Abstract
Competent social organisms will read the social signals of their peers. In primates, the face has evolved to transmit the organism's internal emotional state. Adaptive action suggests that the brain of the receiver has co-evolved to efficiently decode expression signals. Here, we review and integrate the evidence for this hypothesis. With a computational approach, we co-examined facial expressions as signals for data transmission and the brain as receiver and decoder of these signals. First, we show in a model observer that facial expressions form a lowly correlated signal set. Second, using time-resolved EEG data, we show how the brain uses spatial frequency information impinging on the retina to decorrelate expression categories. Between 140 to 200 ms following stimulus onset, independently in the left and right hemispheres, an information processing mechanism starts locally with encoding the eye, irrespective of expression, followed by a zooming out to processing the entire face, followed by a zooming back in to diagnostic features (e.g. the opened eyes in “fear”, the mouth in “happy”). A model categorizer demonstrates that at 200 ms, the left and right brain have represented enough information to predict behavioral categorization performance.
Highlights
Primates use their faces to transmit facial expressions to their peers and communicate emotions
The results presented in figures 4 to 7 reveal a similar pattern of sensitivity to spatial frequency combinations on the left and right hemispheres: Starting with a combination of few high spatial frequency bands, face encoding starts at a local scale with the eyes, around 140 ms following stimulus onset
If the face evolved in part to transmit the relevant internal emotional states of primates, their brains probably co-evolved as fast and efficient decoders of facial expressions
Summary
Primates use their faces to transmit facial expressions to their peers and communicate emotions. The first part outlines the evidence for the proposal that the face has evolved in part as a sophisticated system for signaling affects to peers. Turning to the receiver characteristics of these affects, we review the evidence that the brain comprises a sophisticated network of structures involved in the fast decoding and categorization of emotion signals, using inputs from low-level vision. These inputs represent information at different spatial scales analyzed across a bank of Spatial Frequency filters in early vision
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