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Stochastic modeling of the firing activity of coupled neurons periodically driven

Chapter
Publication Date:
2015
abstract:
A stochastic model for describing the firing activity of a couple of interacting neurons subject to time-dependent stimuli is proposed. Two stochastic differential equations suitably coupled and including periodic terms to represent stimuli imposed to one or both neurons are considered to describe the problem. We investigate the first passage time densities through specified firing thresholds for the involved time non-homogeneous Gauss-Markov processes. We provide simulation results and numerical approximations of the firing densities. Asymptotic behaviors of the first passage times are also given.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
LIF neuronal model; first passage time; Gauss-Markov processes; periodic stimulus; asymptotic regime.
List of contributors:
Carfora, MARIA FRANCESCA
Authors of the University:
CARFORA MARIA FRANCESCA
Handle:
https://iris.cnr.it/handle/20.500.14243/304017
Book title:
Dynamical Systems, Differential Equations and Applications - AIMS Proceedings, 2015
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http://www.aimsciences.org/journals/contentsListPro.jsp?pubID=818
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