From signals to music: a bottom-up approach to the structure of neuronal activity

Autores
Noel, Gabriel David; Mugno, Lionel E.; Andres, Daniela Sabrina
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Introduction: The search for the “neural code” has been a fundamental quest in neuroscience, concerned with the way neurons and neuronal systems process and transmit information. However, the term “code” has been mostly used as a metaphor, seldom acknowledging the formal definitions introduced by information theory, and the contributions of linguistics and semiotics not at all. The heuristic potential of the latter was suggested by structuralism, which turned the methods and findings of linguistics to other fields of knowledge. For the study of complex communication systems, such as human language and music, the necessity of an approach that considers multilayered, nested, structured organization of symbols becomes evident. We work under the hypothesis that the neural code might be as complex as these human-made codes. To test this, we propose a bottom-up approach, constructing a symbolic logic in order to translate neuronal signals into music scores. Methods: We recorded single cells’ activity from the rat’s globus pallidus pars interna under conditions of full alertness, blindfoldedness and environmental silence. We analyzed the signals with statistical, spectral, and complex methods, including Fast Fourier Transform, Hurst exponent and recurrence plot analysis. Results: The results indicated complex behavior and recurrence graphs consistent with fractality, and a Hurst exponent >0.5, evidencing temporal persistence. On the whole, these features point toward a complex behavior of the time series analyzed, also present in classical music, which upholds the hypothesis of structural similarities between music and neuronal activity. Furthermore, through our experiment we performed a comparison between music and raw neuronal activity. Our results point to the same conclusion, showing the structures of music and neuronal activity to be homologous. The scores were not only spontaneously tonal, but they exhibited structure and features normally present in human-made musical creations. Discussion: The hypothesis of a structural homology between the neural code and the code of music holds, suggesting that some of the insights introduced by linguistic and semiotic theory might be a useful methodological resource to go beyond the limits set by metaphoric notions of “code.”
Fil: Noel, Gabriel David. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Instituto de Altos Estudios Sociales; Argentina
Fil: Mugno, Lionel E.. Conservatorio "Alfredo Luis Schiuma"; Argentina
Fil: Andres, Daniela Sabrina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Tecnologias Emergentes y Ciencias Aplicadas. - Universidad Nacional de San Martin. Instituto de Tecnologias Emergentes y Ciencias Aplicadas.; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Laboratorio de Neuroingenieria.; Argentina
Materia
FRACTALS
LINGUISTICS
LÉVI-STRAUSS
MUSIC
NEURAL CODE
STRUCTURAL HEARING
STRUCTURALISM
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/215245

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network_name_str CONICET Digital (CONICET)
spelling From signals to music: a bottom-up approach to the structure of neuronal activityNoel, Gabriel DavidMugno, Lionel E.Andres, Daniela SabrinaFRACTALSLINGUISTICSLÉVI-STRAUSSMUSICNEURAL CODESTRUCTURAL HEARINGSTRUCTURALISMhttps://purl.org/becyt/ford/3.5https://purl.org/becyt/ford/3https://purl.org/becyt/ford/5.4https://purl.org/becyt/ford/5https://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Introduction: The search for the “neural code” has been a fundamental quest in neuroscience, concerned with the way neurons and neuronal systems process and transmit information. However, the term “code” has been mostly used as a metaphor, seldom acknowledging the formal definitions introduced by information theory, and the contributions of linguistics and semiotics not at all. The heuristic potential of the latter was suggested by structuralism, which turned the methods and findings of linguistics to other fields of knowledge. For the study of complex communication systems, such as human language and music, the necessity of an approach that considers multilayered, nested, structured organization of symbols becomes evident. We work under the hypothesis that the neural code might be as complex as these human-made codes. To test this, we propose a bottom-up approach, constructing a symbolic logic in order to translate neuronal signals into music scores. Methods: We recorded single cells’ activity from the rat’s globus pallidus pars interna under conditions of full alertness, blindfoldedness and environmental silence. We analyzed the signals with statistical, spectral, and complex methods, including Fast Fourier Transform, Hurst exponent and recurrence plot analysis. Results: The results indicated complex behavior and recurrence graphs consistent with fractality, and a Hurst exponent >0.5, evidencing temporal persistence. On the whole, these features point toward a complex behavior of the time series analyzed, also present in classical music, which upholds the hypothesis of structural similarities between music and neuronal activity. Furthermore, through our experiment we performed a comparison between music and raw neuronal activity. Our results point to the same conclusion, showing the structures of music and neuronal activity to be homologous. The scores were not only spontaneously tonal, but they exhibited structure and features normally present in human-made musical creations. Discussion: The hypothesis of a structural homology between the neural code and the code of music holds, suggesting that some of the insights introduced by linguistic and semiotic theory might be a useful methodological resource to go beyond the limits set by metaphoric notions of “code.”Fil: Noel, Gabriel David. