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@INPROCEEDINGS{Ebrahimzadeh:1024013,
      author       = {Ebrahimzadeh, pezhman and Bouhadjar, Younes and Schiek,
                      Michael and Strachan, John P. and Neftci, Emre},
      title        = {{A}ttractor states in spiking neural networks},
      publisher    = {G-Node},
      reportid     = {FZJ-2024-01911},
      pages        = {1},
      year         = {2023},
      abstract     = {Considering the brain as a dynamical system allows for a
                      rigorous analysis of some aspects of brain dynamics
                      regarding the working memory and their relation to spike
                      patterns. The concept of attractor networks describes one of
                      the dynamical mechanisms in which the brain maintains
                      persistent activity via creating locally stable attractor
                      states. In this work, we analyze the interplay between the
                      $excitatory\inhibitory$ electrical and chemical synaptic
                      connections as means of creation [and annihilation]
                      mechanism of different dynamical regimes and their
                      respective attractor states considering a network of spiking
                      neurons. The exponentially-decaying external input is
                      introduced as means of a vector field driving the system
                      into a specific attractor. Based on the topological analysis
                      of the state space of the input-driven system, computational
                      capabilities of the attractor states and link to working
                      memory are discussed.},
      month         = {Sep},
      date          = {2023-09-26},
      organization  = {Berstein Conference 2023, Berlin
                       (Germany), 26 Sep 2023 - 29 Sep 2023},
      keywords     = {Computational Neuroscience (Other) / Networks and dynamical
                      systems (Other)},
      cin          = {PGI-14},
      cid          = {I:(DE-Juel1)PGI-14-20210412},
      pnm          = {5234 - Emerging NC Architectures (POF4-523)},
      pid          = {G:(DE-HGF)POF4-5234},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.12751/NNCN.BC2023.174},
      url          = {https://juser.fz-juelich.de/record/1024013},
}