Mu rhythm suppression over sensorimotor regions is associated with greater empathic accuracy |
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Authors: | Shir Genzer Desmond C Ong Jamil Zaki Anat Perry |
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Affiliation: | Department of Psychology, Hebrew University of Jerusalem, Jerusalem 9190501, Israel;Department of Information Systems and Analytics, National University of Singapore, Singapore, 117418, Singapore;Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, 138632, Singapore;Department of Psychology, Stanford University, Stanford, CA 94305, USA |
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Abstract: | When people encounter others’ emotions, they engage multiple brain systems, including parts of the sensorimotor cortex associated with motor simulation. Simulation-related brain activity is commonly described as a ‘low-level’ component of empathy and social cognition. It remains unclear whether and how sensorimotor simulation contributes to complex empathic judgments. Here, we combine a naturalistic social paradigm with a reliable index of sensorimotor cortex-based simulation: electroencephalography suppression of oscillatory activity in the mu frequency band. We recruited participants to watch naturalistic video clips of people (‘targets’) describing emotional life events. In two experiments, participants viewed these clips (i) with video and sound, (ii) with only video or (iii) with only sound and provided continuous ratings of how they believed the target felt. We operationalized ‘empathic accuracy’ as the correlation between participants’ inferences and targets’ self-report. In Experiment 1 (US sample), across all conditions, right-lateralized mu suppression tracked empathic accuracy. In Experiment 2 (Israeli sample), this replicated only when using individualized frequency-bands and only for the visual stimuli. Our results provide novel evidence that sensorimotor representations—as measured through mu suppression—play a role not only in low-level motor simulation, but also in higher-level inferences about others’ emotions, especially when visual cues are crucial for accuracy. |
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Keywords: | empathic accuracy Mu suppression inference EEG affective cognition |
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