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Computational modeling of peripheral pain: a commentary
This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibili...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464699/ https://www.ncbi.nlm.nih.gov/pubmed/26062616 http://dx.doi.org/10.1186/s12938-015-0049-x |
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author | Argüello, Erick J Silva, Ricardo J Huerta, Mónica K Avila, René S |
author_facet | Argüello, Erick J Silva, Ricardo J Huerta, Mónica K Avila, René S |
author_sort | Argüello, Erick J |
collection | PubMed |
description | This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibility at some levels, they do not provide clinically relevant results, and they cannot capture the stochastic character of neural dynamics. On this basis, we provide some suggestions that may be useful in building computational models of pain with a wider range of applications. |
format | Online Article Text |
id | pubmed-4464699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44646992015-06-14 Computational modeling of peripheral pain: a commentary Argüello, Erick J Silva, Ricardo J Huerta, Mónica K Avila, René S Biomed Eng Online Review This commentary is intended to find possible explanations for the low impact of computational modeling on pain research. We discuss the main strategies that have been used in building computational models for the study of pain. The analysis suggests that traditional models lack biological plausibility at some levels, they do not provide clinically relevant results, and they cannot capture the stochastic character of neural dynamics. On this basis, we provide some suggestions that may be useful in building computational models of pain with a wider range of applications. BioMed Central 2015-06-11 /pmc/articles/PMC4464699/ /pubmed/26062616 http://dx.doi.org/10.1186/s12938-015-0049-x Text en © Argüello et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Review Argüello, Erick J Silva, Ricardo J Huerta, Mónica K Avila, René S Computational modeling of peripheral pain: a commentary |
title | Computational modeling of peripheral pain: a commentary |
title_full | Computational modeling of peripheral pain: a commentary |
title_fullStr | Computational modeling of peripheral pain: a commentary |
title_full_unstemmed | Computational modeling of peripheral pain: a commentary |
title_short | Computational modeling of peripheral pain: a commentary |
title_sort | computational modeling of peripheral pain: a commentary |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4464699/ https://www.ncbi.nlm.nih.gov/pubmed/26062616 http://dx.doi.org/10.1186/s12938-015-0049-x |
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