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i

MEG–​EEG PRIMER

ii

iii

MEG–​EEG PRIMER SECOND EDITION

Riitta Hari, MD, PhD Professor Emerita of Systems Neuroscience and Neuroimaging Department of Art and Media Aalto University Espoo, Finland

Aina Puce, PhD Eleanor Cox Riggs Professor in Social Justice and Ethics Department of Psychological & Brain Sciences Indiana University Bloomington, IN, USA

iv

Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and certain other countries.

Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America. © Oxford University Press 2023 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by license, or under terms agreed with the appropriate reproduction rights organization. Inquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above.

You must not circulate this work in any other form and you must impose this same condition on any acquirer.

Library of Congress Cataloging-​in-​Publication Data Names: Hari, Riitta, author. | Puce, Aina, author.

Title: MEG–EEG Primer 2nd Ed./by Riitta Hari and Aina Puce.

Description: New York, NY: Oxford University Press, [2023] | Includes bibliographical references and index.

Identifiers: LCCN 2016039489 | ISBN 9780197542187 (alk. paper) Subjects: | MESH: Magnetoencephalography—methods | Electroencephalography—methods | Brain—physiology | Brain Mapping | Brain Diseases—diagnosis Classification: LCC RC386.6.M36 | NLM WL 141.5.M24 | DDC 616.8/047548—dc23 LC record available at https://lccn.loc.gov/2016039489 DOI: 10.1093/​med/​9780197542187.001.0001 This material is not intended to be, and should not be considered, a substitute for medical or other professional advice.

Treatment for the conditions described in this material is highly dependent on the individual circumstances. And, while this material is designed to offer accurate information with respect to the subject matter covered and to be current as of the time it was written, research and knowledge about medical and health issues are constantly evolving and dose schedules for medications are being revised continually, with new side effects recognized and accounted for regularly.

Readers must therefore always check the product information and clinical procedures with the most up-to-date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulation. The publisher and the authors make no representations or warranties to readers, express or implied, as to the accuracy or completeness of this material. Without limiting the foregoing, the publisher and the authors make no representations or warranties as to the accuracy or efficacy of the drug dosages mentioned in the material. The authors and the publisher do not accept, and expressly disclaim, any responsibility for any liability, loss, or risk that may be claimed or incurred as a consequence of the use and/or application of any of the contents of this material.

Printed by Integrated Books International, United States of America

v

CONTENTS Preface to the Second Edition

xv

Preface to the First Edition

xvii

About the Authors

xix

Preamble

xxi

■ SECTION 1

1. Introduction

3

MEG and EEG Setups

3

Comparison of MEG and EEG

7

Structure of This Primer

12

References

12

2. Insights into the Human Brain

13

Overview of the Human Brain

13

How to Obtain Information about Brain Function

14

Timing in Human Behavior

14

Functional Structure of the Human Cerebral Cortex

15

Cerebellum

17

Communication Between Brain Areas Thalamocortical Connections Intrabrain Connectivity

18 18 18

Electric Signaling in Neurons Membrane Potentials Action Potentials Postsynaptic Potentials

19 21 21 23

References

24 ■ v

vi

vi ■ Contents

3. Basic Physics and Physiology of MEG and EEG

27

An Overview of MEG and EEG Signal Generation

27

Charges and Electric Current

28

Ohm’s and Kirchoff ’s Laws

29

Relationship Between Current and Magnetic Field

30

Superconductivity

31

Inverse Problem

32

Source Currents Primary Current Layers, Open Fields, and Closed Fields Intracortical Cancellation Volume Conduction Spherical Head Model

33 33 35 36 36 37

Some General Points about Source Localization

38

References

40

4. An Overview of EEG and MEG

41

Historical Aspects

41

Early EEG Recordings

42

Early MEG Recordings

44

Types of EEG and MEG Signals Brain Rhythms Evoked and Event-​Related Responses

45 45 46

Advantages and Disadvantages of MEG and EEG Advantages Disadvantages

47 48 48

References

49

■ SECTION 2

5. Instrumentation for EEG and MEG EEG Instrumentation Electrodes General Wet Electrodes Dry Electrodes Hybrid or “Semi-​Dry” Electrode Configurations Special Electrodes Electrodes for Invasive Recordings Electrodes for Portable Devices and Brain–​Computer Interfaces

