Spatial features of synaptic adaptation affecting learning performance

Abstract Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is...

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Autores principales:	Damian L. Berger, Lucilla de Arcangelis, Hans J. Herrmann
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/dd4f573582844bc3a5b28da6087c44ac
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spelling	oai:doaj.org-article:dd4f573582844bc3a5b28da6087c44ac2021-12-02T15:06:22ZSpatial features of synaptic adaptation affecting learning performance10.1038/s41598-017-11424-52045-2322https://doaj.org/article/dd4f573582844bc3a5b28da6087c44ac2017-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-11424-5https://doaj.org/toc/2045-2322Abstract Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.Damian L. BergerLucilla de ArcangelisHans J. HerrmannNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-7 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Damian L. Berger Lucilla de Arcangelis Hans J. Herrmann Spatial features of synaptic adaptation affecting learning performance
description	Abstract Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.
format	article
author	Damian L. Berger Lucilla de Arcangelis Hans J. Herrmann
author_facet	Damian L. Berger Lucilla de Arcangelis Hans J. Herrmann
author_sort	Damian L. Berger
title	Spatial features of synaptic adaptation affecting learning performance
title_short	Spatial features of synaptic adaptation affecting learning performance
title_full	Spatial features of synaptic adaptation affecting learning performance
title_fullStr	Spatial features of synaptic adaptation affecting learning performance
title_full_unstemmed	Spatial features of synaptic adaptation affecting learning performance
title_sort	spatial features of synaptic adaptation affecting learning performance
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/dd4f573582844bc3a5b28da6087c44ac
work_keys_str_mv	AT damianlberger spatialfeaturesofsynapticadaptationaffectinglearningperformance AT lucilladearcangelis spatialfeaturesofsynapticadaptationaffectinglearningperformance AT hansjherrmann spatialfeaturesofsynapticadaptationaffectinglearningperformance
_version_	1718388482752118784

Spatial features of synaptic adaptation affecting learning performance

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