On some computational results for single neurons’ activity modeling

The classical Ornstein–Uhlenbeck diffusion neuronal model is generalized by inclusion of a time-dependent input whose strength exponentially decreases in time. The behavior of the membrane potential is consequently seen to be modeled by a process whose mean and covariance classify it as Gaussian–Markov. The effect of the input on the neuronʹs firing characteristics is investigated by comparing the firing probability densities and distributions for such a process with the corresponding ones of the Ornstein–Uhlenbeck model. All numerical results are obtained by implementation of a recently developed computational method.