Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data
- Autores
- Guisande, Natalí; Pallares Di Nunzio, Monserrat; Martinez, Nataniel; Rosso, Osvaldo Aníbal; Montani, Fernando Fabián
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- In this study, the Hénon map was analyzed using quantifiers from information theory in order to compare its dynamics to experimental data from brain regions known to exhibit chaotic behavior. The goal was to investigate the potential of the Hénon map as a model for replicating chaotic brain dynamics in the treatment of Parkinson’s and epilepsy patients. The dynamic properties of the Hénon map were compared with data from the subthalamic nucleus, the medial frontal cortex, and a q-DG model of neuronal input–output with easy numerical implementation to simulate the local behavior of a population. Using information theory tools, Shannon entropy, statistical complexity, and Fisher’s information were analyzed, taking into account the causality of the time series. For this purpose, different windows over the time series were considered. The findings revealed that neither the Hénon map nor the q-DG model could perfectly replicate the dynamics of the brain regions studied. However, with careful consideration of the parameters, scales, and sampling used, they were able to model some characteristics of neural activity. According to these results, normal neural dynamics in the subthalamic nucleus region may present a more complex spectrum within the complexity–entropy causality plane that cannot be represented by chaotic models alone. The dynamic behavior observed in these systems using these tools is highly dependent on the studied temporal scale. As the size of the sample studied increases, the dynamics of the Hénon map become increasingly different from those of biological and artificial neural systems.
Instituto de Física La Plata - Materia
-
Física
Hénon map
q-DG model of neuronal input–output
Shannon entropy
dynamic behavior
neurophysiological signals
complex spectrumof dynamical characteristics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/160848
Ver los metadatos del registro completo
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Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological dataGuisande, NatalíPallares Di Nunzio, MonserratMartinez, NatanielRosso, Osvaldo AníbalMontani, Fernando FabiánFísicaHénon mapq-DG model of neuronal input–outputShannon entropydynamic behaviorneurophysiological signalscomplex spectrumof dynamical characteristicsIn this study, the Hénon map was analyzed using quantifiers from information theory in order to compare its dynamics to experimental data from brain regions known to exhibit chaotic behavior. The goal was to investigate the potential of the Hénon map as a model for replicating chaotic brain dynamics in the treatment of Parkinson’s and epilepsy patients. The dynamic properties of the Hénon map were compared with data from the subthalamic nucleus, the medial frontal cortex, and a q-DG model of neuronal input–output with easy numerical implementation to simulate the local behavior of a population. Using information theory tools, Shannon entropy, statistical complexity, and Fisher’s information were analyzed, taking into account the causality of the time series. For this purpose, different windows over the time series were considered. The findings revealed that neither the Hénon map nor the q-DG model could perfectly replicate the dynamics of the brain regions studied. However, with careful consideration of the parameters, scales, and sampling used, they were able to model some characteristics of neural activity. According to these results, normal neural dynamics in the subthalamic nucleus region may present a more complex spectrum within the complexity–entropy causality plane that cannot be represented by chaotic models alone. The dynamic behavior observed in these systems using these tools is highly dependent on the studied temporal scale. As the size of the sample studied increases, the dynamics of the Hénon map become increasingly different from those of biological and artificial neural systems.Instituto de Física La Plata2023-04-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/160848enginfo:eu-repo/semantics/altIdentifier/issn/1089-7682info:eu-repo/semantics/altIdentifier/doi/10.1063/5.0142773info: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:UNLP2025-09-29T11:42:01Zoai:sedici.unlp.edu.ar:10915/160848Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:42:01.654SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
title |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
spellingShingle |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data Guisande, Natalí Física Hénon map q-DG model of neuronal input–output Shannon entropy dynamic behavior neurophysiological signals complex spectrumof dynamical characteristics |
title_short |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
title_full |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
title_fullStr |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
title_full_unstemmed |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
title_sort |
Chaotic dynamics of the Hénon map and neuronal input–output: A comparison with neurophysiological data |
dc.creator.none.fl_str_mv |
Guisande, Natalí Pallares Di Nunzio, Monserrat Martinez, Nataniel Rosso, Osvaldo Aníbal Montani, Fernando Fabián |
author |
Guisande, Natalí |
author_facet |
Guisande, Natalí Pallares Di Nunzio, Monserrat Martinez, Nataniel Rosso, Osvaldo Aníbal Montani, Fernando Fabián |
author_role |
author |
author2 |
Pallares Di Nunzio, Monserrat Martinez, Nataniel Rosso, Osvaldo Aníbal Montani, Fernando Fabián |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Física Hénon map q-DG model of neuronal input–output Shannon entropy dynamic behavior neurophysiological signals complex spectrumof dynamical characteristics |
topic |
Física Hénon map q-DG model of neuronal input–output Shannon entropy dynamic behavior neurophysiological signals complex spectrumof dynamical characteristics |
dc.description.none.fl_txt_mv |
In this study, the Hénon map was analyzed using quantifiers from information theory in order to compare its dynamics to experimental data from brain regions known to exhibit chaotic behavior. The goal was to investigate the potential of the Hénon map as a model for replicating chaotic brain dynamics in the treatment of Parkinson’s and epilepsy patients. The dynamic properties of the Hénon map were compared with data from the subthalamic nucleus, the medial frontal cortex, and a q-DG model of neuronal input–output with easy numerical implementation to simulate the local behavior of a population. Using information theory tools, Shannon entropy, statistical complexity, and Fisher’s information were analyzed, taking into account the causality of the time series. For this purpose, different windows over the time series were considered. The findings revealed that neither the Hénon map nor the q-DG model could perfectly replicate the dynamics of the brain regions studied. However, with careful consideration of the parameters, scales, and sampling used, they were able to model some characteristics of neural activity. According to these results, normal neural dynamics in the subthalamic nucleus region may present a more complex spectrum within the complexity–entropy causality plane that cannot be represented by chaotic models alone. The dynamic behavior observed in these systems using these tools is highly dependent on the studied temporal scale. As the size of the sample studied increases, the dynamics of the Hénon map become increasingly different from those of biological and artificial neural systems. Instituto de Física La Plata |
description |
In this study, the Hénon map was analyzed using quantifiers from information theory in order to compare its dynamics to experimental data from brain regions known to exhibit chaotic behavior. The goal was to investigate the potential of the Hénon map as a model for replicating chaotic brain dynamics in the treatment of Parkinson’s and epilepsy patients. The dynamic properties of the Hénon map were compared with data from the subthalamic nucleus, the medial frontal cortex, and a q-DG model of neuronal input–output with easy numerical implementation to simulate the local behavior of a population. Using information theory tools, Shannon entropy, statistical complexity, and Fisher’s information were analyzed, taking into account the causality of the time series. For this purpose, different windows over the time series were considered. The findings revealed that neither the Hénon map nor the q-DG model could perfectly replicate the dynamics of the brain regions studied. However, with careful consideration of the parameters, scales, and sampling used, they were able to model some characteristics of neural activity. According to these results, normal neural dynamics in the subthalamic nucleus region may present a more complex spectrum within the complexity–entropy causality plane that cannot be represented by chaotic models alone. The dynamic behavior observed in these systems using these tools is highly dependent on the studied temporal scale. As the size of the sample studied increases, the dynamics of the Hénon map become increasingly different from those of biological and artificial neural systems. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-03 |
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 |
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article |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/160848 |
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http://sedici.unlp.edu.ar/handle/10915/160848 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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openAccess |
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