53 53 54 54 55 57 57 58 58 59

vii

Contents ■ vii

ExG Electrodes Electrodes for Ultra-​Slow EEG Signals EEG Amplifiers General Differential Amplifiers and Common-​Mode Rejection Effect of Amplifier Input Impedance on CMRR Maximizing CMRR: Grounding and Special Feedback Circuits DC-​Coupled EEG Amplifiers EEG Amplifiers for Simultaneous Use With Other Neuroimaging Techniques Standard Electrode Positions Reference Electrode Configurations General Effect of Reference Electrode Site on the Measured Potential Distribution Re-​Referencing Relative to an Average Reference

59 61 62 62 63 64 64 65 65 65 68 68 69 72

MEG Instrumentation SQUIDs and SQUID Electronics Flux Transformers and Their Configuration Toward On-​Scalp MEG High-​Tc SQUIDs Optically Pumped Magnetometers

75 75 78 79 79 79

Shielding

80

Other Ways to Maintain a Noise-​Free Environment

82

References

83

6. Devices for Sensory Stimulation and Behavioral Monitoring

88

Stimulators Auditory Stimulators Visual Stimulators Somatosensory Stimulators Stimulators for Inducing Acute Pain Passive-​Movement Stimulators Olfactory and Gustatory Stimulators Olfaction Gustation

88 88 89 90 92 93 94 94 96

Devices for Behavioral Monitoring

96

Phantoms for MEG/​EEG Source Analysis and Artifact Removal

96

References

98

7. Practicalities of Data Collection

100

General Principles of Good Experimentation

100

Replicability Checks

101

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viii ■ Contents

EEG Recordings: The Practice Skin Preparation for Electrode-​Impedance Measurement General Skin Preparation for Electrode Application Electrode-​Impedance Measurement

102 102 102 102 103

MEG Recordings: The Practice

104

Measurement of MEG Sensor and EEG Electrode Positions

106

Infection Control in EEG and MEG Recordings General COVID-​19-​Related Issues

110 110 110

Electrical Safety

112

References

114

8. Data Acquisition, Preprocessing, and Sharing

116

Filtering

116

Data Sampling Rate

122

Simulation of EEG and MEG Data

124

Standardization of Data Formats and Analysis Pipelines for Data Sharing Brain Imaging Data Standard, BIDS A Bird’s-​Eye View of a Standardized Data Set Structure

124 125 125

References

128

9. Artifacts

130

Introduction

130

Some Common Artifact-​Removal Methods Blind Source Separation Signal-​Space Projection and Separation Methods

132 132 135

Eye-​Related Artifacts Eye Movements and Eye Blinks Saccades and Microsaccades Removal of Eye-​Related Artifacts

138 138 141 144

Muscle Artifacts Generation and Recognition Removal of Myogenic Artifacts

148 148 152

Cardiac Artifacts Generation and Recognition Removal of Cardiac Artifacts

155 155 157

Respiration-​Related Artifacts Generation and Recognition Removal of Respiration Artifacts

158 158 159

ix

Contents ■ ix

Sweating Generation and Recognition Removal of Sweating Artifacts

160 160 160

Nonphysiological Artifacts Power-​Line Noise and Its Removal Response-​Box Artifacts Artifacts Related to EEG Electrodes and MEG Sensors EEG Artifacts Caused by fMRI Scanning and Noninvasive Brain Stimulation How to Ensure the Signals Come From the Brain

161 161 164 164

References

167

10. Analyzing the Data

165 166

173

Introduction

173

Data Inspection and Preprocessing

174

Analysis of Averaged Data Evoked Versus Induced Activity Signal-​to-​Noise Considerations Segmentation Amplitude and Latency Measures Topographic Maps

175 175 176 177 177 178

Analysis of Unaveraged Data Brain Microstates MEG/​EEG Signal Level and Power Event-​Related Desynchronization/​Synchronization and Temporal Spectral Evolution Time–​Frequency Analyses Phase Resetting and Models of Evoked Activity Cross-​Frequency Coupling

179 179 180

Measures of Association and Connectivity Functional Connectivity Correlation and Coherence Phase-​Locking Factor, Phase-​Locking Value, and Phase-​Lag Index Mutual Information Transfer Entropy Cross-​Correlation Granger Causality Functional Connectivity: Quo Vadis?

