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Reference Guide on Neuroscience H E N RY T . G R E E L Y A N D A N T H O N Y D . W A G N E R Henry T. Greely, J.D., is Deane F. and Kate Edelman Johnson Professor of Law, Professor, by courtesy, of Genetics, and the Director of Center for Law and the Biosciences, Stanford University, Stanford, California. Anthony D. Wagner, Ph.D., is Associate Professor of Psychology and Neuroscience, Stanford University, Stanford, California. ConTenTs I. Introduction, 749 II. The Human Brain, 749 A. Cells, 750 B. Brain Structure, 754 C. Some Aspects of How the Brain Works, 759 III. Some Common Neuroscience Techniques, 761 A. Neuroimaging, 761 1. CAT scans, 762 2. PET scans and SPECT scans, 763 3. MRI—structural and functional, 766 B. EEG and MEG, 772 C. Other Techniques, 773 1. Lesion studies, 773 2. Transcranial magnetic stimulation (TMS), 774 3. Deep brain stimulation (DBS), 775 4. Implanted microelectrode arrays, 775 IV. Issues in Interpreting Study Results, 776 A. Replication, 777 B. Problems in Experimental Design, 777 C. The Number and Diversity of Subjects, 779 D. Applying Group Averages to Individuals, 780 E. Technical Accuracy and Robustness of Imaging Results, 781 F. Statistical Issues, 782 G. Possible Countermeasures, 783 747

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Reference Manual on Scientific Evidence V. Questions About the Admissibility and the Creation of Neuroscience Evidence, 784 A. Evidentiary Rules, 785 1. Relevance, 785 2. Rule 702 and the admissibility of scientific evidence, 785 3. Rule 403, 788 4. Other potentially relevant evidentiary issues, 789 B. Constitutional and Other Substantive Rules, 790 1. Possible rights against neuroscience evidence, 790 2. Possible rights to the creation or use of neuroscience evidence, 795 3. The Fourth Amendment, 796 VI. Examples of the Possible Uses of Neuroscience in the Courts, 796 A. Criminal Responsibility, 799 B. Lie Detection, 802 1. Issues involved in the use of fMRI-based lie detection in litigation, 803 2. Two cases involving fMRI-based lie detection, 805 3. fMRI-based lie detection outside the courtroom, 807 C. Detection of Pain, 807 VII. Conclusion, 811 References on Neuroscience, 812 748

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Reference Guide on Neuroscience I. Introduction Science’s understanding of the human brain is increasing exponentially. We know almost infinitely more than we did 30 years ago; however, we know almost nothing compared with what we are likely to know 30 years from now. The results of advances in understanding human brains—and of the minds they generate—are already beginning to appear in courtrooms. If, as neuroscience indicates, our mental states are produced by physical states of our brain, our increased ability to discern those physical states will have huge implications for the law. Lawyers already are introducing neuroimaging evidence as relevant to questions of individual respon- sibility, such as claims of insanity or diminished responsibility, either on issues of liability or of sentencing. In May 2010, parties in two cases sought to introduce neuroimaging in court as evidence of honesty; we are also beginning to see efforts to use it to prove that a person is in pain. These and other uses of neuroscience are almost certain to increase with our growing knowledge of the human brain as well as continued technological advances in accurately and precisely measuring the brain. This chapter strives to give judges some background knowledge about neuroscience and the strengths and weaknesses of its possible applications in litiga- tion in order to help them become better prepared for these cases.1 The chapter begins with a brief overview of the structure and function of the human brain. It then describes some of the tools neuroscientists use to understand the brain—tools likely to produce findings that parties will seek to introduce in court. Next, it discusses a number of fundamental issues that must be considered when interpreting neuroscientific findings. Finally, after discussing, in general, the issues raised by neuroscience-based evidence, the chapter concludes by analyzing a few illustrative situations in which neuroscientific evidence is likely to appear in court in the future. II. The Human Brain This abbreviated and simplified discussion of the human brain describes the cel- lular basis of the nervous system, the structure of the brain, and finally our current understanding of how the brain works. More detailed, but still accessible, informa- 1. The Law and Neuroscience Project, funded by the John D. and Catherine T. MacArthur Foundation, is preparing a book about law and neuroscience for judges, which should be available by 2011. A Primer on Neuroscience (Stephen Morse & Adina Roskies eds., forthcoming 2011). The Project has already published a pamphlet written by neuroscientists for judges, with brief discussions of issues relevant to law and neuroscience. A Judge’s Guide to Neuroscience: A Concise Introduction (M.S. Gazzaniga & J.S. Rakoff eds., 2010). One early book on a broad range of issues in law and neuroscience also deserves mention: Neuroscience and the Law: Brain, Mind, and the Scales of Justice (Brent Garland ed., 2004). 749

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Reference Manual on Scientific Evidence tion about the human brain can be found in academic textbooks and in popular books for general audiences.2 A. Cells Like most of the human body the nervous system is made up of cells. Adult humans contain somewhere between 50 trillion and 100 trillion human cells. Each of those cells is both individually alive and part of a larger living organism. Each cell in the body (with rare exceptions) contains each person’s entire complement of human genes—his or her genome. The genes, found on very long molecules of deoxyribonucleic acid (DNA) that make up a human’s 46 chromo- somes, work by leading the cells to make other molecules, notably proteins and ribonucleic acid (RNA). We now believe that there are about 23,000 human genes. Cells are different from each other not because they contain different genes but because they turn on and off different sets of genes. All human cells seem to use the same group of several thousand “housekeeping” genes that run the cell’s basic machinery, but skin cells, kidney cells, and brain cells differ in which other genes they use. Scientists count different numbers of “types” of human cells, with estimates ranging from a few hundred to a few thousand (depending largely on how narrowly or broadly one defines a cell type). The most important cells in the nervous system are called neurons. Neurons pass messages from one neuron to another in a complex way that appears to be responsible for brain function, conscious or otherwise. Neurons (Figure 1) come in many sizes, shapes, and subtypes (with their own names), but they generally have three features: a cell body (or “soma”), short extensions called dendrites, and a longer extension called an axon. The cell body contains the nucleus of the cell, which in turn contains the 46 chromosomes with the cell’s DNA. The dendrites and axons both reach out to make connec- tions with other neurons. The dendrites generally receive information from other neurons; the axons send information. Communication between neurons occurs at areas called synapses (Figure 2), where two neurons almost meet. At a synapse, the two neurons will come within 2. The Society for Neuroscience, the very large scholarly society that covers a wide range of brain science, has published a brief and useful primer about the human brain called Brain Facts. The most recent edition, published in 2008, is available free at www.sfn.org/index.aspx?pagename=brainfacts. Some particularly interesting books about various aspects of the brain written for a popular audience include Oliver W. Sacks, The Man Who Mistook His Wife for a Hat and Other Clinical Tales (1990); Antonio R. Damasio, Descartes’ Error: Emotion, Reason, and the Human Brain (1994); Daniel L. Schacter, Searching for Memory: The Brain, the Mind, and the Past (1996); Joseph E. LeDoux, The Emotional Brain: The Mysterious Underpinnings of Emotional Life (1996); Christopher D. Frith, Making Up the Mind: How the Brain Creates Our Mental World (2007); and Sandra Aamodt & Sam Wang, Welcome to Your Brain: Why You Lose Your Car Keys But Never Forget How to Drive and Other Puzzles of Everyday Life (2008). 750

