Similarity in functional brain connectivity at rest predicts interpersonal closeness in the social network of an entire village

Ryan Hyon, Yoosik Youm, Junsol Kim, Jeanyung Chey, Seyul Kwak, Carolyn Parkinson

Research output: Contribution to journalArticlepeer-review

Abstract

People often have the intuition that they are similar to their friends, yet evidence for homophily (being friends with similar others) based on self-reported personality is inconsistent. Functional connectomes—patterns of spontaneous synchronization across the brain—are stable within individuals and predict how people tend to think and behave. Thus, they may capture interindividual variability in latent traits that are particularly similar among friends but that might elude self-report. Here, we examined interpersonal similarity in functional connectivity at rest—that is, in the absence of external stimuli—and tested if functional connectome similarity is associated with proximity in a real-world social network. The social network of a remote village was reconstructed; a subset of residents underwent functional magnetic resonance imaging. Similarity in functional connectomes was positively related to social network proximity, particularly in the default mode network. Controlling for similarities in demographic and personality data (the Big Five personality traits) yielded similar results. Thus, functional connectomes may capture latent interpersonal similarities between friends that are not fully captured by commonly used demographic or personality measures. The localization of these results suggests how friends may be particularly similar to one another. Additionally, geographic proximity moderated the relationship between neural similarity and social network proximity, suggesting that such associations are particularly strong among people who live particularly close to one another. These findings suggest that social connectivity is reflected in signatures of brain functional connectivity, consistent with the common intuition that friends share similarities that go beyond, for example, demographic similarities.

Original languageEnglish
Pages (from-to)33149-33160
Number of pages12
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number52
DOIs
Publication statusPublished - 2021 Dec 29

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS. We thank Dr. Elisa Baek and João Guassi Moreira for helpful discussion. This work was supported by the National Research Foundation of Korea (NRF-2017S1A3A2067165) and Yonsei University Research Grant of 2020 (Y.Y.) and a Sloan Foundation Research Fellowship (C.P.).

Publisher Copyright:
© 2020 National Academy of Sciences. All rights reserved.

All Science Journal Classification (ASJC) codes

  • General

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