Effective Connectivity Dynamic Causal Modeling Graph-​Theoretical Analysis On the Practicalities of Connectivity Analyses

188 188 189 191 191 192 192 192 193 194 194 194 195

Source Modeling Forward and Inverse Problems in MEG and EEG Head Models Single-​Dipole Model

195 195 196 197

180 181 184 185

x

x ■ Contents

Goodness of Fit and Confidence Limits of the Model Spatial Resolution Source Extent Effect of Synchrony Multidipole Models, Distributed Models, and Beamformers Hypothesis Testing With Predetermined Source Locations

198 199 201 203 204 205

Statistical Considerations Group Effects Whole-​Head Analysis of Evoked Responses MEG Signal Detectability and Statistical Power in Group Studies Effect of Source Current Orientation and Location Sensor Sensitivity, Number of Trials, Group Size, Effect Size, and Statistical Power

205 205 207

Common Pitfalls in Data Analysis and Interpretation

211

References

214

209 209 209

■ SECTION 3

11. Brain Rhythms

223

Introduction

223

Alpha Rhythm of the Posterior Cortex

224

Mu Rhythm of the Sensorimotor Cortex

229

Tau Rhythm of the Auditory Cortex

229

Beta Rhythms

231

Theta Rhythms

233

Gamma Rhythms

233

Delta-​Band Activity and Ultra-​Slow Oscillations

235

Coupling Between Different Brain Rhythms

236

Changes in Brain Rhythms During Sleep

237

Effects of Anesthetics and Other Drugs on EEG/​MEG

241

References

243

12. Evoked and Event-​Related Responses

248

Introduction

248

An Initial Example

250

Nomenclature of Evoked Responses and Brain Rhythms

251

Effects of Interstimulus Interval and Stimulus Timing

254

Effects of Other Stimulus Parameters

256

References

257

xi

Contents ■ xi

13. Auditory Responses

260

Aspects of Auditory Stimulation Hearing Threshold Stimulus Type, Duration, Envelope, and Other Characteristics

260 260 261

Auditory Brainstem Responses

262

Middle-​Latency Auditory-​Evoked Responses

263

Long-​Latency Auditory-​Evoked Responses

264

Auditory Steady-​State Responses

268

Frequency Tagging

271

References

272

14. Visual Responses

275

Introduction

275

Visual Stimuli Visual Acuity Distance and Visual Angle of the Stimulus Foveal, Parafoveal, and Extrafoveal Stimulation Luminance and Contrast Spatial Frequency

276 276 276 276 277 278

Electroretinogram and Magnetoretinogram

279

Visual Evoked Potentials and Fields

279

Multifocal Visual Evoked Responses

282

Assessing the Ventral Visual Stream

286

Assessing the Dorsal Visual Stream

288

Visual Steady-​State Responses

288

Decoding of Visual Categories

290

References

292

15. Somatosensory Responses

296

Compound Action Potentials and Fields of Peripheral Nerves

296

Responses from the SI Cortex

299

Responses from the Posterior Parietal Cortex

305

Responses from the SII Cortex

305

Somatosensory Steady-​State Responses

306

High-​Frequency Oscillations in the SI Cortex

307

Pain and Nociceptive Responses

307

References

310

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16. Other Sensory Responses, Multisensory Interaction, and Interoception

314

Olfactory and Gustatory Responses Olfactory Responses Gustatory Responses

314 315 317

Multisensory Interaction Overview Audiotactile Interaction An MEG Case Study Multisensory Integration During Human Communication Other Types of Multisensory Evoked Responses Models of Multisensory Interaction

317 317 319 320 321 322 324

Interoception Overview Visceral Responses Evoked Responses to Distension of Esophagus, Urethra, and Rectum Spontaneous Contractions of the Stomach and Upper Gut Contractions of the Uterus The Brain–​Heart Axis: Evoked Activity to One’s Own Heartbeat Evoked Activity to One’s Own Respiration

325 325 326

References

331

17. Motor Function

336

326 326 329 329 331

Movement-​Related Readiness Potentials and Fields

336

Coherence Between Brain Activity and Movements/​Muscles Overview Cortex–​Muscle Coherence Corticokinematic Coherence Corticovocal Coherence

339 339 339 342 342

More Complex Motor Actions

343

References

346

18. Brain Signals Related to Change Detection

349

Introduction

349

Contingent Negative Variation

350

Mismatch Negativity and Mismatch Field

352

P300 Responses

355

N400 Responses

357

Error-​Related Negativity

359

References

360

xiii

Contents ■ xiii

19. The Social Brain

364

Theoretical Framework

364

Responses to Emotions Depicted by Faces and Bodies

367

Action Viewing and Mirroring

371

Hyperscanning

375

Verbal Communication

377

References

379

20. Brain Disorders

383

Introduction

383

Epilepsy

384

Preoperative Mapping Functional Identification of the Central Sulcus Anatomical Identification of the Central Sulcus Hemispheric Dominance for Speech and Language

386 387 388 389

Stroke

390

Critically Ill Patients Coma Brain Death

392 392 392

Why Have the Clinical Applications for MEG Developed So Slowly?