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Instituto de Altos Estudios Sociales; ArgentinaFil: Mugno, Lionel E.. Conservatorio "Alfredo Luis Schiuma"; ArgentinaFil: Andres, Daniela Sabrina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Tecnologias Emergentes y Ciencias Aplicadas. - Universidad Nacional de San Martin. Instituto de Tecnologias Emergentes y Ciencias Aplicadas.; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Laboratorio de Neuroingenieria.; ArgentinaFrontiers Media2023-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/215245Noel, Gabriel David; Mugno, Lionel E.; Andres, Daniela Sabrina; From signals to music: a bottom-up approach to the structure of neuronal activity; Frontiers Media; Frontiers in Systems Neuroscience; 17; 8-2023; 1-91662-5137CONICET DigitalCONICETenghttps://ri.conicet.gov.ar/handle/11336/215244info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnsys.2023.1171984/fullinfo:eu-repo/semantics/altIdentifier/doi/10.3389/fnsys.2023.1171984info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:33:41Zoai:ri.conicet.gov.ar:11336/215245instacron: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 11:33:41.958CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv From signals to music: a bottom-up approach to the structure of neuronal activity
title From signals to music: a bottom-up approach to the structure of neuronal activity
spellingShingle From signals to music: a bottom-up approach to the structure of neuronal activity
Noel, Gabriel David
FRACTALS
LINGUISTICS
LÉVI-STRAUSS
MUSIC
NEURAL CODE
STRUCTURAL HEARING
STRUCTURALISM
title_short From signals to music: a bottom-up approach to the structure of neuronal activity
title_full From signals to music: a bottom-up approach to the structure of neuronal activity
title_fullStr From signals to music: a bottom-up approach to the structure of neuronal activity
title_full_unstemmed From signals to music: a bottom-up approach to the structure of neuronal activity
title_sort From signals to music: a bottom-up approach to the structure of neuronal activity
dc.creator.none.fl_str_mv Noel, Gabriel David
Mugno, Lionel E.
Andres, Daniela Sabrina
author Noel, Gabriel David
author_facet Noel, Gabriel David
Mugno, Lionel E.
Andres, Daniela Sabrina
author_role author
author2 Mugno, Lionel E.
Andres, Daniela Sabrina
author2_role author
author
dc.subject.none.fl_str_mv FRACTALS
LINGUISTICS
LÉVI-STRAUSS
MUSIC
NEURAL CODE
STRUCTURAL HEARING
STRUCTURALISM
topic FRACTALS
LINGUISTICS
LÉVI-STRAUSS
MUSIC
NEURAL CODE
STRUCTURAL HEARING
STRUCTURALISM
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.5
https://purl.org/becyt/ford/3
https://purl.org/becyt/ford/5.4
https://purl.org/becyt/ford/5
https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Introduction: The search for the “neural code” has been a fundamental quest in neuroscience, concerned with the way neurons and neuronal systems process and transmit information. However, the term “code” has been mostly used as a metaphor, seldom acknowledging the formal definitions introduced by information theory, and the contributions of linguistics and semiotics not at all. The heuristic potential of the latter was suggested by structuralism, which turned the methods and findings of linguistics to other fields of knowledge. For the study of complex communication systems, such as human language and music, the necessity of an approach that considers multilayered, nested, structured organization of symbols becomes evident. We work under the hypothesis that the neural code might be as complex as these human-made codes. To test this, we propose a bottom-up approach, constructing a symbolic logic in order to translate neuronal signals into music scores. Methods: We recorded single cells’ activity from the rat’s globus pallidus pars interna under conditions of full alertness, blindfoldedness and environmental silence. We analyzed the signals with statistical, spectral, and complex methods, including Fast Fourier Transform, Hurst exponent and recurrence plot analysis. Results: The results indicated complex behavior and recurrence graphs consistent with fractality, and a Hurst exponent >0.5, evidencing temporal persistence. On the whole, these features point toward a complex behavior of the time series analyzed, also present in classical music, which upholds the hypothesis of structural similarities between music and neuronal activity. Furthermore, through our experiment we performed a comparison between music and raw neuronal activity. Our results point to the same conclusion, showing the structures of music and neuronal activity to be homologous. The scores were not only spontaneously tonal, but they exhibited structure and features normally present in human-made musical creations. Discussion: The hypothesis of a structural homology between the neural code and the code of music holds, suggesting that some of the insights introduced by linguistic and semiotic theory might be a useful methodological resource to go beyond the limits set by metaphoric notions of “code.”
