Department of Computer, Control and Management Engineering

Two-person neuroscience (2 ​PN) is a recently introduced conceptual and methodological framework used to investigate the neural basis of human social interaction from simultaneous neuroimaging of two or more subjects (hyperscanning). In this study, we adopted a 2 ​PN approach and a multiple-brain connectivity model to investigate the neural basis of a form of cooperation called joint action. We hypothesized different intra-brain and inter-brain connectivity patterns when comparing the interpersonal properties of joint action with non-interpersonal conditions, with a focus on co-representation, a core ability at the basis of cooperation. 32 subjects were enrolled in dual-EEG recordings during a computerized joint action task including three conditions: one in which the dyad jointly acted to pursue a common goal (joint), one in which each subject interacted with the PC (PC), and one in which each subject performed the task individually (Solo). A combination of multiple-brain connectivity estimation and specific indices derived from graph theory allowed to compare interpersonal with non-interpersonal conditions in four different frequency bands. Our results indicate that all the indices were modulated by the interaction, and returned a significantly stronger integration of multiple-subject networks in the joint vs. PC and Solo conditions. A subsequent classification analysis showed that features based on multiple-brain indices led to a better discrimination between social and non-social conditions with respect to single-subject indices. Taken together, our results suggest that multiple-brain connectivity can provide a deeper insight into the understanding of the neural basis of cooperation in humans.