392

References

393

21. MEG/​EEG Combined with Other Brain Imaging Methods

397

Combining MEG and EEG

397

Combining MEG/​EEG with MRI/​f MRI

399

EEG During Noninvasive Brain Stimulation

404

Hybrid MEG–​MRI

406

Multiple Methods and the “New Normal”

406

References

406

22. Stepping Back and Looking Forward: Toward Understanding the Human Brain

410

Further Developments of Instrumentation

411

Working with “Big Data” Mining Knowledge From Large Data Sets Biomarkers

412 412 413

New Targets in MEG/​EEG Research Deep Sources

414 414

xiv

xiv ■ Contents

Inhibition More Focus on Developmental and Life-​Span Studies High-​Resolution Assessment of Behavior

Index

417 418 419

Toward Understanding the Human Brain From Micro-​to Macrolevel and Back Living Matter Is Special The Brain as a Nonlinear Timing System

420 420 422 422

Toward Convergence Research

424

Looking Forward

424

References

425 431

xv

PREFACE TO THE SECOND EDITION We are delighted by the interest and positive feedback that the first edition of our Primer received. We are especially gratified that it has been a useful source for training new students, researchers, and faculty entering the field. Our aims in this second edition remain unchanged: to introduce the basic principles of magnetoencephalography (MEG) and electroencephalography (EEG) as tools to noninvasively study human brain dynamics and to generate an integrated understanding of the two techniques.

Over the last 5 years, interest in high-​resolution, time-​sensitive methods has increased rapidly in the whole human brain-​imaging community, requiring us to slightly broaden our scope. We still attempt to provide a solid basis for applying the MEG and EEG methods—​ including the underlying physics and physiology, instrumentation, recording techniques, data analysis, and interpretation—​without comprehensively covering the rapidly expanding literature in this field.

We have made updates to all chapters, especially in Sections 2 and 3. We have expanded text on MEG/​EEG sensor types and amplifiers, artifacts, new analysis tools, open data repositories, and novel instrumentation. Due to a new concern, brought about by the COVID-​19 pandemic, we now discuss general infection control in all MEG/​EEG measurements. Moreover, we now introduce interoception as an interesting emerging research field.

We end with a broader chapter on the future of understanding human brain function to stimulate our readers’ thinking beyond their own research topics.

We have added some citations to both old and new key literature in the field. Some minor errors have been corrected, and the index has been expanded. The second edition is over 100 pages longer than the original and contains 34 totally new illustrations, with small edits to 36 existing figures. Despite the reorganization, we have tried to keep the Primer as close to the original as possible, to serve as the “ABC book” for all researchers interested in immersing themselves into the exciting world of human brain dynamics. Therefore, we recognize that we have omitted important topics and data and have not been able to expand the presentation as much as some of our readers would have liked to (especially regarding anatomy, clinical applications, and some analysis methods). After all, this is a primer that aims to stimulate the reader to search for additional information and hands-​on databases and to embark on the never-​ending adventure of studying the secrets of the human brain.

We cordially thank our colleagues Synnöve Carlson, Matti Hämäläinen, Veikko Jousmäki, Lauri Parkkonen, Ben Ramsden, Jari Saramäki, Samu Taulu, and Koichi Yokosawa for many helpful discussions on various topics in this book. We also received excellent comments from five anonymous reviewers who were invited by the publisher to ■ xv

xvi

xvi ■ P reface to the S econd E dition

read the first edition; we highly appreciate their constructive suggestions. We are especially grateful to two prereaders of our second edition: Juan Avenado (Aalto University, Finland), with his keen eyes, spotted multiple inconsistencies in our text and figures, and Ann-​Sophie Barwich (Indiana University, USA) guided us to improve the text flow. We are also greatly indebted to Peter Molfese and Kami Salibayeva for help in proofreading the Primer.

