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肠神经系统网络的数学建模。5. 平面神经网络中的兴奋传播。

Mathematic modelling of the enteric nervous network. 5. Excitation propagation in a planar neural network.

作者信息

Miftakhov R N, Wingate D L

机构信息

Gastrointestinal Science Research Unit, Royal London Hospital Medical College, University of London, UK.

出版信息

Med Eng Phys. 1995 Jan;17(1):11-9. doi: 10.1016/1350-4533(95)90372-i.

DOI:10.1016/1350-4533(95)90372-i
PMID:7704338
Abstract

A mathematical model of the enteric nervous system (Auerbach's plexus) as a planar neural network has been developed, based on the actual morphological data of its organization. The network is composed of excitatory (cholinergic) and inhibitory (adrenergic) neurones interconnected by polysynaptic channels, formed of the geometrically non-uniform unmyelinated nerve axons. The synaptic zones are modelled as a three-compartment open pharmacokinetics system, i.e., presynaptic terminal, synaptic cleft and postsynaptic membrane where the pharmacokinetic mechanisms of electrochemical coupling are considered. All the chemical reactions of transformation of acetylcholine and adrenaline within them are described by first order Michaelis-Menten kinetics. The propagation of the electrical impulse along the pathways and in the vicinity of the nerve terminal is described by the modified Hodgkin-Huxley equations. The results of numerical simulation of the propagation of excitation within the neuronal chain, inhibitory feedback circuit, and a planar neuronal network under normal physiological conditions and after treatment with cholinergic/adrenergic agonists and antagonists are presented. The model predicts the dose-dependent influence of pharmacological agents on the neural network function.

摘要

基于肠神经系统(奥尔巴赫神经丛)的实际形态学数据,开发了一种将其作为平面神经网络的数学模型。该网络由通过多突触通道相互连接的兴奋性(胆碱能)神经元和抑制性(肾上腺素能)神经元组成,这些通道由几何形状不均匀的无髓神经轴突形成。突触区被建模为一个三室开放药代动力学系统,即突触前终末、突触间隙和突触后膜,其中考虑了电化学耦合的药代动力学机制。其中乙酰胆碱和肾上腺素转化的所有化学反应均用一级米氏动力学描述。电冲动沿神经通路和神经终末附近的传播用修正的霍奇金-赫胥黎方程描述。给出了在正常生理条件下以及用胆碱能/肾上腺素能激动剂和拮抗剂处理后,神经元链、抑制性反馈回路和平面神经元网络内兴奋传播的数值模拟结果。该模型预测了药物对神经网络功能的剂量依赖性影响。

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