Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates
In the adult brain, it is well known that increases in local neural activity trigger changes in regional blood flow and, thus, changes in cerebral energy metabolism. This regulation mechanism is called neurovascular coupling (NVC). It is not yet clear to what extent this mechanism is present in the...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/28884
- Acceso en línea:
- https://doi.org/10.1007/978-3-030-34461-0_2
https://repository.urosario.edu.co/handle/10336/28884
- Palabra clave:
- Neurometabolic Coupling (NMC)
Transfer Entropy (TE)
EEG
NIRS
Premature Neonates
- Rights
- License
- Restringido (Acceso a grupos específicos)
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14139512600a78c0c92-7a49-43a9-b9a6-9891fe5a2da7-155320cda-97a5-498e-9555-cec06026ceda-1030b734f-9329-40c5-99ee-278c8db6925d-1373c77e3-5093-43fd-831b-0db88cefa50d-1a3aaad06-8ea7-431a-890f-bbab1341f9cb-12020-08-28T15:50:00Z2020-08-28T15:50:00Z2020-01-01In the adult brain, it is well known that increases in local neural activity trigger changes in regional blood flow and, thus, changes in cerebral energy metabolism. This regulation mechanism is called neurovascular coupling (NVC). It is not yet clear to what extent this mechanism is present in the premature brain. In this study, we explore the use of transfer entropy (TE) in order to compute the nonlinear coupling between changes in brain function, assessed by means of EEG, and changes in brain oxygenation, assessed by means of near-infrared spectroscopy (NIRS). In a previous study, we measured the coupling between both variables using a linear model to compute TE. The results indicated that changes in brain oxygenation were likely to precede changes in EEG activity. However, using a nonlinear and nonparametric approach to compute TE, the results indicate an opposite directionality of this coupling. The source of the different results provided by the linear and nonlinear TE is unclear and needs further research. In this study, we present the results from a cohort of 21 premature neonates. Results indicate that TE values computed using the nonlinear approach are able to discriminate between neonates with brain abnormalities and healthy neonates, indicating a less functional NVC in neonates with brain abnormalities. Keywordsapplication/pdfhttps://doi.org/10.1007/978-3-030-34461-0_2ISBN: 978-1-4419-7755-7https://repository.urosario.edu.co/handle/10336/28884engspringer Nature1711Advances in Experimental Medicine and BiologyVol. 1232Advances in Experimental Medicine and Biology, ISBN: 978-1-4419-7755-7, Vol.1232 (2020); pp. 11-17https://link.springer.com/chapter/10.1007/978-3-030-34461-0_2Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecAdvances in Experimental Medicine and Biologyinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURNeurometabolic Coupling (NMC)Transfer Entropy (TE)EEGNIRSPremature NeonatesNonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature NeonatesEntropía de transferencia no lineal para evaluar el acoplamiento neurovascular en recién nacidos prematurosbookPartParte de librohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_3248Caicedo Dorado, AlexanderThewissen, LiesbethNaulaers, GunnarSmits, AnneVan Huffel. SabineAllegaert, Karel10336/28884oai:repository.urosario.edu.co:10336/288842021-06-03 00:49:42.73https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
dc.title.TranslatedTitle.spa.fl_str_mv |
Entropía de transferencia no lineal para evaluar el acoplamiento neurovascular en recién nacidos prematuros |
title |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
spellingShingle |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates Neurometabolic Coupling (NMC) Transfer Entropy (TE) EEG NIRS Premature Neonates |
title_short |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
title_full |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
title_fullStr |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
title_full_unstemmed |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
title_sort |
Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates |
dc.subject.keyword.spa.fl_str_mv |
Neurometabolic Coupling (NMC) Transfer Entropy (TE) EEG NIRS Premature Neonates |
topic |
Neurometabolic Coupling (NMC) Transfer Entropy (TE) EEG NIRS Premature Neonates |
description |
In the adult brain, it is well known that increases in local neural activity trigger changes in regional blood flow and, thus, changes in cerebral energy metabolism. This regulation mechanism is called neurovascular coupling (NVC). It is not yet clear to what extent this mechanism is present in the premature brain. In this study, we explore the use of transfer entropy (TE) in order to compute the nonlinear coupling between changes in brain function, assessed by means of EEG, and changes in brain oxygenation, assessed by means of near-infrared spectroscopy (NIRS). In a previous study, we measured the coupling between both variables using a linear model to compute TE. The results indicated that changes in brain oxygenation were likely to precede changes in EEG activity. However, using a nonlinear and nonparametric approach to compute TE, the results indicate an opposite directionality of this coupling. The source of the different results provided by the linear and nonlinear TE is unclear and needs further research. In this study, we present the results from a cohort of 21 premature neonates. Results indicate that TE values computed using the nonlinear approach are able to discriminate between neonates with brain abnormalities and healthy neonates, indicating a less functional NVC in neonates with brain abnormalities. Keywords |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-08-28T15:50:00Z |
dc.date.available.none.fl_str_mv |
2020-08-28T15:50:00Z |
dc.date.created.spa.fl_str_mv |
2020-01-01 |
dc.type.eng.fl_str_mv |
bookPart |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_3248 |
dc.type.spa.spa.fl_str_mv |
Parte de libro |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1007/978-3-030-34461-0_2 |
dc.identifier.issn.none.fl_str_mv |
ISBN: 978-1-4419-7755-7 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/28884 |
url |
https://doi.org/10.1007/978-3-030-34461-0_2 https://repository.urosario.edu.co/handle/10336/28884 |
identifier_str_mv |
ISBN: 978-1-4419-7755-7 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
17 |
dc.relation.citationStartPage.none.fl_str_mv |
11 |
dc.relation.citationTitle.none.fl_str_mv |
Advances in Experimental Medicine and Biology |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 1232 |
dc.relation.ispartof.spa.fl_str_mv |
Advances in Experimental Medicine and Biology, ISBN: 978-1-4419-7755-7, Vol.1232 (2020); pp. 11-17 |
dc.relation.uri.spa.fl_str_mv |
https://link.springer.com/chapter/10.1007/978-3-030-34461-0_2 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.acceso.spa.fl_str_mv |
Restringido (Acceso a grupos específicos) |
rights_invalid_str_mv |
Restringido (Acceso a grupos específicos) http://purl.org/coar/access_right/c_16ec |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
springer Nature |
dc.source.spa.fl_str_mv |
Advances in Experimental Medicine and Biology |
institution |
Universidad del Rosario |
dc.source.instname.none.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.none.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167460763402240 |