A huge thank you also to Matt Winter and Kami Salibayeva (Social Neuroscience Lab at Indiana University) for assistance with collection and analysis of ExG data for new figures: together we learned to use our new EEG/​ExG recording system without on-​site technical support during the COVID-​19 lockdown! Matt also provided valuable feedback and comments on isolated sections of our chapters. We thank Satu Ilta for drawing and editing most of the new or revised figures of the second edition. We are also immensely grateful again to the digital librarians at Indiana University Libraries for their continued tenacious sourcing of obscure and almost forgotten manuscripts for this second edition.

We thankfully acknowledge Craig Panner from OUP for his enduring patience and humanity. We have appreciated his continued collaboration and facilitation over the years as he shepherded both editions of our Primer to the publication stage.

When preparing the first edition, we were privileged to interact with Professor Fernando Lopes da Silva (1935–​2019), a pioneer in advocating the importance of combining EEG and MEG methods in the assessment of human brain dynamics. We miss Fernando’s kind support and presence but hope that his legacy will live on in new generations of EEGers and MEGers.

Riitta Hari acknowledges funding from Louis Jeantet Foundation and thanks the Department of Art and Media, Aalto University, Finland, for stimulating working environment for an emerita.

Aina Puce expresses her gratitude to both Eleanor Cox Riggs and also the College of Arts and Sciences at Indiana University (Bloomington) for continued support and funding.

She also acknowledges her wonderful colleagues and students in the Department of Psychological and Brain Sciences, at Indiana University.

xvii

PREFACE TO THE FIRST EDITION The aim of this primer is to provide an introduction to the basic principles of magnetoencephalography (MEG) and electroencephalography (EEG). MEG and EEG are time-​ sensitive methods that allow the noninvasive study of human brain activity. We target our message to beginning and intermediate users of MEG/​EEG, assuming that most readers will be graduate students or postdoctoral fellows in systems, cognitive, affective, social, or clinical neuroscience, or perhaps faculty looking to move into these areas. We also hope that scientists interested in interdisciplinary research linked to these research fields may find this primer useful.

Even the best tools cannot yield sound results if the principles underlying the recording techniques, the generation of the signals, as well as the fundamentals of the analysis methods are not well understood. In this primer we thus focus on the basic physical and physiological background of MEG and EEG signals and principles of appropriate experimentation, data analysis, and interpretation. Our goal is to provide the reader with useful information on the practical aspects and typical technical problems faced in MEG or EEG recordings. We thus discuss at some length possible sources of artifacts, the procedures to judge the quality of the recording, and the care required in physiological interpretation.

Consequently, we do not exhaustively review the existing MEG and EEG literature but rather give examples of typical signals and refer to previous review papers and textbooks.

Whenever possible, we try to point out connections to interesting brain functions and brain-​imaging methods to emphasize that the MEG and EEG technologies are not independent of other approaches in neuroscience.

MEG and EEG have often been discussed separately, which has led many researchers to neglect their close relationship. The current neuroscience literature frequently examines results of one or two functional neuroimaging methods in a fairly unbalanced manner. For example, both MEG and EEG papers often cite functional magnetic resonance imaging (fMRI) literature, MEG papers more often cite EEG literature than vice versa, and fMRI papers either largely ignore electrophysiology or may cite scalp or invasive electric potential measurements (electrocorticography or depth electrode measurements) but rarely MEG. To remediate this problem, we try to discuss MEG and EEG in parallel, hoping that the very direct connections between these two methods thereby become clear. At the same time, it is important to develop a common language to facilitate successful interdisciplinary science.

We are indebted to our research teams and colleagues for feedback on the contents of this book, and especially the following individuals who have commented on drafts: Elizabeth ■ xvii

xviii

xviii ■ P reface to the F irst E dition

Bendycki, Sara Driskell, Tommi Himberg, Aapo Hyvärinen, Matti Hämäläinen, Veikko Jousmäki, Miika Koskinen, Kaisu Lankinen, Nancy Lundin, Ben Motz, Timo Nurmi, Ben Ramsden, Elina Pihko, Eero Smeds, and Noah Zarr. We thank Satu Ilta for drawing and redrawing the illustrations, and Lotta Hirvenkari for additional assistance in image preparation. We thank Elizabeth da Silva, Mia Illman, Isaiah Innis, Veikko Jousmäki, Anne Mandel, Timo Nurmi, and Lauri Parkkonen for help in the collection of some new MEG/​EEG data for illustrations in this primer and Nancy Lundin and John Purcell for modeling the EEG caps and nets in Chapter 6. We acknowledge Matti Hämäläinen and Ben Ramsden for in-​ depth discussions on the contents of this primer. Finally, we thank the Staff at the Indiana University Libraries, Bloomington, for their determination in sourcing the more difficult-​ to-​access publications.

