December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
The reliability, stability and consistency of individual differences across multiple face identification tasks.
Author Affiliations
  • Kristen A. Baker
    Brock University
  • Vincent J. Stabile
    Brock University
  • Catherine J. Mondloch
    Brock University
Journal of Vision December 2022, Vol.22, 3781. doi:https://doi.org/10.1167/jov.22.14.3781
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      Kristen A. Baker, Vincent J. Stabile, Catherine J. Mondloch; The reliability, stability and consistency of individual differences across multiple face identification tasks.. Journal of Vision 2022;22(14):3781. https://doi.org/10.1167/jov.22.14.3781.

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

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Abstract

Recognizing unfamiliar faces is difficult: Two images of the same person can look different, and images of two different people can look similar. In two studies we examined individual differences on unfamiliar face identification tasks to determine whether differences in sensitivity and response bias are stable across time and tasks. We also assessed whether recognition (accurately perceiving that two images belong to the same person) and discrimination (telling two people apart) are dissociable processes. In Study 1, participants completed a battery of four unfamiliar face identification tasks that varied in task demands (sorting, same/different, line-up) and the amount of within-person variability in appearance that was present in the stimuli. Approximately one week later, participants completed a second version of the same tasks (same protocol, different stimuli). In Study 2, participants completed two versions of three unfamiliar face identification tasks in which stimuli were presented simultaneously vs. sequentially—thus, introducing memory demands. All tasks showed adequate reliability. Individual differences in sensitivity and bias were consistent across tasks and in the simultaneous vs. sequential versions. Recognition and discrimination were not dissociable when individual differences in bias were controlled for. In Study 3 (ongoing) we are investigating the extent to which performance on unfamiliar face identification tasks predicts the efficiency with which one learns a new face. Face learning efficiency is measured via the difference in recognition accuracy following each of the learning conditions (1, 3, 6, and 9 images). The results have implications for applied settings and theoretical models.

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