A circular model for song motor control in Serinus canaria

Autores
Alonso, Rodrigo; Trevisan, Marcos Alberto; Amador, Ana; Goller, Franz; Mindlin, Bernardo Gabriel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
Fil: Alonso, Rodrigo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Trevisan, Marcos Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Goller, Franz. University Of Utah. Department Of Biology; Estados Unidos
Fil: Mindlin, Bernardo Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
NONLINEAR DYNAMICS
RATE MODELS
BIRDSONG
SONG SYSTEM
MOTOR CONTROL
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:11336/43506
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A circular model for song motor control in Serinus canariaAlonso, RodrigoTrevisan, Marcos AlbertoAmador, AnaGoller, FranzMindlin, Bernardo GabrielNONLINEAR DYNAMICSRATE MODELSBIRDSONGSONG SYSTEMMOTOR CONTROLhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.Fil: Alonso, Rodrigo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Trevisan, Marcos Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Goller, Franz. University Of Utah. Department Of Biology; Estados UnidosFil: Mindlin, Bernardo Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFrontiers Research Foundation2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/43506Alonso, Rodrigo; Trevisan, Marcos Alberto; Amador, Ana; Goller, Franz; Mindlin, Bernardo Gabriel; A circular model for song motor control in Serinus canaria; Frontiers Research Foundation; Frontiers in Computational Neuroscience; 9; 3-2015; 1-91662-5188CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fncom.2015.00041/fullinfo:eu-repo/semantics/altIdentifier/doi/10.3389/fncom.2015.00041info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:46:06Zoai:ri.conicet.gov.ar:11336/43506instacron: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:34982025-09-03 09:46:06.543CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A circular model for song motor control in Serinus canaria
title A circular model for song motor control in Serinus canaria
spellingShingle A circular model for song motor control in Serinus canaria
Alonso, Rodrigo
NONLINEAR DYNAMICS
RATE MODELS
BIRDSONG
SONG SYSTEM
MOTOR CONTROL
title_short A circular model for song motor control in Serinus canaria
title_full A circular model for song motor control in Serinus canaria
title_fullStr A circular model for song motor control in Serinus canaria
title_full_unstemmed A circular model for song motor control in Serinus canaria
title_sort A circular model for song motor control in Serinus canaria
dc.creator.none.fl_str_mv Alonso, Rodrigo
Trevisan, Marcos Alberto
Amador, Ana
Goller, Franz
Mindlin, Bernardo Gabriel
author Alonso, Rodrigo
author_facet Alonso, Rodrigo
Trevisan, Marcos Alberto
Amador, Ana
Goller, Franz
Mindlin, Bernardo Gabriel
author_role author
author2 Trevisan, Marcos Alberto
Amador, Ana
Goller, Franz
Mindlin, Bernardo Gabriel
author2_role author
author
author
author
dc.subject.none.fl_str_mv NONLINEAR DYNAMICS
RATE MODELS
BIRDSONG
SONG SYSTEM
MOTOR CONTROL
topic NONLINEAR DYNAMICS
RATE MODELS
BIRDSONG
SONG SYSTEM
MOTOR CONTROL
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
Fil: Alonso, Rodrigo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Trevisan, Marcos Alberto. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Goller, Franz. University Of Utah. Department Of Biology; Estados Unidos
Fil: Mindlin, Bernardo Gabriel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Sistemas Dinámicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
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/11336/43506
Alonso, Rodrigo; Trevisan, Marcos Alberto; Amador, Ana; Goller, Franz; Mindlin, Bernardo Gabriel; A circular model for song motor control in Serinus canaria; Frontiers Research Foundation; Frontiers in Computational Neuroscience; 9; 3-2015; 1-9
1662-5188
CONICET Digital
CONICET
url http://hdl.handle.net/11336/43506
identifier_str_mv Alonso, Rodrigo; Trevisan, Marcos Alberto; Amador, Ana; Goller, Franz; Mindlin, Bernardo Gabriel; A circular model for song motor control in Serinus canaria; Frontiers Research Foundation; Frontiers in Computational Neuroscience; 9; 3-2015; 1-9
1662-5188
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://www.frontiersin.org/articles/10.3389/fncom.2015.00041/full
info:eu-repo/semantics/altIdentifier/doi/10.3389/fncom.2015.00041
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/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Research Foundation
publisher.none.fl_str_mv Frontiers Research Foundation
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 13.13397

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