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English Pages 368 [365] Year 2015
Brain Stimulation
Brain Stimulation Methodologies and Interventions
Edited by IRVING M. RETI
Copyright © 2015 by Wiley-Blackwell. All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com. Library of Congress Cataloging-in-Publication Data: Brain stimulation (Reti) Brain stimulation : methodologies and interventions / edited by Irving Reti. p. ; cm. Includes bibliographical references and index. ISBN 978-1-118-56829-3 (cloth) I. Reti, Irving (Irving M.), editor. II. Title. [DNLM: 1. Brain–physiology. 2. Deep Brain Stimulation–methods. 3. Electroconvulsive Therapy–methods. 4. Neural Pathways–physiology. 5. Transcranial Magnetic Stimulation. WL 368] QP360 612.8–dc23 2014033466 cover image credit: ©istock.com/Danil Melekhin. Printed in the United States of America 10 9 8 7 6 5 4 3 2 1
Contents
Contributors
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Introduction to Brain Stimulation Irving M. Reti and Andrew D. Chang Introduction A Historical Perspective Focal Activation Connectivity Development of Invasive Brain Stimulation Ethical Issues References
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PART A BRAIN CIRCUITRY AND PLASTICITY
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A Balanced Mind: A Network Perspective on Mood and Motivation Brain Pathways Morten L. Kringelbach Introduction Dysregulation of Emotion and Mood Potential for Intervention Conclusion References Motor Pathways, Basal Ganglia Physiology, and Pathophysiology Hagai Bergman, Shiran Katabi, Maya Slovik, Marc Deffains, David Arkadir, Zvi Israel, and Renana Eitan Introduction The Classic Models of Basal Ganglia Anatomy Basal Ganglia Physiology The Pathophysiology of Hypo- and HyperDopaminergic States
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From Physiology to Understanding and Therapy—the Computational Models of the Basal Ganglia References
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4 Viewing Brain Stimulation from a Plasticity Perspective Jay M. Baraban Long-Term Potentiation: A Primer AMPA Versus NMDA Receptors Distinct Mechanisms of LTP Induction and Expression Synapse Specificity of LTP Relevance of LTP Mechanisms to Mode of Action of tDCS Long-Term Depression Metaplasticity and Monoamines Clues to rTMS Mode of Action Future Directions Summary References
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PART B
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TECHNOLOGY
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(1) Non-Invasive Brain Stimulation Modalities (a) Convulsive
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5 Introduction to Convulsive Therapy Richard D. Weiner Introduction The History of Convulsive Therapy Electroconvulsive Therapy: Basic Principles Electroconvulsive Therapy: Clinical Role Magnetic Seizure Therapy (MST) Focal Electrically Administered Seizure Therapy (FEAST) Future of Convulsive Therapy References
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6 Improving ECT Efficacy and Decreasing Cognitive Side Effects Keith G. Rasmussen Introduction ECT Outcome Assessment: Therapeutic Efficacy and Cognitive Side Effects ECT Treatment Technique: Basic Concepts Electrode Placement Stimulus Dosage Stimulus Parameter Configuration Treatment Frequency Concomitant Psychotropic Drugs
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CONTENTS
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Choice of Anesthetic Drug References
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How Does Electroconvulsive Therapy Work? Irving M. Reti Introduction What Can We Learn from ECT’s Action as an Antidepressant? What Can We Learn from ECT’s Action in Treating Catatonia? How Do Stimulus Parameters that Trigger the Seizure Influence How It Works? Conclusions and Implications for ECT Treatment References
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Magnetic Seizure Therapy for the Treatment of Depression Sarah H. Lisanby and Zhi-De Deng Introduction Definitions Rationale for MST History of MST: A Translational Developmental Trajectory MST Technique E-field Distribution with MST Neurophysiological Effects of MST Safety Antidepressant Efficacy Future Directions for MST Development Conclusions References
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Introduction to Nonconvulsive Brain Stimulation: Focus on Transcranial Magnetic Stimulation Masashi Hamada and John C. Rothwell History of Nonconvulsive Transcranial Brain Stimulation Technique in Humans Basics of Transcranial Magnetic Stimulation New Techniques: Static Magnets and Pulsed Ultrasound References
10 Advances in Transcranial Magnetic Stimulation Technology Angel V. Peterchev, Zhi-De Deng and Stefan M. Goetz Introduction Pulse Source Technology and Waveforms Coils Technical Aspects of Concurrent TMS and Neuroimaging Conclusion and Future Directions References
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11 Applications of TMS to Study Brain Connectivity Gabriela Cantarero and Pablo Celnik Introduction Probing Connectivity using Bifocal TMS Connectivity Studies Using TMS Plus fMRI, PET or EEG Conclusions References 12 Therapeutic Applications of rTMS for Psychiatric and Neurological Conditions Mark S. George, E. Baron Short, Suzanne E. Kerns, Xingbao Li, Colleen Hanlon, Christopher Pelic, Joseph J. Taylor, Bashar W. Badran, Jeffrey J. Borckardt, Nolan Williams, and James Fox Introduction The Depressions The Anxiety Disorders The Schizophrenias Pain Syndromes Movement Disorders Repairing the Damaged Brain Other Conditions Summary and Conclusions References
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13 Transcranial Direct Current Stimulation: Modulation of Brain Pathways and Potential Clinical Applications Michael A. Nitsche, Rafael Polania, and Min-Fang Kuo Introduction Physiological Basis of tDCS Impact of tDCS on Cognition Application of tDCS in Neuropsychiatric Diseases Concluding Remarks References
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(2) Invasive Brain Stimulation Modalities
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14 Epidural Cortical Stimulation Ziad Nahas Introduction Options for Treatment Resistant Depression Epidural Cortical Stimulation Disrupted Emotion Regulation in Depression and EpCS Deficits in Mentalization in Depression and EpCS Comparison Across Brain Stimulation Therapies Summary References
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15 Neurological Indications for Deep Brain Stimulation Jennifer J. Cheng, William S. Anderson, and Frederick A. Lenz Introduction Current Indications for Deep Brain Stimulation Safety of Deep Brain Stimulation Fundamentals of Stimulation Lead Placement Conclusion References 16 Psychiatric Indications for Deep Brain Stimulation Reinier Prosée and Damiaan Denys Introduction Deep Brain Stimulation and Obsessive Compulsive Disorder Deep Brain Stimulation and Major Depressive Disorder Deep Brain Stimulation and Drug Addiction Potential New Indications for Deep Brain Stimulation References
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17 Vagus Nerve Stimulation for Epilepsy and Depression Charles R. Conway, Mark A. Colijn, and Steven C. Schachter Introduction The VNS Therapy Device Vagus Nerve Anatomy Mechanisms of Action of VNS Epilepsy Depression General Safety Considerations Future Directions Summary References
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Index
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Contributors
William S. Anderson, MD, PhD
Associate Professor, Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
David Arkadir, MD, PhD
Department of Neurology, Hebrew University Hadassah Medical School, Jerusalem, Israel
Bashan W. Badran, BS
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Jay M. Baraban, MD, PhD
Professor, Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Hagai Bergman, MD, DSc
Professor, Department of Medical Neurobiology, Hebrew University Hadassah Medical School, Jerusalem, Israel
Jeffrey J. Borckardt, PhD
Associate Professor, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Gabriela Cantarero, PhD
Departments of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Pablo Celnik, MD
Professor, Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Andrew D. Chang, MS
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA xi
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CONTRIBUTORS
Jennifer J. Cheng, MD
Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Mark A. Colijn, MSc
St. Louis University School of Medicine, St. Louis, MO, USA
Charles R. Conway, MD
Associate Professor of Psychiatry, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Marc Deffains, PhD
Department of Medical Neurobiology, Hebrew University Hadassah Medical School, Jerusalem, Israel
Zhi-De Deng, PhD
Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Damiaan Denys, MD, PhD
Chair, Department of Psychiatry, University of Amsterdam, Academic Medical Center, and the Netherlands Institute for Neuroscience, Amsterdam, Netherlands
Renana Eitan, MD
Department of Psychiatry, Hebrew University Hadassah Medical School, Jerusalem, Israel
James Fox, MD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Mark S. George, MD
Professor, Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Stefan M. Goetz, PhD
Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Masashi Hamada, MD, PhD
Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK
Colleen Hanlon, PhD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Zvi Israel, MBBS
Department of Neurosurgery, Hebrew University Hadassah Medical School, Jerusalem, Israel
Shiran Katabi, MSc candidate
Department of Medical Neurobiology, The Hebrew University Hadassah Medical School, Jerusalem, Israel
CONTRIBUTORS
Suzanne E. Kerns, MBBS
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Morten L. Kringelbach, D.Phil.
