Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance
The aim of this study is the ion channel model with noise variance as approximations to the HodgkinHuxley model proposed, due to the Hodgkin-Huxley model affected when inserting some colored noise terms inside the conductances, where those effects captured by colored noise because of the gate multip...
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my.ump.umpir.192512018-10-03T07:27:25Z http://umpir.ump.edu.my/id/eprint/19251/ Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance Khudhur, Ahmed M. Hashim, Yasir Abdalla, Ahmed N. TK Electrical engineering. Electronics Nuclear engineering The aim of this study is the ion channel model with noise variance as approximations to the HodgkinHuxley model proposed, due to the Hodgkin-Huxley model affected when inserting some colored noise terms inside the conductances, where those effects captured by colored noise because of the gate multiplicity. Firstly, it introduces the comparison of ion channel based on Fox, Lu and Linaro models. Additionally, in order to overcome the limitations of other parameter estimation methods, the proposed method fully constrains their models and obtains all model's capabilities of reproducing the data. Finally, the relationship between the sequence of colored noise and the spike frequency are simulated efficiently each gate compared with microscopic simulations of the stochastic Markov process method. In simulation results, the spiking rate generated from the proposed model very close to microscopic simulations and doesn’t effect by the membrane size. Maxwell Scientific Publication Corp. 2017-07-15 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/19251/1/msproof.php_doi%3Drjaset.14.4789 Khudhur, Ahmed M. and Hashim, Yasir and Abdalla, Ahmed N. (2017) Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance. Research Journal of Applied Sciences, Engineering and Technology, 14 (7). pp. 262-270. ISSN 2040-7459 http://www.maxwellsci.com/msproof.php?doi=rjaset.14.4789 doi: 10.19026/rjaset.14.4789 |
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TK Electrical engineering. Electronics Nuclear engineering Khudhur, Ahmed M. Hashim, Yasir Abdalla, Ahmed N. Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
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The aim of this study is the ion channel model with noise variance as approximations to the HodgkinHuxley model proposed, due to the Hodgkin-Huxley model affected when inserting some colored noise terms inside the conductances, where those effects captured by colored noise because of the gate multiplicity. Firstly, it introduces the comparison of ion channel based on Fox, Lu and Linaro models. Additionally, in order to overcome the limitations of other parameter estimation methods, the proposed method fully constrains their models and obtains all model's capabilities of reproducing the data. Finally, the relationship between the sequence of colored noise and the spike frequency are simulated efficiently each gate compared with microscopic simulations of the stochastic Markov process method. In simulation results, the spiking rate generated from the proposed model very close to microscopic simulations and doesn’t effect by the membrane size.
|
format |
Article |
author |
Khudhur, Ahmed M. Hashim, Yasir Abdalla, Ahmed N. |
author_facet |
Khudhur, Ahmed M. Hashim, Yasir Abdalla, Ahmed N. |
author_sort |
Khudhur, Ahmed M. |
title |
Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
title_short |
Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
title_full |
Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
title_fullStr |
Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
title_full_unstemmed |
Development of Neuron Ion Channel Model using Colored Noise Terms in the Conductance |
title_sort |
development of neuron ion channel model using colored noise terms in the conductance |
publisher |
Maxwell Scientific Publication Corp. |
publishDate |
2017 |
url |
http://umpir.ump.edu.my/id/eprint/19251/1/msproof.php_doi%3Drjaset.14.4789 http://umpir.ump.edu.my/id/eprint/19251/ http://www.maxwellsci.com/msproof.php?doi=rjaset.14.4789 |
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13.211869 |