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

Full text
Author(s):	Guimaraes, Karine ; Duarte, Aline Total Authors: 2
Document type:	Journal article
Source:	MATHEMATICS; v. 11, n. 17, p. 11-pg., 2023-09-01.
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. (AU)

FAPESP's process:	19/22219-0 - Representations of neuronal interaction statistics
Grantee:	Karine Damásio Guimarães
Support Opportunities:	Scholarships in Brazil - Post-Doctoral


FAPESP's process:	13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:	Oswaldo Baffa Filho
Support Opportunities:	Research Grants - Research, Innovation and Dissemination Centers - RIDC