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@ARTICLE{Jung:1028958,
      author       = {Jung, Kyesam and Eickhoff, Simon and Caspers, Julian and
                      Popovych, Oleksandr},
      title        = {{S}imulated brain networks reflecting progression of
                      {P}arkinson's disease},
      journal      = {Network neuroscience},
      volume       = {8},
      number       = {4},
      issn         = {2472-1751},
      address      = {Cambridge, MA},
      publisher    = {The MIT Press},
      reportid     = {FZJ-2024-04898},
      pages        = {1400–1420},
      year         = {2024},
      abstract     = {Neurodegenerative progression of Parkinson’s disease
                      affects brain structure and function and, concomitantly,
                      alters topological properties of brain networks. The network
                      alteration accompanied with motor impairment and duration of
                      the disease is not yet clearly demonstrated in the disease
                      progression. In this study, we aim at resolving this problem
                      with a modeling approach based on large-scale brain networks
                      from cross-sectional MRI data. Optimizing whole-brain
                      simulation models allows us to discover brain networks
                      showing unexplored relationships with clinical variables. We
                      observe that simulated brain networks exhibit significant
                      differences between healthy controls (n=51) and patients
                      with Parkinson’s disease (n=60) and strongly correlate
                      with disease severity and disease duration of the patients.
                      Moreover, the modeling results outperform the empirical
                      brain networks in these clinical measures. Consequently,
                      this study demonstrates that utilizing simulated brain
                      networks provides an enhanced view on network alterations in
                      the progression of motor impairment and potential biomarkers
                      for clinical indices.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5232 - Computational Principles (POF4-523) / 5231 -
                      Neuroscientific Foundations (POF4-523)},
      pid          = {G:(DE-HGF)POF4-5232 / G:(DE-HGF)POF4-5231},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {39735513},
      UT           = {WOS:001381061600015},
      doi          = {10.1162/netn_a_00406},
      url          = {https://juser.fz-juelich.de/record/1028958},
}