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Reference Guide on Neuroscience Figure 1. Schematic of the typical structure of a neuron. Source: Quasar Jarosz at en.wikipedia. less than a micrometer (a millionth of a meter) of each other, with the presynaptic side, on the axon, separated from the postsynaptic side, on the dendrite, by a gap called the synaptic cleft. At synapses, when the axon (on the presynaptic side) “fires” (becomes active) it releases molecules, known as neurotransmitters, into the synaptic cleft. Some of those molecules are picked up by special receptors on the dendrite that is on the postsynaptic side of the cleft. More than 100 different neurotransmitters have been identified; among the best known are dopamine, serotonin, glutamate, and acetylcholine. Some of the neurotransmitters released into the synaptic cleft are picked up by special receptors on the postsynaptic side of the cleft by the dendrite. At the postsynaptic side of the cleft, neurotransmitters binding to the recep- tors can have a wide range of effects. Sometimes they cause the receiving (post- synaptic) neuron to “fire,” sometimes they suppress (inhibit) the postsynaptic neuron from firing, and sometimes they seem to do neither. The response of the receiving neuron is a complicated summation of the various messages it receives from multiple neurons that converge, through synapses, on its dendrites. A neuron that does fire does so by generating an electrical current that flows down (away from the cell body) the length of its axon. We normally think of electrical current as flowing in things like copper wiring. In that case, free electrons move down the wire. The electrical currents of neurons are more complicated. Molecules with a positive or negative electrical charge (ions) move through the neuron’s membrane and create differences in the electrical charge between the inside and outside of the neuron, with the current traveling along the axon, rather like a fire brigade passing buckets of water in only one direction 751

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Figure 2. Synapse. Communication between neurons occurs at the synapse, where the sending (presynaptic) and receiving (post- synaptic) neurons meet. When the presynaptic neuron fires, it releases neurotransmitters into the synaptic cleft, which bind to receptors on the postsynaptic neuron. 752 Source: From Carlson. Carlson, Neil R. Foundations of Physiological Psychology (with Neuroscience Animations and Student Study Guide CD-ROM), 6th. © 2005. Printed and electronically reproduced by permission of Pearson Education, Inc., Upper Saddle River, New Jersey.

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Reference Guide on Neuroscience down the line. Firing occurs in milliseconds. This process of moving ions in and out of the cell membrane requires that the cell use large amounts of energy. When the current reaches the end of the axon, it may or may not cause the axon to release neurotransmitters into the synaptic cleft. This complicated part-electrical, part-chemical system is how information passes from one neuron to another. The axons of human neurons are all microscopically narrow, but they vary enormously in length. Some are micrometers long; others, such as neurons run- ning from the base of the spinal cord to the toes, are several feet long. Longer axons tend to be coated with a fatty substance called myelin. Myelin helps insulate the axon and thus increases the strength and efficiency of the electrical signal, much like the insulation wrapped around a copper wire. (The destruction of this myelin sheathing is the cause of multiple sclerosis.) Axons coated with myelin appear white; thus areas of the nervous system that have many myelin-coated axons are referred to as “white matter.” Cell bodies, by contrast, look gray, and so areas with many cell bodies and relatively few axons make up our “gray matter.” White matter can roughly be thought of as the wiring that connects gray matter to the rest of the body or to other areas of gray matter. What we call nerves are really bundles of neurons. For example, we all have nerves that run down our arms to our fingers. Some of those nerves consist of neurons that pass messages from the fingers, up the arm, to other neurons in the spinal cord that then pass the messages on to the brain, where they are analyzed and experienced. This is how we feel things with our fingers. Other nerves are bundles of neurons that pass messages from the brain through the spinal cord to nerves that run down the arms to the fingers, telling them when and how to move. Neurons can connect with other neurons or with other kinds of cells. Neurons that control body movements ultimately connect to muscle cells—these are called motor neurons. Neurons that feed information into the brain start with specialized sensory cells (i.e., cells specialized for detecting different types of stimuli—light, touch, heat, pain, and more) that fire in response to the appro- priate stimulus. Their firings ultimately lead, directly or through other neurons, into the brain. These are sensory neurons. These neurons send information only in one direction—motor neurons ultimately from the brain, sensory neurons to the brain. The paralysis caused by, for example, severe damage to the spinal cord both prevents the legs from receiving messages to move that would come from the brain through the motor neurons and keeps the brain from receiving mes- sages from sensory neurons in the legs about what the legs are experiencing. The break in the spinal column prevents the messages from getting through, just as a break in a local telephone line will keep two parties from connecting. (There are, unfortunately, not yet any human equivalents to wireless service.) Estimates of the number of cells in a human brain vary widely, from a few hundred billion to several trillion. These cells include those that make up blood vessels and various connective tissues in the brain, but most of them are specialized brain cells. About 80 billion to 100 billion of these brain cells are neurons; the 753

