September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Attention Modulates the Ensemble Coding of Facial Expressions
Author Affiliations
  • Haojiang YING
    Psychology, School of Social Sciences, Nanyang Technological University
  • Hong Xu
    Psychology, School of Social Sciences, Nanyang Technological University
Journal of Vision September 2018, Vol.18, 611. doi:10.1167/18.10.611
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      Haojiang YING, Hong Xu; Attention Modulates the Ensemble Coding of Facial Expressions. Journal of Vision 2018;18(10):611. doi: 10.1167/18.10.611.

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

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Abstract

When we are encountered a crowd of faces in a short period of time, how do we process such large amount of information? Do we selectively process some of them (selective attention) or obtain a gist of all the faces (ensemble coding)? It has been shown that we implicitly average the emotions of the faces that we encounter through ensemble coding. However, does selective attention play a role in this ensemble coding? To answer this question, in the current study, participants (n = 11) were instructed to maintain fixation at the central cross and then report the average emotion of four faces that surround the fixation cross under three cueing conditions. In each trial, participant's attention was cued to 1) the happiest face, 2) the saddest face of the group, or 3) the fixation cross. Results showed that cueing to the happiest face (M = 7.67%, SEM = 2.75%; t(10) = 2.78, p = .019, Cohen's d = 0.84) and to the saddest face (M = -8.91%, SEM = 3.29%; t(10) = - 2.71, p = .022, Cohen's d = 0.82) significantly biased the judgment of the ensemble representation toward the cued face's emotion. Also, there is a significant difference between these two conditions (t(10) = 2.89, p = .016, Cohen's d = 0.87). Our results suggest that attention modulates the ensemble coding of facial expressions. The neural mechanisms of ensemble coding are therefore influenced by attention related pathways.

Meeting abstract presented at VSS 2018

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