Individual Faces Were Not Discarded During Extracting Mean Emotion Representations

Abstract

Individuals can perceive the mean emotion or mean identity of a group of faces. It has been considered that individual representations are discarded when extracting a mean representation; for example, the “element-independent assumption” asserts that the extraction of a mean representation does not depend on recognizing or remembering individual items. The “element-dependent assumption” proposes that the extraction of a mean representation is closely connected to the processing of individual items. The processing mechanism of mean representations and individual representations remains unclear. The present study used a classic member-identification paradigm and manipulated the exposure time and set size to investigate the effect of attentional resources allocated to individual faces on the processing of both the mean emotion representation and individual representations in a set and the relationship between the two types of representations. The results showed that while the precision of individual representations was affected by attentional resources, the precision of the mean emotion representation did not change with it. Our results indicate that two different pathways may exist for extracting a mean emotion representation and individual representations and that the extraction of a mean emotion representation may have higher priority. Moreover, we found that individual faces in a group could be processed to a certain extent even under extremely short exposure time and that the precision of individual representations was relatively poor but individual representations were not discarded.

Ensemble Coding of Crowd with Cross-Category Facial Expressions

“…These findings are consistent with previous results that used the member judgement task [ 17 , 45 , 46 ], which found that observers preferred to recognize the unseen average facial expression as a member of the previously presented set. However, some studies suggest that the integration of a group of facial expressions as an average representation using ensemble coding depends on the shape of the feature distribution [ 22 , 23 ], that is, observers perceive a group of cross-category facial expressions as two subsets and form two average representations separately because these crowds are perceived as two-peak distributions.…”

“…As mentioned above, in the BD ensemble condition, even though probe face C (the average representation of the previously presented ensemble) was not presented in the ensemble stimuli, it was perceived as equally familiar as the actually presented probe faces (B faces and D faces), and the familiarities of these three probe faces were significantly larger than those of other unpresented probe faces (A faces and E faces). This average bias accords with previous studies regarding ensemble coding of facial expressions in a member judgement task [17,45,46], where observers tend to recognize the unseen average facial expression as a member of previous ensemble stimuli, implying that observers form an average representation when they perceive a crowd of faces automatically. However, these studies either only showed within-category crowds or did not discriminate the contributions of cross-category crowds from within-category crowds.…”