December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Individual differences in facial expression recognition ability are linked to differences in the efficiency at using the diagnostic visual information
Author Affiliations & Notes
  • Marie-Claude Desjardins
    Université du Québec en Outaouais
  • Daniel Fiset
    Université du Québec en Outaouais
  • Jessica Limoges
    Université du Québec en Outaouais
  • Caroline Blais
    Université du Québec en Outaouais
  • Footnotes
    Acknowledgements  This work was supported by grants from the NSERC and Canada Research Chair programs.
Journal of Vision December 2022, Vol.22, 4067. doi:
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      Marie-Claude Desjardins, Daniel Fiset, Jessica Limoges, Caroline Blais; Individual differences in facial expression recognition ability are linked to differences in the efficiency at using the diagnostic visual information. Journal of Vision 2022;22(14):4067.

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

  • Supplements

There is a common assumption that the ability in facial expression recognition is related to the adequacy of visual strategies, but it has been recently shown that multiple eye fixation patterns may lead to comparable performances (Yitzhak et al., 2020). However, since there is a partial dissociation between eye fixations and visual information utilization, it remains possible that facial recognition ability is associated with this latter component of visual strategies. We tested this hypothesis using the Bubbles method (Gosselin & Schyns, 2001), which allows to measure the visual information successfully used to complete a task. Participants (N=69, 34 males) completed five tasks measuring their facial expression recognition ability: Reading the Mind in the Eyes Test, Films Expression Task, Megamix and two tasks of basic facial expressions categorization. They also completed 4000 trials of a Bubbles task in which they categorized facial expressions (anger, disgust, fear, joy). A principal component analysis was conducted on the five ability measures and the two extracted components were used as ability indexes. Visual information utilization patterns across participants were classified using a K-mean clustering analysis. Three patterns were revealed; in all groups, participants mostly relied on the mouth area, followed by the eyes area, to successfully categorize facial expressions. However, a gradient of efficiency was observed across the three groups, suggesting an increase in the efficiency at using both the eyes and mouth area across the three groups. Most importantly, the ability at recognizing facial expressions also varied across those three groups, with the lower ability group showing the least efficient visual strategy, and the higher ability group showing the most efficient visual strategy. Taken together, these results support the existence of an association between facial expression recognition ability and visual information utilization patterns.


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