Neural heterogeneity promotes robust learning

The authors show that heterogeneity in spiking neural networks improves accuracy and robustness of prediction for complex information processing tasks, results in optimal parameter distribution similar to experimental data and is metabolically efficient for learning tasks at varying timescales.

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Detalles Bibliográficos
Autores principales:	Nicolas Perez-Nieves, Vincent C. H. Leung, Pier Luigi Dragotti, Dan F. M. Goodman
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/5f3aee1234744188899e09099851da31
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id	oai:doaj.org-article:5f3aee1234744188899e09099851da31
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spelling	oai:doaj.org-article:5f3aee1234744188899e09099851da312021-12-02T19:16:33ZNeural heterogeneity promotes robust learning10.1038/s41467-021-26022-32041-1723https://doaj.org/article/5f3aee1234744188899e09099851da312021-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-26022-3https://doaj.org/toc/2041-1723The authors show that heterogeneity in spiking neural networks improves accuracy and robustness of prediction for complex information processing tasks, results in optimal parameter distribution similar to experimental data and is metabolically efficient for learning tasks at varying timescales.Nicolas Perez-NievesVincent C. H. LeungPier Luigi DragottiDan F. M. GoodmanNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Nicolas Perez-Nieves Vincent C. H. Leung Pier Luigi Dragotti Dan F. M. Goodman Neural heterogeneity promotes robust learning
description	The authors show that heterogeneity in spiking neural networks improves accuracy and robustness of prediction for complex information processing tasks, results in optimal parameter distribution similar to experimental data and is metabolically efficient for learning tasks at varying timescales.
format	article
author	Nicolas Perez-Nieves Vincent C. H. Leung Pier Luigi Dragotti Dan F. M. Goodman
author_facet	Nicolas Perez-Nieves Vincent C. H. Leung Pier Luigi Dragotti Dan F. M. Goodman
author_sort	Nicolas Perez-Nieves
title	Neural heterogeneity promotes robust learning
title_short	Neural heterogeneity promotes robust learning
title_full	Neural heterogeneity promotes robust learning
title_fullStr	Neural heterogeneity promotes robust learning
title_full_unstemmed	Neural heterogeneity promotes robust learning
title_sort	neural heterogeneity promotes robust learning
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/5f3aee1234744188899e09099851da31
work_keys_str_mv	AT nicolaspereznieves neuralheterogeneitypromotesrobustlearning AT vincentchleung neuralheterogeneitypromotesrobustlearning AT pierluigidragotti neuralheterogeneitypromotesrobustlearning AT danfmgoodman neuralheterogeneitypromotesrobustlearning
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Neural heterogeneity promotes robust learning

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