【作者】 焦贤发； 黄小娟； 王如彬； 张志康；

【Author】 Xianfa Jiao Xiaojuan Huang (Department of Mathematics, Hefei University of Technology, Hefei, 230009)

【机构】 合肥工业大学数学系； 上海市梅隆路130号华东理工大学信息科学与工程学院认知神经动力学研究所；

【摘要】 本文将非线性时滞随机动力系统对应的Fokker-Planck(简称为FPK)方程,应用到时滞耦合神经元集群的随机相变模型中,通过对模型的数值分析,在三维空间再现了用于描述神经元集群活动的数密度随时间的动态演化。数值分析的结果表明神经元之间的时滞相互作用可以增强神经元集群的相同步活动和改变神经元集群的放电模式。更多还原

【Abstract】 In this article, the Fokker-Planck equation of the nonlinear stochastic dynamical systems with time delay have been used to the stochastic phase model of neuronal population with delay coupling. Numerical simulation has shown that a number density, which is used to describe the activities of neuronal population, is dynamical evolution with time. Numerical simulation also has shown that the time-delay between neurons has enhanced the phase synchronization and changed the firing patterns of neuronal population.更多还原