Professor, CFIN/MindLab (Aarhus) & Department of Psychiatry (Oxford), Aarhus and Oxford Universities, Aarhus, Denmark and Oxford, UK
Min-Fang Kuo, MD, PhD
Department of Clinical Neurophysiology, Göttingen University Medical School, Göttingen, Germany
Frederick A. Lenz, MD
Professor, Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Xingbao Li, MD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Sarah H. Lisanby, MD
J. P. Gibbons Professor and Chair, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Ziad Nahas, MD, MSCR
Chair, Department of Psychiatry, American University of Beirut Medical Center, Beirut, Lebanon
Michael A. Nitsche, MD
Professor, Department of Clinical Neurophysiology, Göttingen University Medical School, Göttingen, Germany
Christopher Pelic, MD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Angel V. Peterchev, PhD
Assistant Professor, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Rafael Polania, PhD
Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Zurich, Switzerland
Reinier Prosée, MS
Department of Psychiatry, University of Amsterdam, Academic Medical Center, Amsterdam, Netherlands
Keith G. Rasmussen, MD
Associate Professor, Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
Irving M. Reti, MBBS
Associate Professor, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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CONTRIBUTORS
John C. Rothwell, PhD
Professor, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, London, UK
Steven C. Schachter, MD
Professor, Department of Neurology, Harvard Medical School, Boston, MA, USA
E. Baron Short, MD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Maya Slovik, MD, PhD candidate
Department of Medical Neurobiology, Hebrew University Hadassah Medical School, Jerusalem, Israel
Joseph J. Taylor, MD, PhD Candidate
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
Richard D. Weiner, MD, PhD
Professor, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
Nolan Williams, MD
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
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Introduction to Brain Stimulation Irving M. Reti and Andrew D. Chang Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Introduction
Brain stimulation refers to neural modulation of specific brain regions or networks, typically by electric or electromagnetic fields. Stimulation can result in therapeutic seizures or be nonconvulsive. Nonconvulsive stimulation can be accomplished either by direct stimulation of neural pathways through implantation of electrodes or noninvasively. Devices and technologies that deliver brain stimulation have emerged as both tools to probe brain function and as therapeutic options for patients with neuropsychiatric disease who fail to respond to or cannot tolerate medications and other therapies. Interest among researchers in brain stimulation has grown enormously in the past decade for several reasons: our understanding of brain function and circuitry has increased immensely; innovative technology to stimulate the brain focally targeting specific networks has developed in parallel; neuropsychiatric disease makes up an increasingly large proportion of disease and disability worldwide, which oftentimes is resistant to conventional pharmacological treatments. Evidence for the increased interest in the field is revealed by a search on PubMed using the key words “Brain Stimulation”: there were 121 hits in 2000, 625 hits in 2007, and 1500 hits in 2013. Although electroconvulsive therapy (ECT) dates back to the 1930s, little is known about how it works; likewise for the newer brain stimulating technologies which are also evolving as technology and our understanding of brain function improve. Moreover, brain stimulation is expanding in scope both as a way to probe brain function and as a treatment. Just as there are texts focused on psychopharmacology for students and researchers, the same is required in the field of brain stimulation. We hope to have created such a volume which is an introduction to this rapidly expanding field. Key to understanding how brain stimulating technologies work is an understanding of brain circuitry that mediates normal and abnormal brain function. As a result of the neuronal activation triggered by brain stimulation, a cascade of molecular events leads to long-lasting neuronal changes especially at the synapse that outlives the initial stimulus and can last hours, days, or longer. Accordingly, the first part of the book focuses on neuronal circuits subserving the motor and limbic systems and the activity dependent changes in neuronal function triggered by brain stimulation (Chapters 2–4). The second part of the book focuses on the brain stimulation technologies themselves that can be categorized as either noninvasive (Chapters 5–13) or invasive (Chapters 14–17). Within the noninvasive category, the technology may be convulsive (Chapters 5–8), relying on therapeutic seizure for efficacy or nonconvulsive (Chapters 9–13) using electromagnetic or electrical stimulation without
Brain Stimulation: Methodologies and Interventions, First Edition. Edited by Irving M. Reti. © 2015 John Wiley & Sons, Inc. Published 2015 by John Wiley & Sons, Inc.
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seizure induction. Chapter authors are leading experts in their specialized area within the field of brain stimulation.
A Historical Perspective
Key milestones in neuroscience discovery have been critical for today’s progress in the field of brain stimulation (Finger 1994; Finger 2000; O’Shea 2013). The field of neuroscience began in earnest when Hippocrates stated that the brain is the seat of intelligence. However, it would not be until 1791 that its electrical nature was elucidated by Luigi Galvani and Alessandro Volta, who used electricity to activate nerves and muscles of the frog. The 19th century saw a boom in discoveries of functional neuroanatomy. For example, Paul Broca and Carl Wernicke described the brain structures responsible for speech and aphasias. In 1889, Sir Victor Horsley published the somatotopic map of the monkey motor cortex, giving rise to the concept of the homunculus. That same year, Santiago Ramon y Cajal posited the “connectionist” theory, according to which the brain functions through complex communication among individual neurons. His work was instrumental in bringing forth the modern era of systems neuroscience, the idea that the nervous system is composed of a series of modular circuits for each brain function. Through the work of Mahlon Delong and others we now recognize a parallel organization of functionally segregated basal ganglia–thalamocortical circuits with each circuit engaging specific regions of the cortex, striatum, pallidum, substantia nigra, and thalamus (Alexander et al. 1986; see Chapters 2 and 3). In parallel to the advances in understanding the circuits that mediate brain function, there have been equally important discoveries in understanding how neurons function at the cellular level, including how neurons communicate and how memories are formed. Donald Hebb’s formulation of long-term potentiation in his 1949 book The Organization of Behavior was a key advance in understanding how neurons adapt in the learning process. He coined the phrase “neurons that fire together, wire together,” which is the basic mechanism underlying synaptic plasticity (see Chapter 4). These and other key neuroscientific discoveries have provided the impetus for understanding and developing brain stimulation modalities. Although brain stimulation is an evolving field, the “gold standard” brain stimulating treatment for depression, ECT, dates back more than 70 years. During the subsequent decades, pharmacologic treatments for neuropsychiatric disease dominated. Most novel brain stimulation methodologies have emerged only in recent years following advances in technology, improved understanding of brain pathways subserving neuropsychiatric disease and treatment response, and as a response to medication ineffectiveness or intolerance. Some of these brain stimulation technologies began as research tools for scientists trying to noninvasively probe brain function, for example, transcranial magnetic stimulation (TMS), and were later co-opted by psychiatrists and neurologists as potential treatments. However, deep brain stimulation (DBS) is an example of a treatment modality that has emerged out of our increasing knowledge about brain pathways subserving neuropsychiatric disease. The burden of neuropsychiatric disease is increasing rapidly and worldwide. According to the World Health Organization, depression is now the leading cause of disability in the world and four of the six leading causes of years lived with disability are due to neuropsychiatric disorders namely depression, alcohol-use disorders, schizophrenia and bipolar disorder. It is estimated that the cost of mental health problems in developed countries is between 3% and 4% of GDP. Unfortunately, medication is ineffective or insufficient for many patients with neuropsychiatric disease. For example, about 30 percent of patients with major depression do not respond to currently available medications or experience intolerable side effects (Rush et al. 2006). Accordingly, there is increased focus on alternative treatment modalities such as brain stimulation as evidenced by the steep rise in research interest in the field, recent clinical trials, and
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regulatory approval of several brain stimulating technologies in the past two decades, for example, DBS for Parkinson’s disease, vagus nerve stimulation (VNS) for epilepsy and depression, and TMS for depression.
