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;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 provided
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/612041
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