Delay-enhanced stability and stochastic resonance in perception bistability under non-Gaussian noise

In this paper we investigate the effect of time delay in an attractor network model of perception bistability driven by non-Gaussian noise. Using delay Langevin and Fokker–Planck approaches, the theoretical analysis of the model is presented. It is found that the mean first-passage time (MFPT) as a function of the time delay exhibits a maximum, which is identified as the characteristic of the delay-enhanced stability of the system. This is different to the case of noise-enhanced stability. The non-Gaussian noise-enhanced stability of the system is also analyzed. The signal-to-noise ratio (SNR) as a function of the noise intensity exhibits a maximum. This maximum implies the identifying characteristic of stochastic resonance (SR), and the time delay and non-Gaussian noise can enhance the SR phenomenon.