Elemental gesture dynamics are encoded by song premotor cortical neurons
- Autores
- Amador, Ana; Sanz Perl Hernandez, Yonatan; Mindlin, Bernardo Gabriel; Margoliash, Daniel
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Quantitative biomechanical models can identify control parameters that are used during movements, and movement parameters that are encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics and upper-vocal-tract filtering to the songs of zebra finches. This reduces the dimensionality of singing dynamics, described as trajectories (motor gestures) in a space of syringeal pressure and tension. Here we assess model performance by characterizing the auditory response ‘replay’ of song premotor HVC neurons to the presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed within a few milliseconds of the extreme time points of the gesture trajectories. Thus, the HVC precisely encodes vocal motor output through activity at the times of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons is used as a ‘forward’ model, representing the sequence of gestures in song to make predictions on expected behaviour and evaluate feedback.
Fil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Mindlin, Bernardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Fil: Margoliash, Daniel. University of Chicago; Estados Unidos - Materia
-
Zebra Finch
Sensorimotor
Nonlinear Dynamical Model
Birdsong - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/2478
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Elemental gesture dynamics are encoded by song premotor cortical neuronsAmador, AnaSanz Perl Hernandez, YonatanMindlin, Bernardo GabrielMargoliash, DanielZebra FinchSensorimotorNonlinear Dynamical ModelBirdsonghttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Quantitative biomechanical models can identify control parameters that are used during movements, and movement parameters that are encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics and upper-vocal-tract filtering to the songs of zebra finches. This reduces the dimensionality of singing dynamics, described as trajectories (motor gestures) in a space of syringeal pressure and tension. Here we assess model performance by characterizing the auditory response ‘replay’ of song premotor HVC neurons to the presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed within a few milliseconds of the extreme time points of the gesture trajectories. Thus, the HVC precisely encodes vocal motor output through activity at the times of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons is used as a ‘forward’ model, representing the sequence of gestures in song to make predictions on expected behaviour and evaluate feedback.Fil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mindlin, Bernardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Margoliash, Daniel. University of Chicago; Estados UnidosNature Publishing Group2013-02-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/2478Amador, Ana; Sanz Perl Hernandez, Yonatan; Mindlin, Bernardo Gabriel; Margoliash, Daniel; Elemental gesture dynamics are encoded by song premotor cortical neurons; Nature Publishing Group; Nature; 495; 7439; 27-2-2013; 59-640028-0836enginfo:eu-repo/semantics/altIdentifier/doi/doi:10.1038/nature11967info:eu-repo/semantics/altIdentifier/url/http://www.nature.com/nature/journal/v495/n7439/full/nature11967.htmlinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:19:47Zoai:ri.conicet.gov.ar:11336/2478instacron: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:34982025-10-22 12:19:48.234CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
title |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
spellingShingle |
Elemental gesture dynamics are encoded by song premotor cortical neurons Amador, Ana Zebra Finch Sensorimotor Nonlinear Dynamical Model Birdsong |
title_short |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
title_full |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
title_fullStr |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
title_full_unstemmed |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
title_sort |
Elemental gesture dynamics are encoded by song premotor cortical neurons |
dc.creator.none.fl_str_mv |
Amador, Ana Sanz Perl Hernandez, Yonatan Mindlin, Bernardo Gabriel Margoliash, Daniel |
author |
Amador, Ana |
author_facet |
Amador, Ana Sanz Perl Hernandez, Yonatan Mindlin, Bernardo Gabriel Margoliash, Daniel |
author_role |
author |
author2 |
Sanz Perl Hernandez, Yonatan Mindlin, Bernardo Gabriel Margoliash, Daniel |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Zebra Finch Sensorimotor Nonlinear Dynamical Model Birdsong |
topic |
Zebra Finch Sensorimotor Nonlinear Dynamical Model Birdsong |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.3 https://purl.org/becyt/ford/1 https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Quantitative biomechanical models can identify control parameters that are used during movements, and movement parameters that are encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics and upper-vocal-tract filtering to the songs of zebra finches. This reduces the dimensionality of singing dynamics, described as trajectories (motor gestures) in a space of syringeal pressure and tension. Here we assess model performance by characterizing the auditory response ‘replay’ of song premotor HVC neurons to the presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed within a few milliseconds of the extreme time points of the gesture trajectories. Thus, the HVC precisely encodes vocal motor output through activity at the times of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons is used as a ‘forward’ model, representing the sequence of gestures in song to make predictions on expected behaviour and evaluate feedback. Fil: Amador, Ana. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina Fil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Mindlin, Bernardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina Fil: Margoliash, Daniel. University of Chicago; Estados Unidos |
description |
Quantitative biomechanical models can identify control parameters that are used during movements, and movement parameters that are encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics and upper-vocal-tract filtering to the songs of zebra finches. This reduces the dimensionality of singing dynamics, described as trajectories (motor gestures) in a space of syringeal pressure and tension. Here we assess model performance by characterizing the auditory response ‘replay’ of song premotor HVC neurons to the presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed within a few milliseconds of the extreme time points of the gesture trajectories. Thus, the HVC precisely encodes vocal motor output through activity at the times of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons is used as a ‘forward’ model, representing the sequence of gestures in song to make predictions on expected behaviour and evaluate feedback. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-02-27 |
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/11336/2478 Amador, Ana; Sanz Perl Hernandez, Yonatan; Mindlin, Bernardo Gabriel; Margoliash, Daniel; Elemental gesture dynamics are encoded by song premotor cortical neurons; Nature Publishing Group; Nature; 495; 7439; 27-2-2013; 59-64 0028-0836 |
url |
http://hdl.handle.net/11336/2478 |
identifier_str_mv |
Amador, Ana; Sanz Perl Hernandez, Yonatan; Mindlin, Bernardo Gabriel; Margoliash, Daniel; Elemental gesture dynamics are encoded by song premotor cortical neurons; Nature Publishing Group; Nature; 495; 7439; 27-2-2013; 59-64 0028-0836 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/doi:10.1038/nature11967 info:eu-repo/semantics/altIdentifier/url/http://www.nature.com/nature/journal/v495/n7439/full/nature11967.html |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Nature Publishing Group |
publisher.none.fl_str_mv |
Nature Publishing Group |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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1846782639872147456 |
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12.982451 |