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具有记忆的下丘脑 - 垂体 - 肾上腺轴模型的稳定性和霍普夫分岔分析

Stability and Hopf bifurcation analysis for the hypothalamic-pituitary-adrenal axis model with memory.

作者信息

Kaslik Eva, Neamtu Mihaela

机构信息

Department of Mathematics and Computer Science, West University of Timişoara, Romania.

Institute e-Austria Timisoara, cam. 045B, Romania.

出版信息

Math Med Biol. 2018 Mar 14;35(1):49-78. doi: 10.1093/imammb/dqw020.

Abstract

This article generalizes the existing minimal model of the hypothalamic-pituitary-adrenal (HPA) axis in a realistic way, by including memory terms: distributed time delays, on one hand and fractional-order derivatives, on the other hand. The existence of a unique equilibrium point of the mathematical models is proved and a local stability analysis is undertaken for the system with general distributed delays. A thorough bifurcation analysis for the distributed delay model with several types of delay kernels is provided. Numerical simulations are carried out for the distributed delays models and for the fractional-order model with discrete delays, which substantiate the theoretical findings. It is shown that these models are able to capture the vital mechanisms of the HPA system.

摘要

本文通过纳入记忆项,以一种现实的方式推广了现有的下丘脑 - 垂体 - 肾上腺(HPA)轴最小模型:一方面是分布时滞,另一方面是分数阶导数。证明了数学模型唯一平衡点的存在性,并对具有一般分布时滞的系统进行了局部稳定性分析。针对具有几种时滞核的分布时滞模型进行了全面的分岔分析。对分布时滞模型和具有离散时滞的分数阶模型进行了数值模拟,证实了理论结果。结果表明,这些模型能够捕捉HPA系统的重要机制。

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