Biological complexity facilitates tuning of the neuronal parameter space.


Journal

PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922

Informations de publication

Date de publication:
07 2023
Historique:
received: 16 02 2023
accepted: 24 05 2023
revised: 18 07 2023
medline: 21 7 2023
pubmed: 3 7 2023
entrez: 3 7 2023
Statut: epublish

Résumé

The electrical and computational properties of neurons in our brains are determined by a rich repertoire of membrane-spanning ion channels and elaborate dendritic trees. However, the precise reason for this inherent complexity remains unknown, given that simpler models with fewer ion channels are also able to functionally reproduce the behaviour of some neurons. Here, we stochastically varied the ion channel densities of a biophysically detailed dentate gyrus granule cell model to produce a large population of putative granule cells, comparing those with all 15 original ion channels to their reduced but functional counterparts containing only 5 ion channels. Strikingly, valid parameter combinations in the full models were dramatically more frequent at ~6% vs. ~1% in the simpler model. The full models were also more stable in the face of perturbations to channel expression levels. Scaling up the numbers of ion channels artificially in the reduced models recovered these advantages confirming the key contribution of the actual number of ion channel types. We conclude that the diversity of ion channels gives a neuron greater flexibility and robustness to achieve a target excitability.

Identifiants

pubmed: 37399220
doi: 10.1371/journal.pcbi.1011212
pii: PCOMPBIOL-D-23-00254
pmc: PMC10353791
doi:

Substances chimiques

Ion Channels 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1011212

Informations de copyright

Copyright: © 2023 Schneider et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Marius Schneider (M)

Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany.
ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany.
Faculty of Physics, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany.

Alexander D Bird (AD)

Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany.
ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany.

Albert Gidon (A)

Institute for Biology, Humboldt-Universität zu Berlin, Berlin, Germany.

Jochen Triesch (J)

Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
Faculty of Physics, Goethe University, Frankfurt/Main, Frankfurt am Main, Germany.
Faculty of Computer Science and Mathematics, Goethe University, Frankfurt am Main, Germany.

Peter Jedlicka (P)

ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany.
Institute of Clinical Neuroanatomy, Neuroscience Center, Goethe University, Frankfurt am Main, Germany.

Hermann Cuntz (H)

Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.
Ernst Strüngmann Institute (ESI) for Neuroscience in cooperation with the Max Planck Society, Frankfurt am Main, Germany.
ICAR3R-Interdisciplinary Centre for 3Rs in Animal Research, Justus Liebig University Giessen, Giessen, Germany.

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