Diffusion approximation of neuronal models revisited

0429102 - FGÚ 2015 RIV US eng J - Journal Article
Čupera, Jakub
Diffusion approximation of neuronal models revisited.
Mathematical Biosciences and Engineering. Roč. 11, č. 1 (2014), s. 11-25. ISSN 1547-1063. E-ISSN 1551-0018.
[International Workshop on Neural Coding (NC) /10./. Praha, 02.09.2012-07.09.2012]
R&D Projects: GA ČR(CZ) GAP103/11/0282
Institutional support: RVO:67985823
Keywords : stochastic model * neuronal activity * first-passage time
Subject RIV: JD - Computer Applications, Robotics
Impact factor: 0.840, year: 2014

Leaky integrate-and-fire neuronal models with reversal potentials have a number of different diffusion approximations, each depending on the form of the amplitudes of the postsynaptic potentials. Probability distributions of the first-passage times of the membrane potential in the original model and its diffusion approximations are numerically compared in order to find which of the approximations is the most suitable one. The properties of the random amplitudes of postsynaptic potentials are discussed. It is shown on a simple example that the quality of the approximation depends directly on them
Permanent Link: http://hdl.handle.net/11104/0234289