xix

ABOUT THE AUTHORS Riitta Hari is a professor emerita of systems neuroscience and neuroimaging at Aalto University, Finland, currently working at the Aalto University’s Department of Art and Media. She is an MD PhD who, after her doctoral education at the Department of Physiology, University of Helsinki, Finland, received specialization in clinical neurophysiology at the Helsinki University Central Hospital, where she worked as a clinical neurophysiologist at the Epilepsy Unit of the Department of Neurology and at the Department of Neurosurgery. In 1982, she moved to Helsinki University of Technology (currently Aalto University) where, for over 30 years, she led a multidisciplinary Brain Research Unit. She has published extensively on MEG research in basic and clinical human neuroscience. She was a founding member of a five-​member team of Mustekala Ky, which laid the foundation for the MEG-​instrument development company Neuromag Oy (currently MEGIN Oy, Helsinki, Finland). Her most recent interests are in the brain basis of human social interaction and in bridging neuroscience and art without privileging either one. She has been financially supported by the Academy of Finland, the European Research Council, the Sigrid Jusélius Foundation, the SalWe Research Program for Mind and Body (by Tekes, the Finnish Funding Agency for Technology and Innovation), the Louis Jeantet Foundation, the Finnish Cultural Foundation, and the Aalto University.

Aina Puce is currently the Eleanor Cox Riggs Professor of Social Ethics and Justice in the Department of Psychological & Brain Sciences at Indiana University, Bloomington, Indiana.

She completed her PhD in the Department of Medicine, University of Melbourne, Australia, and then worked as a postdoctoral fellow and then research scientist in the Department of Neurosurgery at the Yale University School of Medicine, New Haven, Connecticut. Her research in face/​object perception provided major contributions to invasive electrical brain mapping studies in epilepsy-​surgery patients and to fMRI studies in healthy subjects. She has served as the deputy director for the Brain Sciences Institute, Swinburne University in Melbourne, Australia; the director of neuroimaging in the Department of Radiology at the West Virginia University School of Medicine, and the director of the Imaging Research Facility at Indiana University. She has published work on basic and clinical human neuroscience using scalp and intracranial EEG, MEG, and fMRI. Her academic interests are rooted in the brain bases of human nonverbal communication and more recently with art and the brain. She has been heavily involved in international efforts to develop and disseminate best practices in EEG and MEG data acquisition, analysis, and sharing. Her work has been supported by the National Health & Medical Research Council (Australia), the Australia Research Council, the National Institutes for Health (NINDS and NIBIB, USA), West Virginia University, Eleanor Cox Riggs, and the College of Arts and Sciences of Indiana University.

■ xix

xx

xxi

PREAMBLE In the early 1990s, a 38-​year-​old man entered the magnetoencephalography (MEG) laboratory of the Brain Research Unit of the Helsinki University of Technology. He had suffered from epileptic seizures since the age of 14. His seizures typically started by convulsions of the side of his face, which then progressed to a full-​blown generalized seizure with loss of consciousness. Now his generalized seizures were well controlled with modern antiepileptic drugs, but he was left with a type of “focal epilepsy,” consisting of frequent convulsions of his left face but without associated loss of consciousness. These convulsions could occur spontaneously or could be triggered by touching the left side of his mouth or gum: he had a rare type of reflex epilepsy that was touch triggered.

Because of the resistance of the facial convulsions to medication, surgery was planned to remove the brain area, or “epileptic focus,” that was giving rise to the convulsions. Typical for patients with focal seizure disorders, he had already gone through an exhaustive set of examinations to identify the epileptic focus; the examinations included multiple scalp electroencephalography (EEG) and videotelemetric recordings, as well as positron emission tomography (PET). Despite this extensive workup, the brain regions responsible for the epileptic seizures had not been identified. The hope was now to put MEG to the task as it is not affected by the skull, which dampens and smears EEG signals. The first whole-​scalp-​ covering MEG device had just been developed in Finland to simultaneously pick up signals from both hemispheres.

