by E Bizzi · 2009 · Cited by 31 — the discussion with a clear description of fMRI, its physiological basis, the An Introduction to A brief history of human functional brain mapping.
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AMERICAN ACADEMY OF ARTS & SCIENCES UsingImaging to Identify Deceit Scientificand EthicalQuestions Emilio Bizzi, Steven E. Hyman, Marcus E. Raichle, Nancy Kanwisher,Elizabeth A. Phelps,Stephen J.Morse, Walter Sinnott-Armstrong, Jed S. Rakoff, and Henry T. Greely AMERICAN ACADEMY OF ARTS & SCIENCES USING IMAGING TO IDENTIFY DECEIT: SCIENTIFIC AND ETHICAL QUESTIONS AMERICAN ACADEMY OF ARTS & SCIENCES truth_Cover:ocCover5stripe 5/20/2009 2:39 PM Page 1
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© 2009 by the American Academy of Arts and Sciences All rights reserved. ISBN#: 0-87724-077-9 The views expressed in this volume are those held by each contributor and are not necessarily those of the Officers and Fellows of the American Academy of Arts and Sciences. Please direct inquiries to: American Academy of Arts and Sciences 136 Irving Street Cambridge, MA02138-1996Telephone: (617) 576-5000 Fax: (617) 576-5050 Email: aaas@amacad.org Web: www.amacad.org
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Contents1INTRODUCTIONImaging Deception Emilio Bizzi and Steven E. Hyman3CHAPTER 1An Introduction to Functional Brain Imaging in the Context of Lie Detection Marcus E. Raichle 7CHAPTER 2The Use of fMRI in Lie Detection: What Has Been Shown and What Has Not Nancy Kanwisher14CHAPTER 3Lying Outside the Laboratory: The Impact of Imagery and Emotion on the Neural Circuitry of Lie Detection Elizabeth A. Phelps23CHAPTER 4Actions Speak Louder than Images Stephen J. Morse35CHAPTER 5Neural Lie Detection in Courts Walter Sinnott-Armstrong 40CHAPTER 6Lie Detection in the Courts: The Vain Search for the Magic Bullet Jed S. Rakoff 46CHAPTER 7Neuroscience-Based Lie Detection: The Need for Regulation Henry T. Greely 56CONTRIBUTORS
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1Can the relatively new technique of functional magnetic resonance imaging (fMRI) detect deceit? A symposium sponsored by the American Academy of Arts and Sciences,the McGovern Institute at the Massachusetts Institute of Technology (MIT), and Harvard Universitytook on this question by exam- ining the scientific support for using fMRI as well as the legal and ethical questions raised when machine-based means are employed to identify deceit. Marcus Raichle, a professor at Washington University in St. Louis, opens the discussion with a clear description of fMRI, its physiological basis, the methodology underlying the extraction of images, and,most important, the use of image averaging to establish correlations between the fiimagesfland aspects of behavior. While averaging techniques are highly effective in the characterization of functional properties of different brain areas, images ob- tained from a single individual are finoisy,fl a fact that clearly touches upon the reliability of the extracted data and a fortiorimakes detecting deceit a questionable affair. Nancy Kanwisher, a professor at MIT, discusses papers that present sup- posedly direct evidence of the efficacy of detecting deceit with fMRI, but dismisses their conclusions. Kanwisher notes that there is an insurmountable problem with the experimental design of the studies she analyzes. She points out that by necessity the tested populations in the studies consisted of volun- teers, usually cooperative students who wereasked to lie. For Kanwisher this experimental paradigm bears no relationship tothe real-world situation of somebody brought to court and accused of a serious crime. Kanwisher™s conclusions are shared by Elizabeth Phelps, a professor at New York University.Phelps points out that two cortical regionsŠthe para- hippocampal cortex and the fusiform gyrusŠdisplay different activity in rela- tion to familiarity. The parahippocampal cortex shows more activityfor less familiar faces, whereas the fusiform gyrus is more active for familiar faces. However, these neat distinctions can unravel when imagined memories are generated by subjects involved in emotionally charged situations. Phelps points out that the brain regions important to memory do not differentiate between imagined memories and those based on events in the real world. In addition, the perceptual details of memories are affected by emotional states. INTRODUCTIONImaging DeceptionEMILIO BIZZI AND STEVEN E. HYMAN
