Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks

Luboeinski and Tetzlaff develop a theoretical model, which integrates mechanisms underlying the synaptic-tagging-and-capture (STC) hypothesis with calcium-based synaptic plasticity in a recurrent spiking neural network, to describe consolidation of memory representations. They show that STC mechanis...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jannik Luboeinski, Christian Tetzlaff
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/b13fad3d6a5d49d8a558acdd08c9cfb0
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:b13fad3d6a5d49d8a558acdd08c9cfb0
record_format	dspace
spelling	oai:doaj.org-article:b13fad3d6a5d49d8a558acdd08c9cfb02021-12-02T15:52:46ZMemory consolidation and improvement by synaptic tagging and capture in recurrent neural networks10.1038/s42003-021-01778-y2399-3642https://doaj.org/article/b13fad3d6a5d49d8a558acdd08c9cfb02021-03-01T00:00:00Zhttps://doi.org/10.1038/s42003-021-01778-yhttps://doaj.org/toc/2399-3642Luboeinski and Tetzlaff develop a theoretical model, which integrates mechanisms underlying the synaptic-tagging-and-capture (STC) hypothesis with calcium-based synaptic plasticity in a recurrent spiking neural network, to describe consolidation of memory representations. They show that STC mechanisms cause improved memory recall, which may assist the understanding of storing information in biological and artificial neural circuits.Jannik LuboeinskiChristian TetzlaffNature PortfolioarticleBiology (General)QH301-705.5ENCommunications Biology, Vol 4, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Jannik Luboeinski Christian Tetzlaff Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
description	Luboeinski and Tetzlaff develop a theoretical model, which integrates mechanisms underlying the synaptic-tagging-and-capture (STC) hypothesis with calcium-based synaptic plasticity in a recurrent spiking neural network, to describe consolidation of memory representations. They show that STC mechanisms cause improved memory recall, which may assist the understanding of storing information in biological and artificial neural circuits.
format	article
author	Jannik Luboeinski Christian Tetzlaff
author_facet	Jannik Luboeinski Christian Tetzlaff
author_sort	Jannik Luboeinski
title	Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
title_short	Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
title_full	Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
title_fullStr	Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
title_full_unstemmed	Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
title_sort	memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b13fad3d6a5d49d8a558acdd08c9cfb0
work_keys_str_mv	AT jannikluboeinski memoryconsolidationandimprovementbysynaptictaggingandcaptureinrecurrentneuralnetworks AT christiantetzlaff memoryconsolidationandimprovementbysynaptictaggingandcaptureinrecurrentneuralnetworks
_version_	1718385592115396608

Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks

Ejemplares similares