Bashkirtseva Irina, Ryashko Lev
Department of Mathematics, Ural State University, Ekaterinburg, Russia.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Jun;83(6 Pt 1):061109. doi: 10.1103/PhysRevE.83.061109. Epub 2011 Jun 10.
We study excitability phenomena for the stochastically forced FitzHugh-Nagumo system modeling a neural activity. Noise-induced changes in the dynamics of this model can be explained by the high stochastic sensitivity of its attractors. Computational methods based on the stochastic sensitivity functions technique are suggested for the analysis of these attractors. Our method allows us to construct confidence ellipses and estimate a threshold value of a noise intensity corresponding to the neuron excitement. On the basis of the proposed technique, a supersensitive limit cycle is found for the FitzHugh-Nagumo model.
我们研究了用于模拟神经活动的随机强迫FitzHugh-Nagumo系统的兴奋性现象。该模型动力学中由噪声引起的变化可以通过其吸引子的高随机敏感性来解释。我们提出了基于随机敏感性函数技术的计算方法来分析这些吸引子。我们的方法使我们能够构建置信椭圆，并估计与神经元兴奋相对应的噪声强度阈值。基于所提出的技术，我们为FitzHugh-Nagumo模型找到了一个超敏感极限环。