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USINGIMAGINGTOIDENTIFYDECEIT 2Phelps™s compelling description of how imagination, emotions, and mis-perceptions all play a role in shaping memories can be briefly expressed as fibrains do not lie:people do.flThis point is echoed by Stephen Morse,who begins his presentation by stating fiBrains do not commit crimes. Acting peo- ple do.flMorse, a professor at the University of Pennsylvania,takes a skepti- cal view of the potential contributions of neuroscience in the courtroom. Hebelieves that behavioral evidence is usually more useful and informative than information based on brain science, and that when neuroimaging data and behavioral evidence conflict, the behavioral evidence trumps imaging. Morse worries that admitting imaging in the courtroom might sway finaivefl judges and jurors to think that the brain plays a ficausalfl role in a crime. He repeatedly warns that if causation excuses behavior then no one can ever be considered responsible. Walter Sinnott-Armstrong, a professor at Dartmouth College, is also un- enthusiastic about the use of fMRI to detect deceit. His concern is that the error rates in fMRI are significant and that determining error rates is not a simple task. For this reason he believes that evidence from neural lie detection efforts should not be allowed in court. Jed Rakoff, a U.S. district judge,shares Sinnott-Armstrong™s concern about error rates and finds that fMRI-based evidence may be excluded from trials under the Federal Rules of Evidence. Rakoff argues that the golden path to discovering truth is the traditional one of exposing witnesses to cross-exam- ination. He doubts that meaningful correlations between lying and brain images can be reliably established. In addition, he notes that the law recog- nizes many kinds of liesŠfor example, lies of omission, fiwhite lies,fland half- truthsŠand asks whether brain imaging can come close to distinguishing among these complex behavioral responses. Clearly not, he concludes, but traditional cross-examination might do the job. Henry Greely, a professor at Stanford Law School, discusses the consti- tutional and ethical issues raised by fMRI lie detection. He cites as concerns the problems related to the scientific weakness of some fMRI studies, the dis- agreement among the investigators about which brain regions are associated with deception, the limitations of pooled studies, and the artificiality of ex- perimental design.The authors of these seven essays express a dim view of lie detection with fMRI. They also consider the widely used polygraph and conclude that both it and fMRI are unreliable. Often in science when a new technique such as fMRI appears, the scien-tists who promote its use argue that, yes, problems exist but more research will, in the end, give us the magic bullet. Perhaps. In the case of lie detec- tion through fMRI, however, two sets of problems seem insurmountable: 1) problems of research design, which Kanwisher argues no improvement in imaging technology is likely to address; and 2) problems of disentangling emotions, memory,and perception, which, Phelps notes, are processed in thesame region of the brain and thus are commingled.
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USINGIMAGINGTOIDENTIFYDECEIT 4these properties had been pursued for several decades in chemistry laborato- ries using a technique called nuclear magnetic resonance. When this technique was applied to the human body and images began to emerge, the name was changed to fimagnetic resonance imagingfl to assuage concerns about radio- activity that might mistakenly arise because of the use of the term nuclear. Functional MRI(fMRI) has become the dominant mode of imaging function in the human brain.At the heart of functional brain imaging is a relationship between blood flow to the brain and the brain™s ongoing demand for energy. The brain™s voracious appetite for energy derives almost exclusively from glucose, which in the brain is broken down to carbon dioxide and water. The brain is depen- dent on a continuing supply of both oxygen and glucose delivered in flowing blood regardless of moment-to-moment changes in an individual™s activities. For over one hundred years scientists have known that when the brain changes its activity as an individual engages in various tasks the blood flow in- creases to the areas of the brain involved in those tasks. What came as a great surprise was that this increase in blood flow is accompanied by an increase in glucose use but not oxygen consumption. As a result, areas of the brain tran- siently increasing their activity during a task contain blood with increased oxy- gen content (i.e., the supply of oxygen becomes greater than the demand for oxygen). This observation, which has received much scrutiny from research- ers, paved the way for the introduction of MRIas a functional brain tool. By going back to the early research of Michael Faraday in England and, later, Linus Pauling in the United States, researchers realized that hemoglo- bin, the molecules in human red blood cells that carry oxygen from the lungs to the tissue, had interesting magnetic properties. When hemoglobin is carry- ing a full load of oxygen, it can pass through a magnetic