche MA, Liebetanz D, Antal A, Lang N, Tergau F, Paulus W. Modulation of cortical excitability by weak direct current stimulation--technical, safety and functional aspects. Suppl Clin Neurophysiol, 2003;56:255–276. Penfield W, Boldrey E. Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain, 1937;60:389–443. Pfurtscheller G, Müller GR, Pfurtscheller J, Gerner HJ, Rupp R. 'Thought'--control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia. Neurosci Lett, 2003;351:33-36. Pfurtscheller G, Neuper C & Birbaumer N. Human Brain-Computer Interface (BCI). In Alexa Riehle & Eilon Vaadia (Eds.), Motor Cortex in Voluntary Movements. A Distributed System for Distributed Functions (pp. 367-401). Boca Raton: CRC Press. 2005. Plewnia C, Reimold M, Najib A, Reischl G, Plontke SK, Gerloff C. Moderate therapeutic efficacy of positron emission tomography-navigated repetitive transcranial magnetic stimulation for chronic tinnitus: a randomised, controlled pilot study.J Neurol Neurosurg Psychiatry, 2007;78:152-156. Reis J, Schambra HM, Cohen LG, Buch ER, Fritsch B, Zarahn E, Celnik PA, Krakauer JW. Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation. Proc Natl Acad Sci U S A. 2009;106:1590-1595. Rosamond W, Flegal K, Furie K, Go A, Greenlund K, Haase N, Hailpern SM, HoM, Howard V, Kissela B, Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, 'Donnell C, Roger V, Sorlie P, Steinberger J, Thom T, Wilson M, Hong Y: Heart disease and stroke statistics--2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation, 2008;117:e25146. Schalk G, Miller KJ, Anderson NR, Wilson JA, Smyth MD, Ojemann JG, Moran DW, Wolpaw JR, Leuthardt EC. Two-dimensional movement control using electrocorticographic signals in humans. J Neural Eng. 2008;5:75-84. Scheidtmann K. Advances in adjuvant pharmacotherapy for motor rehabilitation: effects of levodopa. Restor Neurol Neurosci, 2004;22:393-398. Scherberger H, Jarvis MR, Andersen RA. Cortical local field potentials encodes movement intentions in the posterior parietal cortex. Neuron, 2005;46:347-354. Schwartz AB. Useful signals from motor cortex. J Physiol, 2007;579:581-601. Sitaram, R., Guan, C., Zhang, H., Thulasidas, M., Hoshi, Y., Ishikawa, A., Shimizu, K., Birbaumer, N. Temporal Classification of Multi-Channel Near Infrared Spectroscopy Signals of Motor Imagery for Developing a Brain-Computer Interface. NeuroImage, 2007;34:1416-1427. Skinner, F. Science and Human Behavior. New York: Macmillan. 1953. Strehl U, Leins U, Goth G, Klinger C, Hinterberger T & Birbaumer N. Self- regulation of slow cortical potentials: a new treatment for children with attention-deficit/hyperactivity disorder. Pediatrics, 2006;118:1530-1540.

Somatosensory Cortex: Roles, Interventions and Traumas : Roles, Interventions and Traumas, Nova Science Publishers, Incorporated, 2009. ProQuest

Copyright © 2009. Nova Science Publishers, Incorporated. All rights reserved.

118

Surjo R. Soekadar, Andrea Caria, Ander Ramos Murguialday, et al.

