Quantized State Simulation of Spiking Neural Networks

Autores
Grinblat, Guillermo Luis; Ahumada, Hernán; Kofman, Ernesto Javier
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity. © 2012, Simulation Councils Inc. All rights reserved.
Fil: Grinblat, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Ahumada, Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Materia
DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
SPIKING NEURAL NETWORKS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/186664
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Quantized State Simulation of Spiking Neural NetworksGrinblat, Guillermo LuisAhumada, HernánKofman, Ernesto JavierDISCRETE EVENT SYSTEMQUANTIZED STATE SYSTEMSSPIKING NEURAL NETWORKShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity. © 2012, Simulation Councils Inc. All rights reserved.Fil: Grinblat, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Ahumada, Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaSage Publications Ltd2012-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/zipapplication/zipapplication/pdfhttp://hdl.handle.net/11336/186664Grinblat, Guillermo Luis; Ahumada, Hernán; Kofman, Ernesto Javier; Quantized State Simulation of Spiking Neural Networks; Sage Publications Ltd; Simulation; 88; 3; 3-2012; 299-3130037-5497CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journals.sagepub.com/doi/abs/10.1177/0037549711399935info:eu-repo/semantics/altIdentifier/doi/10.1177/0037549711399935info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:39:12Zoai:ri.conicet.gov.ar:11336/186664instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:39:13.136CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantized State Simulation of Spiking Neural Networks
title Quantized State Simulation of Spiking Neural Networks
spellingShingle Quantized State Simulation of Spiking Neural Networks
Grinblat, Guillermo Luis
DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
SPIKING NEURAL NETWORKS
title_short Quantized State Simulation of Spiking Neural Networks
title_full Quantized State Simulation of Spiking Neural Networks
title_fullStr Quantized State Simulation of Spiking Neural Networks
title_full_unstemmed Quantized State Simulation of Spiking Neural Networks
title_sort Quantized State Simulation of Spiking Neural Networks
dc.creator.none.fl_str_mv Grinblat, Guillermo Luis
Ahumada, Hernán
Kofman, Ernesto Javier
author Grinblat, Guillermo Luis
author_facet Grinblat, Guillermo Luis
Ahumada, Hernán
Kofman, Ernesto Javier
author_role author
author2 Ahumada, Hernán
Kofman, Ernesto Javier
author2_role author
author
dc.subject.none.fl_str_mv DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
SPIKING NEURAL NETWORKS
topic DISCRETE EVENT SYSTEM
QUANTIZED STATE SYSTEMS
SPIKING NEURAL NETWORKS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity. © 2012, Simulation Councils Inc. All rights reserved.
Fil: Grinblat, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Ahumada, Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
Fil: Kofman, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
description In this work, we explore the usage of quantized state system (QSS) methods in the simulation of networks of spiking neurons. We compare the simulation results obtained by these discrete-event algorithms with the results of the discrete time methods in use by the neuroscience community. We found that the computational costs of the QSS methods grow almost linearly with the size of the network, while they grows at least quadratically in the discrete time algorithms. We show that this advantage is mainly due to the fact that QSS methods only perform calculations in the components of the system that experience activity. © 2012, Simulation Councils Inc. All rights reserved.
publishDate 2012
dc.date.none.fl_str_mv 2012-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/186664
Grinblat, Guillermo Luis; Ahumada, Hernán; Kofman, Ernesto Javier; Quantized State Simulation of Spiking Neural Networks; Sage Publications Ltd; Simulation; 88; 3; 3-2012; 299-313
0037-5497
CONICET Digital
CONICET
url http://hdl.handle.net/11336/186664
identifier_str_mv Grinblat, Guillermo Luis; Ahumada, Hernán; Kofman, Ernesto Javier; Quantized State Simulation of Spiking Neural Networks; Sage Publications Ltd; Simulation; 88; 3; 3-2012; 299-313
0037-5497
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://journals.sagepub.com/doi/abs/10.1177/0037549711399935
info:eu-repo/semantics/altIdentifier/doi/10.1177/0037549711399935
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/zip
application/zip
application/pdf
dc.publisher.none.fl_str_mv Sage Publications Ltd
publisher.none.fl_str_mv Sage Publications Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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