Focal Activation
A major goal of brain stimulating devices is to focally stimulate neural circuits leaving nearby brain regions unaffected. This feature is critical for using these devices as tools to study specific pathways and plasticity within them, and for developing treatments for neuropsychiatric disorders that minimize side effects especially compared with pharmaceuticals. Taking medication has the advantages of convenience and typically being cheaper. However, it may elicit unpleasant or dangerous side effects and must cross the blood-brain barrier, resulting in inadequate or variable levels in the brain. On the other hand, brain stimulating techniques can target key brain regions directly, focally and quickly, facilitating accelerated responses and greater efficacy compared with pharmaceuticals, without producing systemic and local side effects.
Convulsive Stimulation
Long before electricity could be harnessed by man, Hippocrates observed that high fever brought on by malaria could trigger convulsions in mentally disturbed people yielding a therapeutic benefit. In the late 1700s, physicians began using chemical agents to trigger seizures, and in the 1930s, electricity would replace chemical agents as a more predictable method for inducing a seizure. See Chapter 5 for a very thorough introduction to convulsive therapy, including its history. To this day, ECT remains the “gold standard” treatment for medication-resistant depression, and in many developing countries it is the first line treatment for mania and other psychoses as well (Gallegos et al. 2012, Tripathi et al. 2014). Since the introduction of ECT, there have been major advances in how it is delivered, for example, the use of brief rather than sine wave pulses, which significantly reduced cognitive side effects. In recent years, even narrower, so-called ultrabrief pulses have been investigated, which are associated with even less cognitive disturbance. It is thought that narrower pulses reduce the volume of neural tissue being stimulated resulting in fewer cognitive side effects. See Chapter 6 for a comprehensive review of efforts to enhance the efficacy of ECT and decrease its cognitive side effects. Because ECT is such an effective treatment for major mental illness, and yet is associated with memory loss, there is considerable interest in learning more about how it works, in order to optimize its efficacy, minimize cognitive side effects, and guide the development of other potentially efficacious pharmacologic and somatic treatments. Such alternative treatments ideally would not trigger the cognitive side effects of ECT or require anesthesia but would yield similar therapeutic outcomes. Endeavors to understand how ECT works have focused on changes it triggers in the hippocampus and prefrontal cortex, brain regions implicated in the antidepressant efficacy of other modalities. The hippocampus is critical for learning both neutral and emotionally charged information. Hippocampal plasticity, including expression of neurotrophic factors, neurogenesis, and neuritic outgrowth is particularly sensitive to ECT. Connectivity in the prefrontal cortex disrupted by depression is likewise sensitive to the effects of ECT. Emerging data from human, nonhuman primate and theoretical head modeling is teaching us more about how electrode placement and ECT stimulus parameters affect prefrontal and hippocampal plasticity as well as the therapeutic outcome. For a thorough review of this topic see Chapter 7. The search for convulsive therapy focality, in order to reduce cognitive side effects while maintaining efficacy, first led to the development of right unilateral (RUL) electrode placement in the late 1940s as an
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alternative to bitemporal placement. RUL placement avoids direct stimulation over the language centers of the dominant hemisphere. Later, bifrontal placement and more recent electrode configurations, such as focal electrically administered seizure therapy (FEAST), target the prefrontal cortex (reviewed in Chapters 5 and 6). There have also been developments in setting ECT electrical parameters, including pulse width and amplitude that are aimed at more focal stimulation such as lowering and individually titrating pulse amplitude (see Chapters 7 and 8). Developed by Holly Lisanby and Harold Sackeim in the past 15 years, magnetic seizure therapy (MST) is a more focal form of convulsive therapy that utilizes transcranial magnetic induction of electrical currents. See Chapter 8 for a very thorough review of the technique and outcomes. The magnetic field passes through the scalp and skull unimpeded and induces current that is confined to the superficial cortex but that is of sufficient strength to trigger a seizure. The superior spatial targeting of MST compared with conventional ECT spares deeper structures triggering a seizure with the minimum current possible. Studies show that while MST preserves the efficacy of ECT, it results in fewer cognitive side effects even when compared with ultrabrief pulse ECT (McClintock et al. 2013), perhaps because MST has reduced impact on hippocampal plasticity. Nonconvulsive Stimulation Transcranial Magnetic Stimulation
TMS relies on Michael Faraday’s principle of electromagnetic induction. Electric pulses in a figure-of-8 coil induce a changing magnetic field at right angles to the coil that permeates through the scalp and skull and induces an electric field in the brain, focally and noninvasively depolarizing neurons. Secondary neurons are stimulated affecting more distant sites. Barker et al. (1985) built the first magnetic stimulator at the University of Sheffield, which they used to stimulate the motor cortex causing a muscle action potential. Initially, TMS was used for painless, noninvasive mapping of brain function. Repetitive pulses or trains of pulses (“rTMS”) were found to provoke long-lasting up- or downregulation of activity at synapses, including in brain regions that regulate movement and emotion (Huang et al. 2005). See Chapters 4, 9, and 10 for more on the mechanism of action of TMS. rTMS can be used as a tool to probe brain function. For example, dopamine release, which is implicated in depression, addiction, and movement disorders, has been studied in humans using rTMS. Strafella et al. (2001) and Cho and Strafella (2009) have observed that dopamine release in the striatum and anterior cingulate cortex, respectively, is modulated by rTMS over the DLPFC. Similarly, rTMS over the motor cortex also modulates dopamine release in the striatum (Strafella 2003). Also, as outlined briefly below and extensively in other chapters, TMS can also be used to probe functional connectivity between brain regions. The long-lasting changes triggered by rTMS, that outlast the stimulation itself, are also critical to the therapeutic effects of rTMS in treating depression and other neuropsychiatric conditions, which are reviewed extensively in Chapter 12. The observation of hypoactivity in the prefrontal cortex of depressed patients led Mark George and colleagues to evaluate the effectiveness of focal stimulation by rTMS for enhancing activity in this region and combating depression. rTMS has turned out to be devoid of the cognitive side effects associated with ECT. However, although it is more effective than antidepressant medication, it does not seem to be as effective as ECT (Reti 2013). Moreover, it is time-consuming and costly. Therefore, the challenge is learning more about clinical predictors or biomarkers of response and improving its efficacy. Along those lines, increased pulse number, placement over the F3 site of the 10–20 EEG system, concurrent use with antidepressants, and the addition of right sided DLPFC pulses probably account for improved efficacy reported in recent observational studies (Carpenter et al. 2012; Connolly et al. 2012) compared with
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randomized trials conducted several years ago. A new development is recent FDA approval of the H-coil for treating depression, which can stimulate more deeply but also less focally (Levkovitz et al. 2014). It is not known how the H-coil compares with the conventional figure-of-8 coil as a treatment for depression. In Chapter 10, Angel Peterchev and colleagues provide an overview of the state of the art of TMS devices, including pulse sources with flexible control of the output waveform parameters and a wide variety of coil designs. Flexible pulse waveform is an area of active investigation as the pulse shape affects the selectivity of the neural subpopulation activated. The coil geometry and position determine primarily the spatial distribution of the electric field induced in the head. Peterchev and colleagues illustrate the spatial stimulation characteristics of a large number of commercial and experimental coils with electric field simulations, demonstrating a tradeoff between depth and focality. None of the coil designs can achieve both depth and focality simultaneously. Nonetheless, advances are being made in TMS delivery and include the potential for integrating neural responses in real time, akin to work in DBS, described below. One interesting technology on the horizon that has the potential to overcome the difficulty of stimulating both focally and deeply is transcranial pulsed ultrasound that has been demonstrated in the intact mouse brain (Tufail et al. 2010; see also Chapter 9). Transcranial Direct Current Stimulation (tDCS)
Treating medical ailments electrically dates back to antiquity and included harnessing electrical energy from fish (Stillings 1975). The first use of low intensity direct currents for treating neuropsychiatric conditions dates back to 1804 when Aldini reported its effectiveness for melancholia (Zaghi et al. 2010). In the 1960s and 1970s, it was demonstrated that direct currents applied intracerebrally (Bindman et al. 1964) or transcranially (Dymond et al. 1975) could alter cerebral blood flow, as well as EEG patterns and evoked potentials (Pfurtscheller 1970). tDCS was then largely forgotten until Michael Nitsche and Walter Paulus demonstrated, in their studies in the past 15 years, that weak direct current applied to the scalp could modulate cortical excitability, which lasted for minutes to hours after the termination of the stimulation. Whereas TMS triggers an action potential, tDCS instead modulates membrane potential making it more or less likely for another input to cause neuronal firing. (See Chapters 4 and 13 for more on the mechanism of action of tDCS.) Therefore, concurrent stimulation is probably more important for the efficacy of tDCS than it is for TMS, whether that be for psychiatric or neurological applications. For example, recent trials have demonstrated that concurrent cognitive training can augment the antidepressant effect of tDCS (Brunoni et al. 2014; Segrave et al. 2014). tDCS is a simple and inexpensive form of brain stimulation. There are no cognitive side effects. Efforts are also being made to increase focality using alternate electrode configurations and smaller electrodes, so-called high definition tDCS. There is much interest in tDCS ranging from teenagers wanting to improve performance on video games to evaluating tDCS as a treatment for depression. In fact, there is evidence that tDCS can improve the cognitive performance on a task when it is administered concurrently (Martin et al. 2013), and according to the website clinicaltrials.gov there are presently at least a dozen ongoing trials of tDCS for treating depression or bipolar depression.
