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@INPROCEEDINGS{Diaz:825604,
      author       = {Diaz, Sandra and Nowke, Christian and Peyser, Alexander and
                      Hentschel, Bernd and Weyers, Benjamin and Morrison, Abigail
                      and Kuhlen, Torsten},
      title        = {{M}ultiscale approach to explore the relationships between
                      connectivity and function in whole brain simulations},
      reportid     = {FZJ-2016-08049},
      year         = {2016},
      abstract     = {In order to better understand the relationship of
                      connectivity and function in the brain at different scales,
                      in this work we show the results of using point neuron
                      network simulations to complement connectivity information
                      of whole brain simulations based on a dynamic neuron mass
                      model. In our multiscale approach, we simulate a whole brain
                      parcellated into 68 regions using a similar setup as
                      described in Deco et al. 2014. Each region is modeled as a
                      dynamic neuron mass and, in parallel, we also model each
                      region as small point neuron populations in NEST. Structural
                      plasticity in NEST is then used to calculate inner
                      inhibitory connectivity required to match experimentally
                      observed firing rate behavior. An interactive tool was
                      developed in order to steer the structural plasticity
                      algorithm and take all the regions, which are also highly
                      interconnected, to their ideal firing activity. An inner
                      inhibition fitting was first proposed in the work by Deco
                      2014, using an iterative tunning method. In our work, we
                      allow the point neuron network to self generate the
                      connectivity using simple homeostatic rules and then we feed
                      this information to the dynamic mass model simulation. With
                      the resulting connectivity data from the NEST simulations
                      and experimentally obtained DTI inter region connectivity,
                      simulations of the whole brain producing results comparable
                      to experimental fMRI data are possible. Using this approach,
                      the fitting and parameter space exploration times are
                      reduced and a new way to explore the impact of connectivity
                      in function at different scales is presented.},
      month         = {Sep},
      date          = {2016-09-21},
      organization  = {Bernstein Conference 2016, Berlin
                       (Germany), 21 Sep 2016 - 21 Sep 2016},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 574 - Theory, modelling and simulation
                      (POF3-574) / SMHB - Supercomputing and Modelling for the
                      Human Brain (HGF-SMHB-2013-2017) / W2Morrison - W2/W3
                      Professorinnen Programm der Helmholtzgemeinschaft
                      (B1175.01.12) / Virtual Connectomics - Deutschland - USA
                      Zusammenarbeit in Computational Science: Mechanistische
                      Zusammenhänge zwischen Struktur und funktioneller Dynamik
                      im menschlichen Gehirn (BMBF-01GQ1504B) / SLNS - SimLab
                      Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-574 /
                      G:(DE-Juel1)HGF-SMHB-2013-2017 / G:(DE-HGF)B1175.01.12 /
                      G:(DE-Juel1)BMBF-01GQ1504B / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/825604},
}