The topology of interpersonal neural network in weak social ties

Abstract

AbstractPeople often have opportunities to engage in social interactions with strangers, which have been reported to contribute to their well-being. Although strategies for social interaction between strangers differ from those between acquaintances, the differences in neural basis of social interaction have not been fully elucidated. In this study, we examined the geometrical properties of interpersonal neural networks in pairs of strangers and acquaintances during joint tapping using dual electroencephalography (EEG). Twenty-one pairs of participants performed antiphase joint tapping under four different conditions. Intra-brain synchronizations were calculated using the weighted phase lag index (wPLI) for all possible intra-brain pairs of the 29 channels (29C2= 406), and inter-brain synchronizations were calculated using the phase locking value (PLV) for all possible inter-brain pairs of the 29 channels (29 × 29 = 841) in the theta, alpha, and beta frequency bands. Electrode pairs with larger wPLI and PLV than their surrogates were defined as the nodes (EEG channels) and edges (connections between nodes) of the neural networks. We then calculated the global efficiency, local efficiency, clustering coefficient, and modularity derived from graph theory for the combined intra- and inter-brain networks of each pair. No significant differences in the tapping phase variance were identified between the stranger and acquaintance pairs. However, in the combined intra- and inter-brain theta EEG (4–7 Hz) networks, stranger pairs showed larger local efficiency and cluster coefficients than acquaintance pairs, indicating that the two brains of stranger pairs were more densely connected. Moreover, in the beta EEG bands, the modularity of the two brains was low in the fast condition, indicating that the two brains were coupled when the task demand was high. Our results show that weak social ties promote more extensive social interactions and result in dense brain-to-brain coupling.