Connectivity
Appreciating neural circuits and their connections is critical for understanding neuropsychiatric disease and for developing effective treatments, especially brain stimulation treatments, many of which target specific pathways and networks. The term “functional connectivity” refers to how brain regions in a circuit or
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network interact. It is defined as the correlation between remote neurophysiological events in the temporal domain (Friston et al. 1993; Horwitz 2003; Fox et al. 2012a). Functional connectivity can be both monitored and affected by brain stimulation modalities. Assessing Functional Connectivity Using Brain Stimulation Modalities
One can assess functional connectivity noninvasively in normal and disease states using a wide variety of evolving techniques. These techniques include both brain stimulating modalities and functional imaging, sometimes in combination. In Chapter 11, Cantarero and Celnik present a very thorough review of the use of twin TMS for assessing functional connectivity. They describe a paired pulse protocol where one coil is stimulating over the primary motor cortex (M1) and the other coil over a brain region that connects to M1. The readout is the motor evoked potential. Such investigations can reveal markers of disease states that reflect altered connectivity between the two stimulation sites. For example, depression is associated with reduced peripheral cortical paired associative stimulation induced plasticity, a test that is independent of subject motivation and effort (Player et al. 2013). Although bifocal TMS gives precise temporal information about the connectivity of cortical regions connected to the motor cortex, it is limited to the motor system as one needs an observable output in the form of a motor evoked potential. To assess connectivity in other parts of the brain requires other modalities that can sample activity in other areas such as EEG or functional neuroimaging utilizing PET or functional MRI (fMRI). fMRI is an MRI procedure used to assess brain activity by identifying associated changes in blood flow. This procedure can map out neural activity by correlating spontaneous fluctuations in blood-oxygen-level dependent (BOLD) signals in different regions of the brain (Deco et al. 2011). It can assist in determining connectivity in different parts of the brain, in both resting and functional states. When interactions between brain regions are being probed by fMRI when the person is at rest, it is known as “resting state connectivity.” Identified deficits can reveal potential markers of pathological disease states. For example, “hyperconnectivity” within and between the default mode and cognitive control networks has been observed in depression (see Chapter 7). Researchers can also probe connectivity in real time when the brain is reacting to an event, a task the subject is asked to perform, or concurrent TMS over a particular region of the cortex. Brain activity triggered by TMS can be monitored by fMRI or EEG, which is also reviewed in Chapter 11. Concurrent TMS–fMRI is particularly technically challenging because of the magnetic resonance generated by the TMS coil and because of the strong magnetic force of the fMRI scanner on the TMS coil. The design of such devices is thoroughly reviewed in Chapter 10. This is an exciting field as it allows one to detect real-time changes in brain responses in both the stimulated cortical targets and the remote connected regions, as demonstrated in recent motor (Yau et al. 2013) and prefrontal cortex (Chen et al. 2013) connectivity studies. Effects of Brain Stimulation Modalities on Functional Connectivity
The common mechanism underlying convulsive and nonconvulsive therapies is an electric field that triggers either a seizure or nonconvulsive neuromodulation that results in a long-lasting alteration in connectivity. Such changes in connectivity can be assessed in a variety of ways, as described above, which can provide insight into how the brain stimulating technology works, who might respond to it, and how its therapeutic use can be optimized. For example, in the field of rTMS, work by Pascual-Leone and colleagues (Fox et al. 2012b) suggested that the antidepressant efficacy of focal brain stimulation might be optimized by targeting based on connectivity monitored by resting state fMRI, specifically, a negative correlation between the DLPFC stimulation site and the subgenual cingulate. Direct support for that hypothesis has recently been published (Liston et al. 2014). The effects of brain stimulating treatments on connectivity are thoroughly reviewed in this volume. For example, for effects on synaptic plasticity see Chapter 4, for effects of ECT see Chapter 7, for effects of TMS see Chapters 9 and 11, for effects of tDCS see Chapter 13.
