Classifying spatial patterns of brain activity with machine learning methods

Application to lie detection

C. Davatzikos, K. Ruparel, Y. Fan, D. G. Shen, M. Acharyya, J. W. Loughead, R. C. Gur, D. D. Langleben

Research output: Contribution to journalArticle

Abstract

Patterns of brain activity during deception have recently been characterized with fMRI on the multi-subject average group level. The clinical value of fMRI in lie detection will be determined by the ability to detect deception in individual subjects, rather than group averages. High-dimensional non-linear pattern classification methods applied to functional magnetic resonance (fMRI) images were used to discriminate between the spatial patterns of brain activity associated with lie and truth. In 22 participants performing a forced-choice deception task, 99% of the true and false responses were discriminated correctly. Predictive accuracy, assessed by cross-validation in participants not included in training, was 88%. The results demonstrate the potential of non-linear machine learning techniques in lie detection and other possible clinical applications of fMRI in individual subjects, and indicate that accurate clinical tests could be based on measurements of brain function with fMRI.

Original languageEnglish (US)
Pages (from-to)663-668
Number of pages6
JournalNeuroImage
Volume28
Issue number3
DOIs
StatePublished - Nov 15 2005
Externally publishedYes

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Lie Detection
Magnetic Resonance Imaging
Deception
Brain
Aptitude
Magnetic Resonance Spectroscopy
Machine Learning

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

Cite this

Davatzikos, C., Ruparel, K., Fan, Y., Shen, D. G., Acharyya, M., Loughead, J. W., ... Langleben, D. D. (2005). Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection. NeuroImage, 28(3), 663-668. https://doi.org/10.1016/j.neuroimage.2005.08.009

Classifying spatial patterns of brain activity with machine learning methods : Application to lie detection. / Davatzikos, C.; Ruparel, K.; Fan, Y.; Shen, D. G.; Acharyya, M.; Loughead, J. W.; Gur, R. C.; Langleben, D. D.

In: NeuroImage, Vol. 28, No. 3, 15.11.2005, p. 663-668.

Research output: Contribution to journalArticle

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, vol. 28, no. 3, pp. 663-668. https://doi.org/10.1016/j.neuroimage.2005.08.009
Davatzikos, C. ; Ruparel, K. ; Fan, Y. ; Shen, D. G. ; Acharyya, M. ; Loughead, J. W. ; Gur, R. C. ; Langleben, D. D. / Classifying spatial patterns of brain activity with machine learning methods : Application to lie detection. In: NeuroImage. 2005 ; Vol. 28, No. 3. pp. 663-668.
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