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Reference Manual on Scientific Evidence other cells (and the source of most of the uncertainty about the number of cells) are principally another class of cells referred to generally as glial cells. Glial cells play many important roles in the brain, including, for example, producing and maintaining the myelin sheaths that insulate axons and serving as a special immune system for the brain. The full importance of glial cells is still being discovered; emerging data suggest that they may play a larger role in mental processes than as “support staff.” At this point, however, we concentrate on neurons, the brain structures they form, and how those structures work. B. Brain Structure Anatomists refer to the brain, the spinal cord, and a few other nerves directly connecting to the brain as the central nervous system. All the other nerves are part of the peripheral nervous system. This reference guide does not focus on the peripheral nervous system, despite its importance in, for example, assessing some aspects of personal injuries. We also, less fairly, ignore the central nervous system other than the brain, even though the spinal cord, in particular, plays an important role in modulating messages going into and coming out of the brain. The average adult human brain (Figure 3) weighs about 3 pounds and fills a volume of about 1300 cubic centimeters. If liquid, it would almost fill two standard wine bottles with a little space left over. Living brains have a consistency about like that of gelatin. Despite the softness of brains, they are made up of regular shapes and structures that are generally consistent from person to person. Just as every nondamaged or nondeformed human face has two eyes, two ears, Figure 3. Lateral (left) and mid-sagittal (right) views of the human brain. Source: Courtesy of Anthony Wagner. 754

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Reference Guide on Neuroscience one nose, and one mouth with standard numbers of various kinds of teeth, every normal brain has the same set of identifiable structures, both large and small. Neuroscientists have long worked to describe and define particular regions of the brain. In some ways this is like describing parcels of land in property documents, and, like property descriptions, several different methods are used. At the largest scale, the brain is often divided into three parts: the brain stem, the cerebellum, and the cerebrum.3 The brain stem is found near the bottom of the brain and is, in some ways, effectively an extension of the spinal cord. Its various parts play crucial roles in controlling the body’s autonomic functioning, such as heart rate and digestion. The brain stem also contains important regions that regulate processing in the cerebrum. For example, the substantia nigra and ventral tegmental area in the brain stem consist of critical neurons that generate the neurotransmitter dopamine. While the substantia nigra is crucial for motor control, the ventral tegmental area is important for learning about rewards. The loss of neurons in the substantia nigra is at the core of the movement problems of Parkinson’s disease. The cerebellum, which is about the size and shape of a squashed tennis ball, is tucked away in the back of the skull. It plays a major role in fine motor control and seems to keep a library of learned motor skills, such as riding a bicycle. It was long thought that damage to the cerebellum had little to no effect on a person’s personality or cognitive abilities, but resulted primarily in unsteady gait, difficulty in making precise movements, and problems in learning movements. More recent studies of patients with cerebellar damage and functional brain imaging studies of healthy individuals indicate that the cerebellum also plays a role in more cognitive functions, including supporting aspects of working memory, attention, and language. The cerebrum is the largest part of the human brain, making up about 85% of its volume. The cerebrum is found at the front, top, and much of the back of the human brain. The human brain differs from the brains of other mammals mainly because it has a vastly enlarged cerebrum. There are several different ways to identify parts of, or locations in, the cere- brum. First, the cerebrum is divided into two hemispheres—the famous left and right brain. These two hemispheres are connected by tracts of white matter—of axons—most notably the large connection called the corpus callosum. Oddly, the right hemisphere of the brain generally receives messages from and controls the movements of the left side of the body, while the left hemisphere receives mes- sages from and controls the movements of the right side of the body. Each hemisphere of the cerebrum is divided into four lobes (Figure 4): The frontal lobe in the front of the cerebrum (behind the forehead), the parietal lobe at 3. The brain also is sometimes divided into the forebrain, midbrain, and hindbrain. This classification is useful for some purposes, particularly in describing the history and development of the vertebrate brain, but it does not entirely correspond to the categorization of cerebrum, brain stem, and cerebellum, and it is not used in this reference guide. 755

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Reference Manual on Scientific Evidence Figure 4. Lobes of a hemisphere. Each hemisphere of the brain consists of four lobes––the frontal, parietal, temporal, and occipital lobes. Source: http://commons.wikimedia.org/wiki/File:Gray728.svg. This image is in the public domain because its copyright has expired. This applies worldwide. the top and toward the back, the temporal lobe on the side (just behind and above the ears), and the occipital lobe at the back. Thus, one could describe a particular region as lying in the left frontal lobe—the frontal lobe of the left hemisphere. The surface of the cerebrum consists of the cortex, which is a sheet of gray matter a few millimeters thick. The cortex is not a smooth sheet in humans, but rather is heavily folded with valleys, called sulci (“sulcus” in the singular), and bulges, called gyri (“gyrus”). The sulci and gyri have their own names, and so a location can be described as in the inferior frontal gyrus in the left frontal lobe. These folds allow the surface area of the cortex, as well as the total volume of the cortex, to be much greater than in other mammals, while still allowing it to fit inside our skulls, similar to the way the many folds of a car’s radiator give it a very large surface area (for radiating away heat) in a relatively small space. The cerebral cortex is extraordinarily large in humans compared with other species and is clearly centrally involved in much of what makes our brains spe- cial, but the cerebrum contains many other important subcortical structures that we share with other vertebrates. Some of the more important areas include the thalamus, the hypothalamus, the basal ganglia, and the amygdala. These areas all connect widely, with the cortex, with each other, and with other parts of the brain to form complex networks. The functions of all these areas are many, complex, and not fully understood, but some facts are known. The thalamus seems to act as a main relay that carries 756

