August 2014
Volume 14, Issue 10
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Facial expression recognition takes longer in the posterior superior temporal sulcus (pSTS) than in the occipital face are (OFA)
Author Affiliations
  • David Pitcher
    National Institute of Mental Health
Journal of Vision August 2014, Vol.14, 1393. doi:10.1167/14.10.1393
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      David Pitcher; Facial expression recognition takes longer in the posterior superior temporal sulcus (pSTS) than in the occipital face are (OFA). Journal of Vision 2014;14(10):1393. doi: 10.1167/14.10.1393.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recognizing facial expressions is essential for everyday social interaction but our understanding of how the brain performs this task is limited. Neuroimaging studies have identified a face-selective region in the right posterior superior temporal sulcus (rpSTS) that responds more to facial expressions than to facial identity but precisely when the rpSTS begins to causally contribute to expression recognition is unknown. The present study addressed this issue using transcranial magnetic stimulation (TMS). In Experiment 1 repetitive TMS delivered over the rpSTS, at a frequency of 10Hz for 500ms, selectively impaired a facial expression task but had no effect on a matched facial identity task. In Experiment 2, double-pulse TMS (dTMS) was delivered over the rpSTS or over the right occipital face area (rOFA), a face-selective region in lateral occipital cortex, at different latencies up to 210ms after stimulus onset. Task performance was selectively impaired when dTMS was delivered over the rpSTS at 60-100ms and 100-140ms. dTMS delivered over the rOFA impaired task performance at 60-100ms only. These results demonstrate that the rpSTS causally contributes to expression recognition and that it does so at the same latency as the rOFA but over a longer time-scale. The difference in length of the TMS induced impairment between the rpSTS and the rOFA further suggests that the neural computations that contribute to facial expression recognition in each region are functionally distinct.

Meeting abstract presented at VSS 2014

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