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.
On some computational results for single neurons' activity modeling / A., DI CRESCENZO; E., DI NARDO; A. G., Nobile; Pirozzi, Enrica; Ricciardi, LUIGI MARIA. - In: BIOSYSTEMS. - ISSN 0303-2647. - STAMPA. - 58:1-3(2000), pp. 19-26. [10.1016/S0303-2647(00)00102-7]
On some computational results for single neurons' activity modeling
PIROZZI, ENRICA;RICCIARDI, LUIGI MARIA
2000
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
