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Dynamic Image Representation in a Spiking Neural Network Supplied by Astrocytes

Author

Listed:
  • Sergey V. Stasenko

    (Moscow Institute of Physics and Technology, 117303 Moscow, Russia)

  • Victor B. Kazantsev

    (Moscow Institute of Physics and Technology, 117303 Moscow, Russia)

Abstract

The mathematical model of the spiking neural network (SNN) supplied by astrocytes is investigated. The astrocytes are a specific type of brain cells which are not electrically excitable but induce chemical modulations of neuronal firing. We analyze how the astrocytes influence images encoded in the form of the dynamic spiking pattern of the SNN. Serving at a much slower time scale, the astrocytic network interacting with the spiking neurons can remarkably enhance the image representation quality. The spiking dynamics are affected by noise distorting the information image. We demonstrate that the activation of astrocytes can significantly suppress noise influence, improving the dynamic image representation by the SNN.

Suggested Citation

  • Sergey V. Stasenko & Victor B. Kazantsev, 2023. "Dynamic Image Representation in a Spiking Neural Network Supplied by Astrocytes," Mathematics, MDPI, vol. 11(3), pages 1-17, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:561-:d:1042853
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    Cited by:

    1. Sergey V. Stasenko & Victor B. Kazantsev, 2023. "Bursting Dynamics of Spiking Neural Network Induced by Active Extracellular Medium," Mathematics, MDPI, vol. 11(9), pages 1-17, April.
    2. Sergey M. Olenin & Tatiana A. Levanova & Sergey V. Stasenko, 2023. "Dynamics in the Reduced Mean-Field Model of Neuron–Glial Interaction," Mathematics, MDPI, vol. 11(9), pages 1-11, May.

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