Investigating the neural basis of empathy by EEG hyperscanning during a Third Party Punishment

Abstract

The recently developed technique of hyperscanning consists of the simultaneous recording of brain activity from multiple subjects involved in social interaction. The multivariate analysis of data coming from different subjects allows to model a system made of multiple brains interacting, and to characterize it in relation with different processes at the basis of social cognition. In this study, we investigate the empathy established between two subjects during a Third Party Punishment paradigm, in terms of the properties of the multiple-brain network obtained from EEG hyperscanning. Preliminary results show that significantly different multiple-brain network structures characterize a social situation operated by a human agent with respect to a computer based condition, and that the different levels of empathy induced by a fair or unfair treatment received by one of the subjects are characterized by denser inter-subjects connectivity and lower divisibility in the two single brain networks.