Unfolding the spatial and temporal neural processing of lying about face familiarity

Delin Sun, Tatia M.C. Lee, Che Hin Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

Published by Oxford University Press. To understand the neural processing underpinnings of deception, this study employed both neuroimaging (functional magnetic resonance imaging, fMRI) and neurophysiological (event-related potential, ERP) methodologies to examine the temporal and spatial coupling of the neural correlates and processes that occur when one lies about face familiarity. This was performed using simple directed lying tasks. According to cues provided by the researchers, the 17 participants were required to respond truthfully or with lies to a series of faces. The findings confirmed that lie and truth conditions are associated with different fMRI activations in the ventrolateral, dorsolateral, and dorsal medial-frontal cortices; premotor cortex, and inferior parietal gyrus. They are also associated with different amplitudes within the time interval between 300 and 1000 ms post face stimulus, after the initiation (270 ms) of face familiarity processing. These results support the cognitive model that suggests representations of truthful information are first aroused and then manipulated during deception. Stronger fMRI activations at the left inferior frontal gyrus and more positive-going ERP amplitudes within [1765, 1800] ms were observed in the contrast between lie and truth for familiar than for unfamiliar faces. The fMRI and ERP findings, together with ERP source reconstruction, clearly delineate the neural processing of face familiarity deception.
Original languageEnglish
Pages (from-to)927-936
Number of pages10
JournalCerebral Cortex
Volume25
Issue number4
DOIs
Publication statusPublished - 1 Apr 2015

Keywords

  • deception
  • ERP
  • face familiarity
  • fMRI
  • source reconstruction

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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