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@ARTICLE{Zhang:884812,
      author       = {Zhang, Yong Hang and Hao, Shuji and Lee, Annie and
                      Eickhoff, Simon B. and Pecheva, Diliana and Cai, Shirong and
                      Meaney, Michael and Chong, Yap‐Seng and Broekman, Birit F.
                      P. and Fortier, Marielle V. and Qiu, Anqi},
      title        = {{D}o intrinsic brain functional networks predict working
                      memory from childhood to adulthood?},
      journal      = {Human brain mapping},
      volume       = {4},
      number       = {16},
      issn         = {1097-0193},
      address      = {New York, NY},
      publisher    = {Wiley-Liss},
      reportid     = {FZJ-2020-03269},
      pages        = {4574-4586},
      year         = {2020},
      abstract     = {Working memory (WM) is defined as the ability to maintain a
                      representation online to guide goal‐directed behavior. Its
                      capacity in early childhood predicts academic achievements
                      in late childhood and its deficits are found in various
                      neurodevelopmental disorders. We employed resting‐state
                      fMRI (rs‐fMRI) of 468 participants aged from 4 to
                      55 years and connectome‐based predictive modeling (CPM)
                      to explore the potential predictive power of intrinsic
                      functional networks to WM in preschoolers, early and late
                      school‐age children, adolescents, and adults. We defined
                      intrinsic functional networks among brain regions identified
                      by activation likelihood estimation (ALE) meta‐analysis on
                      existing WM functional studies (ALE‐based intrinsic
                      functional networks) and intrinsic functional networks
                      generated based on the whole brain (whole‐brain intrinsic
                      functional networks). We employed the CPM on these networks
                      to predict WM in each age group. The CPM using the
                      ALE‐based and whole‐brain intrinsic functional networks
                      predicted WM of individual adults, while the prediction
                      power of the ALE‐based intrinsic functional networks was
                      superior to that of the whole‐brain intrinsic functional
                      networks. Nevertheless, the CPM using the whole‐brain but
                      not the ALE‐based intrinsic functional networks predicted
                      WM in adolescents. And, the CPM using neither the
                      ALE‐based nor whole‐brain networks predicted WM in any
                      of the children groups. Our findings showed the trend of the
                      prediction power of the intrinsic functional networks to
                      cognition in individuals from early childhood to adulthood.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {574 - Theory, modelling and simulation (POF3-574)},
      pid          = {G:(DE-HGF)POF3-574},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000553581400001},
      doi          = {10.1002/hbm.25143},
      url          = {https://juser.fz-juelich.de/record/884812},
}