高斯白噪声对神经元映射模型动力学的影响*

研究了噪声引发的神经元相干共振现象。基于神经元二维映射模型，用高斯白噪声模拟生物神经系统中的环境噪声，通过数字仿真研究了噪声对神经元动力学特性的影响。研究发现，噪声可以提高静态神经元的可兴奋性，诱导其产生动作电位，当噪声达到某一适中强度时，动作电位的有序性可以达到最佳，产生相干共振现象。研究了系统参数的选取对神经元共振特性的影响，发现控制参数越接近分岔点，相干共振性越好。结果表明合适强度的噪声可以促进神经元的信息传递。

Impact of Gaussian white noise on dynamics of map-based neural model

This paper studied the phenomenon of coherence resonance on neurons induced by noise. Based on the two-dimensional map-based neural model, studied the effect of Gaussian white noise on the dynamics of neurons by numerical simulation, where Gaussian white noise was used to imitate the noisy environments of biological neural systems. It was found that adding the noise led to an enhancement of excitability of silent neurons, even induced spikes. When the noise intensity took an appropriate value, the regularity of spike series achieves best and coherence resonance occured. Moreover, also investigated the influence of system parameters on the resonance dynamics of the neuron. It was found that the resonance characteristic of the system was more obvious when the parameter value was more close to the bifurcation point. The results show an appropriate intensity of noise can enhance the information transmission of neurons.