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

Citation

Youm, Yoosik; Kim, Junsol; Kwak, Seyul; Chey, Jeanyung (2021), Neural and social correlates of attitudinal brokerage: using the complete social networks of two entire villages, Dryad, Dataset, https://doi.org/10.5061/dryad.wdbrv15mz

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 (1) mentalizing regions known to be recruited in reading and understanding others’ belief states; and (2) regions associated with moral judgments or information propagation. This result was corroborated by leave-one-out cross-validation, five-fold 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 brokerage position where people have ties with two people who are not otherwise connected.

Usage Notes

Please read readme.txt. Code to replicate the results are available at https://github.com/JunsolKim/neural-and-social-correlates-of-attitudinal-brokerage

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea., Award: NRF-2017S1A3A2067165