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Mathematical relationships between spinal motoneuron properties
Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity, and afterhyperpolarization duration. We r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612914/ https://www.ncbi.nlm.nih.gov/pubmed/35848819 http://dx.doi.org/10.7554/eLife.76489 |
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author | Caillet, Arnault H Phillips, Andrew TM Farina, Dario Modenese, Luca |
author_facet | Caillet, Arnault H Phillips, Andrew TM Farina, Dario Modenese, Luca |
author_sort | Caillet, Arnault H |
collection | PubMed |
description | Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity, and afterhyperpolarization duration. We reprocessed the data from 40 experimental studies in adult cat, rat, and mouse MN preparations to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, explore the relationships between pairs of MN properties never concurrently observed in previous experiments, or investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modellers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations. |
format | Online Article Text |
id | pubmed-9612914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-96129142022-10-28 Mathematical relationships between spinal motoneuron properties Caillet, Arnault H Phillips, Andrew TM Farina, Dario Modenese, Luca eLife Neuroscience Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity, and afterhyperpolarization duration. We reprocessed the data from 40 experimental studies in adult cat, rat, and mouse MN preparations to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, explore the relationships between pairs of MN properties never concurrently observed in previous experiments, or investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modellers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations. eLife Sciences Publications, Ltd 2022-07-18 /pmc/articles/PMC9612914/ /pubmed/35848819 http://dx.doi.org/10.7554/eLife.76489 Text en © 2022, Caillet et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Caillet, Arnault H Phillips, Andrew TM Farina, Dario Modenese, Luca Mathematical relationships between spinal motoneuron properties |
title | Mathematical relationships between spinal motoneuron properties |
title_full | Mathematical relationships between spinal motoneuron properties |
title_fullStr | Mathematical relationships between spinal motoneuron properties |
title_full_unstemmed | Mathematical relationships between spinal motoneuron properties |
title_short | Mathematical relationships between spinal motoneuron properties |
title_sort | mathematical relationships between spinal motoneuron properties |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612914/ https://www.ncbi.nlm.nih.gov/pubmed/35848819 http://dx.doi.org/10.7554/eLife.76489 |
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