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Development of Invasive Brain Stimulation
Neurosurgery for neuropsychiatric conditions dates back to ancient times. Cave paintings from the Neolithic period demonstrate the practice of trephination or drilling burr holes into the skull to cure mental disorders and epilepsy (Brothwell 1963). More recently, frontal lobotomy, which consisted of destroying the prefrontal cortex or its connections, was practiced widely in the 1940s for the treatment of psychiatric illness, before the introduction of antipsychotic medication, and despite frequent and major adverse effects. It was an improved understanding of functional neuroanatomy and advances in modern neurosurgical techniques such as the development of stereotactic surgery in the 1940s that led to the development of more anatomically specific neurosurgical ablation for severe neuropsychiatric conditions that failed to respond to the increasing pharmacological armamentarium. In parallel with the development of the stereotactic apparatus for ablative surgery, sporadic reports appeared describing depth electrode stimulation of chronically ill psychiatric patients who received transient benefit from such interventions (Hariz et al. 2010). Further advances in our understanding of neural circuitry, experience with ablative surgery, and the development of miniature pacemakers heralded the modern age of invasive brain stimulation focused on movement, rather than psychiatric, disorders with the first trial of DBS for Parkinsonian tremor reported by Benabid in 1987. Movement disorders are now established indications for DBS, and a number of other neurological and psychiatric conditions are under active investigation. In comparison with noninvasive stimulation, invasive brain stimulation offers improved spatial accuracy and does not cause cognitive side-effects nor requires repeated anesthesia as for convulsive therapies. Stimulation can either be chronic, intermittent, or, as described below, precisely synchronized with electrophysiological or behavioral feedback signals. Interestingly, the therapeutic mechanism of DBS appears to vary by the neuropsychiatric condition it is being used to treat and the site it is targeting. Generally speaking, stimulation activates axons, soma, and dendrites. We are starting to learn more about which of these neural elements are responsible for the therapeutic actions of DBS, be they target afferents, target efferents, or fibers of passage. For example, when DBS at the subthalamic nucleus is used to treat Parkinson’s disease, its therapeutic target may be fibers of passage from the motor cortex (Gradinaru et al. 2009). The variable rate of onset when DBS is administered for different conditions also suggests different mechanisms are at work. Contrast the rapid therapeutic effect of DBS for Parkinsonian tremor with the much slower onset observed for other conditions such as DBS for depression. DBS for both neurological and psychiatric indications, including discussions on the mechanisms of action, are thoroughly reviewed in Chapters 15 and 16. Other Invasive Brain Stimulation
While DBS offers the key advantage of focality, the major concern of the treatment is its invasive nature. DBS electrodes must be surgically implanted, causing microlesions along its path from the surface of the brain to the target site. When target sites are superficial, less invasive brain stimulation modalities can be considered. Both epidural cortical stimulation and VNS avoid direct contact of microelectrodes in brain tissue. In the former case, multicontact stimulating paddles are placed in the extradural space over specific cortical regions and connected to a pacemaker-like generator. Epidural cortical stimulation has been investigated for a variety of neurological and psychiatric indications. See Chapter 14 for a comprehensive review of this stimulation modality. In the case of VNS, electrodes are wrapped around the vagus nerve in the carotid sheath. VNS is effective both as an adjunctive agent for patients with partial onset seizures and for treatment resistant depression. See Chapter 17 for a very thorough review of this treatment. Interestingly,
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like DBS, there is variability in how rapidly patients respond suggesting different mechanisms of action are at play. Whereas VNS appears to work on demand for epilepsy as well as have a prophylactic effect, the response for depression appears to emerge slowly over months. There are no satisfactory theories or evidence-supported explanations yet to account for this difference. Bumps Along the Road
The promise of invasive brain stimulation is long-term relief for conditions that are unresponsive in a sustained manner to medications and noninvasive stimulation. However, there have been some setbacks. Northstar Neuroscience Inc, which went bankrupt in 2009, sponsored clinical trials of epidural cortical stimulation for depression and stroke, both of which failed. In the field of DBS for depression, earlier studies were positive for targeted stimulation at both the ventral capsule/ventral striatum (VC/VS) and Brodmann area 25. However, two recent commercially funded DBS trials for depression have failed, namely, a study sponsored by Medtronic Inc targeting the VC/VS (Williams and Okun, 2013) and a study by St Judes Medical Inc targeting Brodmann area 25, which recently failed a futility analysis (Cavuto 2014). Their failure might be related to the industry pushing too fast and too hard to commercialize the technology. Rather, better studies are needed to define the precise tracts that should be targeted, and more attention should be paid to optimizing the treatment parameters. However, DBS research is proceeding apace. Novel areas are being targeted for depression. Pilot studies indicate the medial forebrain bundle (Schlaepfer et al. 2013) and lateral habenula (Sartorius et al. 2010) are promising new targets. Larger clinical trials are underway. In the field of Alzheimer’s disease, both fornix (Lyketsos et al. 2012) and nucleus basalis (Kuhn 2014) are active DBS targets. Real-Time Feedback
For treatments such as DBS and epidural cortical stimulation, chronic stimulation may be unnecessarily excessive. Stimulation parameters are typically optimized by multiple empirical titrations of the stimulation parameters or electrode couplings (Kupsch et al. 2011). This process is time-consuming, requiring close follow-up to monitor both the acute and delayed effects of stimulation (Kupsch et al. 2011). This is particularly problematic for physicians facing the decision of whether to select more vigorous stimulation parameters or wait longer to check if the existing paradigm generates a delayed effect. Moreover, chronic brain stimulation may result in accelerated habituation and rebound symptoms. For example, with thalamic DBS for essential tremor, 13–40% of patients develop tolerance despite accurate electrode placement as quickly as three months after implantation surgery (Pilitsis et al. 2008; Shih et al. 2013). While these effects may be attributed to the natural progression of neurodegeneration, they emphasize the need to improve DBS technologies by dynamically adapting stimulation parameters to patient status. As a proof of concept for the value of this approach, patients who were instructed to turn on DBS only with the onset of essential tremor showed continuous sensitivity to treatment during the 30 months of follow-up (Kronenbuerger et al. 2006). The Defense Advanced Research Projects Agency, an agency of the US Department of Defense, recently announced a funding priority for advancing DBS technologies that not only treat, but also monitor and alter stimulation in real time to maximize efficacy. In response, there has been a boom in sophisticated techniques that integrate DBS with sensors to detect the onset of behavioral symptoms and electrophysiological signals that correlate with them (Rosin et al. 2011; Santos et al. 2011; Carron et al. 2013). Currently focused on Parkinson’s disease, these so-called closed-loop DBS technologies have shown greater efficacy compared with conventional chronic stimulation, improving motor scores by 29% and decreasing stimulation times by 56% (Little et al. 2013).
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Ethical Issues
Although ECT has been around for more than 70 years, the field of brain stimulation is rapidly evolving with interest from researchers, clinicians and patients. When brain stimulation is applied as a treatment, it is often time-consuming and expensive, and in many instances it is still experimental. Because the neuropsychiatric disorder for which the brain stimulation technique is being used is likely severe and could impair a patient’s judgment, patients are particularly vulnerable. This is especially the case with invasive brain stimulation where the patients are quite ill, desperate, and the treatment can have major adverse effects. Accordingly, it is wise to be cautious as well as mindful of psychiatry’s history of periodic misadventures, a prominent example being frontal lobotomy (McHugh 1992). As described in the chapters of this book focused on convulsive and invasive brain stimulation, there are potentially significant neuropsychiatric complications associated with these treatment modalities. For example, DBS in Parkinson’s disease has been reported to result in adverse effects including anxiety, mood fluctuations, and even gambling (Bejjani et al. 1999; Saint-Cyr et al. 2000; Krack et al. 2001; Kulisevsky et al. 2002; Berney et al. 2002), Close psychiatric follow-up is, therefore, critical in these patients. Moreover, the implanted devices can interfere with daily activities in other ways, for example, taking an MRI scan or passing through magnetized areas that interfere with the neurostimulation pacemaker. A DBS implant might also interfere with the patient’s ability to receive ECT. The capacity to give informed consent may be compromised by the neuropsychiatric condition for which the brain stimulation is indicated. Because clinicians and researchers may have substantial financial and even academic gain from treating or enrolling patients in a brain stimulation device trial, conflict of interest or the perception of such may arise. Accordingly, particular care needs to be taken in deciding if a patient is appropriate for treatment or enrollment in a clinical trial. Patients should consult with specialists who have no potential interest in the patient receiving the treatment. A review committee comprising experts in the field may also assist for this purpose. This is especially the case for invasive brain stimulation that requires multidisciplinary collaboration in the fields of neurosurgery, neurology, psychiatry, and psychology. The informed consent procedure needs to be thorough and should preferably involve the family. This is particularly relevant when the patient is a child as brain stimulating treatments have rarely been systemically assessed in children, and the effects on brain development are unknown. For example, many institutions require the review of a pediatric ECT referral by two uninvolved child psychiatrists. For clinical trials, supervision by the local Ethics Committee is essential. References Alexander, G.E., DeLong, M.R. & Strick, P.L. (1986) Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review Neuroscience, 9, 357–381. Barker, A.T., Jalinous, R. & Freeston, I.L. (1985) Non-invasive magnetic stimulation of human motor cortex. Lancet, 1 (8437), 1106–1107. Bejjani, B.P., Damier, P., Arnulf, I. et al. (1999) Transient acute depression induced by high-frequency deep-brain stimulation. The New England Journal of Medicine, 340, 1476–1480. Benabid, A.L., Pollak, P., Louveau, A., Henry, S. & de Rougemont, J. (1987) Combined (thalamotomy and stimulation) stereotactic surgery of the VIM thalamic nucleus for bilateral Parkinson disease. Applied Neurophysiology, 50 (1–6), 344–346. Berney, A., Vingerhoets, F., Perrin, A. et al. (2002) Effect on mood of subthalamic DBS for Parkinson’s disease: a consecutive series of 24 patients. Neurology, 59, 1427–1429. Bindman, L.J., Lippold, O.C.J. & Redfearn, J.W.T. (1964) The action of brief polarizing currents on the cerebral cortex of the rat (1) during current flow and (2) in the production of long-lasting after-effects. Journal of Physiology, 172, 369–382.
