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Biologically inspired load balancing mechanism in neocortical competitive learning

A unique delayed self-inhibitory pathway mediated by layer 5 Martinotti Cells was studied in a biologically inspired neural network simulation. Inclusion of this pathway along with layer 5 basket cell lateral inhibition caused balanced competitive learning, which led to the formation of neuronal clu...

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Detalles Bibliográficos
Autores principales: Tal, Amir, Peled, Noam, Siegelmann, Hava T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949291/
https://www.ncbi.nlm.nih.gov/pubmed/24653679
http://dx.doi.org/10.3389/fncir.2014.00018
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author Tal, Amir
Peled, Noam
Siegelmann, Hava T.
author_facet Tal, Amir
Peled, Noam
Siegelmann, Hava T.
author_sort Tal, Amir
collection PubMed
description A unique delayed self-inhibitory pathway mediated by layer 5 Martinotti Cells was studied in a biologically inspired neural network simulation. Inclusion of this pathway along with layer 5 basket cell lateral inhibition caused balanced competitive learning, which led to the formation of neuronal clusters as were indeed reported in the same region. Martinotti pathway proves to act as a learning “conscience,” causing overly successful regions in the network to restrict themselves and let others fire. It thus spreads connectivity more evenly throughout the net and solves the “dead unit” problem of clustering algorithms in a local and biologically plausible manner.
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spelling pubmed-39492912014-03-20 Biologically inspired load balancing mechanism in neocortical competitive learning Tal, Amir Peled, Noam Siegelmann, Hava T. Front Neural Circuits Neuroscience A unique delayed self-inhibitory pathway mediated by layer 5 Martinotti Cells was studied in a biologically inspired neural network simulation. Inclusion of this pathway along with layer 5 basket cell lateral inhibition caused balanced competitive learning, which led to the formation of neuronal clusters as were indeed reported in the same region. Martinotti pathway proves to act as a learning “conscience,” causing overly successful regions in the network to restrict themselves and let others fire. It thus spreads connectivity more evenly throughout the net and solves the “dead unit” problem of clustering algorithms in a local and biologically plausible manner. Frontiers Media S.A. 2014-03-11 /pmc/articles/PMC3949291/ /pubmed/24653679 http://dx.doi.org/10.3389/fncir.2014.00018 Text en Copyright © 2014 Tal, Peled and Siegelmann. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Tal, Amir
Peled, Noam
Siegelmann, Hava T.
Biologically inspired load balancing mechanism in neocortical competitive learning
title Biologically inspired load balancing mechanism in neocortical competitive learning
title_full Biologically inspired load balancing mechanism in neocortical competitive learning
title_fullStr Biologically inspired load balancing mechanism in neocortical competitive learning
title_full_unstemmed Biologically inspired load balancing mechanism in neocortical competitive learning
title_short Biologically inspired load balancing mechanism in neocortical competitive learning
title_sort biologically inspired load balancing mechanism in neocortical competitive learning
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3949291/
https://www.ncbi.nlm.nih.gov/pubmed/24653679
http://dx.doi.org/10.3389/fncir.2014.00018
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