During the MEG recording, the patient triggered a seizure by touching his left gum with his tongue. Figure P.1 shows MEG signals recorded over a 20-​s interval where, soon after the touch, epileptic spikes, sharp transients, and complex spikes started to appear in the right hemisphere (red trace in panel a), contralateral to the touched gum. The abnormal discharges soon became continuous and spread to the left hemisphere as well (both traces in b), and simultaneously convulsions started in the patient’s left cheek. The whole seizure, as determined from the MEG signals, lasted for 14 seconds and then ended abruptly (in both traces in c).

The source analysis of the MEG signals—​aiming to attribute the measured signals to particular brain regions—​indicated that the epileptic discharges started from the face representation area of the right primary motor cortex and then spread, within 22 ms, to the left hemisphere (see the insert of Figure P.1). This time lag was determined by careful analysis of the time courses of the sources of right-​and left-​hemisphere spikes, and it agreed with interhemispheric conduction via myelinated fibers of about 1 μm in diameter (Aboitiz

■ xxi

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xxii ■ P reamble Right

a

1000 fT/cm

b

c

1s

(a) Right Left (b)

(c) 1000 fT/cm

1s

22 ms

FIGURE P.1. MEG signals in a patient with touch-​triggered focal epilepsy. A 20-​s trace from one (planar) MEG sensor over the right sensorimotor region is shown at the top of the figure, with calibration bars for signal amplitude and time. The segments a, b, and c indicate times of interest that are magnified in the subsequent traces from homologous right-​(red) and left-​hemisphere (blue) MEG sensors. (a) Immediately after touch, epileptic spikes appear in the right hemisphere. (b) Abnormal discharges are seen in both hemispheres but are significantly larger on the right. (c) The epileptic discharge ends abruptly in both hemispheres.

The schematic axial section of the brain depicts the transfer of the spikes in 22 ms from the right to the left hemisphere. Adapted and reprinted from Forss N, Mäkelä JP, Keränen T, Hari R: Trigeminally triggered epileptic hemifacial convulsions. Neuroreport 1995, 6: 918–​920.

With permission from Wolters Kluwer Health, Inc.

et al., 1992). Thus, the primary epileptic focus had been identified in the right hemisphere with a “mirror” focus in the left hemisphere (Forss et al., 1995).

The quite rare types of epileptic discharges seen in this patient raise several questions: How do MEG and EEG differ from each other? What essential steps do we need to take to record reliable MEG and EEG signals, and how can we be sure that the measured

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 PREAMBLE ■ xxiii

signals arise from the brain and not from some external source or from another part of the body? How do we preprocess, analyze, and model the signals, and how do these results relate to findings obtained by other neuroimaging methods? How do we interpret the results from the neuroscientific and clinical points of view? How can we expect these methods to improve in the future? In this Primer, we try to address these questions.

■ REFERENCES Aboitiz F, Scheibel A, Fisher R, Zaidel E: Fiber composition of the human corpus callosum. Brain Res 1992, 598: 143–​153.

Forss N, Mäkelä JP, Keränen T, Hari R: Trigeminally triggered epileptic facial convulsions. Neuroreport 1995, 6: 918–​920.

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1

SECTION 1

2

3

■ CH AP TER 1

INTRODUCTION When all you have is a hammer, everything looks like a nail.

A b r a h a m M a s l ow

One of the secrets of cooking is to learn to correct something if you can, and bear with it if you cannot.

Julia Child

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euronal communication in the brain is associated with minute electrical currents that give rise to both electrical potentials on the scalp (measurable by means of electroencephalography [EEG]) and magnetic fields outside the head (measurable by means of magnetoencephalography [MEG]). Both MEG and EEG are noninvasive neurophysiological methods used to study brain dynamics, temporal changes in the activation patterns and sequences. The differences between MEG and EEG mainly reflect differences in the spread of electric potentials and magnetic fields generated by electric currents in the human brain.

In this chapter, we give an overall description of the main principles of MEG and EEG, going deeper into details in the following chapters.

■ MEG AND EEG SETUPS

Figure 1.1 illustrates MEG and EEG measuring set-​ups. During a conventional MEG recording (top panel), the subject is sitting with her head inside a helmet-​shaped “dewar” vacuum flask that in this specific supercooled device houses an array of 306 extremely sensitive magnetic-​field detectors (middle panel, left); the name of this vacuum-​insulated flask honors its inventor, James Dewar (1842–​1923). To eliminate or dampen external ambient magnetic disturbances, the measurements are performed within a magnetically shielded room. To unravel which part of the brain the MEG signals are coming from, the position of the head with respect to the sensor array must be determined before each session, and it is often—​depending on the availability of this option in the applied measurement device—​ continuously monitored during the recording.

