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Population-based neuroimaging studies that feature complex sampling designs enable researchers to generalize their results more widely. However, several theoretical and analytical questions pose challenges to researchers interested in these data. The following is a resource for researchers interested in using population-based neuroimaging data. We provide an overview of sampling designs and describe the differences between traditional model-based analyses and survey-oriented design-based analyses. To elucidate key concepts, we leverage data from the Adolescent Brain Cognitive Development℠ Study (ABCD Study®), a population-based sample of 11,878 9–10-year-olds in the United States. Analyses revealed modest sociodemographic discrepancies between the target population of 9–10-year-olds in the U.S. and both the recruited ABCD sample and the analytic sample with usable structural and functional imaging data. In evaluating the associations between socioeconomic resources (i.e., constructs that are tightly linked to recruitment biases) and several metrics of brain development, we show that model-based approaches over-estimated the associations of household income and under-estimated the associations of caregiver education with total cortical volume and surface area. Comparable results were found in models predicting neural function during two fMRI task paradigms. We conclude with recommendations for ABCD Study® users and users of population-based neuroimaging cohorts more broadly.

Little is known about how exposure to limited socioeconomic resources (SER) in childhood gets “under the skin” to shape brain development, especially using rigorous whole-brain multivariate methods in large, adequately powered samples. The present study examined resting state functional connectivity patterns from 5821 youth in the Adolescent Brain Cognitive Development (ABCD) study, employing multivariate methods across three levels: whole-brain, network-wise, and connection-wise. Across all three levels, SER was associated with widespread alterations across the connectome. However, critically, we found that parental education was the primary driver of neural associations with SER. These parental education associations with the developing connectome exhibited notable concentrations in somatosensory and subcortical regions, and they were partially accounted for by home enrichment activities, child’s cognitive abilities, and child’s grades, indicating interwoven links between parental education, child stimulation, and child cognitive performance. These results add a new data-driven, multivariate perspective on links between household SER and the child’s developing functional connectome.

Abstract General cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, are poorly understood. The present study examined functional connectomes from 5937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study. Using multivariate predictive modeling methods, we identified whole-brain functional connectivity patterns linked to GCA. In leave-one-site-out cross-validation, we found these connectivity patterns exhibited strong and statistically reliable generalization at 19 out of 19 held-out sites accounting for 18.0% of the variance in GCA scores (cross-validated partial η 2). GCA-related connections were remarkably dispersed across brain networks: across 120 sets of connections linking pairs of large-scale networks, significantly elevated GCA-related connectivity was found in 110 of them, and differences in levels of GCA-related connectivity across brain networks were notably modest. Consistent with prior work, socioeconomic status was a strong predictor of GCA in this sample, and we found that distributed GCA-related brain connectivity patterns significantly statistically mediated this relationship (mean proportion mediated: 15.6%, p

Abstract Although psychiatric phenotypes are hypothesized to organize into a two-factor internalizing–externalizing structure, few studies have evaluated the structure of psychopathology in older adults, nor explored whether genome-wide polygenic scores (PGSs) are associated with psychopathology in a domain-specific manner. We used data from 6003 individuals of European ancestry from the Health and Retirement Study, a large population-based sample of older adults in the United States. Confirmatory factor analyses were applied to validated measures of psychopathology and PGSs were derived from well-powered genome-wide association studies (GWAS). Genomic SEM was implemented to construct latent PGSs for internalizing, externalizing, and general psychopathology. Phenotypically, the data were best characterized by a single general factor of psychopathology, a factor structure that was replicated across genders and age groups. Although externalizing PGSs (cannabis use, antisocial behavior, alcohol dependence, attention deficit hyperactivity disorder) were not associated with any phenotypes, PGSs for major depressive disorder, neuroticism, and anxiety disorders were associated with both internalizing and externalizing phenotypes. Moreover, the variance explained in the general factor of psychopathology increased by twofold (from 1% to 2%) using the latent internalizing or latent one-factor PGSs, derived using weights from Genomic Structural Equation Modeling (SEM), compared with any of the individual PGSs. Collectively, results suggest that genetic risk factors for and phenotypic markers of psychiatric disorders are transdiagnostic in older adults of European ancestry. Alternative explanations are discussed, including methodological limitations of GWAS and phenotypic measurement of psychiatric outcome in large-scale population-based studies.

Youth growing up in disadvantaged neighborhoods are more likely than their advantaged peers to face negative behavioral and mental health outcomes. Although studies have shown that adversity can undermine positive development via its impact on the developing brain, few studies have examined the association between neighborhood disadvantage and neural function, and no study has investigated potential social mechanisms within the neighborhood that might link neighborhood disadvantage to altered neural function. The current study evaluated the association between neighborhood disadvantage and amygdala reactivity during socioemotional face processing. We also assessed whether and which neighborhood-level social processes were related to amygdala reactivity, and whether these social processes mediated or moderated the association between neighborhood disadvantage and altered amygdala reactivity. We examined these aims in a registered report, using a sample of twins aged 7–19 years (N = 354 families, 708 twins) recruited from birth records with enrichment for neighborhood disadvantage. Twins completed a socioemotional face processing fMRI task and a sample of unrelated participants from the twins’ neighborhoods were also recruited to serve as informants on neighborhood social processes. We found that neighborhood disadvantage was associated with greater right amygdala reactivity to threat, but only when neighborhood informants perceived norms in the neighborhood to be more permissive regarding general safety and management. The findings from this research add to the growing literature highlighting the influence of neighborhood disadvantage on amygdala function and the ways that supportive social processes may buffer the impact of adversity on brain function.

Emerging literature links neighborhood disadvantage to altered neural function in regions supporting socioemotional and threat processing. Few studies, however, have examined the proximal mechanisms through which neighborhood disadvantage is associated with neural functioning. In a sample of 7- to 19-year-old twins recruited from disadvantaged neighborhoods (354 families, 708 twins; 54.5% boys; 78.5% White, 13.0% Black, 8.5% other racial/ethnic group membership), we found that exposure to community violence was related to increased amygdala reactivity during socioemotional processing and may be one mechanism linking neighborhood disadvantage to amygdala functioning. Importantly, parenting behavior appeared to modulate these effects, such that high parental nurturance buffered the effect of exposure to community violence on amygdala reactivity. These findings elucidate the potential impact of exposure to community violence on brain function and highlight the role parents can play in protecting youth from the neural effects of exposure to adversity.