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Updated: Mar 20, 2026

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
Published on: July 21, 2021
Unlocking interbrain neural signatures differences during triadic cooperation and competition: Evidence from EEG
Yuqin Li1, Senqi Li1, Jiaxin Xie1
1The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China; Brain-Computer Interface & Brain-Inspired Intelligence Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 611731, China.
None:
Cooperation and competition are fundamental to human social interaction. While recent hyperscanning studies have linked stronger interbrain synchrony (IBS) to successful cooperation, most have focused on dyadic interactions, leaving the underlying neural mechanisms of group-level social behavior largely unknown. Here, we employed EEG hyperscanning to investigate interbrain neural dynamics of triadic cooperative and competitive interactions. Distinct interbrain network patterns emerged in the delta and beta bands, with cooperation showing enhanced frontal-parietal IBS and more efficient network properties. Non-parametric cluster-based permutation tests further identified significant regional differences in a left-lateralized frontal-temporal-parietal cluster in both bands. Crucially, increased delta-band frontal-parietal IBS was closely associated with better group-level cooperative performance. Moreover, classification and prediction models based on delta-band interbrain metrics successfully distinguished interaction types and predicted cooperative outcomes. These findings uncover interbrain neurocognitive traits that reflect specific social behavioral contexts, highlighting the pivotal role of frontal-parietal synchrony and delta-band modulations in supporting group cooperation. Together, our results advance the understanding of the neural basis of triadic social interaction and underscore the potential of interbrain network signatures as biomarkers for decoding and predicting complex social behaviors.

