抑制性神经元作用下相位神经编码的神经动力学分析

Neurodynamics analysis on phase neural coding in the presence of inhibitory neurons

在考虑抑制性神经元作用的情况下,利用随机相变动力学理论对由神经振子群组成的神经网络进行相位编码的分析研究。建立一种抑制性神经元耦合作用下的随机非线性相变动力学模型,并依据所建立的模型对其自发活动以及在刺激作用下的动态演化过程进行数值分析。研究结果表明网络中抑制性神经元的存在能够降低兴奋性神经振子集群的数密度的幅值,并且抑制性神经元耦合系数的增大能够控制兴奋性神经振子集群的变化趋势。在刺激条件下,随着刺激强度的变化能够改变神经振子的发放频率。还考察了不同刺激情况下的相位编码的数密度演化。

The phase coding in the neural network composed of neural oscillator population was studied in accordance with the theory of stochastic phase dynamics in the presence of inhibitory neurons.A stochastic nonlinear phase dynamic model was presented under coupling action of inhibitory neurons,and the dynamic evolution process and spontaneous behavior were numerically analyzed by use of simulation according to the model.The results indicate that inhibitory neurons can reduce the amplitude of average number density in excitatory neural oscillator population,and the trend of synchronization motion of excitatory neural oscillator population can be controlled through increasing coupling coefficient of inhibitory neurons.The firing density of population of neural oscillator and the evolution of average number density were investigated by varying the stimulation intensity.