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Processing of emotional body language within the visual social cognition network

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Erb,  M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Sokolov, A., Erb, M., Pollick, F., Frackowiak, R., Friston, K., & Pavlova, M. (2016). Processing of emotional body language within the visual social cognition network. Poster presented at 39th European Conference on Visual Perception (ECVP 2016), Barcelona, Spain.


Cite as: https://hdl.handle.net/21.11116/0000-0000-7B12-2
Abstract
Despite the significance of the brain networks for visual perception of emotions and intentions are indispensable in our everyday life, their architecture remains little understood. Here, we performed functional MRI (fMRI) and diffusion tensor imaging (DTI) in healthy subjects who had to recognize emotions (happy, neutral and angry) conveyed by a point-light arm seen knocking on an invisible door. Data pre-processing, fMRI data and dynamic causal modelling (DCM) analysis were performed with SPM12, and probabilistic tractography on the DTI data by using FSL. The data reveal higher activations in the right superior temporal sulcus (STS) and caudate nucleus for happy as compared to neutral knocking. Angry versus neutral knocking activate the inferior insula, perigenual anterior cingulate cortex (ACC) and posterior midcingulate cortex (MCC) in the left hemisphere. The cerebellar vermis (lobule IX) and right amygdala respond most strongly to neutral knocking. Structural and effective connectivity analysis reveals how emotional content of visually perceived stimuli is extracted and processed within this network. In summary, processing of emotional body motion appears to be lateralized depending on the emotional content. Combining information on function and structure may help to better understand neuropsychiatric conditions with impaired visual social cognition.