Open AccessLimits to the generalizability of resting-state functional magnetic resonance imaging studies of youth: An examination of ABCD Study® baseline data
Author(s) -
Kelly T. Cosgrove,
Timothy J. McDermott,
Evan J. White,
Matthew W. Mosconi,
Wesley K. Thompson,
Martin P. Paulus,
Carlos CardenasIniguez,
Robin L. Aupperle
Publication year - 2022
Publication title -
brain imaging and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.239
H-Index - 50
eISSN - 1931-7565
pISSN - 1931-7557
DOI - 10.1007/s11682-022-00665-2
Subject(s) - generalizability theory , psychology , functional magnetic resonance imaging , population , neuropsychology , resting state fmri , noise (video) , audiology , medicine , developmental psychology , cognition , artificial intelligence , psychiatry , computer science , environmental health , neuroscience , image (mathematics)
This study examined how resting-state functional magnetic resonance imaging (rs-fMRI) data quality and availability relate to clinical and sociodemographic variables within the Adolescent Brain Cognitive Development Study. A sample of participants with an adequate sample of quality baseline rs-fMRI data containing low average motion (framewise displacement ≤ 0.15; low-noise; n = 4,356) was compared to a sample of participants without an adequate sample of quality data and/or containing high average motion (higher-noise; n = 7,437) using Chi-squared analyses and t-tests. A linear mixed model examined relationships between clinical and sociodemographic characteristics and average head motion in the sample with low-noise data. Relative to the sample with higher-noise data, the low-noise sample included more females, youth identified by parents as non-Hispanic white, and youth with married parents, higher parent education, and greater household incomes (ORs = 1.32-1.42). Youth in the low-noise sample were also older and had higher neurocognitive skills, lower BMIs, and fewer externalizing and neurodevelopmental problems (ds = 0.12-0.30). Within the low-noise sample, several clinical and demographic characteristics related to motion. Thus, participants with low-noise rs-fMRI data may be less representative of the general population and motion may remain a confound in this sample. Future rs-fMRI studies of youth should consider these limitations in the design and analysis stages in order to optimize the representativeness and clinical relevance of analyses and results.