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Caroline Blais, Daniel Fiset, Cynthia Roy, Martin Arguin, Frédéric Gosselin; Individual differences in the visual strategies underlying facial expression categorization. Journal of Vision 2012;12(9):1283. doi: 10.1167/12.9.1283.
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© ARVO (1962-2015); The Authors (2016-present)
Having the skills to decode the facial expressions of others is crucial for successful social interactions. Individual differences in this ability exist among the healthy population. We used Bubbles and eye-tracking to investigate how the visual information extraction strategies used for facial expression categorization are related to individual differences in the ability to perform this task. In the Bubbles task, 41 participants (4000 trials per participant) were asked to categorize facial expressions (six basic emotions plus neutral and pain). Sparse versions of these stimuli were created by sampling facial information at random spatial locations and at five non-overlapping spatial frequency bands. For each participant, a classification image showing what information in the stimuli correlated with accuracy was constructed by performing a multiple linear regression on the bubbles locations and accuracy. Subsequently, a group classification image was constructed by calculating a weighted average of all the individual classification images using an index of individual performance as weights (i.e. the number of bubbles necessary to maintain an average accuracy of 61%, transformed into z-scores across participants). We found that the most efficient observers use the left eye area more than the least efficient observers (r=0.43, p<0.05). An ideal observer analysis showed that the area comprising both eyes is the most informative to discriminate across all expressions, confirming that the most efficient observers use a strategy closer to the ideal one. The eye-tracking task (N=20) was identical to the Bubbles task, except that the face stimuli were presented without bubbles. We observed a similar pattern of results: the best participants had a leftward bias in their fixation maps. We propose that the best participants have a more efficient right hemisphere face processor, which allows them to process the most diagnostic information-the eyes-more efficiently, and results in a leftward bias in the information utilization.
Meeting abstract presented at VSS 2012
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