Interbrain neural correlates of self and other integration in joint statistical learning - Zheng Zheng; Jun Wang (npj Science of Learning)
Abstract While statistical learning is often studied individually, its collective representation through self-other integration remains unclear. This study examines dynamic self-other integration and its multi-brain mechanism using simultaneous recordings from dyads. Participants (N = 112) each repeatedly responded to half of a fixed stimulus sequence with either an active partner (joint context) or a passive observer (baseline context). Significant individual statistical learning was evident in the joint context, characterized by decreased reaction time (RT) and intra-brain neural responses, followed by a quadratic trend (i.e., first increasing and then decreasing) upon insertion of an interference sequence. More importantly, Brain-to-Brain Coupling (BtBC) in the theta band also showed learning and modulation-related trends, with its slope negatively and positively correlating with the slopes of RT and intra-brain functional connectivity, respectively. These results highlight the dynamic nature of self-other integration in joint statistical learning, with statistical regularities implicitly and spontaneously modulating this process. Notably, the BtBC serves as a key neural correlate underlying the dynamics of self-other integration.