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@ARTICLE{Plschke:837640,
      author       = {Pläschke, Rachel N. and Cieslik, Edna and Müller,
                      Veronika and Hoffstaedter, Felix and Plachti, Anna and
                      Varikuti, Deepthi and Goosses, Mareike and Latz, Anne and
                      Caspers, Svenja and Jockwitz, Christiane and Moebus, Susanne
                      and Gruber, Oliver and Eickhoff, Claudia R. and Reetz,
                      Kathrin and Heller, Julia and Südmeyer, Martin and Mathys,
                      Christian and Caspers, Julian and Grefkes, Christian and
                      Kalenscher, Tobias and Langner, Robert and Eickhoff, Simon},
      title        = {{O}n the integrity of functional brain networks in
                      schizophrenia, {P}arkinson's disease, and advanced age:
                      {E}vidence from connectivity-based single-subject
                      classification},
      journal      = {Human brain mapping},
      volume       = {38},
      number       = {12},
      issn         = {1065-9471},
      address      = {New York, NY},
      publisher    = {Wiley-Liss},
      reportid     = {FZJ-2017-06518},
      pages        = {5845–5858},
      year         = {2017},
      abstract     = {Previous whole-brain functional connectivity studies
                      achieved successful classifications of patients and healthy
                      controls but only offered limited specificity as to affected
                      brain systems. Here, we examined whether the connectivity
                      patterns of functional systems affected in schizophrenia
                      (SCZ), Parkinson's disease (PD), or normal aging equally
                      translate into high classification accuracies for these
                      conditions. We compared classification performance between
                      pre-defined networks for each group and, for any given
                      network, between groups. Separate support vector machine
                      classifications of 86 SCZ patients, 80 PD patients, and 95
                      older adults relative to their matched healthy/young
                      controls, respectively, were performed on functional
                      connectivity in 12 task-based, meta-analytically defined
                      networks using 25 replications of a nested 10-fold
                      cross-validation scheme. Classification performance of the
                      various networks clearly differed between conditions, as
                      those networks that best classified one disease were usually
                      non-informative for the other. For SCZ, but not PD,
                      emotion-processing, empathy, and cognitive action control
                      networks distinguished patients most accurately from
                      controls. For PD, but not SCZ, networks subserving
                      autobiographical or semantic memory, motor execution, and
                      theory-of-mind cognition yielded the best classifications.
                      In contrast, young–old classification was excellent based
                      on all networks and outperformed both clinical
                      classifications. Our pattern-classification approach
                      captured associations between clinical and developmental
                      conditions and functional network integrity with a higher
                      level of specificity than did previous whole-brain analyses.
                      Taken together, our results support resting-state
                      connectivity as a marker of functional dysregulation in
                      specific networks known to be affected by SCZ and PD, while
                      suggesting that aging affects network integrity in a more
                      global way.},
      cin          = {INM-7 / INM-11 / INM-1 / INM-3},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-11-20170113 /
                      I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)INM-3-20090406},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572)},
      pid          = {G:(DE-HGF)POF3-572},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:28876500},
      UT           = {WOS:000414683400002},
      doi          = {10.1002/hbm.23763},
      url          = {https://juser.fz-juelich.de/record/837640},
}