Fil: Noel, Gabriel David. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Martín. Instituto de Altos Estudios Sociales; Argentina
Fil: Mugno, Lionel E.. Conservatorio "Alfredo Luis Schiuma"; Argentina
Fil: Andres, Daniela Sabrina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Tecnologias Emergentes y Ciencias Aplicadas. - Universidad Nacional de San Martin. Instituto de Tecnologias Emergentes y Ciencias Aplicadas.; Argentina. Universidad Nacional de San Martin. Escuela de Ciencia y Tecnologia. Laboratorio de Neuroingenieria.; Argentina
description Introduction: The search for the “neural code” has been a fundamental quest in neuroscience, concerned with the way neurons and neuronal systems process and transmit information. However, the term “code” has been mostly used as a metaphor, seldom acknowledging the formal definitions introduced by information theory, and the contributions of linguistics and semiotics not at all. The heuristic potential of the latter was suggested by structuralism, which turned the methods and findings of linguistics to other fields of knowledge. For the study of complex communication systems, such as human language and music, the necessity of an approach that considers multilayered, nested, structured organization of symbols becomes evident. We work under the hypothesis that the neural code might be as complex as these human-made codes. To test this, we propose a bottom-up approach, constructing a symbolic logic in order to translate neuronal signals into music scores. Methods: We recorded single cells’ activity from the rat’s globus pallidus pars interna under conditions of full alertness, blindfoldedness and environmental silence. We analyzed the signals with statistical, spectral, and complex methods, including Fast Fourier Transform, Hurst exponent and recurrence plot analysis. Results: The results indicated complex behavior and recurrence graphs consistent with fractality, and a Hurst exponent >0.5, evidencing temporal persistence. On the whole, these features point toward a complex behavior of the time series analyzed, also present in classical music, which upholds the hypothesis of structural similarities between music and neuronal activity. Furthermore, through our experiment we performed a comparison between music and raw neuronal activity. Our results point to the same conclusion, showing the structures of music and neuronal activity to be homologous. The scores were not only spontaneously tonal, but they exhibited structure and features normally present in human-made musical creations. Discussion: The hypothesis of a structural homology between the neural code and the code of music holds, suggesting that some of the insights introduced by linguistic and semiotic theory might be a useful methodological resource to go beyond the limits set by metaphoric notions of “code.”
publishDate 2023
dc.date.none.fl_str_mv 2023-08
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/11336/215245
Noel, Gabriel David; Mugno, Lionel E.; Andres, Daniela Sabrina; From signals to music: a bottom-up approach to the structure of neuronal activity; Frontiers Media; Frontiers in Systems Neuroscience; 17; 8-2023; 1-9
1662-5137
CONICET Digital
CONICET
url http://hdl.handle.net/11336/215245
identifier_str_mv Noel, Gabriel David; Mugno, Lionel E.; Andres, Daniela Sabrina; From signals to music: a bottom-up approach to the structure of neuronal activity; Frontiers Media; Frontiers in Systems Neuroscience; 17; 8-2023; 1-9
1662-5137
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://ri.conicet.gov.ar/handle/11336/215244
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fnsys.2023.1171984/full
info:eu-repo/semantics/altIdentifier/doi/10.3389/fnsys.2023.1171984
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
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dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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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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