Humans frequently encounter crowds in daily life, and the collective emotional state of these groups provides vital social information that influences behavior and decision-making. Variance in facial expressions within a crowd serves as an indicator of the diversity of emotions, modulating the strength and stability of the group's emotional signal. Previous studies of low-level visual features have shown that the visual system adapts to the statistical properties of variance, producing systematic aftereffects in subsequent variance perception, such that the perceived level of variance shifts in the direction opposite to the adaptor. However, it remains unclear whether similar adaptation to variance occurs for complex, socially meaningful information such as facial expressions. In this study, we examined whether adaptation to the variance of facial expressions in crowds leads to aftereffects in perceived variance. Using morphed facial stimuli that varied incrementally between happy and angry expressions, we created crowd images composed of individuals with different degrees of emotional variability. In Experiment 1, participants judged the variance of facial expressions before and after adapting to stimuli with small or large variance. Experiment 2 examined adaptation using more intense expressions to enhance perceived variability. Across both experiments, perceived emotional variance shifted in the opposite direction to the adaptor, indicating robust aftereffects of facial-expression variance. These findings provide behavioral evidence consistent with the idea that the human visual system encodes the variance of facial expressions, and that adaptation to ensemble variance dynamically recalibrates perception in social contexts.
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Kudaka et al. (2025) studied this question.
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