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Biological complexity facilitates tuning of the neuronal parameter space
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 al...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353791/ https://www.ncbi.nlm.nih.gov/pubmed/37399220 http://dx.doi.org/10.1371/journal.pcbi.1011212 |
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author | Schneider, Marius Bird, Alexander D. Gidon, Albert Triesch, Jochen Jedlicka, Peter Cuntz, Hermann |
author_facet | Schneider, Marius Bird, Alexander D. Gidon, Albert Triesch, Jochen Jedlicka, Peter Cuntz, Hermann |
author_sort | Schneider, Marius |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10353791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-103537912023-07-19 Biological complexity facilitates tuning of the neuronal parameter space Schneider, Marius Bird, Alexander D. Gidon, Albert Triesch, Jochen Jedlicka, Peter Cuntz, Hermann PLoS Comput Biol Research Article 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. Public Library of Science 2023-07-03 /pmc/articles/PMC10353791/ /pubmed/37399220 http://dx.doi.org/10.1371/journal.pcbi.1011212 Text en © 2023 Schneider et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Schneider, Marius Bird, Alexander D. Gidon, Albert Triesch, Jochen Jedlicka, Peter Cuntz, Hermann Biological complexity facilitates tuning of the neuronal parameter space |
title | Biological complexity facilitates tuning of the neuronal parameter space |
title_full | Biological complexity facilitates tuning of the neuronal parameter space |
title_fullStr | Biological complexity facilitates tuning of the neuronal parameter space |
title_full_unstemmed | Biological complexity facilitates tuning of the neuronal parameter space |
title_short | Biological complexity facilitates tuning of the neuronal parameter space |
title_sort | biological complexity facilitates tuning of the neuronal parameter space |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10353791/ https://www.ncbi.nlm.nih.gov/pubmed/37399220 http://dx.doi.org/10.1371/journal.pcbi.1011212 |
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