ArticleBMC medicine2024
Hierarchical individual variation and socioeconomic impact on personalized functional network topography in children.
Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Multivariate environmental exposures are reflected in whole-brain functional connectivity and cognition in youth.Developmental cognitive neuroscience · 2026Article
- Machine learning algorithm reveals neurodevelopmental signatures of combined family income and neighborhood disadvantage in adolescents.Scientific reports · 2026Article
- The effect of the "exposome" on developmental brain health and cognitive outcomes.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- Investigating hierarchical critical periods in human neurodevelopment.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- A systematic bibliometric and meta analysis of key factors and emerging AI and ML insights in shaping child cognitive development.Discover mental health · 2025Review
- Predicting sugar-sweetened beverage intake from the brain and known risk factors in adolescents.Physiology & behavior · 2025Article
- Human thalamocortical structural connectivity develops in line with a hierarchical axis of cortical plasticity.Nature neuroscience · 2025Article
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Authors and funding
16 authors.
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Abstract
backgroundThe spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored.
methodsWe used a machine learning approach-spatially regularized non-negative matrix factorization (NMF)-to delineate 17 personalized functional networks in children aged 9-10 years, utilizing high-quality functional MRI data from 6001 participants in the Adolescent Brain Cognitive Development study. Partial least square regression approach with repeated random twofold cross-validation was used to evaluate the association between the multivariate pattern of functional network topography and three SES factors, including family income-to-needs ratio, parental education, and neighborhood disadvantage.
resultsWe found that individual variations in personalized functional network topography aligned with the hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicted the three SES factors from unseen individuals. The associations between functional topography and SES factors were also hierarchically organized along the sensorimotor-association cortical axis, exhibiting stronger positive associations in the higher-order association cortex. Additionally, we have made the personalized functional networks publicly accessible.
conclusionsThese results offer insights into how SES influences neurodevelopment through personalized functional neuroanatomy in childhood, highlighting the cortex-wide, hierarchically organized plasticity of the functional networks in response to diverse SES backgrounds.
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