Eye movements and blinks that cause prominent artifacts in the recording are best monitored by means of an electro-​oculogram (electrical activity from eye and lid movements) or with an infrared camera (as shown in Figure 1.1, top panel), although they can be detected also from the frontal MEG (and EEG) channels. During the recording, the subject must keep her head as still as possible in the relatively tight helmet-​shaped ■ 3

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4 ■ section 1 MEG device Dewar

Screen Infrared camera

EEG net

Visual stimulus Connector: EEG cable to amplifier

EEG cable EEG amplifiers

FIGURE 1.1. MEG and EEG recording setups. Schematic MEG layout (top panel) displays subject sitting comfortably with her head placed in a “dewar.” In front of her are a back-​ projection screen for visual stimulus presentation and an infrared camera for monitoring eye movements. EEG setup (bottom panel) shows a subject, with attached EEG sensors, sitting in front of a computer monitor for visual stimulation. EEG amplifiers (to which the electrodes are connected via the thick EEG cable) appear in the foreground. Middle panels show MEG (left) and EEG (right) sensor arrays, respectively.

dewar housing the sensor array. She can speak and moderately move her hands and eyes, although in that case some artifact-​suppression methods may be needed. Her facial and bodily actions can be recorded with a video and monitored with response pads, accelerometers, and surface electromyogram (electrical activity from muscles), also including the electro-​oculogram. The electrocardiogram (electrical activity from the heart) can also be recorded.

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CHAPTER 1 Introduction ■ 5

During the EEG recording (Figure 1.1, bottom panel), the subject is more free to move, although head and body movements may cause artifacts and, as with MEG, are in most cases discouraged. The subject wears an EEG cap or elasticized “net,” in this case with 256 electrodes, attached to the scalp (middle panel, right). A response pad is on the subject’s lap (not seen in the figure), and a monitor to present visual stimuli is located at a distance in front of the subject to minimize electrical interference. As with MEG recordings, other electrical signals from the body—​such as the heart and muscles—​can also be recorded together with the EEG. To avoid other types of external electrical interference, EEG is preferably measured inside a Faraday cage that dampens power-​line artifacts and other electrical noise, although recordings of sufficient quality can also be performed in regular rooms, operating theaters, and even in real-​life settings using mobile EEG devices.

EEG can be recorded simultaneously with MEG, provided that the EEG electrodes and wires are nonmagnetic and do not take up too much space to prevent the subject’s head from fitting into the MEG helmet.

EEG and MEG signals are closely related. Figure 1.2 shows that a neuronal current (depicted with an arrow) in a local brain area, here representing activation of the auditory cortex to an abrupt sound, generates both MEG (magnetic field, left) and EEG (electric potential, middle) signal distributions. The resulting MEG pattern can be predicted using the “right-​hand rule” (as outlined in Figure 1.2, right panel).

Figure 1.2 also shows that the MEG and EEG patterns are at right angles with respect to each other. The electric potential distribution on the scalp is more widespread than the corresponding pattern of the radial component of the magnetic field, here also computed on the scalp, although in practice the MEG signals are recorded about 20 mm above the scalp.

This difference in spread between the MEG and EEG patterns arises because the concentrically layered structure of the head with different electrical conductivities for cerebrospinal fluid, skull, and scalp tissues leads to spread, or “smearing” of the electric potentials, but MEG

EEG

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FIGURE 1.2. Relationship between the site and direction of intracellular current and MEG and EEG signal distributions on the head. The schematic example depicts isofield lines for MEG (left) and isopotential lines for EEG (center) about 100 ms after a sound that activates the auditory cortex; the elicited net current (dipole) is displayed by the yellow arrow. The MEG and EEG patterns are rotated by 90 degrees with respect to one another. For MEG, positive and negative signs signify magnetic flux leaving and entering the head, respectively. For EEG, positive and negative signs indicate the polarities of the scalp potentials. The broken lines on each field pattern show the respective isofield and isopotential lines where the signal is zero. The MEG pattern can be understood on the basis of the “right-​hand rule” that is illustrated in the panel on the right: when the current flows to exit the right thumb, the magnetic field lines curl in the direction of the fingers of the right hand.