Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons

Little is known about the brain’s computations that enable the recognition of faces. Here, the authors use unsupervised deep learning to show that the brain disentangles faces into semantically meaningful factors, like age or the presence of a smile, at the single neuron level.

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Autores principales:	Irina Higgins, Le Chang, Victoria Langston, Demis Hassabis, Christopher Summerfield, Doris Tsao, Matthew Botvinick
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/7644350a1e17449c9aab6e68c258b6f9
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spelling	oai:doaj.org-article:7644350a1e17449c9aab6e68c258b6f92021-11-14T12:34:04ZUnsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons10.1038/s41467-021-26751-52041-1723https://doaj.org/article/7644350a1e17449c9aab6e68c258b6f92021-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-26751-5https://doaj.org/toc/2041-1723Little is known about the brain’s computations that enable the recognition of faces. Here, the authors use unsupervised deep learning to show that the brain disentangles faces into semantically meaningful factors, like age or the presence of a smile, at the single neuron level.Irina HigginsLe ChangVictoria LangstonDemis HassabisChristopher SummerfieldDoris TsaoMatthew BotvinickNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Irina Higgins Le Chang Victoria Langston Demis Hassabis Christopher Summerfield Doris Tsao Matthew Botvinick Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
description	Little is known about the brain’s computations that enable the recognition of faces. Here, the authors use unsupervised deep learning to show that the brain disentangles faces into semantically meaningful factors, like age or the presence of a smile, at the single neuron level.
format	article
author	Irina Higgins Le Chang Victoria Langston Demis Hassabis Christopher Summerfield Doris Tsao Matthew Botvinick
author_facet	Irina Higgins Le Chang Victoria Langston Demis Hassabis Christopher Summerfield Doris Tsao Matthew Botvinick
author_sort	Irina Higgins
title	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
title_short	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
title_full	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
title_fullStr	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
title_full_unstemmed	Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
title_sort	unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7644350a1e17449c9aab6e68c258b6f9
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Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons

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