September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
High test-retest reliability of a neural index of rapid automatic discrimination of unfamiliar individual faces
Author Affiliations & Notes
  • Milena Dzhelyova
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium
    Cognitive Science and Assessment Institute (COSA), University of Luxembourg, Luxembourg
  • Giulia Dormal
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium
  • Corentin Jacques
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium
  • Caroline Michel
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium
  • Christine Schiltz
    Cognitive Science and Assessment Institute (COSA), University of Luxembourg, Luxembourg
  • Bruno Rossion
    Psychological Sciences Research Institute and Institute of Neuroscience, Université catholique de Louvain (UCLouvain), 1348 Louvain-la-Neuve, Belgium
    Université de Lorraine, CNRS, CRAN, F-54000 Nancy, France
    Université de Lorraine, CHRU-Nancy, Service de Neurologie, F-54000 Nancy, France
Journal of Vision September 2019, Vol.19, 136c. doi:https://doi.org/10.1167/19.10.136c
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      Milena Dzhelyova, Giulia Dormal, Corentin Jacques, Caroline Michel, Christine Schiltz, Bruno Rossion; High test-retest reliability of a neural index of rapid automatic discrimination of unfamiliar individual faces. Journal of Vision 2019;19(10):136c. doi: https://doi.org/10.1167/19.10.136c.

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

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Abstract

A key aspect of human individual face recognition is the ability to discriminate unfamiliar individual faces. Since many general processes contribute to explicit behavioural performance in individual face discrimination tasks, measuring unfamiliar individual face discrimination ability in humans is challenging. In recent years, a fast periodic visual stimulation approach has provided objective (frequency-locked) implicit electrophysiological indices of individual face discrimination that are highly sensitive at the individual level. Here we evaluate the test-retest reliability of this response across scalp electroencephalographic (EEG) recording sessions separated by more than two months, in the same 30 individuals. We found no test-retest difference overall across sessions in terms of amplitude and spatial distribution of the EEG individual face discrimination response. Moreover, with only 4 minutes of recordings, the variable individual face discrimination response across individuals was highly stable (i.e., reliable) in terms of amplitude, spatial distribution and shape. This stable EEG response was also significantly correlated with speed, but not accuracy rate, of the Benton face recognition task (BFRT-c, Rossion, & Michel, 2018). Overall, these observations strengthen the diagnostic value of FPVS-EEG as an objective and rapid flag for specific difficulties at individual face recognition in the human population. Rossion, B., & Michel, C. (2017). Normative data for accuracy and response times at the computerized Benton Facial Recognition Test (BFRT-c). Behavior Research Methods

Acknowledgement: FNRS, CNRS 
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