Robust persistent activity in neural fields with asymmetric connectivity

Detalhes bibliográficos
Autor(a) principal: Horta, Cláudia
Data de Publicação: 2006
Outros Autores: Erlhagen, Wolfram
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/5762
Resumo: Modeling studies have shown that recurrent interactions within neural networks are capable of self-sustaining non-uniform activity profiles. These patterns are thought to be the neural basis of working memory. However, the lack of robustness challenge this view as already small deviations from the assumed interaction symmetry destroy the attractor state. Here we analyze attractor states of a neural field model composed of bistable neurons. We show the existence of self-stabilized patterns that robustly represent the cue position in the presence of a substantial asymmetry in the connection profile. Using approximation techniques we derive an explicit expression for a threshold value describing the transition to a traveling activity wave.
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spelling Robust persistent activity in neural fields with asymmetric connectivityNeural fieldBistabilityWorking memorySpatial orientationScience & TechnologyModeling studies have shown that recurrent interactions within neural networks are capable of self-sustaining non-uniform activity profiles. These patterns are thought to be the neural basis of working memory. However, the lack of robustness challenge this view as already small deviations from the assumed interaction symmetry destroy the attractor state. Here we analyze attractor states of a neural field model composed of bistable neurons. We show the existence of self-stabilized patterns that robustly represent the cue position in the presence of a substantial asymmetry in the connection profile. Using approximation techniques we derive an explicit expression for a threshold value describing the transition to a traveling activity wave.Elsevier ScienceUniversidade do MinhoHorta, CláudiaErlhagen, Wolfram2006-062006-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/5762eng"Neurocomputing". ISSN 0925-2312. 69:10-12 (June 2006) 1141-1145.0925-231210.1016/j.neucom.2005.12.062http://dx.doi.org/10.1016/j.neucom.2005.12.062info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:20:34Zoai:repositorium.sdum.uminho.pt:1822/5762Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:13:44.803899Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Robust persistent activity in neural fields with asymmetric connectivity
title Robust persistent activity in neural fields with asymmetric connectivity
spellingShingle Robust persistent activity in neural fields with asymmetric connectivity
Horta, Cláudia
Neural field
Bistability
Working memory
Spatial orientation
Science & Technology
title_short Robust persistent activity in neural fields with asymmetric connectivity
title_full Robust persistent activity in neural fields with asymmetric connectivity
title_fullStr Robust persistent activity in neural fields with asymmetric connectivity
title_full_unstemmed Robust persistent activity in neural fields with asymmetric connectivity
title_sort Robust persistent activity in neural fields with asymmetric connectivity
author Horta, Cláudia
author_facet Horta, Cláudia
Erlhagen, Wolfram
author_role author
author2 Erlhagen, Wolfram
author2_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Horta, Cláudia
Erlhagen, Wolfram
dc.subject.por.fl_str_mv Neural field
Bistability
Working memory
Spatial orientation
Science & Technology
topic Neural field
Bistability
Working memory
Spatial orientation
Science & Technology
description Modeling studies have shown that recurrent interactions within neural networks are capable of self-sustaining non-uniform activity profiles. These patterns are thought to be the neural basis of working memory. However, the lack of robustness challenge this view as already small deviations from the assumed interaction symmetry destroy the attractor state. Here we analyze attractor states of a neural field model composed of bistable neurons. We show the existence of self-stabilized patterns that robustly represent the cue position in the presence of a substantial asymmetry in the connection profile. Using approximation techniques we derive an explicit expression for a threshold value describing the transition to a traveling activity wave.
publishDate 2006
dc.date.none.fl_str_mv 2006-06
2006-06-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/5762
url http://hdl.handle.net/1822/5762
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv "Neurocomputing". ISSN 0925-2312. 69:10-12 (June 2006) 1141-1145.
0925-2312
10.1016/j.neucom.2005.12.062
http://dx.doi.org/10.1016/j.neucom.2005.12.062
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dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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