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Brothwell, D.R. (1963) Digging up Bones; the Excavation, Treatment and Study of Human Skeletal Remains. British Museum (Natural History), London, pp. 126. Brunoni, A.R., Boggio, P.S., De Raedt, R. et al. (2014) Cognitive control therapy and transcranial direct current stimulation for depression: a randomized, double-blinded, controlled trial. Journal of Affective Disorders, 162, 43–49. Carpenter, L.L., Janicak, P.G., Aaronson, S.T. et al. (2012) Transcranial magnetic stimulation (Tms) for major depression: a multisite, naturalistic, observational study of acute treatment outcomes in clinical practice. Depression and Anxiety, 29 (7), 587–596. Carron, R. et al. (2013) Closing the loop of deep brain stimulation. Frontiers in Systems Neuroscience, 7, 112. Cavuto, J. (2014) Depressing innovation. Neurotech Business Report. 2014 http://www.neurotechreports.com/pages/ publishersletterDec13.html Chen, A.C., Oathes, D.J., Chang, C. et al. (2013) Causal interactions between fronto-parietal central executive and default-mode networks in humans. Proceedings of the National Academy of Sciences of the United States of America, 110 (49), 19944–19949. Cho, S.S. & Strafella, A.P. (2009) rTMS of the left dorsolateral prefrontal cortex modulates dopamine release in the ipsilateral anterior cingulate cortex and orbitofrontal cortex. PLoS One, 4 (8), e6725. Connolly, R.K., Helmer, A., Cristancho, M.A., Cristancho, P. & O’Reardon, J.P. (2012) Effectiveness of transcranial magnetic stimulation in clinical practice post-FDA approval in the United States: results observed with the first 100 consecutive cases of depression at an academic medical center. Journal of Clinical Psychiatry, 73, e567–e573. Deco, G., Jirsa, V.K. & McIntosh, A.R. (2011) Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature Reviews Neuroscience, 12 (1), 43–56. Dymond, A.M., Coger, R.W. & Serafetinides, E.A. (1975) Intracerebral current levels in man during electrosleep therapy. Biological Psychiatry, 10, 101–104. Finger, S. (1994) Origins of Neuroscience. Oxford University Press, New York. Finger, S. (2000) Minds Behind the Brain: A History of the Pioneers and Their Discoveries. Oxford University Press, New York. Fox, M.D., Liu, H. & Pascual-Leone, A. (2012a) Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity. Neuroimage, 66C, 151–160. Fox, M.D., Buckner, R.L., White, M.P., Greicius, M.D. & Pascual-Leone, A. (2012b) Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biological Psychiatry, 72 (7), 595–603. Friston, K.J., Frith, C.D., Liddle, P.F. & Frackowiak, R.S. (1993) Functional connectivity: the principal-component analysis of large (PET) data sets. Journal of Cerebral Blood Flow and Metabolism, 13 (1), 5–14. Gallegos, J., Vaidya, P., D’Agati, D. et al. (2012) Decreasing adverse outcomes associated with unmodified ECT: suggestions and possibilities. Journal of ECT, 28, 77–81. Gradinaru, V., Mogri, M., Thompson, K.R., Henderson, J.M. & Deisseroth, K. (2009) Optical deconstruction of Parkinsonian neural circuitry. Science, 324 (5925), 354–359. Hariz, M.I., Blomstedt, P. & Zrinzo, L. (2010) Deep brain stimulation between 1947 and 1987: the untold story. Neurosurgical Focus, 29 (2), E1. Horwitz, B. (2003) The elusive concept of brain connectivity. Neuroimage, 19 (2 Pt 1), 466–470. Krack, P., Kumar, R., Ardouin, C. et al. (2001) Mirthful laughter induced by subthalamic nucleus stimulation. Movement Disorders, 16, 867–875. Huang, Y.Z., Edwards, M.J., Rounis, E., Bhatia, K.P. & Rothwell, J.C. (2005) Theta burst stimulation of the human motor cortex. Neuron, 45 (2), 201–206. Kronenbuerger, M., Fromm, C., Block, F., et al. (2006) On-demand deep brain stimulation for essential tremor: a report on four cases. Movement Disorders, 21 (3), 401–405. Kuhn, J., Hardenacke, K., Lenartz, D. et al. (2014) Deep brain stimulation of the nucleus basalis of Meynert in Alzheimer’s dementia. Molecular Psychiatry. [Epub ahead of print] Kulisevsky, J., Berthier, M.L., Gironell, A. et al. (2002) Mania following deep brain stimulation for Parkinson’s disease. Neurology, 59, 1421–1424.
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Kupsch, A., Tagliati, M., Vidailhet, M. et al. (2011) Early postoperative management of DBS in dystonia: programming, response to stimulation, adverse events, medication changes, evaluations, and troubleshooting. Movement Disorders, 26 (Suppl 1), S37–S53. Levkovitz Y., Isserles M., Padberg F., et al. (2014) Safety and efficacy of deep transcranial magnetic stimulation for major depression. World Psychiatry, in press. Liston, C., Chen, A.C., Zebley, B.D. et al. (2014) Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological Psychiatry, 76 (7), 517–526. Little, S., Pogosyan, A., Neal, S. et al. (2013) Adaptive deep brain stimulation in advanced Parkinson disease. Annals of Neurology, 74 (3), 449–457. Lyketsos, C.G., Targum, S.D., Pendergrass, J.C. & Lozano, A.M. (2012) Deep brain stimulation: a novel strategy for treating Alzheimer’s disease. Innovations in Clinical Neuroscience, 9 (11–12), 10–17. Martin, D.M., Liu, R., Alonzo, A. et al. (2013) Can transcranial direct current stimulation enhance outcomes from cognitive training? A randomized controlled trial in healthy participants. International Journal of Neuropsychopharmacology, 16 (9), 1927–1936. McClintock, S.M., Husain, M., Cullum, C.M. et al. The effects of an index course of magnetic seizure therapy and electroconvulsive therapy on verbal learning and memory. Abstract, ACNP meeting, 2013 McHugh, P.R.. Psychiatric misadventures. The American Scholar Autumn, 1992. O’Shea, M. (2013) The brain: Milestones of neuroscience. New Scientist, 218 (2911), 2–3. Pilitsis, J.G., Metman, L.V., Toleikis, J.R., Hughes, L.E., Sani, S.B. & Bakay, R.A. (2008) Factors involved in long-term efficacy of deep brain stimulation of the thalamus for essential tremor. Journal of Neurosurgery, 109, 640–646. Pfurtscheller, G. (1970) Changes in the evoked and spontaneous brain activity of man during extracranial polarization. Zeitschrift fur die gesamte experimentelle Medizin, 152, 284–293. Player, M.J., Taylor, J.L., Weickert, C.S. et al. (2013) Neuroplasticity in depressed individuals compared with healthy controls. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 38, 2101–2108. Reti, I.M. (2013) A rational insurance coverage policy for repetitive transcranial magnetic stimulation for major depression. Journal of ECT, 29 (2), e27–e28. Rosin, B. et al. (2011) Closed-loop deep brain stimulation is superior in ameliorating Parkinsonism. Neuron, 72 (2), 370–84. Rush, A.J., Trivedi, M.H., Wisniewski, S.R. et al. (2006) Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. The American Journal of Psychiatry, 163, 1905–1917. Saint-Cyr, J.A., Trepanier, L.L., Kumar, R. et al. (2000) Neuropsychological consequences of chronic bilateral stimulation of the subthalamic nucleus in Parkinson’s disease. Brain, 123, 2091–2108. Santos, F.J., Costa, R.M. & Tecuapetla, F. (2011) Stimulation on demand: closing the loop on deep brain stimulation. Neuron, 72 (2), 197–198. Sartorius, A., Kiening, K.L., Kirsch, P. et al. (2010) Remission of major depression under deep brain stimulation of the lateral habenula in a therapy-refractory patient. Biological Psychiatry, 67 (2), e9–e11. Schlaepfer, T.E., Bewernick, B.H., Kayser, S., Mädler, B. & Coenen, V.A. (2013) Rapid effects of deep brain stimulation for treatment-resistant major depression. Biological Psychiatry, 73 (12), 1204–1212. Segrave, R.A., Arnold, S., Hoy, K. & Fitzgerald, P.B. (2014) Concurrent cognitive control training augments the antidepressant efficacy of tDCS: a pilot study. Brain Stimulation, 7 (2), 325–331. Shih, L.C., LaFaver, K., Lim, C., Papavassiliou, E. & Tarsy, D. (2013) Loss of benefit in VIM thalamic deep brain stimulation (DBS) for essential tremor (ET): How prevalent is it? Parkinsonism and Related Disorders., 19, 676–679. Stillings, D. (1975) A survey of the history of electrical stimulation for pain to 1900. Medical Instrumentation, 9 (6), 255–259. Strafella, A.P., Paus, T., Barrett, J. & Dagher, A. (2001) Repetitive transcranial magnetic stimulation of the human prefrontal cortex induces dopamine release in the caudate nucleus. Journal of Neuroscience, 21 (15), RC157. Strafella, A.P., Paus, T., Fraraccio, M. & Dagher, A. (2003) Striatal dopamine release induced by repetitive transcranial magnetic stimulation of the human motor cortex. Brain, 126 (12), 2609–15. Tripathi, A., Winek, N., Goel, K. et al. (2014) Electroconvulsive therapy pre-treatment with low dose propofol: comparison with unmodified treatment. Journal of Psychiatric Research, 53, 173–179. Tufail, Y., Matyushov, A., Baldwin, N. et al. (2010) Transcranial pulsed ultrasound stimulates intact brain circuits. Neuron, 66, 681–694.
