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

Karine Guimarães () and Aline Duarte
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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

Mathematics, 2023, vol. 11, issue 17, 1-11

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.

Keywords: stochastic model; computational model; GABAergic neurons; substantia nigra pars reticulata (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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