Sullivan KJ, Knowlton BJ, Dobkin BH. Step training with body weight support: effect of treadmill speed and practice paradigms on poststroke locomotor recovery. Arch Phys Med Rehabil. 2002;83:683-691. Takeuchi N, Tada T, Toshima M, Chuma T, Matsuo Y, Ikoma K. Inhibition of the unaffected motor cortex by 1 Hz repetitive transcranical magnetic stimulation enhances motor performance and training effect of the paretic hand in patients with chronic stroke. J Rehabil Med. 2008;40:298-303. Taub E, Miller NE, Novack TA, Cook EW 3rd, Fleming WC, Nepomuceno CS, Connell JS, Crago JE. Technique to improve chronic motor deficit after stroke. Arch Phys Med Rehabil, 1993;74:347-354. Taub E, Uswatte G, Mark VW, Morris DM. The learned nonuse phenomenon: implications for rehabilitation. Eura Medicophys, 2006;42:241-256. Taylor DM, Tillery SI & Schwartz AB. Direct cortical control of 3D neuroprosthetic devices. Science, 2002;296:1829-1832. Terney D, Chaieb L, Moliadze V, Antal A, Paulus W. Increasing human brain excitability by transcranial high-frequency random noise stimulation. J Neurosci., 2008;28:1414714155. Theodore WH. Transcranial magnetic stimulation in epilepsy. Epilepsy Curr. 2003;3:191– 197. Velliste M, Perel S, Spalding MC, Whitford AS, Schwartz AB. Cortical control of a prosthetic arm for self-feeding. Nature, 2008;453:1098-1101. Wassermann EM. Risk and safety of repetitive transcranial magnetic stimulation: report and suggested guidelines from the International Workshop on the Safety of Repetitive Transcranial Magnetic Stimulation, June 5-7, 1996. Electroencephalogr Clin Neurophysiol, 1998;108:1-16. Weiskopf N, Veit R, Erb M, Mathiak K, Grodd W, Goebel R & Birbaumer N. Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. NeuroImage, 2003;19:577-586. Whitall J, McCombe Waller S, Silver KH, Macko RF. Repetitive bilateral arm training with rhythmic auditory cueing improves motor function in chronic hemiparetic stroke. Stroke, 2000;31:2390-2395. Wolf SL, Winstein CJ, Miller JP, Taub E, Uswatte G, Morris D, Giuliani C, Light KE, Nichols-Larsen D; EXCITE Investigators. Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA, 2006;296:2095-2104. Wolpaw JR, Birbaumer N, Heetderks WJ, McFarland DJ, Peckham PH, Schalk G, Donchin E, Quatrano LA, Robinson CJ and Vaughan TM. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng, 2000:8:164-173. Wolpaw JR & McFarland DJ. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Science USA, 2004;101:17849-17854. Wolpaw JR. Brain-computer interfaces as new brain output pathways. J Physiol, 2007;579:613-619.

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Rehabilitation After Stroke Using Brain-Computer-Interfaces…

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World Health Organization, The World Health Report 2003: shaping the furure. Geneva: World Health Organization, 2003. Yoo SS, Fairneny T, Chen NK, Choo SE, Panych LP, Park H, Lee SY, Jolesz FA. Braincomputer interface using fMRI: spatial navigation by thoughts. Neuroreport, 2004;15:1591-1595. Ziemann U, Meintzschel F, Korchounov A, Ilić TV. Pharmacological modulation of plasticity in the human motor cortex. Neurorehabil Neural Repair, 2006;20:243-251.

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In: Somatosensory Cortex: Roles, Interventions and Traumas ISBN 978-1-60741-876-4 Editor: Niels Johnsen and Rolf Agerskov © 2008 Nova Science Publishers, Inc.

Chapter 6

Mechanisms of Epileptogenesis in the Somatosensory Cortex in Rats with Genetic Absence Epilepsy Evgenia Yu. Sitnikova Institute of Higher Nervous Activity and Neurophysiology, Moscow, Russian Federation

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Abstract The primary somatosensory cortex (SmI) is known to be implicated in the pathogenesis of absence epilepsy, as it has been demonstrated in rodent strains with a genetic predisposition to this disease. The current Chapter provides some data in favor to the ‘cortical focus theory’ of absence epilepsy [Meeren et al., 2002; Meeren et al., 2005], that considers the area of perioral projections in the SmI as a trigger zone of absence seizures (epileptic focus). Our study focuses onto the neuronal mechanisms which are responsible for involvement of the SmI in the pathogenesis of absence epilepsy. Electroencephalographic investigations in vivo and histological (microscopic) analysis of cortical tissue were performed in a WAG/Rij rat genetic model of absence epilepsy. It is found that epileptic discharges appear in the cortex as a result of functional disorder, i.e., due to too strong synchronization between neurons in the SmI and surrounding areas. Our data confirm that some microanatomical disorder in the neocortex (such as a cellular disorganization and changes in neuron-glia ratio) can lead to cortical dysfunction and thus promote development of epileptic activity. In general, a complex functional and microstructural impairment of the SmI may result in a serious neurological disorder, namely, absence epilepsy.

