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
NOBILE, Amelia Giuseppina;
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.File in questo prodotto:
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