September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Unveiling Mental Self-Images from Face Perception and Memory
Author Affiliations & Notes
  • Arijit De
    University of Toronto
  • Shao Feng Liu
    University of Toronto
  • Yong Zhong Liang
    University of Toronto
  • Moaz Shoura
    University of Toronto
  • Adrian Nestor
    University of Toronto
  • Footnotes
    Acknowledgements  Natural Sciences and Engineering Research Council of Canada
Journal of Vision September 2024, Vol.24, 683. doi:https://doi.org/10.1167/jov.24.10.683
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      Arijit De, Shao Feng Liu, Yong Zhong Liang, Moaz Shoura, Adrian Nestor; Unveiling Mental Self-Images from Face Perception and Memory. Journal of Vision 2024;24(10):683. https://doi.org/10.1167/jov.24.10.683.

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

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Abstract

Human cognition and behavior are intricately shaped by self-perception, self-concept and self-esteem. While prior work has begun to uncover visual traits of self-representations, detailed depictions of mental self-images and their evaluation with respect to systematic biases are still largely missing from the field. To address this, our study aims to uncover self-images from perception and memory, as well as to assess their sensitivity to specific perceptual abilities and personality traits. To this end, female Caucasian adults (N=30) evaluated the visual similarity between pairs of female face stimuli, including images of their own faces, as well as between mental images of themselves, as recalled from memory, and other face stimuli. Perception and memory-based self-images were then derived through behavior-based image reconstruction as applied to similarity data and assessed with respect to their visual content. Our investigation revealed significant levels of reconstruction accuracy relative to actual face images of the participants. It further revealed systematic correspondence between perception and memory-based representations of the self. Further, it demonstrated the impact of specific factors (e.g., as captured by self-attractiveness ratings) on the content of self-images. Thus, our findings shed new light on self-representations, on their visual content and on the factors that impact their veracity.

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