THE STOCHASTIC, MARKOVIAN, HODGKIN-HUXLEY TYPE OF MATHEMATICAL MODEL OF THE NEURON
The aim of this paper is to show how the Hodgkin-Huxley model of the neuron's membrane potential can be extended to a stochastic one. This extension can be done either by adding fluctuations to the equations of the model or by using Markov kinetic schemes' formalism. We are presenting a ne...
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Published in | Neural Network World Vol. 25; no. 3; pp. 219 - 239 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Prague
Institute of Information and Computer Technology
01.01.2015
Czech Technical University in Prague, Faculty of Transportation Sciences |
Subjects | |
Online Access | Get full text |
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Summary: | The aim of this paper is to show how the Hodgkin-Huxley model of the neuron's membrane potential can be extended to a stochastic one. This extension can be done either by adding fluctuations to the equations of the model or by using Markov kinetic schemes' formalism. We are presenting a new extension of the model. This modification simplifies computational complexity of the neuron model especially when considering a hardware implementation. The hardware implementation of the extended model as a system on a chip using a field-programmable gate array (FPGA) is demonstrated in this paper. The results confirm the reliability of the extended model presented here. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1210-0552 2336-4335 |
DOI: | 10.14311/NNW.2015.25.012 |