Quantitative estimation of the nonstationary behavior of neural spontaneous activity
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFS |
Texto Completo: | https://ri.ufs.br/handle/riufs/1775 |
Resumo: | The “stationarity time” (ST) of neuronal spontaneous activity signals of rat embryonic cortical cells, measured by means of a planar Multielectrode Array (MEA), was estimated based on the “Detrended Fluctuation Analysis” (DFA). The ST is defined as the mean time interval during which the signal under analysis keeps its statistical characteristics constant. An upgrade on the DFA method is proposed, leading to a more accurate procedure. Strong statistical correlation between the ST, estimated from the Absolute Amplitude of Neural Spontaneous Activity (AANSA) signals and the Mean Interburst Interval (MIB), calculated by classical spike sorting methods applied to the interspike interval time series, was obtained. In consequence, the MIB may be estimated by means of the ST, which further includes relevant biological information arising from basal activity. The results point out that the average ST of MEA signals lies between 2-3 seconds. Furthermore, it was shown that a neural culture presents signals that lead to different statistical behaviors, depending on the relative geometric position of each electrode and the cells. Such behaviors may disclose physiological phenomena, which are possibly associated with different adaptation/facilitation mechanisms. |
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Destro Filho, Joao BatistaEstombelo Montesco, Carlos AlbertoMurta Junior, Luiz OtavioMartinoia, SergioChiappalone, MichelaMarques, Suélen MoreiraNeves, Amanda Ferreira2016-05-19T12:58:59Z2016-05-19T12:58:59Z2010DESTRO FILHO, J. B. et al. Quantitative estimation of the nonstationary behavior of neural spontaneous activity. Computational Intelligence and Neuroscience, v. 2010, 2010. Disponível em: <http://www.hindawi.com/journals/cin/2010/785919/>. Acesso em: 19 maio 2016.1687-5273https://ri.ufs.br/handle/riufs/1775Creative Commons Attribution LicenseThe “stationarity time” (ST) of neuronal spontaneous activity signals of rat embryonic cortical cells, measured by means of a planar Multielectrode Array (MEA), was estimated based on the “Detrended Fluctuation Analysis” (DFA). The ST is defined as the mean time interval during which the signal under analysis keeps its statistical characteristics constant. An upgrade on the DFA method is proposed, leading to a more accurate procedure. Strong statistical correlation between the ST, estimated from the Absolute Amplitude of Neural Spontaneous Activity (AANSA) signals and the Mean Interburst Interval (MIB), calculated by classical spike sorting methods applied to the interspike interval time series, was obtained. In consequence, the MIB may be estimated by means of the ST, which further includes relevant biological information arising from basal activity. The results point out that the average ST of MEA signals lies between 2-3 seconds. Furthermore, it was shown that a neural culture presents signals that lead to different statistical behaviors, depending on the relative geometric position of each electrode and the cells. Such behaviors may disclose physiological phenomena, which are possibly associated with different adaptation/facilitation mechanisms.Hindawi Publishing CorporationStationarity timeNeuronal spontaneous activityQuantitative estimation of the nonstationary behavior of neural spontaneous activityinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional da UFSinstname:Universidade Federal de Sergipe (UFS)instacron:UFSinfo:eu-repo/semantics/openAccessTHUMBNAILNonstationaryNeuralActivity.pdf.jpgNonstationaryNeuralActivity.pdf.jpgGenerated Thumbnailimage/jpeg1586https://ri.ufs.br/jspui/bitstream/riufs/1775/4/NonstationaryNeuralActivity.pdf.jpg0ed046db6d73cbaf6cf8e2a4fb7d5fc7MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://ri.ufs.br/jspui/bitstream/riufs/1775/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTNonstationaryNeuralActivity.pdf.txtNonstationaryNeuralActivity.pdf.txtExtracted texttext/plain44629https://ri.ufs.br/jspui/bitstream/riufs/1775/3/NonstationaryNeuralActivity.pdf.txt8afe6bb2164d38a046b5a4f15a257f12MD53ORIGINALNonstationaryNeuralActivity.pdfNonstationaryNeuralActivity.pdfapplication/pdf3678148https://ri.ufs.br/jspui/bitstream/riufs/1775/1/NonstationaryNeuralActivity.pdfb99355fb6fe5ae5b05803d772da712e2MD51riufs/17752016-05-20 02:00:17.876oai:ufs.br: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Repositório InstitucionalPUBhttps://ri.ufs.br/oai/requestrepositorio@academico.ufs.bropendoar:2016-05-20T05:00:17Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS)false |
dc.title.pt_BR.fl_str_mv |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
title |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
spellingShingle |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity Destro Filho, Joao Batista Stationarity time Neuronal spontaneous activity |
title_short |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
title_full |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
title_fullStr |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
title_full_unstemmed |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
title_sort |
Quantitative estimation of the nonstationary behavior of neural spontaneous activity |
author |
Destro Filho, Joao Batista |
author_facet |
Destro Filho, