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Two opposite voltage-dependent currents control the unusual early development pattern of embryonic Renshaw cell electrical activity

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Boeri, Juliette, Meunier, Claude, Le Corronc, Hervé, Branchereau, Pascal, Timofeeva, Yulia, Lejeune, François-Xavier, Mouffle, Christine, Arulkandarajah, Hervé, Mangin, Jean Marie, Legendre, Pascal and Czarnecki, Antonny (2021) Two opposite voltage-dependent currents control the unusual early development pattern of embryonic Renshaw cell electrical activity. eLife, 10 . e62639. doi:10.7554/elife.62639

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Official URL: https://doi.org/10.7554/elife.62639

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Abstract

Renshaw cells (V1R) are excitable as soon as they reach their final location next to the spinal motoneurons and are functionally heterogeneous. Using multiple experimental approaches, in combination with biophysical modeling and dynamical systems theory, we analyzed, for the first time, the mechanisms underlying the electrophysiological properties of V1R during early embryonic development of the mouse spinal cord locomotor networks (E11.5–E16.5). We found that these interneurons are subdivided into several functional clusters from E11.5 and then display an unexpected transitory involution process during which they lose their ability to sustain tonic firing. We demonstrated that the essential factor controlling the diversity of the discharge pattern of embryonic V1R is the ratio of a persistent sodium conductance to a delayed rectifier potassium conductance. Taken together, our results reveal how a simple mechanism, based on the synergy of two voltage-dependent conductances that are ubiquitous in neurons, can produce functional diversity in embryonic V1R and control their early developmental trajectory.

Item Type: Journal Article
Subjects: Q Science > QP Physiology
Divisions: Faculty of Science > Centre for Complexity Science
Faculty of Science > Computer Science
SWORD Depositor: Library Publications Router
Library of Congress Subject Headings (LCSH): Interneurons , Interneurons -- Electric properties, Neural networks (Neurobiology), Neural networks (Neurobiology) -- Computer simulation
Journal or Publication Title: eLife
Publisher: eLife Sciences Publications, Ltd
ISSN: 2050-084X
Official Date: 26 April 2021
Dates:
DateEvent
26 April 2021Published
24 April 2021Accepted
Volume: 10
Article Number: e62639
DOI: 10.7554/elife.62639
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
DEQ20160334891Fondation pour la recherche médicalehttp://viaf.org/viaf/131037754
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