Stochastic modeling of the firing activity of coupled neurons periodically driven

DOI10.3934/proc.2015.0195zbMath1335.60127OpenAlexW2324773609WikidataQ58160130 ScholiaQ58160130MaRDI QIDQ260747

Enrica Pirozzi, Maria Francesca Carfora

Publication date: 22 March 2016

Published in: Discrete and Continuous Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/proc.2015.0195

zbMATH Keywords

stochastic differential equationsfirst passage timeasymptotic regimeGauss-Markov processesLIF neuronal modelperiodic stimulus

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Neural biology (92C20) Applications of stochastic analysis (to PDEs, etc.) (60H30) Diffusion processes (60J60) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

Related Items (1)

An optimal Gauss-Markov approximation for a process with stochastic drift and applications

Cites Work

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• Gauss-diffusion processes for modeling the dynamics of a couple of interacting neurons
• The first passage time problem for Gauss-diffusion processes: algorithmic approaches and applications to LIF neuronal model
• On the evaluation of firing densities for periodically driven neuron models
• A computational approach to first-passage-time problems for Gauss–Markov processes
• Gaussian Process Approach to Spiking Neurons for Inhomogeneous Poisson Inputs
• On a Stochastic Leaky Integrate-and-Fire Neuronal Model
• Computer Aided Systems Theory – EUROCAST 2005
• Stochastic Dynamics of a Finite-Size Spiking Neural Network
• On the asymptotic behaviour of first-passage-time densities for one-dimensional diffusion processes and varying boundaries

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