Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

TL;DR

This study introduces hyper-brain networks derived from EEG data to analyze and predict cooperative or defective behavior in social interactions, revealing neural connectivity patterns associated with decision-making.

Contribution

It presents a novel hyper-brain network approach to simultaneously analyze inter- and intra-brain connectivity during social decision-making tasks.

Findings

Defectors show less inter-brain connectivity and higher modularity.

Hyper-brain network patterns can predict defection before decisions are made.

Connectivity changes precede observable cooperative or defective choices.

Abstract

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity - i.e. the tendency to form two separate subgraphs - than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network.