Abstract Adolescence is a critical period of brain maturation, yet how functional dynamics relate to white-matter microstructure at the individual level remains poorly understood. We developed a machine learning workflow to predict fractional anisotropy (FA) from distributed resting-state functional connectivity (FC) in two large adolescent cohorts: NCANDA (n=814, 12–22 years, longitudinal) and HCP-Development (n=472, 12–22 years, cross-sectional). Whole-brain FA could be modestly predicted from FC (r=0.16 in NCANDA; r=0.27 in HCP-D). The accuracy of predicting regional FA significantly varied across 27 white-matter regions, with highest structure-function coupling detected in fiber tracts subserving unimodal cortical regions. These regional accuracy scores were reproducible between datasets (r=0.95). Region-specific analyses also revealed tract-clustered FC predictors, highlighting distinct large-scale functional circuits underlying regional microstructural integrity. We then defined a “structure–function gap” as the residual between predicted and observed FA in each white-matter region. These gap measures were significantly associated with a broad constellation of cognitive and behavioral measures, particularly involving memory, impulsivity, and executive function. Notably, significant behavioral coupling emerged in Corticospinal and Cingulum pathways. Together, these findings establish individualized structure–function coupling as a reproducible, anatomically specific, and behaviorally informative marker in youth, offering a new framework to link distributed FC patterns to white-matter development and behavioral variability.
Jafrasteh et al. (Thu,) studied this question.
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