A simple parametric representation of the Hodgkin-Huxley model.

The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of...

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Autores principales:	Alejandro Rodríguez-Collado, Cristina Rueda
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8420d3c131274221b5e9fb8e4d28261d
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spelling	oai:doaj.org-article:8420d3c131274221b5e9fb8e4d28261d2021-12-02T20:06:40ZA simple parametric representation of the Hodgkin-Huxley model.1932-620310.1371/journal.pone.0254152https://doaj.org/article/8420d3c131274221b5e9fb8e4d28261d2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254152https://doaj.org/toc/1932-6203The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators' identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.Alejandro Rodríguez-ColladoCristina RuedaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 7, p e0254152 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Alejandro Rodríguez-Collado Cristina Rueda A simple parametric representation of the Hodgkin-Huxley model.
description	The Hodgkin-Huxley model, decades after its first presentation, is still a reference model in neuroscience as it has successfully reproduced the electrophysiological activity of many organisms. The primary signal in the model represents the membrane potential of a neuron. A simple representation of this signal is presented in this paper. The new proposal is an adapted Frequency Modulated Möbius multicomponent model defined as a signal plus error model in which the signal is decomposed as a sum of waves. The main strengths of the method are the simple parametric formulation, the interpretability and flexibility of the parameters that describe and discriminate the waveforms, the estimators' identifiability and accuracy, and the robustness against noise. The approach is validated with a broad simulation experiment of Hodgkin-Huxley signals and real data from squid giant axons. Interesting differences between simulated and real data emerge from the comparison of the parameter configurations. Furthermore, the potential of the FMM parameters to predict Hodgkin-Huxley model parameters is shown using different Machine Learning methods. Finally, promising contributions of the approach in Spike Sorting and cell-type classification are detailed.
format	article
author	Alejandro Rodríguez-Collado Cristina Rueda
author_facet	Alejandro Rodríguez-Collado Cristina Rueda
author_sort	Alejandro Rodríguez-Collado
title	A simple parametric representation of the Hodgkin-Huxley model.
title_short	A simple parametric representation of the Hodgkin-Huxley model.
title_full	A simple parametric representation of the Hodgkin-Huxley model.
title_fullStr	A simple parametric representation of the Hodgkin-Huxley model.
title_full_unstemmed	A simple parametric representation of the Hodgkin-Huxley model.
title_sort	simple parametric representation of the hodgkin-huxley model.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/8420d3c131274221b5e9fb8e4d28261d
work_keys_str_mv	AT alejandrorodriguezcollado asimpleparametricrepresentationofthehodgkinhuxleymodel AT cristinarueda asimpleparametricrepresentationofthehodgkinhuxleymodel AT alejandrorodriguezcollado simpleparametricrepresentationofthehodgkinhuxleymodel AT cristinarueda simpleparametricrepresentationofthehodgkinhuxleymodel
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A simple parametric representation of the Hodgkin-Huxley model.

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