title: On some computational results for single neurons' activity modeling.
abstract: 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 neuron's 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.
authors.affiliation: Dipartimento de Matematica, Università della Basilicata, Potenza, Italy.
authors.forename: A
authors.initials: A
authors.lastname: Di Crescenzo
authors.forename: E
authors.initials: E
authors.lastname: Di Nardo
authors.forename: A G
authors.initials: AG
authors.lastname: Nobile
authors.forename: E
authors.initials: E
authors.lastname: Pirozzi
authors.forename: L M
authors.initials: LM
authors.lastname: Ricciardi
mesh_terms: D019295:Computational Biology; D008390:Markov Chains; D008564:Membrane Potentials; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*