Automatic reconstruction of physiological gestures used in a model of birdsong production
Highly coordinated learned behaviors are key to understanding neural processes integrating the body and the environment. Birdsong production is a widely studied example of such behavior in which numerous thoracic muscles control respiratory inspiration and expiration: the muscles of the syrinx contr...
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00223077_v114_n5_p2912_Boari http://hdl.handle.net/20.500.12110/paper_00223077_v114_n5_p2912_Boari |
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paper:paper_00223077_v114_n5_p2912_Boari2023-06-08T14:49:12Z Automatic reconstruction of physiological gestures used in a model of birdsong production Amador, Ana Bird’s own song Dynamical systems Modeling software Peripheral vocal production model Vocal learning animal experiment Article automation biomechanics breathing muscle dynamics electrophysiology gesture male morphology motor control nonhuman priority journal Taeniopygia guttata telencephalon vocal cord vocalization action potential animal animal structures automated pattern recognition biological model computer simulation finch high vocal center nerve cell physiology procedures sound sound detection trachea vocalization Action Potentials Animal Structures Animals Computer Simulation Finches High Vocal Center Models, Neurological Neurons Pattern Recognition, Automated Sound Sound Spectrography Trachea Vocalization, Animal Highly coordinated learned behaviors are key to understanding neural processes integrating the body and the environment. Birdsong production is a widely studied example of such behavior in which numerous thoracic muscles control respiratory inspiration and expiration: the muscles of the syrinx control syringeal membrane tension, while upper vocal tract morphology controls resonances that modulate the vocal system output. All these muscles have to be coordinated in precise sequences to generate the elaborate vocalizations that characterize an individual's song. Previously we used a low-dimensional description of the biomechanics of birdsong production to investigate the associated neural codes, an approach that complements traditional spectrographic analysis. The prior study used algorithmic yet manual procedures to model singing behavior. In the present work, we present an automatic procedure to extract low-dimensional motor gestures that could predict vocal behavior. We recorded zebra finch songs and generated synthetic copies automatically, using a biomechanical model for the vocal apparatus and vocal tract. This dynamical model described song as a sequence of physiological parameters the birds control during singing. To validate this procedure, we recorded electrophysiological activity of the telencephalic nucleus HVC. HVC neurons were highly selective to the auditory presentation of the bird's own song (BOS) and gave similar selective responses to the automatically generated synthetic model of song (AUTO). Our results demonstrate meaningful dimensionality reduction in terms of physiological parameters that individual birds could actually control. Furthermore, this methodology can be extended to other vocal systems to study fine motor control. © 2015 the American Physiological Society. Fil:Amador, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2015 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00223077_v114_n5_p2912_Boari http://hdl.handle.net/20.500.12110/paper_00223077_v114_n5_p2912_Boari |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Bird’s own song Dynamical systems Modeling software Peripheral vocal production model Vocal learning animal experiment Article automation biomechanics breathing muscle dynamics electrophysiology gesture male morphology motor control nonhuman priority journal Taeniopygia guttata telencephalon vocal cord vocalization action potential animal animal structures automated pattern recognition biological model computer simulation finch high vocal center nerve cell physiology procedures sound sound detection trachea vocalization Action Potentials Animal Structures Animals Computer Simulation Finches High Vocal Center Models, Neurological Neurons Pattern Recognition, Automated Sound Sound Spectrography Trachea Vocalization, Animal |
| spellingShingle |
Bird’s own song Dynamical systems Modeling software Peripheral vocal production model Vocal learning animal experiment Article automation biomechanics breathing muscle dynamics electrophysiology gesture male morphology motor control nonhuman priority journal Taeniopygia guttata telencephalon vocal cord vocalization action potential animal animal structures automated pattern recognition biological model computer simulation finch high vocal center nerve cell physiology procedures sound sound detection trachea vocalization Action Potentials Animal Structures Animals Computer Simulation Finches High Vocal Center Models, Neurological Neurons Pattern Recognition, Automated Sound Sound Spectrography Trachea Vocalization, Animal Amador, Ana Automatic reconstruction of physiological gestures used in a model of birdsong production |
| topic_facet |
Bird’s own song Dynamical systems Modeling software Peripheral vocal production model Vocal learning animal experiment Article automation biomechanics breathing muscle dynamics electrophysiology gesture male morphology motor control nonhuman priority journal Taeniopygia guttata telencephalon vocal cord vocalization action potential animal animal structures automated pattern recognition biological model computer simulation finch high vocal center nerve cell physiology procedures sound sound detection trachea vocalization Action Potentials Animal Structures Animals Computer Simulation Finches High Vocal Center Models, Neurological Neurons Pattern Recognition, Automated Sound Sound Spectrography Trachea Vocalization, Animal |
| description |
Highly coordinated learned behaviors are key to understanding neural processes integrating the body and the environment. Birdsong production is a widely studied example of such behavior in which numerous thoracic muscles control respiratory inspiration and expiration: the muscles of the syrinx control syringeal membrane tension, while upper vocal tract morphology controls resonances that modulate the vocal system output. All these muscles have to be coordinated in precise sequences to generate the elaborate vocalizations that characterize an individual's song. Previously we used a low-dimensional description of the biomechanics of birdsong production to investigate the associated neural codes, an approach that complements traditional spectrographic analysis. The prior study used algorithmic yet manual procedures to model singing behavior. In the present work, we present an automatic procedure to extract low-dimensional motor gestures that could predict vocal behavior. We recorded zebra finch songs and generated synthetic copies automatically, using a biomechanical model for the vocal apparatus and vocal tract. This dynamical model described song as a sequence of physiological parameters the birds control during singing. To validate this procedure, we recorded electrophysiological activity of the telencephalic nucleus HVC. HVC neurons were highly selective to the auditory presentation of the bird's own song (BOS) and gave similar selective responses to the automatically generated synthetic model of song (AUTO). Our results demonstrate meaningful dimensionality reduction in terms of physiological parameters that individual birds could actually control. Furthermore, this methodology can be extended to other vocal systems to study fine motor control. © 2015 the American Physiological Society. |
| author |
Amador, Ana |
| author_facet |
Amador, Ana |
| author_sort |
Amador, Ana |
| title |
Automatic reconstruction of physiological gestures used in a model of birdsong production |
| title_short |
Automatic reconstruction of physiological gestures used in a model of birdsong production |
| title_full |
Automatic reconstruction of physiological gestures used in a model of birdsong production |
| title_fullStr |
Automatic reconstruction of physiological gestures used in a model of birdsong production |
| title_full_unstemmed |
Automatic reconstruction of physiological gestures used in a model of birdsong production |
| title_sort |
automatic reconstruction of physiological gestures used in a model of birdsong production |
| publishDate |
2015 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00223077_v114_n5_p2912_Boari http://hdl.handle.net/20.500.12110/paper_00223077_v114_n5_p2912_Boari |
| work_keys_str_mv |
AT amadorana automaticreconstructionofphysiologicalgesturesusedinamodelofbirdsongproduction |
| _version_ |
1768541644550832128 |