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毛细胞纤毛束模型中噪声诱导兴奋性的随机敏感性分析。

Stochastic sensitivity analysis of the noise-induced excitability in a model of a hair bundle.

作者信息

Bashkirtseva Irina, Neiman Alexander B, Ryashko Lev

机构信息

Department of Mathematics, Ural Federal University, Pr. Lenina 51, Ekaterinburg, Russia.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2013 May;87(5):052711. doi: 10.1103/PhysRevE.87.052711. Epub 2013 May 17.

DOI:10.1103/PhysRevE.87.052711
PMID:23767570
Abstract

We study effect of weak noise on the dynamics of a hair bundle model near the excitability threshold and near a subcritical Hopf bifurcation. We analyze numerically noise-induced structural changes in the probability density and the power spectral density of the model. In particular, we show that weak noise can induce oscillations with two distinct frequencies in both excitable and limit-cycle regimes. We then applied a recently developed technique of stochastic sensitivity functions which allows us to estimate threshold values of noise intensity corresponding to these transitions.

摘要

我们研究了弱噪声对接近兴奋性阈值和亚临界霍普夫分岔的毛细胞束模型动力学的影响。我们对模型概率密度和功率谱密度中噪声诱导的结构变化进行了数值分析。特别地,我们表明在可兴奋和极限环状态下,弱噪声都能诱导出具有两个不同频率的振荡。然后,我们应用了一种最近开发的随机灵敏度函数技术,该技术使我们能够估计与这些转变相对应的噪声强度阈值。

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