Diffusion approximation of neuronal models revisited
Language English Country United States Media print
Document type Journal Article, Research Support, Non-U.S. Gov't
- MeSH
- Action Potentials physiology MeSH
- Diffusion MeSH
- Humans MeSH
- Mathematics MeSH
- Membrane Potentials physiology MeSH
- Models, Neurological * MeSH
- Neurons physiology MeSH
- Normal Distribution MeSH
- Computer Simulation MeSH
- Poisson Distribution MeSH
- Probability MeSH
- Stochastic Processes MeSH
- Synaptic Potentials MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
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.
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