Diffusion approximation of neuronal models revisited
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...
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| Format: | Article |
| Language: | English |
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AIMS Press
2013-08-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2014.11.11 |
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| Summary: | 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 itsdiffusion approximations are numerically compared in order to find whichof the approximations is the most suitable one.The properties of the random amplitudes of postsynapticpotentials are discussed.It is shown on a simple example that the quality of the approximation depends directly on them. |
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| ISSN: | 1551-0018 |