信号噪声下整合发放神经元模型的随机共振

Stochastic resonance in integrate-and-fire neuron model by signal noise

文章基于整合发放神经元模型,研究了信号噪声与背景噪声共同作用下神经元系统的随机共振现象。利用随机平均法推导出了神经元系统的输出幅值增益精确表达式,并考察了背景噪声、信号噪声相关时间和信号噪声与背景噪声两噪声的关联强度对神经元系统输出幅值增益的影响。通过数值模拟发现,当背景噪声较弱时,神经元系统有明显的随机共振现象;当信号噪声自相关时间较短及背景噪声与信号噪声间两噪声间关联强度较小时,神经元系统也会出现随机共振现象。

In this paper, stochastic resonance（SR） of an integrate-and-fire neuron model subjected tosignal noise and background noise is investigated. The amplitude gain of the output signal is obtainedby the method of stochastic averaging, and the influence of background noise, noise correlation timeand correlation intensity between background noise and signal noise on the output amplitude gain isstudied. The results of numerical simulation show that when the background noise is weak, or thenoise correlation time is relatively short, or the correlation intensity between background noise andsignal noise is small, the SR occurs in neuronal systems.