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122

Evgenia Yu. Sitnikova

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Introduction Absence epilepsy is a non-convulsive generalized type of epilepsy which is characterized by a brief impairment of consciousness with minimal myoclonic jerks of eyes and perioral automatisms and associated with 2-4 Hz spike-wave complexes in the electroencephalogram (EEG) [Panayiotopoulos, 1999]. Some inbred rodent strains, such as GAERS (Genetic Absence Epilepsy Rats from Strasbourg) and WAG/Rij (Wistar Albino Glaxo from Rijswijk) [Coenen and van Luijtelaar, 2003; Depaulis and van Luijtelaar, 2006], have a genetic predisposition to absence epilepsy. Both rat strains exhibit characteristic spike-wave discharges (SWDs) in their EEG. Behavioral expression of SWDs in these rats, e.g., immobility, minimal facial myoclonic jerks and twitches [van Luijtelaar and Coenen, 1986; Marescaux et al., 1992], are similar to the clinical manifestation of absence seizures in humans. Also EEG profile of SWDs in epileptic rats and in human patients are comparable [Bosnyakova et al., 2007; Sitnikova and Luijtelaar, 2007]. WAG/Rij rats are used as a reliable model of absence epilepsy in various fields neuroscience and related disciplines, such as pharmacology [van Luijtelaar, 1997; Bouwman et al., 2007], EEG [Bosnyakova et al., 2007; Sitnikova and Luijtelaar, 2007; Sitnikova et al., 2008], basic neurophysiology [van Luijtelaar and Bikbaev, 2007; Tolmacheva and van Luijtelaar, 2007; D’Antuono, 2006], behavioral investigations [Sarkisova et al., 2008] etc. In the current chapter, we use data obtained in WAG/Rij rats in order to highlight the role of the somatosensory cortex (SmI) in the pathogenesis of absence epilepsy. It is remarkable that some physiological and anatomical features in rodent brain fundamentally differ from that in human and feline brains (earlier theories of generalized epilepsies were grounded on neurophysiological studies in cats). The frequency of SWDs in rats is 7–11 Hz [van Luijtelaar and Coenen, 1986; Coenen and van Luijtelaar, 2003], but in cats, it is 3-4.5 Hz and about the same to 2.5-4 Hz in humans. In humans and also in cats, GABA-ergic inhibitory interneurons are present throughout the thalamus, including relay nuclei, but in rats, inhibitory interneurons are absent in thalamus, except the lateral geniculate nucleus and reticular thalamic nucleus [Jones, 1985, Ohara et al., 1983]. In rodents, the vast majority of thalamic nuclei receive only external inhibitory inputs from the RTN, while intrinsic inhibition is absent in the largest part of the thalamus. SWDs are known be produced in thalamo-cortical network; the cortex and the thalamus are both involved in the pathogenesis of absence seizures (Table 1). According to a classical ‘cortico-reticular’ theory of absence epilepsy of P. Gloor [Gloor et al., 1979; 1990; Kostopoulos, 2000], cortical hyperexcitability is the prime course of spike-wave seizures. A global role of the cortex in absence epilepsy was demonstrated in GAERS by means of spreading depression technique [Vergnes and Marescaux, 1992]. In particular, unilateral application of KCl onto the cortical surface deactivated neocortical activity and blocked the occurrence of SWDs in the injected hemisphere, but SWDs were still present in the untreated side both in the cortex and the thalamus. Early studies in GAERS [Marescaux et al., 1992] and WAG/Rij rats [Inoue et al., 1993] have shown that SWDs have a thalamic origin, although they are well expressed in the cortex. Large electrolytic lesions in the lateral thalamus are known to suppress SWDs in GAERS [Avanzini et al., 2000]. In opposite, studies in other animal models have demonstrated that SWDs have a cortical origin (in

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WAG/Rij rats [Meeren et al., 2002; Sitnikova and van Luijtelaar, 2004]). It seems that the local neocortical networks comprise a minimal substrate to produce spike-and-wave paroxysms (in cats [Steriade and Contreras, 1998; Steriade, 2005], in WAG/Rij rats [Sitnikova and van Luijtelaar, 2006]. Table 1. The role of the cortex and the thalamus in pathogenesis of absence seizures Thalamus

Cortex

References Spike-and-wave seizures are depressed after thalamic lesions or pharmacological inactivation of the thalamus.

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Cortical and thalamic cells exhibit prolonged firing in phase with the ‘spike’ component in EEG and silent during the EEG-‘wave’. Spindle oscillations, which are generated by thalamic neuronal circuits, can be gradually transformed into spikeand-wave discharges. Manipulations that promote or antagonize spindles also affect spike-and-wave seizures. Knock-out mice lacking the gene for the T-type calcium current in thalamic relay cells display a resistance to absence seizures. This suggests that bursting activity in thalamic cells mediated by T-type current is responsible for spikewave seizures.

References A form of spike-andwave activity can still be present in the cortex after thalamic inactivation or thalamectomy.

Pellegrini et al., 1979; Steriade and Contreras, 1998

During spike-andwave occuring in the seizures cortex, majority of thalamic neurons are steadily hyperpolarized and completely silent.

Steriade and Contreras, 1995; Pinault et al., 1998

Steriade et al. 1994; Avoli and Gloor, 1982; Kostopoulos, 2000; van Luijtelaar, 1997; see also refs in Destexhe and Sejnowski 2001.

The threshold for epileptogenesis was much lower in the cortex compared to the thalamus.

Steriade and Contreras, 1998

Kim et al., 2001.

Injections of high doses of GABAA antagonists (penicillin or bicuculline) into the cortex resulted in spike-and-wave seizures.

Gloor et al., 1979; Steriade and Contreras, 1998

Pellegrini et al., 1979; Avoli and Gloor, 1982; Vergnes and Marescaux, 1992 Pollen, 1964; Steriade, 1974; Avoli et al., 1983; Buzsaki et al., 1988; Inoue et al., 1993; Seidenbecher et al., 1998.

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Cited by Sitnikova, 2008.

It is essential that the above-mentioned early theories considered the cortex ‘as a whole’, but overlooked functional distinctions between different areas of neocortex. Recent outcomes of the nonlinear association analysis of SWDs in WAG/Rij rats indicated that cortical regions differ in respect to the epileptogenesis. In epileptic rats, the region of perioral projections in the somatosensory cortex (vibrissae and lips) is found to be a primary epileptic focus of seizure activity [Meeren et al., 2002]. It appeared that, being initiated in the perioral area in the SmI, seizure spreads throughout the cortex and, after a few milliseconds delay, enters the thalamus. This means that the thalamus was only secondarily involved in SWDs [Meeren et al., 2002; 2005]. In rodents, the area of perioral projections in the SmI is a central part of the vibrissal trigeminal system. This area has unique functional and anatomic features that may encourage occurrence of epileptic discharges. The present chapter stays in line with the new ‘cortical focus’ theory of generalized absence seizures [Meeren et al., 2002; Meeren et al., 2005] and it is mainly focused on local cortical mechanisms of absence epilepsy in WAG/Rij rats. The first section demonstrates the effect of the local deactivation of the epileptic focus in the SmI on the incidence of SWDs [see also Sitnikova and van Luijtelaar, 2004]. The second section shows that this epileptic zone in WAG/Rij rats is characterized by a remarkable cytoachitectonical disorder [Karpova et al., 2005]. The third section describes network mechanisms of SWDs, i.e., interactions between the SmI and functionally related regions in parietal and frontal cortex at seizure onset.

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1. Somatosensory Cortex Contains Epileptic Focus of Absence Seizures In 2002, Meeren and co-workers introduced a ‘cortical focus theory of absence epilepsy’ by demonstrating that absence seizures in WAG/Rij rats are triggered by the SmI. These authors apply non-linear association EEG analysis SWDs first appear in the SmI and then spread to other cortical regions and to the thalamus. Therefore, the thalamus is only secondarily involved in EEG seizure activity [Meeren et al., 2002; 2005]. This ‘cortical focus theory’ is further supported by clinical neurophysiologists, who noted that spike-and-wave seizures are not fully generalized [Holmes et al., 2004; Craiu et al., 2006]. Before that, Seidenbecher and co-workers (1998) have already mentioned that the SmI plays an important role in absence epilepsy in GAERS: (1) precursor activity (or ‘embryonic’ SW-seizures) could be recorded in cortical and thalamic units before the paroxysm could be evident in the gross EEG; (2) spike-concurrent component of SWDs was associated with rhythmic bursting activity in (mono-)synaptically connected regions in the SmI (layers IV/V), in the specific (somatosensory) thalamic regions and in the reticular thalamic nucleus. Interestingly that SWD-related activity in layers IV/V of the SmI started significantly earlier than the related burst firing in the reticular and ventrobasal thalamic neurons [Seidenbecher et al., 1998]. Widespread networks of neocortical neurons might be the exclusive pacemakers for some EEG rhythms. First, some cortical neurons are endowed with intrinsic abilities for the generation and synchronization of self-sustained oscillations in frequencies of 5 - 12 Hz

