Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks

Autores
Baravalle, Román; Rosso, Osvaldo Aníbal; Montani, Fernando Fabián
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Electroencephalography (EEG) signals depict the electrical activity that take place at the surface of the brain, and provide an important tool for understanding a variety of cognitive processes. The EEG are the product of synchronized activity of the brain and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects performs a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane H x C, where the enhanced complexity in the gamma 1, gamma 2 and beta 1 bands allow us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2 and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, while in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that corresponds to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks.
Instituto de Física de Líquidos y Sistemas Biológicos
Materia
Física
Electroencephalography
Cognitive processes
Rhythmic oscillations
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/97725

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spelling Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasksBaravalle, RománRosso, Osvaldo AníbalMontani, Fernando FabiánFísicaElectroencephalographyCognitive processesRhythmic oscillationsElectroencephalography (EEG) signals depict the electrical activity that take place at the surface of the brain, and provide an important tool for understanding a variety of cognitive processes. The EEG are the product of synchronized activity of the brain and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects performs a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane H x C, where the enhanced complexity in the gamma 1, gamma 2 and beta 1 bands allow us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2 and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, while in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that corresponds to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks.Instituto de Física de Líquidos y Sistemas Biológicos2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf75513-75531http://sedici.unlp.edu.ar/handle/10915/97725enginfo:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/87939info:eu-repo/semantics/altIdentifier/url/https://aip.scitation.org/doi/abs/10.1063/1.5025187info:eu-repo/semantics/altIdentifier/issn/1054-1500info:eu-repo/semantics/altIdentifier/doi/10.1063/1.5025187info:eu-repo/semantics/altIdentifier/hdl/11336/87939info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:20:31Zoai:sedici.unlp.edu.ar:10915/97725Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:20:32.145SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
title Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
spellingShingle Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
Baravalle, Román
Física
Electroencephalography
Cognitive processes
Rhythmic oscillations
title_short Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
title_full Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
title_fullStr Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
title_full_unstemmed Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
title_sort Rhythmic activities of the brain: quantifying the high complexity of beta and gamma oscillations during visuomotor tasks
dc.creator.none.fl_str_mv Baravalle, Román
Rosso, Osvaldo Aníbal
Montani, Fernando Fabián
author Baravalle, Román
author_facet Baravalle, Román
Rosso, Osvaldo Aníbal
Montani, Fernando Fabián
author_role author
author2 Rosso, Osvaldo Aníbal
Montani, Fernando Fabián
author2_role author
author
dc.subject.none.fl_str_mv Física
Electroencephalography
Cognitive processes
Rhythmic oscillations
topic Física
Electroencephalography
Cognitive processes
Rhythmic oscillations
dc.description.none.fl_txt_mv Electroencephalography (EEG) signals depict the electrical activity that take place at the surface of the brain, and provide an important tool for understanding a variety of cognitive processes. The EEG are the product of synchronized activity of the brain and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects performs a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane H x C, where the enhanced complexity in the gamma 1, gamma 2 and beta 1 bands allow us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2 and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, while in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that corresponds to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks.
Instituto de Física de Líquidos y Sistemas Biológicos
description Electroencephalography (EEG) signals depict the electrical activity that take place at the surface of the brain, and provide an important tool for understanding a variety of cognitive processes. The EEG are the product of synchronized activity of the brain and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects performs a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane H x C, where the enhanced complexity in the gamma 1, gamma 2 and beta 1 bands allow us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2 and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, while in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that corresponds to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/97725
url http://sedici.unlp.edu.ar/handle/10915/97725
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/87939
info:eu-repo/semantics/altIdentifier/url/https://aip.scitation.org/doi/abs/10.1063/1.5025187
info:eu-repo/semantics/altIdentifier/issn/1054-1500
info:eu-repo/semantics/altIdentifier/doi/10.1063/1.5025187
info:eu-repo/semantics/altIdentifier/hdl/11336/87939
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
75513-75531
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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