Variability in Brain Structure and Function Reflects Lack of Peer Support

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Matthias Schurz - , Radboud University Nijmegen, University of Oxford, University of Innsbruck (Author)
  • Lucina Q Uddin - , University of Miami (Author)
  • Philipp Kanske - , Chair of Clinical Psychology an Behavioral Neuroscience, Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Claus Lamm - , University of Vienna (Author)
  • Jérôme Sallet - , University of Oxford, Université de Lyon (Author)
  • Boris C Bernhardt - , McGill University (Author)
  • Rogier B Mars - , Radboud University Nijmegen, University of Oxford (Author)
  • Danilo Bzdok - , McGill University (Author)

Abstract

Humans are a highly social species. Complex interactions for mutual support range from helping neighbors to building social welfare institutions. During times of distress or crisis, sharing life experiences within one's social circle is critical for well-being. By translating pattern-learning algorithms to the UK Biobank imaging-genetics cohort (n = ~40 000 participants), we have delineated manifestations of regular social support in multimodal whole-brain measurements. In structural brain variation, we identified characteristic volumetric signatures in the salience and limbic networks for high- versus low-social support individuals. In patterns derived from functional coupling, we also located interindividual differences in social support in action-perception circuits related to binding sensory cues and initiating behavioral responses. In line with our demographic profiling analysis, the uncovered neural substrates have potential implications for loneliness, substance misuse, and resilience to stress.

Details

Original languageEnglish
Pages (from-to)4612-4627
Number of pages16
JournalCerebral cortex (New York, N.Y. : 1991)
Volume31
Issue number10
Publication statusPublished - Oct 2021
Peer-reviewedYes

External IDs

PubMedCentral PMC8408465
Scopus 85116111623

Keywords

Keywords

  • Bayesian hierarchical modeling, machine learning, population neuroscience, salience network, social brain