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Aftereffects support opponent coding of face gender.

Stephen Pond1, Nadine Kloth, Elinor McKone

  • 1ARC Centre of Excellence in Cognition and its Disorders, School of Psychology, University of Western Australia, Crawley, WA, Australia.

Journal of Vision
|December 24, 2013
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Summary

Face gender perception may use opponent coding, challenging multichannel theories. New research indicates aftereffects align with perceived sexual dimorphism, supporting norm-based models for face processing.

Keywords:
caricaturingface gender aftereffectsface perceptionmultichannel codingnorm-based opponent coding

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Area of Science:

  • Neuroscience
  • Cognitive Psychology
  • Vision Science

Background:

  • Norm-based opponent coding is a prevalent model for neural representation of facial features.
  • Previous research suggested face gender perception might utilize multichannel coding, based on aftereffect patterns with caricatured faces.

Purpose of the Study:

  • To test the assumption that caricaturing increases perceived sexual dimorphism.
  • To re-evaluate face gender coding models by minimizing low-level adaptation effects.
  • To investigate the relationship between face gender aftereffects and perceived sexual dimorphism.

Main Methods:

  • Study 1: Assessed the impact of caricaturing on perceived sexual dimorphism for male and female faces.
  • Study 2: Minimized low-level retinotopic adaptation and measured face gender aftereffects with varying levels of perceived sexual dimorphism.

Main Results:

  • Caricaturing enhanced perceived sexual dimorphism for male faces but not female faces.
  • Face gender aftereffects were positively correlated with the perceived sexual dimorphism of adaptors.
  • No decrease in aftereffects was observed for extreme adaptors, even with higher dimorphism levels.

Conclusions:

  • The assumption that caricaturing increases perceived sexual dimorphism is not universally true for faces.
  • Findings challenge multichannel coding models for face gender perception.
  • Results support norm-based opponent coding for higher-level dimensions in face gender perception.