摘要
对一类动态饱和突触神经模型中信号传导性质进行了研究。模型的动态过程采用高阶Milstein随机微分方程解法进行求解,其信号输入输出特性用集平均互相关系数进行衡量。集平均互相关系数的数值分析结果表明,适宜的噪声能够增强信号传导,并且通过调节饱和势比值大小和突触神经群体数目,观测到噪声增强信号传导的非线性现象更加显著。
The synaptie signal transduction in a dynamical saturation neuron model is studied. At the pre-synaptic and post-synaptic stages, the evolution of neurotransmitter molecules in the syn- aptic cleft can be described by a dynamical saturation model. In the presence of noise, the signal transduction in this model is characterized by the ensemble-averaged correlation coefficient. The evolution of synaptic signal transmission is solved by the Milstein＇s high-order method of stochas- tic differential equation. The numerical result of the ensemble average correlation coefficient dem- onstrates the effect of noise-enhanced signal transduction in a single neuron model and an ensem- ble population of synaptic saturation neurons. Moreover, the noise-enhanced signal transduction effect is more visible by tuning the ratio of saturating current and the population of neurons.
出处
《复杂系统与复杂性科学》
EI
CSCD
北大核心
2013年第2期59-62,共4页
Complex Systems and Complexity Science
基金
山东省自然科学基金(ZR2010FM006)
关键词
突触神经模型
互相关系数
信号传导
噪声增强
neural synaptic model
correlation coefficient
signal transduction
noise enhancement
