Mechanisms of spikes generation in piecewise Rulkov model

In this paper a piecewise discontinuous Rulkov neuron model is considered. It is shown that even in the case of a one-dimensional map, the presence of a random perturbation leads to the spiking. Two mechanisms of spike generation caused by the random behavior of one of the parameters are investigated. We show that the coexistence of two attractors is not the only prerequisite for the occurrence of spiking. The confidence domain method based on stochastic sensitivity function is successfully applied to predict the level of the noise intensity necessary to the spike generation. The main statistical characteristics of interspike intervals depending on the noise intensity are demonstrated.In this paper a piecewise discontinuous Rulkov neuron model is considered. It is shown that even in the case of a one-dimensional map, the presence of a random perturbation leads to the spiking. Two mechanisms of spike generation caused by the random behavior of one of the parameters are investigated. We show that the coexistence of two attractors is not the only prerequisite for the occurrence of spiking. The confidence domain method based on stochastic sensitivity function is successfully applied to predict the level of the noise intensity necessary to the spike generation. The main statistical characteristics of interspike intervals depending on the noise intensity are demonstrated.