When confronted with a scene of emotional faces, our brains automatically average the individual facial expressions together to create the gist of the collective emotion. Here, we tested whether this ensemble averaging could also occur for facial attractiveness, and in turn shape two related face perception phenomena: adaptation and the cheerleader effect. In our first two experiments, we showed that adaptation aftereffects could indeed be shaped by ensemble statistics; viewing an increasingly unattractive group of faces conversely increased attractiveness judgments for a subsequently presented face. Not only did group adaptation aftereffects occur, but their effects were equivalent to those observed from the morphed average face of the group, suggesting that the visual system had averaged the group together.In our last two experiments, we showed that viewing a target face in an increasingly unattractive group led to the target being perceived as increasingly more attractive: a 'cheerleader' effect. Moreover, our results suggest that this cheerleader effect likely comprises of both a social positive effect and a contrastive process, requiring variance between the surrounding and target faces; i.e., the visual system appeared incapable of boosting a target's attractiveness when all of the faces in the scene were identical.Furthermore, the mean group attractiveness ratings strongly predicted both the cheerleader effect and adaptation aftereffects, with the latter two also interrelated. This suggests that ensemble statistics is the common underlying process linking each of these phenomena. In order to be perceived as beautiful, being surrounded by unattractive friends may help.

How do we interpret the rapidly changing visual stimuli we encounter? How does our past visual experience shape our perception? Recent work has suggested that our visual system is able to interpret multiple faces presented temporally via integration or ensemble coding. Visual adaptation is widely used to probe such short term plasticity. Here we use an adaptation paradigm to investigate whether integration or averaging of emotional faces occurs during a rapid serial visual presentation (RSVP). In four experiments, we tested whether the RSVP of distinct emotional faces could induce adaptation aftereffects and whether these aftereffects were of similar magnitudes as their statistically averaged face. Experiment 1 showed that the RSVP faces could generate significant facial expression aftereffects (FEAs) across happy and sad emotions. Experiment 2 revealed that the magnitudes of the FEAs from RSVP faces and their paired average faces were comparable and significantly correlated. Experiment 3 showed that the FEAs depended on the mean emotion of the face stream, regardless of variations in emotion or the temporal frequency of the stream. Experiment 4 further indicated that the emotion of the average face of the stream, but not the emotion of individual faces matched for identity to the test faces, determined the FEAs. Together, our results suggest that the visual system interprets rapidly presented faces by ensemble coding, and thus implies the formation of a facial expression norm in face space.

Our brains can extract a summary representation of the facial characteristics provided by a group of faces. To date, there has been a lack of clarity as to what calculations the brain is actually performing during this ensemble perception. For example, does ensemble processing average the fiducial points (e.g., distance between the eyes, width of the mouth) and surface characteristics (e.g., skin tone) of a set of faces in a fashion that produces what we call a 'morph average' face from the group? Or does ensemble perception extract a general 'gist average' of the face set (e.g., these faces are unattractive)? Here, we take advantage of the fact that the 'morph average' face derived from a group of faces is more attractive than the 'gist average'. If ensemble perception is performing morph averaging, then the adaptation aftereffects elicited by a morphed average face from a group should be equivalent to those elicited by the group. By contrast, if ensemble perception reflects gist averaging, then the aftereffects produced by the group should be distinct from those elicited by the more attractive morphed average face. In support of the morph averaging hypothesis, we show that the adaptation aftereffects derived via temporal ensemble perception of a group of faces are equal to those produced by the group's morphed average face. Moreover, these effects increase as a linear function of increasing attractiveness in the underlying group. We also reveal that spatial ensemble processing is not equal to temporal ensemble processing, but instead reflects the 'gist' attractiveness of the group of faces; e.g., these faces are unattractive. Finally, we show that gist averaging of a spatially presented group of faces is abolished when a temporal manipulation is additionally employed; under these circumstances, morph averaging becomes apparent again. In summary, we have shown for the first time that temporal and spatial ensemble statistics reflect qualitatively different perceptual calculations.

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