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Reference Guide on Neuroscience information to and from the cerebral cortex, particularly for vision, hearing, touch, and proprioception (one’s sense of the position of the parts of one’s body). It also is, importantly, involved in sleep, wakefulness, and consciousness. The hypothalamus has a wide range of functions, including the regulation of body temperature, hunger, thirst, and fatigue. The basal ganglia are a group of regions in the brain that are involved in motor control and learning, among other things. They seem to be strongly involved in selecting movements, as well as in learning through reinforcement (as a result of rewards). The amygdala appears to be impor- tant in emotional processing, including how we attach emotional significance to particular stimuli. In addition, many other parts of the brain, in the cortex or elsewhere, have their own special names, usually with Latin or Greek roots that may or may not seem descriptive today. The hippocampus, for example, is named for the Greek word for seahorse. For most of us, these names will have no obvious rhyme or rea- son, but merely must be learned as particular structures in the brain—the superior colliculus, the tegmentum, the globus pallidus, the substantia nigra, the cingulate cortex, and more. All of these structures come in pairs, with one in the left hemi- sphere and one in the right hemisphere; only the pineal gland is unpaired. Brain atlases include scores of names for particular structures or regions in the brain and detailed information about the structures or regions. Some of these smaller structures may have special importance to human behavior. The nucleus accumbens, for example, is a small subcortical region in each hemisphere of the cerebrum that appears important for reward processing and motivation. In experiments with rats that received stimulation of this region in return for pressing a lever, the rats would press the lever almost to the exclu- sion of any other behavior, including eating. The nucleus accumbens in humans appears linked to appetitive motivation, responding in anticipation of primary rewards (such as pleasure from food and sex) and secondary rewards (such as money). Through interactions with the orbital frontal cortex and dopamine- generating neurons in the midbrain (including the ventral tegmental area), the nucleus accumbens is considered part of a “reward network.” With a hypothesized role in addictive behavior and in reward computations, more broadly, this putative reward network is a topic of considerable ongoing research. All of these various locations, whether defined broadly by area or by the names of specific structures, can be further subdivided using directions: front and back, up and down, toward the middle, or toward the sides. Unfortunately, the directions often are not expressed in a straightforward manner, and several differ- ent terminological conventions exist. Locations toward the front or back of the brain can be referred to as either anterior or posterior or as rostral or caudal (liter- ally, toward the nose, or beak, or the tail). Locations toward the bottom or top of the brain are termed inferior or superior or, alternatively, as ventral or dorsal (toward the stomach or toward the back). A location toward the middle of the brain is called medial; one toward the side is called lateral. Thus, different loca- 757

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Reference Manual on Scientific Evidence B. Lie Detection The use of neuroscience methods for lie detection probably has received more attention than any other issue raised in this chapter.56 This is due in part to the cultural interest in lie detection, dating back in its technological phase nearly 90 years to the invention of the polygraph.57 But it is also due to the fact that two commercial firms currently are offering fMRI-based lie detection services for sale in the United States: Cephos and No Lie MRI.58 Currently, as far as we know, 56. For a technology whose results have yet to be admitted in court, the legal and ethical issues raised by fMRI-based lie detection have been discussed in an amazingly long list of scholarly publications from 2004 to the present. An undoubtedly incomplete list follows: Nita Farahany, supra note 27; Brown & Murphy, supra note 20; Anthony D. Wagner, supra note 12; Frederick Schauer, Can Bad Science Be Good Evidence?: Neuroscience, Lie-Detection, and the Mistaken Conflation of Legal and Scientific Norms, 95 Cornell L. Rev. 1191 (2010); Frederick Schauer, Neuroscience, Lie-Detection, and the Law: A Contrarian View, 14 Trends Cog. Sci. 101 (2010); Emilio Bizzi et al., Using Imaging to Identify Deceit: Scientific and Ethical Questions (2009); Joelle Anne Moreno, The Future of Neuroimaged Lie Detection and the Law, 42 Akron L. Rev. 717 (2009); Julie Seaman, Black Boxes: fMRI Lie Detection and the Role of the Jury, 42 Akron L. Rev. 931 (2009); Jane Campbell Moriarty, Visions of Deception: Neuroimages and the Search for Truth, 42 Akron L. Rev. 739 (2009); Dov Fox, supra note 27; Benjamin Holley, It’s All in Your Head: Neurotechnological Lie Detection and the Fourth and Fifth Amendments, 28 Dev. Mental Health L. 1 (2009); Brian Reese, Comment: Using fMRI as a Lie Detector—Are We Lying to Ourselves? 19 Alb. L.J. Sci. & Tech. 205 (2009); Cooper Ellenberg, Student Article: Lie Detection: A Changing of the Guard in the Quest for Truth in Court? 33 Law & Psychol. Rev. 139 (2009); Julie Seaman, Black Boxes, 58 Emory L.J. 427 (2008); Matthew Baptiste Holloway, supra note 27; William Federspiel, supra note 27; Greely & Illes, supra note 28; Sarah E. Stoller & Paul R. Wolpe, supra note 27; Mark Pettit, FMRI and BF Meet FRE: Braining Imaging and the Federal Rules of Evidence, 33 Am. J.L. & Med. 319 (2007); Jonathan H. Marks, Interrogational Neuroimaging in Counterterrorism: A “No-Brainer” or a Human Rights Hazard? 33 Am. J.L. & Med. 483 (2007); Leo Kittay, Admissibility of fMRI Lie Detection: The Cultural Bias Against “Mind Reading” Devices, 72 Brook. L. Rev. 1351, 1355 (2007); Jeffrey Bellin, The Significance (if Any) for the Federal Criminal Justice System of Advances in Lie Detector Technology, Temp. L. Rev. 711 (2007); Henry T. Greely, The Social Consequences of Advances in Neuroscience: Legal Problems; Legal Perspectives, in Neuroethics: Defining the Issues in Theory, Practice and Policy 245 (Judy Illes ed., 2006); Charles N.W. Keckler, Cross-Examining the Brain: A Legal Analysis of Neural Imaging for Credibility Impeachment, 57 Hastings L.J. 509 (2006); Archie Alexander, Functional Magnetic Resonance Imaging Lie Detection: Is a “Brainstorm” Heading Toward the “Gatekeeper”? 7 Hous. J. Health L. & Pol’y (2006); Michael S. Pardo, supra note 27; Erich Taylor, supra note 27; Paul R. Wolpe et al., Emerging Neurotechnologies for Lie-Detection: Promises and Perils, 5 Am. J. Bioethics 38, 42 (2005); Henry T. Greely, Premarket Approval Regulation for Lie Detection: An Idea Whose Time May Be Coming, 5 Am. J. Bioethics 50–52 (2005); Sean Kevin Thompson, Note: The Legality of the Use of Psychiatric Neuroimaging in Intelligence Interrogation, 90 Cornell L. Rev. 1601 (2005); Henry T. Greely, Prediction, Litigation, Privacy, and Property: Some Possible Legal and Social Implications of Advances in Neuroscience, in Neuroscience and the Law: Brain, Mind, and the Scales of Justice 114–56 (Brent Garland ed., 2004); and Judy Illes, A Fish Story? Brain Maps, Lie Detection, and Personhood, 6 Cerebrum 73 (2004). 57. An interesting history of the polygraph can be found in Ken Alder, The Lie Detectors: The History of an American Obsession (2007). Perhaps the best overall discussion of the polygraph, including some discussion of its history, is found in the National Research Council report, supra note 14, commissioned in the wake of the Wen Ho Lee case, on the use of the technology for screening. 58. The Web sites for the two companies are at Cephos, www.cephoscorp.com (last visited July 3, 2010); and No Lie MRI, http://noliemri.com (last visited July 3, 2010). 802