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[Silva et al., 1991]. Pyramidal neurons in deep cortical layers could fire in intrinsically bursting mode independently from thalamus with rhythmic recurrent spike bursts of 5-10 Hz thus producing rhythmic oscillations in the frequency of SWDs [Connors and Gutnick, 1990; Flint and Connors, 1996; Drinkenburg et al., 1993]. Second, pyramidal cells and inhibitory interneurons are capable to synchronize their bursting activity and oscillate, thus comprising ordinary oscillatory networks [Fellous et al., 2001]. Third, cortico-thalamic neurons (mostly pyramidal cells in layer VI) could effectively control thalamic activity [Deschênes et al., 1998]; it is noteworthy that descending cortico-thalamic projections are several times more intensive then ascending thalamo-cortical ones [Rouiller and Welker, 2000]. The pyramidal neurons of layers V-VI send projections to various subcortical areas. These projection pathways mediate spreading of seizure activity throughout the brain [Deschênes et al., 1998]. The primary somatosensory cortex is known to be implicated in top-down modulation of sensory processing of tactile information [Nicolelis, 2005]. Rodents obtain sensory information about location and texture of external objects using rhythmic movements of their facial whiskers (i.e. vibrissae1). Movements of vibrissae consist of rhythmical protraction and retraction of vibrissae with a frequency of 7 - 12 Hz or ‘whisker twitching’ [Ahissar et al., 1997; Kleinfield et al., 1999]. The whisker twitching movements are triggered by synchronous 7–12 Hz oscillations, which are initiated by the SmI and latter spreads to the thalamus, so-called ‘somatosensory rhythm’ [Nicolelis et al., 1995; Nicolelis and Fanselow, 2002]. It is important that ‘SmI plays a much bigger role in driving activity in the thalamus during whisker twitching than it does during other states’ [Fanselow et al, 2001, p.15334]. It is also known that 7–12 Hz somatosensory rhythm can either be blocked by local lesions in SmI or by local injections of muscimol (GABAA agonist) into the vibrissal region of the SmI [Nicolelis and Fanselow, 2002]. In WAG/Rij and GAERS rat strains absence epilepsy is known to be associated with genetically predetermined impairment of membrane and neuronal mechanisms, including serious disturbances in protein and enzyme synthesis, in properties of ion channels and membrane, as well in neurotransmission and neuromodulation [Coenen and van Luijtelaar, 2003]. We hypothesized that in these animals, 7-12 Hz somatosensory rhythm could be transformed in hypersynchronous high-voltage epileptic discharges ~10 Hz and could be recorded in EEG as SWDs [Sitnikova, van Luijtelaar, 2004; van Luijtelaar and Sitnikova, 2007; Sitnikova, 2008]. It is known that albino rats are more predisposed to absence epilepsy as compared to other rat strains (hooded, brown and agouti rats) [Inoue et al., 1990]. The albino gene also associates with poor visual abilities. Deficit of visual information could be compensated by reinforcing the other sensory systems, for instance, vibrissal system. It needs to be emphasized that ‘7-12 Hz oscillations alone cannot lead to seizure activity. Instead, genetic manipulations (like those resulting from successive inbreeding) are required to make epileptic activity to emerge’ [Wiest and Nicolelis 2003, p. 914]. Altogether suggests that intrinsic oscillatory activity in the somatosensory cortex might encourage epileptic discharges and promote epileptic seizure state.

1

Vibrissae (‘whiskers’, macrovibrissae) are the long hairs that protrude from the mystacial pad. Vibrissae are used to palpate objects.

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Figure 1. EEG tracks recorded epidurally in different cortical loci after local intracortical microinjections of 2% and 4% lidocaine. The tip of cannula was very close to the channel named ‘injected site’ (distance between them was 2 mm). A. Local cortical deactivation after microinjection of 2% lidocaine resulted in diminishing seizure activity. EEG pattern of spike-wave activity became irregular, and ‘spiky oscillations’ were often seen instead of SWDs. B. Microinjection of 4% lidocaine enhanced generalized seizure activity (incidence of SWDs was increased), and had a local effect in ‘injected site’ (spiking activity, which is asterisked).

We examined the role of the SmI in the incidence of absence seizures by means of reversible deactivation of this epileptogenic zone with microdoses of lidocaine [Sitnikova and van Luijtelaar, 2004]. The drug was injected unilaterally in doses 2% and 4% in 10 male WAG/Rij rats (body weights 370-470 g). Each rat was implanted by a cannula of steel tubing (ID 0.5 mm, OD 1.0 mm) under the right SmI (AP –2; L 7) to enable the needle penetration for injections as deep as 1.5 mm. Stainless steel electrodes (Plastic One, MS 303/1) were used to record EEG at the cortical surface symmetrically in the frontal cortex (AP 2; L +/-3), in the right SmI (at the close vicinity to cannula, AP 0; L 7) and in the right occipital cortex (AP -6;

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L 4). EEG was recorded monopolarly with ground and reference electrodes symmetrically over the two sides of cerebellum. Distances between the tip of cannula and active electrodes are given in Table 2. Table 2. Mean distances between the tip of cannula and active electrodes

