Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study

Jianzhong Chen, Angela Tam, Valeria Kebets, Csaba Orban, Leon Qi Rong Ooi, Christopher L. Asplund, Scott Marek, Nico U.F. Dosenbach, Simon B. Eickhoff, Danilo Bzdok, Avram J. Holmes, B. T.Thomas Yeo

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

How individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood.

Original languageEnglish
Article number2217
JournalNature communications
Volume13
Issue number1
DOIs
StatePublished - Dec 2022

Fingerprint

Dive into the research topics of 'Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study'. Together they form a unique fingerprint.

Cite this