Can Current Technology Identify Liars?by Nisha Cooch, PhD | March 5, 2014
Identifying deception is something humans have attempted to do for centuries. Initial techniques, such as facial expression interpretation, were developed without technology. Later, simple technologies, such as the polygraph, were designed to detect physiological changes consistent with the autonomic arousal that often accompanies the act of lying. More recently, a powerful technique, functional magnetic resonance imaging (fMRI), has gained popularity as a potential lie detector and is sometimes used commercially for this purpose.
fMRI detects changes in blood flow, and because more active brain areas experience enhanced blood flow, fMRI can provide information about neural activity level. Because the technique has been used successfully in neuroscience research focused on mapping functionality, the idea arose that fMRI should be useful in identifying the function of lying. Consistent with this notion, studies have shown that differences in brain activation revealed through fMRI can facilitate the identification of falsehoods. Further, a recent meta-analysis found a high degree of consistency among studies as to the areas of the brain involved in lying. These areas, located largely in the prefrontal cortex, are important for executive functioning.
If we contemplate the cognitive process of lying, the involvement of executive functions is intuitive. Specifically, while voluntarily lying, one must keep track of two sets of circumstances: those consistent with the truth, and those consistent with the lie. This requirement would certainly increase cognitive load and the activation of relevant brain areas. However, individual brain differences can produce inconsistent activity patterns. For example, a recent study showed that when criminals with antisocial personality disorder lied, they lacked the pattern of prefrontal activity that has consistently been observed in healthy volunteers.
Even when considering lying only in those who lack psychiatric illness, detecting lies through fMRI is complicated by several factors. First, whereas lying may necessitate enhanced cognitive processing, such cognitive processing can occur independent of dishonesty. Further, if one intends to lie, the resulting cognitive load is not necessarily eased while that person tells the truth. Accordingly, studies have found that those being dishonest demonstrate more activity in areas of the brain associated with executive functioning both when telling the truth and when lying.
Another complicating factor is that not all lies are equivalent. Though someone committed to telling the truth may be burdened with a smaller cognitive load, liars may be able to make their lies less cognitively laborious so that the activity associated with their dishonesty resembles activity normally associated with honesty. For example, researchers have shown that the patterns of brain activity associated with well rehearsed lies diverge from those associated with spontaneous lies.
As with the commercial use of fMRI in strategic marketing, use of fMRI for lie detection remains controversial and has yet to be deemed admissible in a court of law. Though fMRI is an effective tool for elucidating brain function, much more research is required to determine if this technique will provide a reliable method for revealing dishonesty.
Christ SE, Van Essen DC, Watson JM, Brubaker LE, & McDermott KB (2009). The contributions of prefrontal cortex and executive control to deception: evidence from activation likelihood estimate meta-analyses. Cerebral cortex (New York, N.Y. : 1991), 19 (7), 1557-66 PMID: 18980948
Davatzikos C, Ruparel K, Fan Y, Shen DG, Acharyya M, Loughead JW, Gur RC, & Langleben DD (2005). Classifying spatial patterns of brain activity with machine learning methods: application to lie detection. NeuroImage, 28 (3), 663-8 PMID: 16169252
Farah MJ, Hutchinson JB, Phelps EA, & Wagner AD (2014). Functional MRI-based lie detection: scientific and societal challenges. Nature reviews. Neuroscience, 15 (2), 123-31 PMID: 24440904
Ganis G, Kosslyn SM, Stose S, Thompson WL, & Yurgelun-Todd DA (2003). Neural correlates of different types of deception: an fMRI investigation. Cerebral cortex (New York, N.Y. : 1991), 13 (8), 830-6 PMID: 12853369
Greene JD, & Paxton JM (2009). Patterns of neural activity associated with honest and dishonest moral decisions. Proceedings of the National Academy of Sciences of the United States of America, 106 (30), 12506-11 PMID: 19622733
Heeger DJ, & Ress D (2002). What does fMRI tell us about neuronal activity? Nature reviews. Neuroscience, 3 (2), 142-51 PMID: 11836522
Jiang W, Liu H, Liao J, Ma X, Rong P, Tang Y, & Wang W (2013). A functional MRI study of deception among offenders with antisocial personality disorders. Neuroscience, 244, 90-8 PMID: 23578713
Jueptner M, & Weiller C (1995). Review: does measurement of regional cerebral blood flow reflect synaptic activity? Implications for PET and fMRI. NeuroImage, 2 (2), 148-56 PMID: 9343597
Kozel FA, Johnson KA, Mu Q, Grenesko EL, Laken SJ, & George MS (2005). Detecting deception using functional magnetic resonance imaging. Biological psychiatry, 58 (8), 605-13 PMID: 16185668
Antifeminism – An Online Trend
Poor Social Judgment – An Aspect of Schizophrenia
Brain Trickery – Seeing in Slow Motion
Swear Your Pain Away
Memory Manipulation – Promises and Perils
The Phantom Sound Of Tinnitus
Thinking Slow About Thinking Fast – Part IV – The Framing Effect
Treating Children and Teens Diagnosed with Schizophrenia
Welcome to the new Brain Blogger! We just completed a complete redesign of our desktop and mobile Brain Blogger sites. Powered by the web-design expertise... READ MORE →
Do not miss out ever again. Subscribe and get latest Brain Blogger articles straight to your inbox.
Like what you read? Give to Brain Blogger sponsored by GNIF with a tax-deductible donation.Make A Donation