Journal
NATURE COMMUNICATIONS
Volume 8, Issue -, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-017-00908-7
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Funding
- National Institutes of Mental Health [K01MH097978, R01-MH103291, R01-106482]
- National Institute on Drug Abuse [R03DA037405]
- National Institute on Alcohol Abuse and Alcoholism [K01AA021511]
- Jacobs Foundation
- AIM for Mental Health, a program of One Mind Institute (IMHRO)
- Pediatric Imaging, Neurocognition and Genetics Study (PING) (National Institutes of Health) [RC2DA029475]
- National Institute on Drug Abuse
- Eunice Kennedy Shriver National Institute of Child Health & Human Development
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Despite calls to incorporate population science into neuroimaging research, most studies recruit small, non-representative samples. Here, we examine whether sample composition influences age-related variation in global measurements of gray matter volume, thickness, and surface area. We apply sample weights to structural brain imaging data from a community-based sample of children aged 3-18 (N = 1162) to create a weighted sample that approximates the distribution of socioeconomic status, race/ethnicity, and sex in the U.S. Census. We compare associations between age and brain structure in this weighted sample to estimates from the original sample with no sample weights applied (i.e., unweighted). Compared to the unweighted sample, we observe earlier maturation of cortical and sub-cortical structures, and patterns of brain maturation that better reflect known developmental trajectories in the weighted sample. Our empirical demonstration of bias introduced by non-representative sampling in this neuroimaging cohort suggests that sample composition may influence understanding of fundamental neural processes.
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