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@ARTICLE{Kusch:1025738,
      author       = {Kusch, Lionel and Diaz, Sandra and Klijn, Wouter and
                      Sontheimer, Kim and Bernard, Christophe and Morrison,
                      Abigail and Jirsa, Viktor},
      title        = {{M}ultiscale co-simulation design pattern for neuroscience
                      applications},
      journal      = {Frontiers in neuroinformatics},
      volume       = {18},
      issn         = {1662-5196},
      address      = {Lausanne},
      publisher    = {Frontiers Research Foundation},
      reportid     = {FZJ-2024-03121},
      pages        = {1156683},
      year         = {2024},
      abstract     = {Integration of information across heterogeneous sources
                      creates added scientific value. Interoperability of data,
                      tools and models is, however, difficult to accomplish across
                      spatial and temporal scales. Here we introduce the toolbox
                      Parallel Co-Simulation, which enables the interoperation of
                      simulators operating at different scales. We provide a
                      software science co-design pattern and illustrate its
                      functioning along a neuroscience example, in which
                      individual regions of interest are simulated on the cellular
                      level allowing us to study detailed mechanisms, while the
                      remaining network is efficiently simulated on the population
                      level. A workflow is illustrated for the use case of The
                      Virtual Brain and NEST, in which the CA1 region of the
                      cellular-level hippocampus of the mouse is embedded into a
                      full brain network involving micro and macro electrode
                      recordings. This new tool allows integrating knowledge
                      across scales in the same simulation framework and
                      validating them against multiscale experiments, thereby
                      largely widening the explanatory power of computational
                      models.},
      cin          = {JSC / IAS-6 / INM-6},
      ddc          = {610},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-6-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / 5232 - Computational
                      Principles (POF4-523) / 5234 - Emerging NC Architectures
                      (POF4-523) / SLNS - SimLab Neuroscience (Helmholtz-SLNS) /
                      HBP SGA3 - Human Brain Project Specific Grant Agreement 3
                      (945539) / HBP SGA2 - Human Brain Project Specific Grant
                      Agreement 2 (785907) / ICEI - Interactive Computing
                      E-Infrastructure for the Human Brain Project (800858)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-5232 /
                      G:(DE-HGF)POF4-5234 / G:(DE-Juel1)Helmholtz-SLNS /
                      G:(EU-Grant)945539 / G:(EU-Grant)785907 /
                      G:(EU-Grant)800858},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38410682},
      UT           = {WOS:001174378600001},
      doi          = {10.3389/fninf.2024.1156683},
      url          = {https://juser.fz-juelich.de/record/1025738},
}