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Reference Guide on Neuroscience evidence from fMRI-based lie detection has not been admitted into evidence in any court, but it was offered—and rejected—in two cases, United States v. Semrau59 and Wilson v. Corestaff Services, L.P.,60 in May 2010.61 This section will begin by analyzing the issues raised for courts by this technology and then will discuss these two cases, before ending with a quick look at possible uses of this kind of technology outside the courtroom. 1. Issues involved in the use of fMRI-based lie detection in litigation Published research on fMRI and detecting deception dates back to about 2001.62 As noted above, to date between 20 and 30 peer-reviewed articles from about 15 laboratories have appeared claiming to find statistically significant correlations between patterns of brain activation and deception. Only a handful of the pub- lished studies have looked at the accuracy of determining deception in individual subjects as opposed to group averages. Those studies generally claim accuracy rates of between about 75% and 90%. No Lie MRI has licensed the methods used by one laboratory, that of Dr. Daniel Langleben at the University of Pennsylvania; Cephos has licensed the method used by another laboratory, that of Dr. Frank A. Kozel, first at the Medical University of South Carolina and then at the University of Texas Southwestern Medical Center. (The method used by a British researcher, Dr. Sean Spence, has been used on a British reality television show.) All of these studies rely on research subjects, typically but not always col- lege students, who are recruited for a study of deception. They are instructed to answer some questions truthfully in the scanner and to answer other questions inaccurately.63 In the Langleben studies, for example, right-handed, healthy, male 59. No. 07-10074 M1/P, Report and Recommendation (W.D. Tenn. May 31, 2010). 60. 2010 NY slip op. 20176, 1 (N.Y. Super. Ct. 2010); 900 N.Y.S.2d 639; 2010 N.Y. Misc. LEXIS 1044 (2010). 61. In early 2009, a motion to admit fMRI-based lie detection evidence, provided by No Lie MRI, was made, and then withdrawn, in a child custody case in San Diego. The case is discussed in a prematurely entitled article, Alexis Madrigal, MRI Lie Detection to Get First Day in Court, WIRED SCI. (Mar. 16, 2009), available at http://blog.wired.com/wiredscience/2009/03/noliemri.html (last visited July 3, 2010). A somewhat similar method of using EEG to look for signs of “recognition” in the brain was admitted into one state court hearing for postconviction relief at the trial court level in Iowa in 2001, and both it and another EEG-based method have been used in India. As far as we know, evidence from the use of EEG for lie detection has not been admitted in any other U.S. cases. See supra note 28. 62. The most recent reviews of the scientific literature on this subject are Anthony D. Wagner, supra note 12; and S.E. Christ et al., The Contributions of Prefrontal Cortex and Executive Control to Deception: Evidence from Activation Likelihood Estimate Meta-Analyses, 19 Cerebral Cortex 2557 (2009). See also Greely & Illes, supra note 28 (for discussion of the articles through early 2007). The following discussion is based largely on those sources. 63. At least one fMRI study has attempted to investigate self-motivated lies, told by subjects who were not instructed to lie, but who chose to lie for personal gain. Joshua D. Greene & Joseph M. Paxton, Patterns of Neural Activity Associated with Honest and Dishonest Moral Decisions, 106 Proc. Nat’l Acad. Sci. 12,506 (2009). The experiment was designed to make it easy for subjects to realize they 803

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Reference Manual on Scientific Evidence University of Pennsylvania undergraduates were shown images of playing cards while in the scanner and asked to indicate whether they saw a particular card. They were instructed to answer truthfully except when they saw one particular card. Some of Kozel’s studies used a different experimental paradigm, in which the subjects were put in a room and told to take either a watch or a ring. When asked in the scanner separately whether they had taken the watch and then whether they had taken the ring, they were to reply “no” in both cases—truthfully once and falsely the other time. When analyzed in various ways, the fMRI results showed statistically different patterns of brain activation (small changes in BOLD response) when the subjects were lying and when they were telling the truth. In general, these studies are not guided by a consistent hypothesis about which brain regions should be activated or deactivated during truth or decep- tion. The results are empirical; they see particular patterns that differ between the truth state and the lie state. Some have argued that the patterns show greater mental effort when deception is involved; others have argued that they show more impulse control when lying. Are fMRI-based lie detection methods accurate? As a class of experiments, these studies are subject to all the general problems discussed in Section IV regard- ing fMRI scans that might lead to neuroscience evidence. So far there are only a few studies involving a limited number of subjects. (The method used by No Lie MRI seems ultimately to have been based on the responses of four right-handed, healthy, male University of Pennsylvania undergraduates.64) There have been, to date, no independent replications of any group’s findings. The experience of the research subjects in these fMRI studies of deception seems to be different from “lying” as the court system would perceive it. The subjects knew they were involved in research, they were following orders to lie, and they knew that the most harm that could come to them from being detected in a lie might be lesser payment for taking part in the experiment. This seems hard to compare to a defendant lying about participating in a murder. More fundamen- tally, it is not clear how one could conduct ethical but realistic experiments with lie detection. Research subjects cannot credibly be threatened with jail if they do not convince the researcher of the truth of their lies. Only a handful of researchers have published studies showing reported accu- racy rates with individual subjects and only with a small number of subjects.65 would be given more money if they lied about how many times they correctly predicted a coin flip. Investigators could not, however, determine if a subject lied in any particular trial. 64. Daniel D. Langleben et al., Telling Truth from Lie in Individual Subjects with Fast Event-Related fMRI, 26 Hum. Brain Mapping 262, 267 (2005). 65. See discussion in Anthony D. Wagner, supra note 12, at 29–35. Wagner analyzes 11 peer- reviewed, published papers. Seven come from Kozel’s laboratory; three come from Langleben’s. The only exception is a paper from John Cacciopo’s group, which concludes “ [A]lthough fMRI may permit investigation of the neural correlates of lying, at the moment it does not appear to provide a very accurate marker of lying that can be generalized across individuals or even perhaps across types 804

