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Decoding Human Interaction Type From Inter-Brain Synchronization by Using EEG Brain Network

delete2024-01-01
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PRE
AI
X
Xiangcun Wang
R
Ran Shi
吴瑕 cover
吴瑕 (Xia Wu)
张家才 (Jiacai Zhang) *
DOI:10.1109/JBHI.2023.3329742delete
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Abstract

Abstract

En 中文
Cooperation and competition are two common forms of interpersonal interactions and exploring inter-brain synchronization in these two forms can help to further deliberate the underlying neural mechanisms of interpersonal interactions. Recently, studies revealed that electrode-paired inter-brain synchronization plays an important role in human interactions. This study investigated the neural correlates of interpersonal synchronization at the brain network scale and interaction type. Firstly, the network-wise inter-brain synchronization (NIBS) index reflecting cross-brain network synchronization from the global brain perspective was advanced. Secondly, statistical analysis demonstrated that there are differences in NIBS activities between cooperative and competitive interactions. And a row-filtered depthwise separable convolution network was proposed to classify the NIBS features. Results of EEG hyper-scanning data showed significant differences in NIBS between cooperative and competitive tasks, and a comparative study manifested that the cross-brain synchronization in cooperative tasks is more consistent than that of competitive tasks. The neural decoder using a modified convolution network achieved a peak accuracy of 96.05% under the binary classification(cooperation vs competition).
Keywords:
EEG hyper-scanning
interpersonal interaction
inter-brain synchronization
neural decoding

Journal

IEEE Journal of Biomedical and Health Informatics cover
IEEE Journal of Biomedical and Health Informatics
IF:
6.8
Papers:
4.5K
Citations:
2.0W

Organization

B
Beijing Normal University
Scholars:
3.3W
Papers: 2.7W
Citations: 4.2W