August 2014
Volume 14, Issue 10
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Individual differences in face recognition abilities linked to variations in diagnostic facial information.
Author Affiliations
  • Jessica Royer
    Université du Québec en Outaouais
  • Sandra Lafortune
    Université du Québec en Outaouais
  • Justin Duncan
    Université du Québec en Outaouais
  • Caroline Blais
    Université du Québec en Outaouais
  • Daniel Fiset
    Université du Québec en Outaouais
Journal of Vision August 2014, Vol.14, 1442. doi:
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      Jessica Royer, Sandra Lafortune, Justin Duncan, Caroline Blais, Daniel Fiset; Individual differences in face recognition abilities linked to variations in diagnostic facial information.. Journal of Vision 2014;14(10):1442. doi:

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

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Face recognition is a complex task on perceptual and cognitive levels. Indeed, significant differences in face recognition abilities exist within the normal population (Duchaine & Nakayama, 2006), and these differences could be accounted for by qualitative and quantitative variations in the perceptual mechanisms associated with face identification. Forty-five participants (18 men; Mage=21.96; SD=3.13) were recruited for this study. The first task consisted of a 1000 trials 2AFC match-to-sample design. Using Bubbles (Gosselin & Schyns, 2001) we investigated whether visual strategies in face recognition differ within a normal population. Bubblized versions of faces were created by sampling facial information at random spatial locations and at five non-overlapping spatial frequency bands. Accuracy was maintained at 75% by adjusting the number of bubbles on a trial-by-trial basis using QUEST (Watson & Pelli, 1983); thus, the number of bubbles reflected the relative ability of the participants. The second task completed by our participants was the Cambridge Face Memory Test + (CFMT+; Russell, Duchaine, & Nakayama, 2009), a measure of face recognition ability. Classification images showing the information in the stimuli that correlated with accuracy were constructed by performing a multiple linear regression on the bubbles locations and accuracy. We constructed one (n=17) for the participants who obtained the best scores on the CFMT+, and one for those (n=13) who obtained the worst scores (0.5 SD above and below the mean, respectively; M=67.54; SD=12.48). A pixel test was applied to each classification image to determine its statistical significance (Zcrit=3.36, p<0.05; corrected for multiple comparisons). Our results indicate that the most skillful participants exclusively use the eye region when identifying faces, whereas the least skillful participants use information stemming from both the region of the eyes and the mouth. These results suggest that differences in perceptual mechanisms of face recognition also exist within the normal population.

Meeting abstract presented at VSS 2014


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