A method to generate first passage times for a class of stochastic processes is proposed. It does not require construction of the trajectories as usually needed in simulation studies, but is based on an integral equation whose unknown quantity is the probability density function of the studied first passage times and on the application of the hazard rate method. The proposed procedure is particularly efficient in the case of the Ornstein-Uhlenbeck process, which is important for modeling spiking neuronal activity.

A Simple Algorithm to Generate Firing Times for Leaky Integrate-and-Fire Neuronal Model / Buonocore, Aniello; Caputo, Luigia; M. F., Carfora; Pirozzi, Enrica. - In: MATHEMATICAL BIOSCIENCES AND ENGINEERING. - ISSN 1547-1063. - 11:1(2014), pp. 1-10. [10.3934/mbe.2014.11.1]

A Simple Algorithm to Generate Firing Times for Leaky Integrate-and-Fire Neuronal Model

BUONOCORE, ANIELLO;CAPUTO, LUIGIA;PIROZZI, ENRICA
2014

Abstract

A method to generate first passage times for a class of stochastic processes is proposed. It does not require construction of the trajectories as usually needed in simulation studies, but is based on an integral equation whose unknown quantity is the probability density function of the studied first passage times and on the application of the hazard rate method. The proposed procedure is particularly efficient in the case of the Ornstein-Uhlenbeck process, which is important for modeling spiking neuronal activity.
2014
A Simple Algorithm to Generate Firing Times for Leaky Integrate-and-Fire Neuronal Model / Buonocore, Aniello; Caputo, Luigia; M. F., Carfora; Pirozzi, Enrica. - In: MATHEMATICAL BIOSCIENCES AND ENGINEERING. - ISSN 1547-1063. - 11:1(2014), pp. 1-10. [10.3934/mbe.2014.11.1]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/555913
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