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Control of Hopf Bifurcation Type of a Neuron Model Using Washout Filter

机译:使用冲洗过滤器控制神经元模型的Hopf分岔类型

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A quantitative mathematical model of neurons should not only include enough details to consider the dynamics of single neurons but also minimize the complexity of the model so that the model calculation is convenient. The two-dimensional Prescott model provides a good compromise between the authenticity and computational efficiency of a neuron. The dynamic characteristics of the Prescott model under external electrical stimulation are studied by combining analytical and numerical methods in this paper. Through the analysis of the equilibrium point distribution, the influence of model parameters and external stimulus on the dynamic characteristics is described. The occurrence conditions and the type of Hopf bifurcation in the Prescott model are analyzed, and the analytical determination formula of the Hopf bifurcation type in the neuron model is obtained. Washout filter control is used to change the Hopf bifurcation type, so that the subcritical Hopf bifurcation transforms to supercritical Hopf bifurcation, so as to realize the change of the dynamic characteristics of the model.
机译:神经元的定量数学模型不仅包括足够的细节来考虑单个神经元的动态,而且还可以最小化模型的复杂性,以便模型计算方便。二维普雷斯特模型在神经元的真实性和计算效率之间提供了良好的折衷。通过在本文中结合分析和数值方法,研究了外部电刺激下的普雷斯特模型的动态特性。通过分析平衡点分布,描述了模型参数和外部刺激对动态特性的影响。分析了预剖模型中的跳跃分叉的发生条件和跳蚤分叉的类型,并且获得了神经元模型中HOPF分岔型的分析法测定公式。冲洗过滤器控制用于改变Hopf分岔型,使得子临界Hopf分叉转换为超临界Hopf分岔,以实现模型的动态特性的变化。

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