by Zachary Shapiro
The United States legal system places a great deal of importance on juries. With this faith comes a belief that juries are effective and reliable in determining the credibility of witnesses that testify in front of them. However, research has found that people, while generally good at lying, are terrible at detecting the lies of others. Scientific research has found that, in a face-to-face meeting, the average person is able to detect deception at only a slightly better than 50% rate, meaning that most people are no better at detecting deception than would be expected from pure guessing.
This tension has led courts to search for a technology-based method of lie detection, which could objectively improve on human’s natural inability to detect deception. While polygraphs have been around for a long time, there is tremendous (and well deserved) skepticism of this modality. In 2003, a National Academy of Sciences report found there was a startling lack of research in regards to the accuracy of polygraph machines under varying conditions. This study estimated that the accuracy of polygraphs was roughly 75%, but could be as high as 99% or as low as 55% depending on a variety of factors. These factors include the experience of the operator, the setting of the test (experimental vs. forensic), and what questioning format is employed.
The skepticism towards polygraphs partially explains the hope that one day, new and more accurate technology will replace them. Today, this enthusiasm is primarily aimed at the potential for functional neuroimaging to serve as an effective lie detector. Functional magnetic resonance imaging (fMRI) for lie detection is different from using a polygraph, in that neuroimaging measures the central (brain) rather than the peripheral (blood pressure, heart rate, respiration rate and galvanic skin response) correlates of nervous system activity. While, brain-based lie detection was pioneered in the late 1980s, using the method of EEG, fMRI is now touted as the preferred method, due to its superior ability to localize signals in the brain.
In recent years, as the technology has improved, numerous experiments have been conducted in order to test whether fMRI can be a useful tool in the detection of deception. Some studies have already found an ability to detect deception using fMRI to be in the correct rate of 95-99%, and under specific, laboratory controlled conditions, fMRI was able to distinguish lies from the truth in individual subjects with 76% to 90% accuracy.  Such studies help explain why the enthusiasm for fMRI-based lie detection has exploded in recent years. However, without an appropriate understanding of the limitations of this technology at this point in time, we risk advancing a modality that could bring with it more problems than solutions. As I have previously written, neuroimaging studies face key flaws that limit the potential to generalize the results widely, or adopt neuroimaging as an effective tool for lie detection at this stage in it development.
In my next post, I will highlight some of the problems with the use of fMRI as a means of lie detection, and will explore some of the evidentiary issues that have arisen when defendants attempt to introduce fMRI-based evidence for truth determinations.
 Vrij, A. Detecting lies and deceit: Pitfalls and opportunities. 2. Chichester, England: Wiley; 2008.
 Ekman P, O’Sullivan M. Who can catch a liar? American Psychologist. 1991; 46:913– 920.10.1037/0003-066X.46.9.913 [PubMed: 1958011]
 Lykken, D. (1998). A Tremor in the Blood: Uses and Abuses of the Lie Detector, 2d ed. New York: Perseus.
 Stern, PC., editor. The polygraph and lie detection. Report of the National Research Council Committee to Review the Scientific Evidence on the Polygraph. Washington, DC: The National Academies Press; 2003.
Langleben, Daniel D. and Moriarty, Jane Campbell, Using Brain Imaging for Lie Detection: Where Science, Law, and Policy Collide (March 1, 2012). Psychology, Public Policy, and Law, September 2012; Duquesne University School of Law Research Paper No. 2012-12.
 Rosenfeld JP, Cantwell B, Nasman VT, Wojdac V, Ivanov S, Mazzeri L. A modified, event-related potential-based guilty knowledge test. International Journal of Neuroscience. 1988;
 Ganis G, Rosenfeld JP, Meixner J, Kievit RA, Schendan HE. Lying in the scanner: Covert countermeasures disrupt deception detection by functional magnetic resonance imaging. Neuroimage. 2011; 55:312–319.10.1016/j.neuroimage.2010.11.025 [PubMed: 21111834]; Langleben DD, Loughead JW, Bilker WB, Ruparel K, Childress AR, Busch SI, et al. Telling truth from lie in individual subjects with fast event-related fMRI. Human Brain Mapping. 2005; 26:262–272.10.1002/hbm.20191 [PubMed: 16161128]