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@ARTICLE{Manos:1020019,
      author       = {Manos, Thanos and Diaz, Sandra and Fortel, Igor and
                      Driscoll, Ira and Zhan, Liang and Leow, Alex},
      title        = {{E}nhanced simulations of whole-brain dynamics using hybrid
                      resting-state structural connectomes},
      journal      = {Frontiers in computational neuroscience},
      volume       = {17},
      issn         = {1662-5188},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2023-05834},
      pages        = {1295395},
      year         = {2023},
      abstract     = {The human brain, composed of billions of neurons and
                      synaptic connections, is an intricate network coordinating a
                      sophisticated balance of excitatory and inhibitory
                      activities between brain regions. The dynamical balance
                      between excitation and inhibition is vital for adjusting
                      neural input/output relationships in cortical networks and
                      regulating the dynamic range of their responses to stimuli.
                      To infer this balance using connectomics, we recently
                      introduced a computational framework based on the Ising
                      model, which was first developed to explain phase
                      transitions in ferromagnets, and proposed a novel hybrid
                      resting-state structural connectome (rsSC). Here, we show
                      that a generative model based on the Kuramoto phase
                      oscillator can be used to simulate static and dynamic
                      functional connectomes (FC) with rsSC as the coupling weight
                      coefficients, such that the simulated FC aligns well with
                      the observed FC when compared with that simulated
                      traditional structural connectome.},
      cin          = {JSC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / HBP SGA3 - Human
                      Brain Project Specific Grant Agreement 3 (945539) / DFG
                      project 491111487 - Open-Access-Publikationskosten / 2022 -
                      2024 / Forschungszentrum Jülich (OAPKFZJ) (491111487) /
                      SLNS - SimLab Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(EU-Grant)945539 /
                      G:(GEPRIS)491111487 / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38188355},
      UT           = {WOS:001134314300001},
      doi          = {10.3389/fncom.2023.1295395},
      url          = {https://juser.fz-juelich.de/record/1020019},
}