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从一个神经元模型出发，研究了由１０００个神经元组成的网络中神经元动作电位发放的动力学特性。由神经元动作电位发放的动态时间—空间图形和时间间隔序列，我们发现在周期性外刺激下网络动力学行为表现出复杂的时空结构。通过调节参数Ｔ１，Ｔ２和Ｊ，我们讨论了网络的不同激发模式和网络中信息传递特性，发现周期性外刺激明显地对神经网络的状态具有调制作用，网络的同步激发模式对应于较简单的时空图形，是一类较为简单的信息处理过程。
Starting from a neuron model, we studied the kinetic properties of neuron action potential distribution in a network of 1000 neurons. The dynamic time-space patterns and time interval sequences released by neuronal action potentials show that the network dynamics behave in a complex space-time structure under periodic external stimuli. By adjusting the parameters T1, T2 and J, we discuss the different excitation modes and the information transmission characteristics in the network. We find that the periodic external stimulation obviously modulates the state of the neural network, and the synchronous excitation mode of the network corresponds to the simpler Spatio-temporal graphics, is a relatively simple type of information processing.