Temporal dynamics of resting EEG networks are associated with prosociality

Bastian Schiller,Bastian Schiller,Markus Heinrichs,Markus Heinrichs,Sarah Teige-Mocigemba,Karl Christoph Klauer,Tobias Kleinert

doi:10.1038/s41598-020-69999-5

Abstract

As prosociality is key to facing many of our societies’ global challenges (such as fighting a global pandemic), we need to better understand why some individuals are more prosocial than others. The present study takes a neural trait approach, examining whether the temporal dynamics of resting EEG networks are associated with inter-individual differences in prosociality. In two experimental sessions, we collected 55 healthy males’ resting EEG, their self-reported prosocial concern and values, and their incentivized prosocial behavior across different reward domains (money, time) and social contexts (collective, individual). By means of EEG microstate analysis we identified the temporal coverage of four canonical resting networks (microstates A, B, C, and D) and their mutual communication in order to examine their association with an aggregated index of prosociality. Participants with a higher coverage of microstate A and more transitions from microstate C to A were more prosocial. Our study demonstrates that temporal dynamics of intrinsic brain networks can be linked to complex social behavior. On the basis of previous findings on links of microstate A with sensory processing, our findings suggest that participants with a tendency to engage in bottom-up processing during rest behave more prosocially than others.

Highlights

Prosocial behavior, such as cooperating, sharing resources, and providing aid, is widespread, universal[1,2] and, as shown recently, of critical importance to solve global issues like fighting a pandemic[3]
We detected correlations ranging from 0.772–0.922 with regard to microstate coverage, duration, and occurrence, and correlations ranging from 0.281 to 0.720 concerning microstate transitions. These findings show the potential of microstate parameters to serve as neural trait markers that might be associated with inter-individual differences in prosociality
Can someone’s task-free neurophysiological processing reveal information on someone’s prosociality? By analyzing the spatio-temporal dynamics of resting EEG recordings the present study demonstrates that an individual’s propensity of how to engage the four canonical EEG resting networks is associated with an index of an individual’s domain-general prosociality

Summary

Introduction

Prosocial behavior, such as cooperating, sharing resources, and providing aid, is widespread, universal[1,2] and, as shown recently, of critical importance to solve global issues like fighting a pandemic[3]. We analyze changes in scalp electrical potential topographies, thereby considering changes in global network activity Using these networks’ intrinsically generated activity, we attempt to identify associations of brain activity and prosocial behavior independent from specific social contexts. Almost 80% of the variance in the resting EEG data can be explained by just four archetypal microstates A–D, i.e., resting networks which may result from evolutionarily determined, brain-intrinsic biases toward particular patterns of co-activation suited to representing environmentally relevant information[29] These networks’ temporal dynamics have been proven to be highly reliable, specific, and reproducible across multiple independent studies[30,31], ideally qualifying them as neural trait markers. Due to our study’s exploratory nature, we applied Bonferroni-correction for multiple tests to our findings

Methods

Results

Conclusion