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The order of complexity of visuomotor learning

BACKGROUND: Learning algorithms come in three orders of complexity: zeroth-order (perturbation), first-order (gradient descent), and second-order (e.g., quasi-Newton). But which of these are used in the brain? We trained 12 people to shoot targets, and compared them to simulated subjects that learne...

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Detalles Bibliográficos
Autores principales: Kim, John, Mostafa, Fariya, Tweed, Douglas Blair
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469048/
https://www.ncbi.nlm.nih.gov/pubmed/28606114
http://dx.doi.org/10.1186/s12868-017-0368-x
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author Kim, John
Mostafa, Fariya
Tweed, Douglas Blair
author_facet Kim, John
Mostafa, Fariya
Tweed, Douglas Blair
author_sort Kim, John
collection PubMed
description BACKGROUND: Learning algorithms come in three orders of complexity: zeroth-order (perturbation), first-order (gradient descent), and second-order (e.g., quasi-Newton). But which of these are used in the brain? We trained 12 people to shoot targets, and compared them to simulated subjects that learned the same task using various algorithms. RESULTS: Humans learned significantly faster than optimized zeroth-order algorithms, but slower than second-order ones. CONCLUSIONS: Human visuomotor learning is too fast to be explained by zeroth-order processes alone, and must involve first or second-order mechanisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12868-017-0368-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-54690482017-06-14 The order of complexity of visuomotor learning Kim, John Mostafa, Fariya Tweed, Douglas Blair BMC Neurosci Research Article BACKGROUND: Learning algorithms come in three orders of complexity: zeroth-order (perturbation), first-order (gradient descent), and second-order (e.g., quasi-Newton). But which of these are used in the brain? We trained 12 people to shoot targets, and compared them to simulated subjects that learned the same task using various algorithms. RESULTS: Humans learned significantly faster than optimized zeroth-order algorithms, but slower than second-order ones. CONCLUSIONS: Human visuomotor learning is too fast to be explained by zeroth-order processes alone, and must involve first or second-order mechanisms. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12868-017-0368-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-12 /pmc/articles/PMC5469048/ /pubmed/28606114 http://dx.doi.org/10.1186/s12868-017-0368-x Text en © The Author(s) 2017 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 Research Article
Kim, John
Mostafa, Fariya
Tweed, Douglas Blair
The order of complexity of visuomotor learning
title The order of complexity of visuomotor learning
title_full The order of complexity of visuomotor learning
title_fullStr The order of complexity of visuomotor learning
title_full_unstemmed The order of complexity of visuomotor learning
title_short The order of complexity of visuomotor learning
title_sort order of complexity of visuomotor learning
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5469048/
https://www.ncbi.nlm.nih.gov/pubmed/28606114
http://dx.doi.org/10.1186/s12868-017-0368-x
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