Statistics of a leaky integrate-and-fire model of neurons driven by dichotomous noise.
The behavior of a stochastic leaky integrate-and-fire model of neurons is considered. The effect of temporally correlated random neuronal input is modeled as a colored two-level (dichotomous) Markovian noise. Relying on the Riemann method, exact expressions for the output interspike interval density and for the serial correlation coefficient are derived, and their dependence on noise parameters (such as correlation time and amplitude) is analyzed. Particularly, noise-induced sign reversal and a resonancelike amplification of the kurtosis of the interspike interval distribution are established. The features of spike statistics, analytically revealed in our study, are compared with recently obtained results for a perfect integrate-and-fire neuron model.
School of Natural Sciences and Health, Tallinn University, 29 Narva Road, 10120 Tallinn, Estonia.
Romi
R
Mankin
School of Natural Sciences and Health, Tallinn University, 29 Narva Road, 10120 Tallinn, Estonia.
Neeme
N
Lumi
D000200:Action Potentials; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes