Towards Modeling Cholinergic Modulation for Neuromorphic Computing

DOI Open Access
  • Takano Naruaki
    Department of Information Science and Technology, The University of Tokyo
  • Kohno Takashi
    Institute of Industrial Science, The University of Tokyo

Description

Digital Spiking Silicon Neuron (DSSN) model is a qualitative neuron model specifically designed for digital circuit implementation which exhibits high biological plausibility. In this study we analyzed the behavior of an all-to-all network composed of 3-variable DSSN model which has a slow negative feedback variable corresponding to a slow calcium-dependent potassium current. We observed the network dynamics by altering the magnitude of the slow negative feedback current which is known to be controlled by cholinergic modulation, and the strength of neuronal interaction. By altering these parameters, we obtained various pattern retrieval dynamics, such as chaotic transitions within stored patterns or stable and high retrieval performance. We will briefly discuss potential applications of these results for neuromorphic computing.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390283659853337984
  • DOI
    10.5954/icarob.2020.os6-3
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
    • OpenAIRE
  • Abstract License Flag
    Disallowed

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