Functional MRI-based lie detection: scientific and societal challenges

Farah, Martha J.; Hutchinson, J. Benjamin; Phelps, Elizabeth A.; Wagner, Anthony D.

doi:10.1038/nrn3665

Cited by 171 publications

(209 citation statements)

References 56 publications

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“…To the extent that imaging cannot provide help with high-stake problems, the public should be protected from claims that it can. For example, a seemingly 'scientific' method for detecting lies or diagnosing psychiatric disorders 66,97 has a strong appeal to the general public who cannot be expected to appreciate the gap between what is claimed and what is established fact.…”

Section: Boxmentioning

confidence: 99%

“…Lie detection is one example that has been pursued in legal contexts, although it has not so far been admitted into US courts and has yet to demonstrate validity, reliability or resistance to countermeasures outside of the laboratory 66 . Another application concerns pain: brain-based biomarkers for pain would help discriminate real suffering from malingering-a pivotal issue in many lawsuits-and have been admitted as evidence in at least one US case 67 .…”

Section: Human Neuroscience In the Courtroommentioning

confidence: 99%

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Progress and challenges in probing the human brain

Poldrack

Farah

2015

Nature

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248

165

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Section: Boxmentioning

confidence: 99%

Section: Human Neuroscience In the Courtroommentioning

confidence: 99%

Progress and challenges in probing the human brain

Poldrack

Farah

2015

Nature

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248

165

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“…One of the most significant open questions is whether memory decoding is vulnerable to "countermeasures": strategies deployed to mask memory signals and "beat" detection tests (Farah et al, 2014). Rissman et al (2010) reported indirect evidence suggesting a vulnerability to strategic goal states, because the ability to detect previously encountered from novel faces was reduced to near chance when participants' memory was implicitly, rather than explicitly, probed.…”

Section: Introductionmentioning

confidence: 99%

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection

Uncapher¹,

Boyd-Meredith²,

Chow

et al. 2015

J. Neurosci.

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Remembering a past event elicits distributed neural patterns that can be distinguished from patterns elicited when encountering novel information. These differing patterns can be decoded with relatively high diagnostic accuracy for individual memories using multivoxel pattern analysis (MVPA) of fMRI data. Brain-based memory detection-if valid and reliable-would have clear utility beyond the domain of cognitive neuroscience, in the realm of law, marketing, and beyond. However, a significant boundary condition on memory decoding validity may be the deployment of "countermeasures": strategies used to mask memory signals. Here we tested the vulnerability of fMRI-based memory detection to countermeasures, using a paradigm that bears resemblance to eyewitness identification. Participants were scanned while performing two tasks on previously studied and novel faces: (1) a standard recognition memory task; and (2) a task wherein they attempted to conceal their true memory state. Univariate analyses revealed that participants were able to strategically modulate neural responses, averaged across trials, in regions implicated in memory retrieval, including the hippocampus and angular gyrus. Moreover, regions associated with goal-directed shifts of attention and thought substitution supported memory concealment, and those associated with memory generation supported novelty concealment. Critically, whereas MVPA enabled reliable classification of memory states when participants reported memory truthfully, the ability to decode memory on individual trials was compromised, even reversing, during attempts to conceal memory. Together, these findings demonstrate that strategic goal states can be deployed to mask memory-related neural patterns and foil memory decoding technology, placing a significant boundary condition on their real-world utility.

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“…Other objections mounted by neuroskeptics include problems with the neuroimaging methodology itself and doubts about the interpretation or overinterpretation of results. For a discussion of neuroskepticism as well as a set of counterarguments, see, for example, Farah et al (2014), and Rachul and Zarzeczny (2012).…”

mentioning

confidence: 99%

Business Ethics: The Promise of Neuroscience

2016

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Recent advances in cognitive neuroscience research portend well for furthering understanding of many of the fundamental questions in the field of business ethics, both normative and empirical. This article provides an overview of neuroscience methodology and brain structures, and explores the areas in which neuroscience research has contributed findings of value to business ethics, as well as suggesting areas for future research. Neuroscience research is especially capable of providing insight into individual reactions to ethical issues, while also raising challenging normative questions about the nature of moral responsibility, autonomy, intent, and free will. This article also provides a brief summary of the papers included in this special issue, attesting to the richness of scholarly inquiry linking neuroscience and business ethics. We conclude that neuroscience offers considerable promise to the field of business ethics, but we caution against overpromise.

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Functional MRI-based lie detection: scientific and societal challenges

Cited by 171 publications

References 56 publications

Progress and challenges in probing the human brain

Progress and challenges in probing the human brain

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection

Business Ethics: The Promise of Neuroscience

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