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A Network-Level Stochastic Model for Pacemaker GABAergic Neurons in Substantia Nigra Pars Reticulata

Author

Listed:
  • Karine Guimarães

    (Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo 05508-220, Brazil)

  • Aline Duarte

    (Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo 05508-220, Brazil)

Abstract

In this paper we present computational simulations of a mathematical model describing the time evolution of membrane potentials in a GABAergic neural network. This model, with stochastic and evolutionary characteristics, is an application of the version introduced previously where the authors present the continuous time version of a new class of stochastic models for biological neural networks. The goal is to computationally simulate the model (with the interaction conditions of a GABAergic network) and make biological inferences. More specifically, the computational simulations of the model that describe spiking neurons with electrophysiological characteristics of a brain region called substantia nigra pars reticulata, emphasize changes in desynchronized firing activity and how changes in individual activity propagate through the network.

Suggested Citation

  • Karine Guimarães & Aline Duarte, 2023. "A Network-Level Stochastic Model for Pacemaker GABAergic Neurons in Substantia Nigra Pars Reticulata," Mathematics, MDPI, vol. 11(17), pages 1-11, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3778-:d:1231885
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