随机共振是一种常见于非线性系统中的由适当的噪声引起的系统最优响应现象。神经系统含有噪声,相关生物实验和理论研究均证明噪声有助于神经信号的检测和处理,且当前对神经系统信息处理与存储机制的研究是一大热点。文章回顾了最近发表的关于随机共振的研究成果,从噪声、随机共振的引申概念和网络模型三个方面,总结了目前对神经模型中随机共振的研究进展,并简单讨论了这类研究的发展趋势。 Stochastic resonance is a system-best response phenomenon caused by proper noise, which is common in nonlinear systems. Nervous system contains noise, biological experiments and theoretical studies have proved that noise contributes to the detection and processing of neural signals, and the current research on neural information processing and storage mechanism is a hot topic. This paper reviews the recent research results on stochastic resonance and summarizes the current research progress on stochastic resonance in neural models from the concepts of noise, stochastic resonance extension and network model, and briefly discusses the development of such studies trend.