TY  - JOUR
AU  - Chen, Jianzhong
AU  - Tam, Angela
AU  - Kebets, Valeria
AU  - Orban, Csaba
AU  - Ooi, Leon Qi Rong
AU  - Asplund, Christopher L.
AU  - Marek, Scott
AU  - Dosenbach, Nico U. F.
AU  - Eickhoff, Simon B.
AU  - Bzdok, Danilo
AU  - Holmes, Avram J.
AU  - Yeo, B. T. Thomas
TI  - Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study
JO  - Nature Communications
VL  - 13
IS  - 1
SN  - 2041-1723
CY  - [London]
PB  - Nature Publishing Group UK
M1  - FZJ-2022-02853
SP  - 2217
PY  - 2022
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - pmid:35468875
UR  - <Go to ISI:>//WOS:000787388900018
DO  - DOI:10.1038/s41467-022-29766-8
UR  - https://juser.fz-juelich.de/record/908808
ER  -