|Alternative Title||Mean Representation of Multiple Facial Expressions|
|Place of Conferral||北京|
|Keyword||表情面孔 情绪 个体表征 平均表征 精确性|
|Other Abstract||People could extract mean expression of multiple faces pretty precisely. However, the mechanism of how we make such ensemble representation was far from clear. This study aimed to explore the relationship between individual representation and mean representation, to be specific, how the precision of individual representation influences mean representation.|
Experiment 1 examined how durations of multiple faces impact individual representation and the implicit mean representation. It was found that there was a bias to indicate the face with mean emotion as the member of the set. As the duration increased, the probability of judging “actual set member” as the member of the set increased and then kept constant; the probability of judging the “mean emotion face” as the member of the set increased, kept constant and then dropped, but was still comparable to that of “actual set member”.
Experiment 2 explored how durations of multiple faces influence explicit discrimination of mean emotion. The results showed that the ability to discriminate mean emotion was very similar to regular emotion discrimination. However, when the duration of face set was 50ms, people could uptake information of mean emotion from heterogeneous faces much quickly than that of emotion from homogeneous faces.
Experiment 3 manipulated the accuracy of individual representation by changing positions of the faces in the field of vision and found that faces in the foveal vision were given more weight than those in the extrafoveal vision in mean emotion representation.
Experiment 4 controlled the physical saliency and emotional intensity of face stimuli and investigated how emotion saliency of faces in the extrafoveal vision modulated the mean emotion representation. It was found that there was an advantage for happy faces in the extrafoveal vision.
The present study suggests that the mean representation is dependent on the precision of individual representation to some extent and people may conduct a precision-weighted averaging. On the other hand, when the quality of individual representation is rather low, the mean representation can serve as a compensatory mechanism and still kept pretty high precision. The study also demonstrates that the visual field influences the mean representation along with the emotional saliency. The present study improves our understanding of mean representation of multiple facial expressions, contributes to the development of theories of multiple- and single-face processing and sheds new light on emotional processing study.
|季琭妍. 多面孔表情的平均表征[D]. 北京. 中国科学院研究生院,2014.|
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