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Stimulus Sensitivity of a Spiking Neural Network Model

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  • معلومة اضافية
    • Contributors:
      Statistique pour le Vivant et l’Homme (SVH); Laboratoire Jean Kuntzmann (LJK ); Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]); ANR-11-LABX-0023,MME-DII,Modèles Mathématiques et Economiques de la Dynamique, de l'Incertitude et des Interactions(2011)
    • بيانات النشر:
      Springer Science and Business Media LLC, 2018.
    • الموضوع:
      2018
    • نبذة مختصرة :
      International audience; Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.
    • ISSN:
      1572-9613
      0022-4715
    • Rights:
      OPEN
    • الرقم المعرف:
      edsair.doi.dedup.....eb18ce38215bb4128269830990f31f21