Abstract
Emotion perception is a crucial question in cognitive neuroscience and the underlying neural substrates have been the subject of intense study. One of our previous studies demonstrated that motion-sensitive areas are involved in the perception of facial expressions. However, it remains unclear whether emotions perceived from whole-person stimuli can be decoded from the motion-sensitive areas. In addition, if emotions are represented in the motion-sensitive areas, we may further ask whether the representations of emotions in the motion-sensitive areas can be shared across individual subjects. To address these questions, this study collected neural images while participants viewed emotions (joy, anger, and fear) from videos of whole-person expressions (contained both face and body parts) in a block-design functional magnetic resonance imaging (fMRI) experiment. Multivariate pattern analysis (MVPA) was conducted to explore the emotion decoding performance in individual-defined dorsal motion-sensitive regions of interest (ROIs). Results revealed that emotions could be successfully decoded from motion-sensitive ROIs with statistically significant classification accuracies for three emotions as well as positive versus negative emotions. Moreover, results from the cross-subject classification analysis showed that a person’s emotion representation could be robustly predicted by others’ emotion representations in motion-sensitive areas. Together, these results reveal that emotions are represented in dorsal motion-sensitive areas and that the representation of emotions is consistent across subjects. Our findings provide new evidence of the involvement of motion-sensitive areas in the emotion decoding, and further suggest that there exists a common emotion code in the motion-sensitive areas across individual subjects.
Highlights
The ability to understand emotions is a crucial social skill in humans
Our results showed that emotions perceived from whole-person expressions can be robustly decoded in dorsal motion-sensitive areas
Successful cross-subject emotion decoding suggests that the emotion representations in motion-sensitive areas could be shared across participants
Summary
The ability to understand emotions is a crucial social skill in humans. It has been proposed that body language plays an important role in conveying emotions (Calbi et al, 2017). Body language refers to the non-verbal signals in which physical behaviors, including facial expressions, body posture, gestures, eye movement, touch and the use of space, are used to express our true. Cross-Subject Commonality of Emotion Representations feelings and emotions. According to experts, these non-verbal signals make up a huge part of our daily communication. Humans can recognize others’ emotions from their wholeperson expressions and perceive them in a categorical manner. Since the human brain can readily decode emotions, considerable functional magnetic resonance imaging (fMRI) studies have investigated the potential neural substrates and mechanisms underlying the perception of emotions
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