Seeing the Mean: Ensemble Coding for Sets of Faces

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Abstract

We frequently encounter groups of similar objects in our visual environment: a bed of flowers, a basket of oranges, a crowd of people. How does the visual system process such redundancy? Research shows that rather than code every element in a texture, the visual system favors a summary statistical representation of all the elements. The authors demonstrate that although it may facilitate texture perception, ensemble coding also occurs for faces—a level of processing well beyond that of textures. Observers viewed sets of faces varying in emotionality (e.g., happy to sad) and assessed the mean emotion of each set. Although observers retained little information about the individual set members, they had a remarkably precise representation of the mean emotion. Observers continued to discriminate the mean emotion accurately even when they viewed sets of 16 faces for 500 ms or less. Modeling revealed that perceiving the average facial expression in groups of faces was not due to noisy representation or noisy discrimination. These findings support the hypothesis that ensemble coding occurs extremely fast at multiple levels of visual analysis.

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