ArticleCommunications biology2022
White matter connectivity in brain networks supporting social and affective processing predicts real-world social network characteristics.
Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Article
- White matter microstructure and structural network alterations in children with global developmental delay.Pediatric research · 2026Article
- Connectome-based predictive modeling of concurrent and longitudinal substance use vulnerability in adolescence.Developmental cognitive neuroscience · 2026Article
- Free water, occipital volume and changes in depressive symptoms in the LifeAfter90 study.Scientific reports · 2026Article
- Article
- Connectome-Based Predictive Modeling of Concurrent and Prospective Substance Use in Adolescence.bioRxiv : the preprint server for biology · 2025Article
- Leveraging AI-Driven Neuroimaging Biomarkers for Early Detection and Social Function Prediction in Autism Spectrum Disorders: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Interactions between neural representations of the social and spatial environment.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- White matter connectivity and social functioning in survivors of pediatric brain tumor.Journal of neuro-oncology · 2024Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human behavior is embedded in social networks. Certain characteristics of the positions that people occupy within these networks appear to be stable within individuals. Such traits likely stem in part from individual differences in how people tend to think and behave, which may be driven by individual differences in the neuroanatomy supporting socio-affective processing. To investigate this possibility, we reconstructed the full social networks of three graduate student cohorts (N = 275; N = 279; N = 285), a subset of whom (N = 112) underwent diffusion magnetic resonance imaging. Although no single tract in isolation appears to be necessary or sufficient to predict social network characteristics, distributed patterns of white matter microstructural integrity in brain networks supporting social and affective processing predict eigenvector centrality (how well-connected someone is to well-connected others) and brokerage (how much one connects otherwise unconnected others). Thus, where individuals sit in their real-world social networks is reflected in their structural brain networks. More broadly, these results suggest that the application of data-driven methods to neuroimaging data can be a promising approach to investigate how brains shape and are shaped by individuals' positions in their real-world social networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.