Representing brain-behavior associations by retaining high-motion minoritized youth.

Abstract

Background: Population neuroscience datasets provide an opportunity for researchers to estimate reproducible effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals.

Methods: We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development^SM Study (N = 5,733). For the two methods, brain-behavior associations were computed as the partial Spearman's Rank correlations (R_s) between functional connectivity and cognitive performance (NIH Cognition Toolbox) as well as externalizing and internalizing psychopathology (Child Behavior Checklist [CBCL]) while adjusting for participant sex assigned at birth and head motion.

Results: Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Motion-ordering and bagging methods retained more than 99% of Black and Hispanic youth. Both methods produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data.

Conclusions: The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and result in reproducible effect sizes in diverse populations.