The impact of in-scanner head motion on structural connectivity derived from diffusion MRI.

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TitleThe impact of in-scanner head motion on structural connectivity derived from diffusion MRI.
Publication TypeJournal Article
Year of Publication2018
AuthorsBaum, GL, Roalf, DR, Cook, PA, Ciric, R, Rosen, AFG, Xia, C, Elliott, MA, Ruparel, K, Verma, R, Tunc, B, Gur, RC, Gur, RE, Bassett, DS, Satterthwaite, TD
JournalNeuroimage
Volume173
Pagination275-286
Date Published2018 06
ISSN1095-9572
KeywordsAdolescent, Artifacts, Brain, Child, Diffusion Magnetic Resonance Imaging, Female, Head, Humans, Image Interpretation, Computer-Assisted, Male, Motion, Neural Pathways, Neuroimaging, Young Adult
Abstract

Multiple studies have shown that data quality is a critical confound in the construction of brain networks derived from functional MRI. This problem is particularly relevant for studies of human brain development where important variables (such as participant age) are correlated with data quality. Nevertheless, the impact of head motion on estimates of structural connectivity derived from diffusion tractography methods remains poorly characterized. Here, we evaluated the impact of in-scanner head motion on structural connectivity using a sample of 949 participants (ages 8-23 years old) who passed a rigorous quality assessment protocol for diffusion magnetic resonance imaging (dMRI) acquired as part of the Philadelphia Neurodevelopmental Cohort. Structural brain networks were constructed for each participant using both deterministic and probabilistic tractography. We hypothesized that subtle variation in head motion would systematically bias estimates of structural connectivity and confound developmental inference, as observed in previous studies of functional connectivity. Even following quality assurance and retrospective correction for head motion, eddy currents, and field distortions, in-scanner head motion significantly impacted the strength of structural connectivity in a consistency- and length-dependent manner. Specifically, increased head motion was associated with reduced estimates of structural connectivity for network edges with high inter-subject consistency, which included both short- and long-range connections. In contrast, motion inflated estimates of structural connectivity for low-consistency network edges that were primarily shorter-range. Finally, we demonstrate that age-related differences in head motion can both inflate and obscure developmental inferences on structural connectivity. Taken together, these data delineate the systematic impact of head motion on structural connectivity, and provide a critical context for identifying motion-related confounds in studies of structural brain network development.

DOI10.1016/j.neuroimage.2018.02.041
Alternate JournalNeuroimage
PubMed ID29486323
PubMed Central IDPMC5911236
Grant ListP50 MH096891 / MH / NIMH NIH HHS / United States
R01 MH112847 / MH / NIMH NIH HHS / United States
R01 NS099348 / NS / NINDS NIH HHS / United States
R01 MH107235 / MH / NIMH NIH HHS / United States
R01 DC009209 / DC / NIDCD NIH HHS / United States
R21 MH106799 / MH / NIMH NIH HHS / United States
R01 MH112070 / MH / NIMH NIH HHS / United States
RC2 MH089924 / MH / NIMH NIH HHS / United States
K01 MH102609 / MH / NIMH NIH HHS / United States
R01 HD086888 / HD / NICHD NIH HHS / United States
R01 MH109520 / MH / NIMH NIH HHS / United States
R01 NS085211 / NS / NINDS NIH HHS / United States
R01 MH107703 / MH / NIMH NIH HHS / United States
RC2 MH089983 / MH / NIMH NIH HHS / United States