Predicted missing information biases ensemble perception of temporally ordered facial expressions - Jiahao Lu; Jun Wang (Scientific Reports)
Abstract By observing dynamically changing facial expressions, humans can use a specialized capacity known as ensemble coding to effortlessly obtain a summary representation of an individual’s emotional state. However, few studies have examined whether the missing expression informed by the statistical regularity in the changing facial expressions can be sampled and then influence the perceptual averaging process. In Experiment 1a and 1b, we manipulated the amount of prior information from local regularity by varying the position of the missing expression in the temporal sequence (1a: Neutral to Disgust and/or Disgust to Neutral,1b: Neutral to Happy and/or Happy to Neutral) within a trial. Results showed that ensemble estimates were towards the mean of expressions including both the presented and the missing faces, only when sufficient predictability (e.g. a missing expression in the late position) informed by local regularity. In Experiment 2, we added prior information from global regularities to help boost the predictability of an early missing expression by keeping the emotional direction consistent in a block. However, estimates were not towards the mean of expressions including both the presented and the missing expressions as expected. Although the generalizability may be limited, these findings suggest that prior information at different levels of hierarchical predictive coding may exert qualitatively different influences on the perceptual averaging of temporally ordered facial expressions with missing items.