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@ARTICLE{Chen:908808,
      author       = {Chen, Jianzhong and Tam, Angela and Kebets, Valeria and
                      Orban, Csaba and Ooi, Leon Qi Rong and Asplund, Christopher
                      L. and Marek, Scott and Dosenbach, Nico U. F. and Eickhoff,
                      Simon B. and Bzdok, Danilo and Holmes, Avram J. and Yeo, B.
                      T. Thomas},
      title        = {{S}hared and unique brain network features predict
                      cognitive, personality, and mental health scores in the
                      {ABCD} study},
      journal      = {Nature Communications},
      volume       = {13},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {FZJ-2022-02853},
      pages        = {2217},
      year         = {2022},
      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.},
      cin          = {INM-7},
      ddc          = {500},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5252},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:35468875},
      UT           = {WOS:000787388900018},
      doi          = {10.1038/s41467-022-29766-8},
      url          = {https://juser.fz-juelich.de/record/908808},
}