Restricted Ornstein–Uhlenbeck process and applications in neuronal models with periodic input signals
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摘要
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.
论文关键词：60G15,60J60,92C20,65C30,Gauss–Markov processes,Integrate-and-fire model,Firing densities,Volterra integral equations,Asymptotic behavior,Simulation
论文评审过程：Received 5 June 2014, Revised 30 January 2015, Available online 7 February 2015.
论文官网地址：https://doi.org/10.1016/j.cam.2015.01.042
