
A simple algorithm to generate firing times for leaky integrate-and-fire neuronal model
Author(s) -
Aniello Buonocore,
Luigia Caputo,
Enrica Pirozzi,
Maria Francesca Carfora
Publication year - 2014
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2014.11.1
Subject(s) - simple (philosophy) , process (computing) , algorithm , computer science , hazard , probability density function , class (philosophy) , stochastic process , function (biology) , mathematics , mathematical optimization , statistical physics , artificial intelligence , statistics , physics , ecology , philosophy , epistemology , evolutionary biology , biology , operating system
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.