September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Rapid categorization of gender from natural face images in the human brain
Author Affiliations
  • Diane Rekow
    Group « Developmental Ethology and Cognitive Psychology », Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRA, Université Bourgogne Franche-Comté, F-21000 Dijon, France
  • Jean-Yves Baudouin
    Group « Developmental Ethology and Cognitive Psychology », Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRA, Université Bourgogne Franche-Comté, F-21000 Dijon, France
  • Bruno Rossion
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCL), 1348 Louvain-la-Neuve, Belgium Service de Neurologie, Centre Hospitalier Universitaire de Nancy, F-54035 Nancy, France
  • Arnaud Leleu
    Group « Developmental Ethology and Cognitive Psychology », Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRA, Université Bourgogne Franche-Comté, F-21000 Dijon, France
Journal of Vision September 2018, Vol.18, 1339. doi:10.1167/18.10.1339
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      Diane Rekow, Jean-Yves Baudouin, Bruno Rossion, Arnaud Leleu; Rapid categorization of gender from natural face images in the human brain. Journal of Vision 2018;18(10):1339. doi: 10.1167/18.10.1339.

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

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Abstract

Human faces are readily and automatically categorized for gender across a wide range of variable cues, a critical visual function for social interactions. To identify an implicit measure of rapid face gender categorization, we recorded scalp electroencephalogram (EEG) from 32 participants (16 females). In a first experiment, highly variable face images from one gender alternated at a rapid rate of 6 Hz (i.e., 6 images per second) with images of the other gender inserted every 6th stimuli, objectively isolating a gender categorization response at a 1 Hz rate in the EEG spectrum. In a second experiment, images from only one gender (i.e., male or female face images) were inserted at the 1 Hz categorization rate in a 6 Hz sequence of non-face objects. In the first experiment, a significant categorization response was identified for both face genders over the right occipito-temporal cortex, but the response was larger for female faces presented among males than the reverse. This asymmetrical pattern suggests either greater generalization across female than male exemplars, or a more inclusive female category. Results from the second experiment provide an answer: a larger generic face categorization response is recorded for male faces, indicating higher generalizability across male than female faces, and thus supporting the second interpretation. Importantly, these effects disappear for upside-down faces, ruling out any contribution of low-level physical variability across images. Moreover, no own-gender bias was found. Altogether, these findings reveal that rapid visual gender categorization from natural face images can be objectively isolated and quantified in the human brain in a few minutes of recording. They also suggest that male faces are highly generalizable within a well-defined category that excludes female faces, while female face category boundaries are less demarcated, female exemplars sharing some male characteristics. Keywords: face gender, categorization, EEG, fast periodic visual stimulation, frequency-tagging

Meeting abstract presented at VSS 2018

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