field without caus- ing any disturbance. However, when hemoglobin loses oxygen to the tissue, it disrupts any magnetic field through which it passes. MRIis based on the use of powerful magnetic fields, thousands of times greater than the earth™s magnetic fields. Under normal circumstances when blood passes through an organ like the brain and loses oxygen to the tissue, the areas of veins that are draining oxygen-poor blood show up as little dark lines in MRI images, reflect- ing the loss of the MRIsignal in those areas. Now suppose that a sudden in- crease in blood flow locally in the brain is not accompanied by an increase in oxygen consumption. The oxygen content of these very small draining veins increases. The magnetic field in the area is restored, resulting in a local in- crease in the imaging signal. This phenomenon was first demonstrated with MRIby Seiji Ogawa at Bell Laboratories in New Jersey. He called the phe- nomenon the fiblood oxygen level dependentfl (BOLD) contrast of MRIand advocated its use in monitoring brain function. As a result researchers now have fMRIusing BOLDcontrast, a technique that is employed thousands of times daily in laboratories throughout the world. A standard maneuver in functional brain imaging over the last twenty-five years has been to isolate changes in the brain associated with particular tasks by subtracting images taken in a control state from the images taken duringthe performance of the task in which the researcher is interested. The control
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state is often carefully chosen so as to contain most of the elements of the task of interest save that which is of particular interest to the researcher. For exam- ple,to fiisolatefl areas of the brain concerned with reading words aloud, one might select as the control task passively viewing words. Having eliminated areas of the brain concerned with visual word perception, the resulting fidif- ference imagefl would contain only those areas concerned with reading aloud. Another critical element in the strategy of functional brain imaging is theuse of image averaging. A single difference image obtained from one individ- ual appears finoisy,fl nothing like the images usually seen in scientific articles or the popular press. Image averaging is routinely applied to imaging data and usually involves averaging data from a group of individuals. While this technique is enormously powerful in detecting common features of brain function across people, in the process it completely obscures important indi- vidual differences. Where individual differences are not a concern, this is not a problem. However, in the context of lie detection researchers and others are specifically interested in the individual. Thus, where functional brain imaging is proposed for the detection of deception, it must be clear that the imaging strategy to be employed will provide satisfactory imaging data for valid interpretation (i.e., images of high statistical quality). 1LESSONS FROM THE POLYGRAPH In 2003,the National Academy of Sciences (NAS) made a series of recom- mendations in its report on The Polygraph and Lie Detection.Although thesesrecommendations were primarily spawned by a consideration of the polygraph, they are relevant to the issues raised by the use of functional brain imaging as a tool for the detection of deception.2Most people think of specific incidents or crimes when they think of liedetection. For example, an act of espionage has been committed and a sus- pect has been arrested. Under these circumstances the polygraph seems to perform above chance. The reason for this, the NAS committee believed, was something that psychologists have called the fibogus pipelinefl: If a person sin- cerely believed a given object (say a chair attached to electrical equipment) was a lie detector and that person was wired to the object and had commit- ted a crime, a high probability exists (much greater than chance) that under interrogation the person would confess to the crime. The confession would have nothing to do with the basic scientific validity of the technique (i.e., the chair attached to electrical equipment) and everything to do with the individ- ual™s belief in the capability of the device to detect a lie. However, contrary to the belief that lie detection techniques such as the polygraph are most com- monly used to detect the lies of the accused, by far the most important use of these techniques in the United States is in employee screening, pre-employ- ment, and retention in high-security environments. The U.S. government performs tens of thousands of such studies each year in its various security 5FUNCTIONALBRAINIMAGING 1. For a more in-depth explanation of functional brain imaging, see Raichle (2000); and Raichle and Mintun (2006).2. I was a member of the NAScommittee that authored the report.
