title: Using Brain Imaging for Lie Detection: Where Science, Law and Research Policy Collide.
abstract: Progress in the use of functional magnetic resonance imaging (fMRI) of the brain to evaluate deception and differentiate lying from truth-telling has created anticipation of a breakthrough in the search for technology-based methods of lie detection. In the last few years, litigants have attempted to introduce fMRI lie detection evidence in courts. This article weighs in on the interdisciplinary debate about the admissibility of such evidence, identifying the missing pieces of the scientific puzzle that need to be completed if fMRI-based lie detection is to meet the standards of either legal reliability or general acceptance. We believe that theDaubert's"known error rate" is the key concept linking the legal and scientific standards. We posit that properly-controlled clinical trials are the most convincing means to determine the error rates of fMRI-based lie detection and confirm or disprove the relevance of the promising laboratory research on this topic. This article explains the current state of the science and provides an analysis of the case law in which litigants have sought to introduce fMRI lie detection. Analyzing the myriad issues related to fMRI lie detection, the article identifies the key limitations of the current neuroimaging of deception science as expert evidence and explores the problems that arise from using scientific evidence before it is proven scientifically valid and reliable. We suggest that courts continue excluding fMRI lie detection evidence until this potentially useful form of forensic science meets the scientific standards currently required for adoption of a medical test or device. Given a multitude of stakeholders and, the charged and controversial nature and the potential societal impact of this technology, goodwill and collaboration of several government agencies may be required to sponsor impartial and comprehensive clinical trials that will guide the development of forensic fMRI technology.
authors.affiliation: Associate Professor, University of Pennsylvania Perelman School of Medicine.
authors.forename: Daniel D
authors.initials: DD
authors.lastname: Langleben
authors.forename: Jane Campbell
authors.initials: JC
authors.lastname: Moriarty