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Ensemble Coding of Crowd with Cross-Category Facial Expressions
Zhi Yang1,2, Yifan Wu1,2, Shuaicheng Liu1,2
1Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.
Abstract:
Ensemble coding allows observers to form an average to represent a set of elements. However, it is unclear whether observers can extract an average from a cross-category set. Previous investigations on this issue using low-level stimuli yielded contradictory results. The current study addressed this issue by presenting high-level stimuli (i.e., a crowd of facial expressions) simultaneously (Experiment 1) or sequentially (Experiment 2), and asked participants to complete a member judgment task. The results showed that participants could extract average information from a group of cross-category facial expressions with a short perceptual distance. These findings demonstrate cross-category ensemble coding of high-level stimuli, contributing to the understanding of ensemble coding and providing inspiration for future research.
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