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SmI, epileptic zone (close to the injected site) Frontal left (intact hemisphere) Frontal (injected hemisphere) Occipital cortex

distance from cannula, mm 1.2 – 2.0 2.2 – 3.5 6.2 – 7.0 7.8 – 8.8

It is found that injections of 2% lidocaine resulted in a significant decrease of EEG total power in the SmI at the close vicinity of the injected site. During passive wakefulness a decrease in EEG power was significant in 8-30 Hz. During SWDs a decrease in power was found in 0.5-4 Hz and 8-100 Hz (data are not shown). No changes in EEG power were found in the frontal EEG, suggesting that deactivation was rather local. Sham microinjection (saline) did not affect overall EEG waveform, nor the pattern of SWDs. After microinjection of 2% lidocaine, EEG pattern of SWDs became irregular (Figure 1A); spiky oscillations appeared in different EEG channels independently from each other. These irregular oscillations no longer meet the criteria for SWDs, they were not recognized by the automatic system as SWDs and were not counted. The incidence of SWDs significantly reduced after 2% lidocaine injections as compared to control (Figure 2). The number of SWDs per hour significantly reduced after 2% lidocaine microinjections. Sharp difference in the number of SWDs after 2% lidocaine and shame injections is getting smaller over time and it tends to diminish at the end of the first post-injection hour.

Figure 2. The effects of local microinjections of lidocaine in concentration 2% and 4% in the incidence of SWDs.

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Local administration of 4% lidocaine in three out of seven animals resulted in occurrence of local spikes in EEG, as recorded at the close vicinity to the injected site in the SmI (Figure 1B); in other four animals EEG waveform was unchanged. The number of SWDs significantly increased after 4% lidocaine injection (Fig 2). Most likely, microinjection of 4% lidocaine irritates epileptic focus in the SmI. This increases the incidence of generalized SWDs and brings about focal epileptic discharges in some animals.

2. Somatosensory Cortex is Involved in Local Neuronal Circuit Producing Absence Seizures

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Visual inspection of cortical field potential recorded during SWDs revealed polyspiking events and fast ripple components in frontal and parietal areas [Sitnikova and van Luijtelaar, 2007]. These fast transient EEG events are likely to be associated with epilepogenic processes that accompany initiation of epileptic discharges [Sitnikova, 2008]. It was hypothesized that fast EEG components during initial state of spike-wave seizures could manifest dysfunction of the somatosensory cortex, as well as epileptogenic processes in the somatosensory cortex and its closest neighborhood.

Figure 3. Сortico-cortical EEG coherence as measured at the onset of SWDs in WAG/Rij rats. Graphs in the right show group average of EEG coherence spectra in differential scores (ΔCoh). ΔCoh is computed as a ratio between EEG coherence values obtained in a period 1 sec before the onset of SWDs [Coh(preSWD)] versus 1 sec after the onset of epileptic discharges, Coh(SWD).

We obtained some evidences in favor to this hypothesis by elucidating epileptic synchronization processes within intracortical network during early stage of absence seizures [Sitnikova and van Luijtelaar, 2006]. For that purpose, linear associations (coherence) are measured between thalamic and cortical regions immediately before SWDs and during the first second of seizure activity. It was found that the onset of SWDs was associated with an

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increased coherence in frequencies 5 - 60 Hz with two maxima around 10 and 20 Hz. The frequency of two maxima corresponds with the mean frequency of SWDs (8-11.5 Hz) and its harmonic 16-21.5 Hz. The projection area of vibrissae, SmI(vib), specifically associated with adjacent area of limb projections and with frontal cortex. These associations were characterized by a consistent increase of synchrony in a broad frequency window, including all frequencies from delta to gamma band. This might imply that minimal neuronal oscillatory circuit, which is primary involved in the initiation of SWDs, comprises vibrissal and limb projection areas in the SmI and the frontal cortex (Figure 3). From our EEG coherence study [Sitnikova and van Luijtelaar, 2007] it is also followed that absence seizures are underlaid by a very complex changes of neuronal synchronization between different parts of thalamo-cortical network. We distinguished at least five interacting resonant circuits, and each circuit was characterized by peculiar pattern of network synchronization. • • •

•

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•

Local cortico-cortical networks with the highest coherence (maximum in 21.3 Hz) were thought to be responsible for the initiation of SWDs. Non-local cortical networks, in which coherence was moderate (maximum in 19.3 Hz), were likely to be involved in unilateral spreading of seizure activity. In trans-hemispheric networks, coherence was very high and revealed an additional maximum in 15.8 Hz. These networks could be responsible for bilateral propagation and synchronization of seizure activity. Intra-thalamic networks showed moderate synchronization in 9.5 Hz; and seemed to just passively maintain major seizure rhythm. Thalamo-cortical networks are likely to be involved in synchronizing rhythmic activity in cortex and thalamus, i.e., reinforce resonant thalamo-cortical oscillations.

