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@INPROCEEDINGS{Domhof:943298,
      author       = {Domhof, Justin and Eickhoff, Simon and Popovych, Oleksandr},
      title        = {{R}eliability and subject specificity of personalized
                      dynamical whole-brain models},
      reportid     = {FZJ-2023-00905},
      year         = {2022},
      abstract     = {Dynamical whole-brain models originally provided a
                      biophysically-inspiredapproach to investigate the
                      relationship between the structural (SC) andfunctional (FC)
                      brain connectivity and are also used nowadays to studythe
                      dynamical regimes of the brain and how these relate to
                      various subjecttraits. Nevertheless, it is unclear how the
                      modeling results perform in termsof test-retest reliability
                      and subject specificity. We systematically assessthese
                      aspects of the modeling results and examine how they relate
                      tothe reliability and subject specificity of empirical
                      data.We used the empirical SC and FC matrices of 200 healthy
                      unrelated subjectsfrom the Human Connectome Project to build
                      individual models based on networksof neural mass models and
                      systems of coupled phase oscillators. The lattermodel used
                      region-specific natural frequencies extracted from empirical
                      datathat were either subject specific or the same for all
                      subjects to varythe extent of model personalization. The
                      models were simulated for a broadrange of parameter settings
                      to yield the simulated FC matrices exhibitingthe highest
                      correlation with the empirical FCs.We show that the
                      reliability of the simulated FC can exceed that of
                      theempirical one, especially, for the structural atlases and
                      for thepersonalized models. Also, the subject specificity of
                      the simulated FC mayoutperform that of the empirical one,
                      where the personalized phase oscillator modelwith
                      subject-specific frequencies generated FCs with a much
                      higher subject specificitythan the other, less personalized
                      modeling paradigms. In addition, the atlashas a larger
                      influence on the reliability and specificity of the
                      simulated FCthan on that of the empirical FC, where a
                      distinction between structurally- andfunctionally-derived
                      atlases can be made.Taken together, our results indicate
                      that whole-brain dynamical modelscan generate simulated
                      connectomes with high reliability and (subject)specificity
                      and may outperform the empirical data in this respect.In
                      turn, this suggests that these models potentially reduce the
                      variance inthe empirical FC across different realizations
                      for a single subject by providinga reliable model fit for
                      further analyses. We underline the critical roles thatthe
                      parcellation and model implementation have on the modeling
                      results. Ourfindings also suggest that the application of
                      the dynamical whole-brain modelingshould be tightly
                      connected with an estimate of the reliability of the
                      results.},
      month         = {Sep},
      date          = {2022-09-29},
      organization  = {NIC Symposium 2022, Jülich (Germany),
                       29 Sep 2022 - 30 Sep 2022},
      subtyp        = {After Call},
      cin          = {INM-7},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5232 - Computational Principles (POF4-523) / 5231 -
                      Neuroscientific Foundations (POF4-523) / HBP SGA3 - Human
                      Brain Project Specific Grant Agreement 3 (945539) /
                      VirtualBrainCloud - Personalized Recommendations for
                      Neurodegenerative Disease (826421)},
      pid          = {G:(DE-HGF)POF4-5232 / G:(DE-HGF)POF4-5231 /
                      G:(EU-Grant)945539 / G:(EU-Grant)826421},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/943298},
}