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Reference Guide on Neuroscience Some of the studies used complex and somewhat controversial statistical tech- niques. And although subjects in at least one experiment were invited to try to use countermeasures against being detected, no specific countermeasures were tested. Beyond the scientific validity of these techniques lie a host of legal questions. How accurate is accurate enough for admissibility in court or for other legal sys- tem uses? What are the implications of admissible and accurate lie detection for the Fourth, Fifth, Sixth, and Seventh Amendments? Would jurors be allowed to consider the failure, or refusal, of a party to take a lie detector test? Would lie detection be available in discovery? Would each side get to do its own tests—and who would pay? Accurate lie detection could make the justice system much more accurate. Incorrect convictions might become rare; so might incorrect acquittals. Accurate lie detection also could make the legal system much more efficient. It seems likely that far fewer cases would go to trial if the witnesses could expect to have their veracity accurately determined. Inaccurate lie detection, on the other hand, holds the potential of ruining the innocent and immunizing the guilty. It is at least daunting to remember some of the failures of the polygraph, such as the case of Aldrich Ames, a Soviet (and then Russian) mole in the Central Intelligence Agency, who passed two Agency poly- graph tests while serving as a paid spy.66 The courts already have begun to decide whether and how to use these new methods of lie detection in the judicial process; the rest of society also will soon be forced to decide on their uses and limits. 2. Two cases involving fMRI-based lie detection On May 31, 2010, U.S. Magistrate Judge Tu M. Pham of the Western District of Tennessee issued a 39-page report and recommendation on the prosecution’s motion to exclude evidence from an fMRI-based lie detection report by Cephos in the case of United States v. Semrau.67 The report came after a hearing on May 13–14 featuring testimony from Steve Laken, CEO of Cephos, for admission, and from two experts arguing against admission. (The district judge adopted the magistrate’s report during the trial.) The defendant in this case, a health professional accused of defrauding Medi- care, offered as evidence a report from Cephos stating that he was being truthful of lies by the same individuals.” G. Monteleone et al., Detection of Deception Using fMRI: Better Than Chance, But Well Below Perfection, 4 Soc. Neurosci. 528 (2009). However, that study only looked at one brain region at a time, and it did not test combinations or patterns, which might have improved the predictive power. 66. See Senate Select Committee on Intelligence, Assessment of the Aldrich H. Ames Espionage Case and Its Implications for U.S. Intelligence (1994). 67. See supra note 59. The district court judge assigned to the case had a scheduling conflict on the date of the hearing on the prosecution’s motion, and so the hearing was held before a magistrate judge from that district. 805

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Reference Manual on Scientific Evidence when he answered a set of questions about his actions and knowledge concerning the alleged crimes. Judge Pham first analyzed the motion under Rule 702, using the Daubert criteria. He concluded that the technique was testable and had been the subject of peer-reviewed publications. On the other hand, he concluded that the error rates for its use in realistic situations were unknown. Furthermore, he found there were no standards for its appropriate use. To the extent that the publications relied on by Cephos to establish its reliability constituted such standards, those standards had not actually been followed in the tests of the defendant. Cephos actually scanned Dr. Semrau 2 times on 1 day, asking questions about one aspect of the criminal charges during the first scan and then about another aspect in the second scan. The company’s subsequent analysis of those scans indicated that the defendant had been truthful in the first scan but deceptive in the second scan. Cephos then scanned him a third time, several days later, on the second subject but with revised questions, and concluded that he was telling the truth that time. Nothing in the publications relied upon by Cephos indicated that the third scan was appropriate. Finally, Judge Pham found that the method was not generally accepted in the relevant scientific community as sufficiently reliable for use in court, citing several publications, including some written by the authors whose methods Cephos used. The magistrate judge then examined the motion under Rule 403 and found that the potential prejudicial effect of the evidence outweighed its probative value. He noted that the test had been conducted without the government’s knowledge or participation, in a context where the defendant risked nothing by taking the test—a negative result would never be disclosed. He noted the jury’s central role in determining credibility and considered the likelihood that the lie detection evidence would be a lengthy and complicated distraction from the jury’s central mission. Finally, he noted that the probative value of the evidence was greatly reduced because the report only gave a result concerning the defendant’s general truthfulness when responding to more than 10 questions about the events but did not even purport to say whether the defendant was telling the truth about any particular question. Earlier that month, a state trial court judge in Brooklyn excluded another Cephos lie detection report in a civil case, Wilson v. Corestaff Services, L.P.68 This case involved a claim by a former employee under state law that she had been subject to retaliation for reporting sexual harassment. The plaintiff offered evi- dence from a Cephos report finding that her main witness was truthful when he described how defendant’s management said it would retaliate against the plaintiff. That case did not involve an evidentiary hearing or, indeed, any expert tes- timony. The judge decided the lie detection evidence was not appropriate under New York’s version of the Frye test, noting that, in New York, “courts have advised that the threshold question under Frye in passing on the admissibility 68. Wilson v. Corestaff Services, L.P., supra note 60. 806