It is striking that frontal cortex and SmI displayed the most broad-band increase of coherence (5-60 Hz, including gamma frequencies) at the onset of absence seizures. Therefore, the fast transients in EEG may result form too strong synchronization in local cortical networks (that include the SmI and the frontal cortex), but the thalamus is scarcely involved. Altogether, in epileptic rats, network associations in somatosensory part of thalamocortical system seem to be impaired [Sitnikova and van Luijtelaar, 2006], and this may imply that absence epilepsy also correlates with a deficiency of sensory mechanisms that control processing of somatosensory information. Indeed, it is known that WAG/Rij rats could not perceive information during SWDs [Meeren et al., 1998; Inoue et al., 1993]. Also human patients become irresponsive to external stimuli during absence seizures. It has been assumed [Yamauchi, 1998] that in humans responsiveness is mostly altered when the wave-component in spike-wave discharge reaches its maximum2, i.e., when the entire cortex is deeply inhibited. In all, functional abilities of cortical cells during absence seizures are severely impaired, sensory perception is disturbed and this causes an abrupt impairment of consciousness (clinical/behavioral manifestation of absence epilepsy). 2

The wave in SWDs represents neuronal inhibition.

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3. Cytoarchitectural Disorder in the Somatosensory Cortex Correlates with Absence Epilepsy In animal models of absence epilepsy, the cellular structure of cortical tissue is almost unexplored. In a pioneering study, Karpova and co-workers (2005) have compared the cytoarchitecture of pyramidal cells in superficial cortical layers (I–III) in the somatosensory and motor areas in epileptic WAG/Rij and control ACI3 rats. The authors examined two zones: (1) an ‘epileptic zone’ of vibrissal projections in the SmI and (2) a ‘non-epileptic zone’ - the area of hind limb projections in the SmI and the motor area in the frontal cortex. In both rat strains, neurons in the ‘epileptic zone’ are characterized by an increased branching (as revealed by the three parameters: the number of free terminals, the number of branching points and the number of dendritic segments). These differences in branching parameters of neurons can be accounted for the regional and functional differences between the investigated zones irrespectively of epileptic processes. It is important that atypically oriented pyramidal neurons are present in the ‘epileptic zone’ in WAG/Rij rats. Apical dendrites of these cells are obliquely oriented, often split in two branches; cellular bodies are localized outside the layer boundaries. Unfortunately, the authors do not explain this phenomenon; yet disorientation and atypical morphology of pyramidal cells may correlate with the epileptic activity and can be accounted for at least two factors:

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•

•

An early disorder of migration. As known, during prenatal life, when pyramidal cells migrate from the ventricular zone to their final target region, they extend their apical dendrites towards radial glial fibers. In such a way, pyramids acquire the final orientation perpendicular to cortical surface [Miller, 1988]. Orientation of pyramidal cells does not change after the end of migration. Atypical orientation of pyramidal cells may result from an impairment of neuro-glial interactions during the earliest stages of development (probably, genetically determined). A disorder of maturation. Apical dendrites of pyramidal neurons ascend to the superficial plexiform layer, where they make synaptic contacts with neuromodulatory afferents (mostly, noradrenaline- and serotonine-ergic). This neuromodulatory supply is necessary for the normal maturation of neuronal cells [Raevsky, 1995]. In WAG/Rij rats, neuromodulatory mechanisms might be impaired, and this might encourage disorientation of apical dendrites of pyramids in superficial cortical layers.

Another important finding of Karpova et al. (2005) is that pyramid cells in the ‘epileptic zone’ in WAG/Rij rats differ from analogous cells in ACI rats: they have longer dendritic segments and a larger radius of dendritic area. These findings can be interpreted as consequences of epileptic processes in this zone, which are responsible for triggering of seizure activity. An average area of synaptic contacts in epileptic animals is expanded by

