The paper studies the phase coding in the neural networks composed of neural oscillator populations through the theory of the stochastic phase dynamics under the presence of inhibitory neurons, builds a stochastic nonlinear phase dynamic model subject to coupling action of inhibitory neurons, and numerically analyses the process of dynamic evolution and spontaneous behavior under the condition of simulation according to the model. The results prove that inhibitory neurons can reduce the amplitude of the average number density in excitatory neural oscillator population, and trend of the synchronization motion of excitatory neural oscillator population can be controlled through increasing coupling coefficient of inhibitory neurons. Firing density of population of neural oscillator and evolution of average number density is studied through variety of the stimulation intensity.
['Yan Liu', 'Rubin Wang', 'Zhikang Zhang', 'Xianfa Jiao']
Analysis of Neurodynamics on Phase Neural Coding in the Presence of Inhibitory Neurons