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Reference Guide on Neuroscience of expert’s testimony is whether the testimony is ‘within the ken of the typical juror.’”69 Because credibility is a matter for the jury, the judge concluded that this kind of evidence was categorically excluded under New York’s version of Frye. He also noted that “even a cursory review of the scientific literature demonstrates that the plaintiff is unable to establish that the use of the fMRI test to determine truth- fulness or deceit is accepted as reliable in the relevant scientific community.”70 3. fMRI-based lie detection outside the courtroom Lie detection might have applications to litigation without ever being introduced in trials. As is the case today with the polygraph, the fact that it is not generally admissible in court might not stop the police or the prosecutors from using it to investigate alleged crimes. Similarly, defense counsel might well use it to attempt to persuade the authorities that their clients should not be charged or should be charged with lesser offenses. One could imagine the same kinds of pretrial uses of lie detection in civil cases, as the parties seek to affect each other’s percep- tions of the merits of the case. Such lie detection efforts could also affect society, and the law, outside of litigation. One could imagine prophylactic lie detection at the beginning of con- tractual relations, seeking to determine whether the other side honestly had the present intention of complying with the contract’s terms. One can also imagine schools using lie detection as part of investigations of student misconduct or par- ents seeking to use lie detection on their children. The law more broadly may have to decide whether and how private actors can use lie detection, determining whether, for example, to extend to other contexts—or to weaken or repeal—the Employee Polygraph Protection Act.71 The current fMRI-based methods of lie detection provide one kind of pro- tection for possible subjects—they are obvious. No one is going to be put into an MRI for an hour and asked to respond, repeatedly, to questions without realizing something important is going on. Should researchers develop less obtrusive or obvious methods of neuroscience-based lie detection, we will have to deal with the possibilities of involuntary and, indeed, surreptitious lie detection. C. Detection of Pain No matter where an injury occurs and no matter where it seems to hurt, pain is felt in the brain.72 Without sensory nerves leading to the brain from a body 69. Id. at 6, citing People v. Cronin, 60 N.Y.2d 430, 458 N.E.2d 351, 470 N.Y.S.2d 110 (1983). 70. See Wilson, supra note 60, at 7. 71. See supra text accompanying note 32. 72. See Brain Facts, supra note 2, at 19–21, 49–50, which includes a useful brief description of the neuroscience of pain. 807

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Reference Manual on Scientific Evidence region, there is usually no experience of pain. Without the brain machinery and functioning to process the signal, no pain is perceived. Pain turns out to be complicated—even the common pain that is experienced from an acute injury to, say, an arm. Neurons near the site of the injury called nociceptors transmit the pain signal to the spinal cord, which relays it to the brain. But other neurons near the site of the injury will, over time, adapt to affect the pain signal. Cells in the spinal cord can also modulate the pain signal that is sent to the brain, making it stronger or weaker. The brain, in turn, sends signals down to the spinal cord that cause or, at least, affect these modulations. And the actual sensation of pain—the “ouch”—takes place in the brain. The immediate and localized sensation is processed in the somatosensory cortex, the brain region that takes sensory inputs from different body parts (with each body part getting its own portion of the somatosensory cortex) and pro- cesses them into a perceived sensation. The added knowledge that the sensation is painful seems to require the participation of other regions of the brain. Using fMRI and other techniques, some researchers have identified what they call the “pain matrix” in the brain, regions that are activated when experimental subjects, in scanners, are exposed to painful stimuli. The brain regions identified as part of the so-called pain matrix vary from researcher to researcher, but generally include the thalamus, the insula, parts of the anterior cingulate cortex, and parts of the cerebellum.73 Researchers have run experiments with subjects in the scanner receiving painful or not painful stimuli and have attempted to find activation patterns that appear when pain is perceived and that do not appear when pain is absent. (The subjects usually are given nonharmful painful stimuli such as having their skin touched with a hot metal rod or coated with a pepper-derived substance that causes a burning sensation.) Some have reported substantial success, detect- ing pain in more than 80% of the cases.74 Other studies have found a positive correlation between the degree of activation in the pain matrix and the degree of subjective pain, both as reported by the subject and as possibly indicated by the heat of the rod or the amount of the painful substance—the higher the tem- perature or the concentration of the painful substance, the greater the average activation in the pain matrix.75 Other neuroscience studies of individual pain look not at brain function dur- ing painful episodes but at brain structure. Some researchers, for example, claim that different regions of the brain have different average size and neuron densities 73. A good review article on the uses of fMRI in studying pain is found in David Borsook & Lino R. Becerra, Breaking Down the Barriers: fMRI Applications in Pain, Analgesia and Analgesics, 2 Molecular Pain 30 (2006). 74. See, e.g., Irene Tracey, Imaging Pain, 101 Brit J. Anaesth. 32 (2008). 75. See, e.g., Robert C. Coghill et al., Neural Correlates of Interindividual Differences in the Subjective Experience of Pain, 100 Proc. Nat’l Acad. Sci. 8538 (2003). 808

