Restricted Gauss-Markov processes are used to construct inhomogeneous leaky integrate-and-fire stochastic models for single neuron’s activity in the presence of a lower reflecting boundary and periodic input signals. The first-passage time problem through a time-dependent threshold is explicitly developed; numerical, simulation and asymptotic results for firing densities are provided
Restricted Ornstein-Uhlenbeck process and applications in neuronal models with periodic input signals / Buonocore, Aniello; Caputo, Luigia; Nobile, A. G.; Pirozzi, Enrica. - In: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS. - ISSN 0377-0427. - 285:(2015), pp. 59-71. [doi:10.1016/j.cam.2015.01.042]
Restricted Ornstein-Uhlenbeck process and applications in neuronal models with periodic input signals
BUONOCORE, ANIELLO;CAPUTO, LUIGIA;PIROZZI, ENRICA
2015
Abstract
Restricted Gauss-Markov processes are used to construct inhomogeneous leaky integrate-and-fire stochastic models for single neuron’s activity in the presence of a lower reflecting boundary and periodic input signals. The first-passage time problem through a time-dependent threshold is explicitly developed; numerical, simulation and asymptotic results for firing densities are providedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.