Open AccessDiffusion approximation of neuronal models revisited
Author(s) -
Jakub Čupera
Publication year - 2014
Publication title -
mathematical biosciences and engineering
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2014.11.11
Subject(s) - heavy traffic approximation , amplitude , diffusion , statistical physics , approximations of π , simple (philosophy) , physics , mathematics , quality (philosophy) , quantum mechanics , statistics , philosophy , epistemology
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.