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Williams, N.R. & Okun, M.S. (2013) Deep brain stimulation (DBS) at the interface of neurology and psychiatry. Journal of Clinical Investigation, 123 (11), 4546–4556. Yau, J.M., Hua, J., Liao, D.A. & Desmond, J.E. (2013) Efficient and robust identification of cortical targets in concurrent TMS-fMRI experiments. Neuroimage, 76, 134–144. Zaghi, S., Acar, M., Hultgren, B., Boggio, P.S. & Fregni, F. (2010) Noninvasive brain stimulation with low-intensity electrical currents: putative mechanisms of action for direct and alternating current stimulation. Neuroscientist, 16 (3), 285–307.
PART A
BRAIN CIRCUITRY AND PLASTICITY
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A Balanced Mind: A Network Perspective on Mood and Motivation Brain Pathways Morten L. Kringelbach Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK Centre for Functionally Integrative Neuroscience (CFIN), University of Aarhus, Aarhus, Denmark Nuffield Department of Surgery, John Radcliffe Hospital, Oxford, UK
Introduction
The central premise of this chapter is that in order to more effectively treat disorders of mood and motivation, we need to develop a better understanding of the functional neuroanatomy of mood and motivation pathways as well as hedonic processing more generally. Importantly, malignant disorders of mood and motivation such as depression, drug addiction, chronic pain, and eating disorders are characterized by the decreased or missing ability to experience pleasure, anhedonia, which is perhaps best understood as a dysregulation of the brain’s pleasure networks. Thus, in order to help with these disorders, we have to further our understanding of the cortical and subcortical mechanisms involved in pleasure and hedonic processing in general. This chapter explores the evidence for the underlying brain mechanisms and principles of pleasure and hedonic processing in the human brain. This evidence comes from human neuroimaging, neuropsychology, and neurosurgery. In particular, this chapter concentrates on the network anatomy and physiology relevant to basal ganglia thalamocortical circuitry primarily regulating mood and motivation as well as the pathophysiologic changes in these networks that lead to their dysregulation and the development of conditions such as depression, eating disorders, and addiction.
Overview of the Study of Emotion and Mood
Emotion is central to human life and is intimately connected with consciousness. Yet, historically, the link with consciousness has led to a relative neglect of emotion as a subject of systematic scientific inquiry in comparison with other fields, such as cognition. However, the past few decades have seen a significant increase in research on emotion, leading to important new discoveries of the brain mechanisms involved. Importantly, it has become clear that a better understanding of the underlying brain mechanisms of emotion must rely on investigating reward and hedonic processing. The concept of emotion can usefully be subdivided into two components: (1) the emotional state that can be measured through physiological changes such as autonomic response and (2) feelings, seen as the subjective experience of emotion. The latter is linked with qualia and the hard problem of consciousness, that is to say, what is it like subjectively to experience an emotional state. How the brain gives rise to Brain Stimulation: Methodologies and Interventions, First Edition. Edited by Irving M. Reti. © 2015 John Wiley & Sons, Inc. Published 2015 by John Wiley & Sons, Inc.
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consciousness remains an unsolved problem, but it is becoming increasingly clear which brain areas are involved in producing and representing emotional states, which can also be studied in other animals. The findings from neuroimaging and anatomical evidence from lesions in humans and other higher primates have pointed to the role of several interconnected brain structures in emotion. An early attempt to synthesize the emotion literature was the theory proposed by James Papez (1937) where the cingulate cortex was seen as important for the experience of emotion, whereas emotional expression was governed by the hypothalamus, and these two structures were linked by the thalamus and the hippocampus. This theory was further elaborated by Paul MacLean with his proposal for the evolution of the triune primate brain with three functionally distinct systems, of which the limbic system was the one mediating emotion (MacLean 1949, 1990). The term limbic lobe (Lat. limbus, border) was proposed by Paul Broca in 1878 who coined the name for those structures surrounding the brain stem and corpus callosum on the medial walls of the brain (Broca 1878). Broca did not mention a specific role for the limbic lobe in emotion, and indeed subsequent research has found that the concept of emotion mediated by a unifying limbic system is too simplistic. These early pioneering theories were built on a paucity of experimental data, and with the recent flourishing of emotion research, and especially given the ever-increasing amount of correlational human neuroimaging data and causal brain stimulation, we are now in a much better position to evaluate which brain structures are crucial to emotion and hedonic processing. Overall, investigations of the normal and damaged human brain show that the most likely candidates in human brain structures for the processing and mediation of emotion and feelings can be found in a complex network including subcortical regions (nucleus accumbens, ventral pallidum, periaqueductal gray, amygdala) and cortical regions (the orbitofrontal, cingulate and insular cortices) (Lindquist et al. 2012). Core Affect: Wanting, Liking, and Learning
In order to better understand the complex states of emotion and motivation, it has proven beneficial to focus on their core affect components of reward and hedonic processing. Crucially, it has been argued that these core affect components are important for guiding the crucial survival-related decision-making involved in optimizing resource allocation of brain resources (Kringelbach 2005; Kringelbach and Berridge 2009). Historically, there has been a focus on drive and need states rather than core affect. Early drive theories of motivation proposed that need potentiated previously learned habits, and that need reduction strengthened new stimulus-response habit bonds (Hull 1951). This was then taken to mean that hedonic behavior is controlled by need states. But these theories do not, for example, explain why people still continue to eat when sated. This led to theories of incentive motivation where hedonic behavior is mostly determined by the incentive value of a stimulus or its capacity to function as a reward (Bindra 1978). Here, need states such as hunger are still important but work only indirectly on the stimulus’ incentive value. An important conceptual addition to this was alliesthesia, which is the principle of modulation of the hedonic value of a consummatory sensory stimulus by homeostatic factors (Cabanac 1971). The scientific study of hedonia (from the ancient Greek word hedone from the sweet taste of honey, hedus) has undergone substantial progress over the past ten years (Kringelbach and Berridge 2010). In particular, pleasure research has led to the important discovery in both humans and other animals that pleasure consists of multiple subcomponents and processes relating to the wanting, liking, and learning phases of the pleasure cycle (Berridge 1996; Kringelbach 2005; Kringelbach and Berridge 2009). Pleasures also vary over time and go through distinct cycles (see Figure 2.1) (Georgiadis and Kringelbach 2012; Kringelbach et al. 2012). Typically, we go through a phase of expectation, craving, or wanting for a reward, which sometimes leads to a phase of consummation or liking of the reward that can have a peak
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Pleasure
Engaging with food consumption Terminating food intake Initiating food foraging
Wanting
Liking
Learning
Time Figure 2.1 Pleasure cycle. The brain needs to optimize resource allocation for survival, and individuals are limited in the number of concurrent behaviors. Survival depends on the engagement with rewards and typically follows a cyclical time course common to many everyday moments of positive affect. Within this pleasure cycle rewards act as motivational magnets to initiate, sustain, and switch state. Typically, rewarding moments go through a phase of expectation or wanting for a reward, which sometimes leads to a phase of consummation or liking of the reward, which can have a peak level of pleasure (e.g., encountering a loved one, a tasty meal, sexual orgasm, drug rush, winning a gambling bet). This can be followed by a satiety or learning phase, where one learns and updates predictions for the reward. Here we propose that anhedonia can be conceptualized as specific deficits within this pleasure cycle. The various phases of the pleasure cycle have been the subject of active investigation with a recent focus on computational mechanisms underlying prediction, evaluation, and prediction error (Friston and Kiebel 2009; Zhang et al. 2009). Note also that a very few rewards might possibly lack a satiety phase. Suggested candidates for a brief or missing satiety phase have included money, some abstract rewards, and some drug and brain stimulation rewards that activate dopamine systems rather directly.
