Sample composition alters associations between age and brain structure

Kaja Z. LeWinn (), Margaret A. Sheridan, Katherine M. Keyes, Ava Hamilton and Katie A. McLaughlin
Additional contact information
Kaja Z. LeWinn: University of California
Margaret A. Sheridan: University of North Carolina at Chapel Hill
Katherine M. Keyes: Columbia University
Ava Hamilton: Columbia University
Katie A. McLaughlin: University of Washington

Nature Communications, 2017, vol. 8, issue 1, 1-14

Abstract: Abstract 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.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-017-00908-7 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-00908-7

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-017-00908-7

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().