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@INPROCEEDINGS{Zeraati:873634,
      author       = {Zeraati, Roxana and Engel, Tatiana and Levina, Anna},
      title        = {{C}ritical avalanches in a spatially structured model of
                      cortical {O}n-{O}ff dynamics},
      reportid     = {FZJ-2020-00877},
      year         = {2019},
      note         = {Roxana Zeraati was employed at the FZJ through the project
                      SMARTSTART Computational Neuroscience, DB001423.},
      abstract     = {Spontaneous cortical activity unfolds across different
                      spatial scales. On a local scale of individual columns,
                      activity spontaneously transitions between episodes of
                      vigorous (On) and faint (Off) spiking, synchronously across
                      cortical layers. On a wider spatial scale of interacting
                      columns, activity propagates as neural avalanches, with
                      sizes distributed as an approximate power-law with
                      exponential cutoff, suggesting that brain operates close to
                      a critical point. We investigate how local On-Off dynamics
                      can coexist with critical avalanches. To this end, we
                      developed a branching network model capable of capturing
                      both of these dynamics. Each unit in the model represents a
                      cortical column, that spontaneously transitions between On
                      and Off episodes and has spatially structured connections to
                      other columns. We found that models with local connectivity
                      do not exhibit critical dynamics in the limit of a large
                      system size. While for a critical network, it is expected
                      that the cut-off of the avalanche-size distribution scales
                      with the system size, in models with nearest-neighbor
                      connectivity, it stays constant above a characteristic size.
                      We demonstrate that the scaling can be recovered by
                      increasing the radius of connections or by rewiring a small
                      fraction of local connections to long-range random
                      connections. Our results highlight the possible role of
                      long-range connections in defining the operating regime of
                      the brain dynamics.},
      month         = {Mar},
      date          = {2019-03-31},
      organization  = {Verhandlungen der Deutschen
                       Physikalischen Gesellschaft, Regensburg
                       (Germany), 31 Mar 2019 - 5 Apr 2019},
      subtyp        = {Other},
      cin          = {INM-6 / IAS-6 / INM-10},
      cid          = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
                      I:(DE-Juel1)INM-10-20170113},
      pnm          = {574 - Theory, modelling and simulation (POF3-574) /
                      Smartstart - SMARTSTART Training Program in Computational
                      Neuroscience (90251)},
      pid          = {G:(DE-HGF)POF3-574 / G:(EU-Grant)90251},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/873634},
}