level of pleasure (e.g., orgasm). Consummation is invariably followed by a satiety or learning phase, where we learn and update our predictions for the reward (although learning can of course happen throughout the cycle). Hedonic processing thus consists of multifaceted psychological processes of which the nonconscious and conscious parts can be studied with a variety of methods. Examples of pleasure-elicited behavioral “liking” reaction are the affective orofacial expressions elicited by the hedonic impact of sweet tastes. These facial liking reactions were first described in newborn human infants (Steiner 1973, 1974; Steiner et al. 2001) and then extended to rodents (Grill and Norgren 1978a, b; Pfaffmann et al. 1977). Several studies have now shown that sweet tastes elicit positive facial liking expressions (i.e., rhythmic licking of lips) in human infants and in rats, whereas bitter tastes elicit facial “disliking” expressions (i.e., gapes.). Since facial liking reactions appear to be similar between humans and other mammals (Berridge 2000; Steiner et al. 2001), findings from animal studies are applicable and useful for our understanding of human pleasure. In humans, neuroimaging offers a powerful way to investigate the whole pleasure cycle in the human brain. One way to investigate liking is to take subjective hedonic ratings throughout a human neuroimaging experiment and then correlate these ratings with changes in activity in the human brain. This allows for a unique window on the hedonic processes evaluating the pleasantness of salient stimuli. Such measures are, however, only correlational in nature and will need to be combined with experiments offering causal inferences such as using brain stimulation techniques in patients (Kringelbach et al. 2007). The evidence from humans and other animals suggests a surprisingly high degree of substantial overlap among brain systems involved in various pleasures. The regions involved in the different aspects of hedonia are cortical regions (e.g., orbitofrontal, anterior cingulate, and insula cortices) and subcortical structures (nucleus accumbens, ventral pallidum, amygdala, and mesolimbic tegmentum) (see Figure 2.2). Yet, the progress in pleasure research using very precise brain manipulations has allowed researchers to start to determine the role of each of these regions. Kent Berridge and colleagues have demonstrated that there are so-called hedonic hotspots in the nucleus accumbens and ventral pallidum that can amplify or
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BRAIN STIMULATION: METHODOLOGIES AND INTERVENTIONS
Right Dorsal 6.2
250% 200% 125% No change 75%. These data together with other open-label studies suggest that the efficacy of VNS Therapy in DRE may improve over time (Morris and Mueller 1999; Murphy 1999; Kuba et al. 2003; Labar 2004; Spanaki et al. 2004; Uthman et al. 2004; Siddiqui et al. 2010), which is generally not seen with AEDs. However, results from long-term studies should be interpreted cautiously inasmuch as they lacked control groups and AED adjustments were allowed and may have contributed to improved seizure control. Determining the subset of patients with DRE who are most likely to experience improved seizure control with VNS Therapy is not yet possible (Labar 2004; Janszky et al. 2005; Tecoma and Iragui 2006; Elliott et al. 2011), though different studies have identified a variety of favorable prognostic factors (Labar et al. 1999; Patwardhan et al. 2000; Murphy et al. 2003; Englot et al. 2011; Colicchio et al. 2012), including lesional epilepsy and short duration of epilepsy. With regard to tolerability and safety, long-term studies of VNS Therapy in patients with DRE generally show improved tolerability over time (Morris and Mueller 1999). For example, 444 patients continued treatment after participating in a clinical study. The most commonly reported side effects at the end of the first year of treatment were voice alteration (29%), tingling sensation (12%), dyspnea (8%), and cough (8%), whereas the prevalence of these complaints decreased after 2 years to 19%, 4%, 3%, and 6%, and after 3 years to 50% decrease in seizure frequency; at 1 year, 21 of 31 patients had >50% reduction. Side effects were mild and transient, and quality-of-life (QOL) scores improved significantly during the first year of treatment. A unique feature of VNS Therapy for epilepsy is on-demand stimulation, which some patients find effective for attenuating or ending seizures, assuming that they perceive seizure onset and can utilize the magnet (Boon et al. 2001). In the E03 study, use of the active magnet among patients randomized to high stimulation terminated more seizures than the inactive magnet in the control group (21.3% versus 11.9%) (Morris 2003). Similarly, a case series of children reported that the majority could attenuate or terminate their seizures (Patwardhan et al. 2000). Outcomes of VNS Therapy Other Than Seizure Control
Epilepsy therapies are typically assessed for their impact on measures of QOL and mood. In most studies of VNS Therapy, QOL improved (Lundgren et al. 1998a; Morrow et al. 2000; Patwardhan et al. 2000; Cramer 2001; Gates et al. 2001; Helmers et al. 2001; Galli et al. 2003a; Murphy et al. 2003; Shahwan et al. 2009), especially but not exclusively in those who achieved the highest reduction in seizure frequency. Interestingly, given that improvement in seizure control appears to increase over time together with decreases in side effects, QOL also appears to increase (improve) over time. Some, not all, studies suggest that mood and other depressive symptoms in patients with DRE may improve with VNS Therapy (Elger et al. 2000; Harden et al. 2000; Hoppe et al. 2001). Three studies demonstrated mood improvements with VNS Therapy for up to 6 months (Elger et al. 2000; Harden et al. 2000; Klinkenberg et al. 2012b). Though different mood scales were used, two of these studies included adults with long-standing, poorly controlled partial-onset seizures, and in each study AEDs remained constant (Elger et al. 2000; Harden et al. 2000). Degree of seizure reduction and mood improvement were unrelated, and in one study, there was no correlation between the “dose” of the VNS treatment and mood improvement (“dose” was calculated by multiplying percent ‘on’ time by stimulus intensity) (Harden et al. 2000). Hoppe et al. used self-report questionnaires and evaluated changes in mood and health-related QOL following 6 months of treatment with VNS Therapy in 28 patients with stable AED regimens and low baseline depression scores (Hoppe et al. 2001). Improvements in tenseness, negative arousal, and dysphoria – but not of depression – were observed. VNS may also improve daytime alertness and vigilance and reduce daytime sleepiness, though it has the potential to exacerbate sleep apnea (Frost et al. 2001; Malow et al. 2001; Galli et al. 2003a; Rizzo et al. 2003). Interestingly, stimulation with current intensity