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USINGIMAGINGTOIDENTIFYDECEIT 6agencies and secret national laboratories. This is a sobering fact given the con- cerns raised by the NASreport about the use of the polygraph in screening. As a screening technique the polygraph performs poorly and would likely falsely incriminate many innocent employees while missing the small number of spies in their midst. The NAScommittee could find no available and prop- erly tested substitute, including functional brain imaging, that could replace the polygraph.The NAScommittee found many problems with the scientific data it re- viewed. The scientific evidence on means of lie detection was of poor quality with a lack of realism, and studies were poorly controlled, with few tests of validity. For example, the changes monitored (e.g., changes in skin conduc- tance, respiration, and heart rate) were not specific to deception. To compound the problem, studies often lacked a theory relating the monitored responses to the detection of truthfulness. Changes in cardiac output, peripheral vascu- lar resistance, and other measures of autonomic function were conspicuous by their absence. Claims with regard to functional brain imaging hinged for the most part on dubious extrapolations from group averages. Countermeasures (i.e., strategies employed by a subject to fibeat the poly- graphfl) remain a subject clouded in secrecy within the intelligence commu- nity. Yet information on such measures is freely available on the Internet! Re- gardless, countermeasures remain a challenge for many techniques, although one might hold some hope that imaging could have a unique role here. For example, any covert voluntary motor or cognitive activity employed by a sub- ject would undoubtedly be associated with predictable changes in functional brain imaging signals. At present we have no good ways of detecting deception despite our very great need for them. We should proceed in acquiring such techniques and tools in a manner that will avoid the problems that have plagued the detec- tion of deception since the beginning of recorded history. Expanded research should be administered by organizations with no operational responsibility for detecting deception. This research should operate under normal rules of sci- entific research with freedom and openness of communication to the extent possible while protecting national security. Finally, the research should vigor- ously explore alternatives to the polygraph, including functional brain imaging. REFERENCESNational Academy of Sciences. 2003. The polygraph and lie detection.Washington, DC: National Research Council. Raichle, M. E. 2008. A brief history of human brain mapping. Trends in Neuroscience(S0166-2236(08)00265-8[pii]10.1016/j.tins.2008.11.001).Raichle, M. 2000. A brief history of human functional brain mapping. In Brain mapping: The systems,ed. A. Toga and J. Mazziotta. San Diego: Academic Press. Raichle, M. E., and M. A. Mintun. 2006. Brain work and brain imaging.Annual Review of Neuroscience29:449Œ476.
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7Can you tell what somebody is thinking just by looking at magnetic resonance imaging (MRI) data from their brain? 1My colleagues and I have shown thata part of the brain we call the fifusiform face areafl is most active when a per- son looks at faces (Kanwisher et al. 1997). A separate part of the brain is most active when a person looks at images of places (Epstein and Kanwisher 1998). People can selectively activate these regions during mental imagery. If a sub- ject closes her eyes while in an MRI scanner and vividly imagines a group of faces, she turns on the fusiform face area. If the same subject vividly imagines a group of places, she turns on the place area. When my colleagues and I first got these results, we wondered how far we could push them. Could we tell just by looking at the fMRI data what someone was thinking? We decided to run an experiment to determine whether we could tell in a single trial whether a subject was imagining a face or a place (O™Craven and Kanwisher 2000).My collaborator Kathy O™Craven scanned the subjects, and once every twelve seconds said the name of a famous person or a familiar place. The sub- ject was instructed to form a vivid mental image of that person or place. After twelve seconds Kathy would say, in random order, the name of another per- son or place. She then gave me the fMRI data from each subject™s face and place areas. Figure 1 shows the data from one subject. The x-axis shows time, and the y-axis shows the magnitude of response in the face area (black) and the place area (gray). The arrows indicate the times at which instructions were given to the subject. My job was to look at these data and determine for each trial whether the subject was imagining a face or a place. Just by eyeballing the data, I correctly determined in over 80 percent of the trials whether the sub- ject was imagining faces or places. I worried for a long time before we pub- lished these data that people might think we could use an MRI to read their minds. Would they not realize the results obtained in my experiment were for CHAPTER 2The Use of fMRI in LieDetection: What Has Been Shown and What Has NotNANCY KANWISHER1. This article is based on remarks made at the American Academy of Arts and Sciences™s conference on February 2, 2007.
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