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Stability analysis of a neural field self-organizing map

We provide theoretical conditions guaranteeing that a self-organizing map efficiently develops representations of the input space. The study relies on a neural field model of spatiotemporal activity in area 3b of the primary somatosensory cortex. We rely on Lyapunov’s theory for neural fields to der...

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Detalles Bibliográficos
Autores principales: Detorakis, Georgios, Chaillet, Antoine, Rougier, Nicolas P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708616/
https://www.ncbi.nlm.nih.gov/pubmed/33259016
http://dx.doi.org/10.1186/s13408-020-00097-6
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author Detorakis, Georgios
Chaillet, Antoine
Rougier, Nicolas P.
author_facet Detorakis, Georgios
Chaillet, Antoine
Rougier, Nicolas P.
author_sort Detorakis, Georgios
collection PubMed
description We provide theoretical conditions guaranteeing that a self-organizing map efficiently develops representations of the input space. The study relies on a neural field model of spatiotemporal activity in area 3b of the primary somatosensory cortex. We rely on Lyapunov’s theory for neural fields to derive theoretical conditions for stability. We verify the theoretical conditions by numerical experiments. The analysis highlights the key role played by the balance between excitation and inhibition of lateral synaptic coupling and the strength of synaptic gains in the formation and maintenance of self-organizing maps.
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spelling pubmed-77086162020-12-04 Stability analysis of a neural field self-organizing map Detorakis, Georgios Chaillet, Antoine Rougier, Nicolas P. J Math Neurosci Short Report We provide theoretical conditions guaranteeing that a self-organizing map efficiently develops representations of the input space. The study relies on a neural field model of spatiotemporal activity in area 3b of the primary somatosensory cortex. We rely on Lyapunov’s theory for neural fields to derive theoretical conditions for stability. We verify the theoretical conditions by numerical experiments. The analysis highlights the key role played by the balance between excitation and inhibition of lateral synaptic coupling and the strength of synaptic gains in the formation and maintenance of self-organizing maps. Springer Berlin Heidelberg 2020-12-01 /pmc/articles/PMC7708616/ /pubmed/33259016 http://dx.doi.org/10.1186/s13408-020-00097-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Short Report
Detorakis, Georgios
Chaillet, Antoine
Rougier, Nicolas P.
Stability analysis of a neural field self-organizing map
title Stability analysis of a neural field self-organizing map
title_full Stability analysis of a neural field self-organizing map
title_fullStr Stability analysis of a neural field self-organizing map
title_full_unstemmed Stability analysis of a neural field self-organizing map
title_short Stability analysis of a neural field self-organizing map
title_sort stability analysis of a neural field self-organizing map
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708616/
https://www.ncbi.nlm.nih.gov/pubmed/33259016
http://dx.doi.org/10.1186/s13408-020-00097-6
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