September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Natural brief facial expression changes detection at a single glance: evidence from Fast Periodic Visual Stimulation
Author Affiliations & Notes
  • Stéphanie Matt
    Laboratoire 2LPN (EA7489) - Université de Lorraine (France)
    Laboratoire INTERPSY (EA4432) - Université de Lorraine (France)
  • Milena Dzhelyova
    Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain (Belgium)
  • Louis Maillard
    CRAN (UMR 7039 CNRS) - CHU de Nancy - Université de Lorraine (France)
  • Joëlle Lighezzolo-Alnot
    Laboratoire INTERPSY (EA4432) - Université de Lorraine (France)
  • Bruno Rossion
    Institute of Research in Psychological Science, Institute of Neuroscience, University of Louvain (Belgium)
    CRAN (UMR 7039 CNRS) - CHU de Nancy - Université de Lorraine (France)
  • Stéphanie Caharel
    Laboratoire 2LPN (EA7489) - Université de Lorraine (France)
Journal of Vision September 2019, Vol.19, 181c. doi:https://doi.org/10.1167/19.10.181c
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      Stéphanie Matt, Milena Dzhelyova, Louis Maillard, Joëlle Lighezzolo-Alnot, Bruno Rossion, Stéphanie Caharel; Natural brief facial expression changes detection at a single glance: evidence from Fast Periodic Visual Stimulation. Journal of Vision 2019;19(10):181c. doi: https://doi.org/10.1167/19.10.181c.

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

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Abstract

The processing of emotional facial expressions has been studied mainly with stereotypical face stimuli, but contextual information leads to drastic modulation in the categorization of facial expressions (Aviezer et al., 2017). In the human brain, brief facial expression changes are quickly read from faces (Dzhelyova et al., 2017). Yet, how reliably these changes are detected with realistic faces embedded in a natural context remain unknown. In this study, faces varied in viewpoint, identity, gender, age, ethnic origin and background context. We recorded 128-channel EEG in 17 participants while they viewed 50s sequences with a neutral-expression face at a rate of 5.99 Hz (F) at two faces orientations (upright, inverted). Every five faces, the faces changed expression to one of the six basic expression (fear, disgust, happiness, anger, surprised or sadness; Ekman, 1993), one emotion per sequence (e.g ANeutralANeutralANeutralANeutralANeutralBExpressiveANeutral …). EEG responses at 5.99 Hz reflect general visual processing, while the EEG responses at F/5 = 1.1998 Hz and its harmonics (e.g., 2F/5 = 2.3996, etc.) index detection of a brief change of natural facial expression. Despite the wide variety across images, a F/5 response was observed for each individual participant, pointing to robust facial expression categorization processes. At the group-level, the categorization response was measured over occipito-temporal sites and was largely reduced when faces were inverted, indicating that it reflects high-level processes. Despite evidence (Leleu et al., 2018; Hinojosa et al., 2015) suggesting that sad expressions are more subtle and thus lead to weaker responses than other emotions, our observations with natural expressions highlight a stronger response for this emotion, especially over the left hemisphere. Moreover, we observed a right hemisphere dominance for a shift from neutral to fearful faces and a left hemisphere dominance for a shift from neutral to happy faces.

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