Diffusion approximation of neuronal models revisited

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F14%3A00429102" target="_blank" >RIV/67985823:_____/14:00429102 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3934/mbe.2014.11.11" target="_blank" >http://dx.doi.org/10.3934/mbe.2014.11.11</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3934/mbe.2014.11.11" target="_blank" >10.3934/mbe.2014.11.11</a>

Result language
angličtina
Original language name
Diffusion approximation of neuronal models revisited
Original language description
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
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Project
<a href="/en/project/GAP103%2F11%2F0282" target="_blank" >GAP103/11/0282: The role of noise in neuronal information processing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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