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

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 in...

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Autores principales: Noel, Gabriel D., Mugno, Lionel E., Andres, Daniela S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450627/
https://www.ncbi.nlm.nih.gov/pubmed/37637704
http://dx.doi.org/10.3389/fnsys.2023.1171984
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author Noel, Gabriel D.
Mugno, Lionel E.
Andres, Daniela S.
author_facet Noel, Gabriel D.
Mugno, Lionel E.
Andres, Daniela S.
author_sort Noel, Gabriel D.
collection PubMed
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.”
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spelling pubmed-104506272023-08-26 From signals to music: a bottom-up approach to the structure of neuronal activity Noel, Gabriel D. Mugno, Lionel E. Andres, Daniela S. Front Syst Neurosci Neuroscience 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.” Frontiers Media S.A. 2023-08-11 /pmc/articles/PMC10450627/ /pubmed/37637704 http://dx.doi.org/10.3389/fnsys.2023.1171984 Text en Copyright © 2023 Noel, Mugno and Andres. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Noel, Gabriel D.
Mugno, Lionel E.
Andres, Daniela S.
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
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_short 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
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450627/
https://www.ncbi.nlm.nih.gov/pubmed/37637704
http://dx.doi.org/10.3389/fnsys.2023.1171984
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