Neurons and astrocytes interaction in neuronal network: A game-theoretic approach

被引:1
作者
Zareh, Masoumeh [1 ]
Manshaei, Mohammad Hossein [1 ]
Adibi, Mehdi [2 ]
Montazeri, Mohammad Ali [1 ]
机构
[1] Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran
[2] Univ New South Wales, Sch Psychol, Sydney, NSW, Australia
基金
英国医学研究理事会;
关键词
Neuron; Astrocyte; Morris-Lecar model; Dynamic game; Bayesian game; Chemical synapse; Neural network; SYNCHRONIZATION; OSCILLATIONS;
D O I
10.1016/j.jtbi.2019.02.024
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A neuron is the fundamental unit of the nervous system and the brain, crucial for transducing information in form of trains of electrical pulses known as action potentials. The connection between neurons is through synapses, enabling communication between neurons. This communication link is one of the key elements in processing of information from a neuron to another neuron. The strength of the synapses may vary over time, a phenomenon known as synaptic plasticity. This is the process by which it is believed memory and learning is governed. Recent studies revealed environmental factors affect the strength of synapses, and the way neurons communicate to each other. This poses the question as to what extent the pre- and post- synaptic neurons sense the environmental changes, and in turn adjust their synaptic link. Here, we model the behavior of an interconnected neuronal network in various environmental conditions as a multi-agent system in a game theoretic framework. We focus on a CA1 lattice subfield as an example plastic neuronal network. Our analysis revealed the neuronal network converges to different equilibria depending on the environmental changes. The model well-predicts the behavior of the network compared to a well-known theoretical model of individual neurons. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:76 / 89
页数:14
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