Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Schneider, Marius, Bird, Alexander D., Gidon, Albert, Triesch, Jochen, Jedlicka, Peter, Cuntz, Hermann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
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
_version_ 1785074779550646272
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
work_keys_str_mv AT schneidermarius biologicalcomplexityfacilitatestuningoftheneuronalparameterspace
AT birdalexanderd biologicalcomplexityfacilitatestuningoftheneuronalparameterspace
AT gidonalbert biologicalcomplexityfacilitatestuningoftheneuronalparameterspace
AT trieschjochen biologicalcomplexityfacilitatestuningoftheneuronalparameterspace
AT jedlickapeter biologicalcomplexityfacilitatestuningoftheneuronalparameterspace
AT cuntzhermann biologicalcomplexityfacilitatestuningoftheneuronalparameterspace