Restricted Ornstein–Uhlenbeck process and applications in neuronal models with periodic input signals

A. Buonocore ^[1] ; L. Caputo ^[1] ; A.G. Nobile ^[2] ; E. Pirozzi ^[1]
1. [1] Università di Napoli Federico II, Italy
2. [2] Università di Salerno, Italy
Localización: Journal of computational and applied mathematics, ISSN 0377-0427, Vol. 285, Nº 1 (September 2015), 2015, págs. 59-71
Idioma: inglés
DOI: 10.1016/j.cam.2015.01.042
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Resumen
- Restricted Gauss–Markov processes are used to construct inhomogeneous leaky integrate-and-fire stochastic models for single neurons 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.