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lengthening of dendritic segments and increasing radius of dendritic trees. Therefore, each neuron makes may have more synaptic contacts and may be involved in more widespread neuronal networks. This may facilitate spreading of seizure across ‘epileptic zone’. Altogether, microanatomy of pyramidal neurons in the neocortex in WAG/Rij rats is somewhat abnormal. Alteration of dendrite’s geometry may result to an impairment of interactions between individual neurons. As known, pyramidal cells of superficial layers are the source of long-range projections to remote cortical regions, thus the former nay be involved in synchronization of intrinsic cortical oscillations [Gray and McCormick, 1996]. Therefore, associations between the prime epileptic zone in the perioral area in the SmI and other cortical areas may be changed in a way that facilitates synchronization, propagation and generalization of SWDs. Recently, we have examined the microanatomy of the neocortex in epileptic WAG/Rij rats and compared it with healthy control animals (ACI rats). Brain slices (thickness 20 μm) were studied in five male WAG/Rij rats and five male ACI rats in the age of six months. Slices were stained with Nissl and inspected under light microscope. Quantitative microscopic analysis was performed in vibrissal area in the SmI (S1BF, according to atlas of rat brain [Paxinos and Watson, 1986]). Microphotographs were taken using a Nikon Eclipse E200 microscope and Canon F640 camera. Cytoarchitecture of cortical tissue was first investigated using low magnification (4x objective). The most sharp differences between epileptic WAG/Rij rats and healthy control rats were found in layer V (Figure 4).

Figure 4. Microphotographs of Nissl-stained slices (20 μm thickness) in the area of barrelfield in the SmI (S1BF). All microphotographs were taken in different individuals. Left insertion indicate zone topography as determined by Atlas of Rat Brain [Paxinos and Watson, 1986]. Noteworthy, layer V is well pronounced in control animals, but it is less well recognized in WAG/Rij rats. Zoomed areas from layer V demonstrate that large pyramid cells in WAG/Rij rats are purely stained and their size is smaller as compared to control animals.

3

Agouti Copenhagen Irish rats, commonly used as a control strain since these rats showed no or at least very few SWDs in a comparative strain study [Inoue et al., 1993].

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It was found that layer V is well defined in non-epileptic ACI rats and it was poorly pronounced in epileptic WAG/Rij rats. With a closer look in cellular content in layer V with a higher magnification (Figure 4, corresponding areas in layer V are zoomed), we found that large pyramid cells in WAG/Rij rats were of smaller size and they were poorly stained as compared to that in control animals. Abovementioned local disturbances in the size and staining pattern of pyramidal cells in layer V in WAG/Rij rats are likely to result from early developmental disorder (i.e., a disorder of maturation of neuronal cells). It is known that cellular morphogenesis is mainly takes place during first postnatal weeks, when neuronal cells are rapidly growing up and differentiating. This process is controlled by neuromodulatory systems (mainly by catecholamines: noradrenalin, serotonin and dopamin) [Raevsky, 1991]. Development of absence seizures in WAG/Rij rats and in other rat strains (GAERS, APO-SUS rats) are known to correlate with a deficiency of dopamine- and noradrenalin-ergic neurotransmission [Midzyanovskaya, 2006; De Bruin, 2000; Birioukova, 2005]. We hypothesize that abnormal cytoarchitecture in layer V in WAG/Rij rats is caused by an impairment of catecholaminergic neurotransmission during early ontogenesis. This problem is worth studying in the future. On the basis of microscopic analysis at higher magnification, some further details of cellular microstructure could be added. Here we focused in the superficial and deep layers in the SmI (a, b in Figure 5). In particular, in differences between epileptic and non-epileptic rat strains in respect to the quantitative properties in a population of neuronal and glial cells. In microphotographs, which were taken using 40x objective lens, neuronal and glial cells were recognized and computed in square fields (50x50 μm). Two fields per layer and per rat were analyzed (in total, 207 microphotographs and 414 fields in ten rats). In microphotographs, neurons were distinguished from glial cells by their size, morphology and staining pattern (Figure 6). The first criterion was intensity of a cresyl violet stained cytoplasm. Glial cells were identified by the absence of stained cytoplasm, while neurons revealed more heterogeneous cytoplasmic staining pattern (Nissl substance). Second criterion was staining pattern of a nucleus and a nucleolus. Neurons were characterized by a dark nucleolus within a lightly stained nucleus. Nucleolus in glial cells was absent. Glial cells were identified by the presence of dark nucleus and thick nuclear membrane. Neurons were distinguished by a darkly stained cytoplasm, even if their nucleus and nucleolus were not clearly distinguishable. Statistical data analysis indicated that a population of glial cells in the SmI was impaired in epileptic rats as compared to control ACI rats (Figure 6). WAG/Rij rats were characterized by a low density of glial cells [ANOVA of the ‘strain’ effect for two levels (WAG/Rij and ACI): F(1;246) = 19.5; p