Neural and social correlates of attitudinal brokerage: Using the complete social networks of two entire villages

Yoosik Youm, Junsol Kim, Seyul Kwak, Jeanyung Chey

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

To avoid polarization and maintain small-worldness in society, people who act as attitudinal brokers are critical. These people maintain social ties with people who have dissimilar and even incompatible attitudes. Based on resting-state functional magnetic resonance imaging (n = 139) and the complete social networks from two Korean villages (n = 1508), we investigated the individual-level neural capacity and social-level structural opportunity for attitudinal brokerage regarding gender role attitudes. First, using a connectome-based predictive model, we successfully identified the brain functional connectivity that predicts attitudinal diversity of respondents' social network members. Brain regions that contributed most to the prediction included mentalizing regions known to be recruited in reading and understanding others' belief states. This result was corroborated by leave-one-out cross-validation, fivefold cross-validation and external validation where the brain connectivity identified in one village was used to predict the attitudinal diversity in another independent village. Second, the association between functional connectivity and attitudinal diversity of social network members was contingent on a specific position in a social network, namely, the structural brokerage position where people have ties with two people who are not otherwise connected.

Original languageEnglish
Article number20202866
JournalProceedings of the Royal Society B: Biological Sciences
Volume288
Issue number1944
DOIs
Publication statusPublished - 2021 Feb 10

Bibliographical note

Publisher Copyright:
© 2021 The Authors.

All Science Journal Classification (ASJC) codes

  • General Immunology and Microbiology
  • General Biochemistry,Genetics and Molecular Biology
  • General Environmental Science
  • General Agricultural and Biological Sciences

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