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Reference Guide on Neuroscience in patients who have had long-term chronic pain than in those who have not had such pain.76 Pain is clearly complicated. Placebos, distractions, or great need can some- times cause people not to sense, or perhaps not to notice, pain that could other- wise be overwhelming. Similarly, some people can become hypersensitive to pain, reporting severe pain when the stimulus normally would be benign. Amputees with phantom pain—the feeling of pain in a limb that has been gone for years— have been scanned while reporting this phantom pain. They show activation in the pain matrix. In some fMRI studies, people who have been hypnotized to feel pain, even when there is no painful stimulus, show activation in the pain matrix.77 And in one fMRI study, subjects who reported feeling emotional distress, as a result of apparently being excluded from a “game” being played among research subjects, also showed, on average, statistically significant activation of the pain matrix.78 Pain also plays an enormous role in the legal system.79 The existence and extent of pain is a matter for trial in hundreds of thousands of injury cases each year. Perhaps more importantly, pain figures into uncounted workers’ compensa- tion claims and Social Security disability claims. Pain is often difficult to prove, and the uncertainty of a jury’s response to claimed pain probably keeps much liti- gation alive. We know that the tests for pain currently presented to jurors, judges, and other legal decisionmakers are not perfect. Anecdotes of and the assessments by pain experts both are convincing that some nontrivial percentage of success- ful claimants are malingering and only pretending to feel pain; a much greater percentage may be exaggerating their pain. A good test for whether a person is feeling pain, and, even better, a “scien- tific” way to measure the amount of that pain—at least compared to other pains felt by that individual, if not to pain as perceived by third parties—could help resolve a huge number of claims each year. If such pain detection were reliable, it would make justice both more accurate and more certain, leading to faster, and 76. See, e.g., Vania Apkarian et al., Chronic Back Pain Is Associated with Decreased Prefrontal and Thalamic Gray Matter Density, 24 J. Neurosci. 10,410 (2004); see also Arne May, Chronic Pain May Change the Structure of the Brain, 137 Pain 7 (2008); Karen D. Davis, Recent Advances and Future Prospects in Neuroimaging of Acute and Chronic Pain, 1 Future Neurology 203 (2006). 77. Stuart W. Derbyshire et al., Cerebral Activation During Hypnotically Induced and Imagined Pain, 23 NeuroImage 392 (2004). 78. Naomi I. Eisenberg, Does Rejection Hurt? An fMRI Study of Social Exclusion, 302 Science 290 (2003). 79. The only substantial analysis of the legal implications of using neuroimaging to detect pain is found in Adam J. Kolber, Pain Detection and the Privacy of Subjective Experience, 33 Am. J.L. & Med. 433 (2007). Kolber expands on that discussion in interesting ways in Adam J. Kolber, The Experiential Future of the Law, 60 Emory L.J. 585, 595–601 (2011). The possibility of such pain detection was briefly discussed earlier in two different 2006 publications: Henry T. Greely, Prediction, Litigation, Privacy, and Property: Some Possible Legal and Social Implications of Advances in Neuroscience, supra note 56, at 141–42; and Charles Keckler, Cross-Examining the Brain, supra note 56, at 544. 809

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Reference Manual on Scientific Evidence cheaper, resolution of many claims involving pain. The legal system, as well as the honest plaintiffs and defendants within it, would benefit. A greater understanding of pain also might lead to broader changes in the legal system. For example, emotional distress often is treated less favorably than direct physical pain. If neuroscience were to show that, in the brain, emotional distress seemed to be the same as physical pain, the law might change. Perhaps more likely, if neuroscience could provide assurance that sincere emotional pain could be detected and faked emotional distress would not be rewarded, the law again might change. Others have argued that even our system of criminal pun- ishment might change if we could measure, more accurately, how much pain different punishments caused defendants, allowing judges to let the punishment fit the criminal, if not the crime.80 A “pain detector” might even change the practice of medicine in legally relevant ways, by giving physicians a more certain way to check whether their patients are seeking controlled substances to relieve their own pain or whether they are seeking them to abuse or to sell for someone else to abuse. In at least one case, a researcher who studies the neuroscience of pain was retained as an expert witness to testify regarding whether neuroimaging could pro- vide evidence that a claimant was, in fact, feeling pain. The case settled before the hearing.81 In another case, a prominent neuroscientist was approached about being a witness against the admissibility of fMRI-based evidence of pain, but, before she had decided whether to take part, the party seeking to introduce the evidence changed its mind. This issue has not, as of the time of this writing, reached the courts yet, but lawyers clearly are thinking about these uses of neuroscience. (And note that in some administrative contexts, the evidentiary rules will not apply in their full rigor, possibly making the admission of such evidence more likely.) Do either functional or structural methods of detecting pain work and, if so, how well? We do not know. These studies share many of the problems outlined in Section IV. The studies are few in number, with few subjects (and usually sets of subjects that are not very diverse). The experiments—usually involving giv- ing college students a painful stimulus—are different from the experience of, for example, older people who claim to have low back pain. Independent replication is rare, if it exists at all. The experiments almost always report that, on average, the group shows a statistically significant pattern of activation that differs depending on whether they are receiving the painful stimulus, but the group average does not in itself tell us about the sensitivity or specificity of such a test when applied to individuals. And the statistical and technical issues are daunting. In the area of pain, the issue of countermeasures may be the most interest- ing, particularly in light of the experiments conducted with hypnotized subjects. Does remembered pain look the same in an fMRI scan as currently experienced 80. Adam J. Kolber, How to Improve Empirical Dessert, 75 Brook. L. Rev. 429 (2009). 81. Greg Miller, Brain Scans of Pain Raise Questions for the Law, 323 Science 195 (2009). 810

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Reference Guide on Neuroscience pain? Does the detailed memory of a kidney stone pain look any different from the present sensation of low back pain? Can a subject effectively convince himself that he is feeling pain and so appear to the scanner to be experiencing pain? The answers to these questions are clear—we do not yet know. Pain detection also would raise legal questions. Could a plaintiff be forced to undergo a “pain scan”? If a plaintiff offered a pain scan in evidence, could the defendant compel the plaintiff to undergo such a scan with the defendant’s machine and expert? Would it matter if the scan were itself painful or even dan- gerous? Who would pay for these scans and for the experts to interpret them? Detecting pain would be a form of neuroscience evidence with straight- forward and far-reaching applications to the legal system. Whether it can be done, and, if so, how accurately it can be done, remain to be seen. So does the legal system’s reaction to this possibility. VII. Conclusion Atomic physicist Niels Bohr is credited with having said “It is always hard to predict things, especially the future.”82 It seems highly likely that the massively increased understanding of the human brain that neuroscience is providing will have significant effects on the law and, more specifically, on the courts. Just what those effects will be cannot be accurately predicted, but we hope that this guide will provide some useful background to help judges cope with whatever neuro- science evidence comes their way. 82. This quotation has been attributed to many people, especially Yogi Berra, but Bohr seems to be the most likely candidate, even though it does not appear in anything he published. See discussion in Henry T. Greely, Trusted Systems and Medical Records: Lowering Expectations, 52 Stan. L. Rev. 1585, 1591–92 n.9 (2000). One of the authors, however, recently had a conversation with a scientist from Denmark, who knew the phrase (in Danish) as an old Danish saying and not something original with Bohr. 811

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Reference Manual on Scientific Evidence References on Neuroscience Fundamental Neuroscience (Larry R. Squire et al. eds., 3d ed. 2008). Eric R. Kandel et al., Principles of Neural Science (4th ed. 2000). The Cognitive Neurosciences (Michael S. Gazzaniga ed., 4th ed. 2009). 812