Keywords: Adolescents, Adolescents, Cortical Thickness, Sleep, Machine learning
Motivation: Sleep deficits are prevalent in adolescent populations. Studies have shown that reduced sleep time significantly correlates with lower cortical thickness. However, there is considerable heterogeneity in how insufficient sleep affects individuals.
Goal(s): To understand the heterogeneous effects of insufficient sleep on the brain.
Approach: We employed a novel machine learning method (SuStaIn) to unravel the heterogeneous effects of insufficient sleep on the adolescent brain.
Results: We identified three progression paths of cortical thickness associated with insufficient sleep, originating from different brain areas: postcentral, pericalcarine, and entorhinal. Three subtypes were distinctive in sleep behaviors, comorbidity, cognitive function, and academic performance.
Impact: We identified three distinct effect patterns of insufficient sleep on cortical thickness with unique sleep behaviors, disease comorbidity, cognitive function, and academic performances. These findings contribute to a comprehensive understanding of the impact of insufficient sleep on adolescent development.
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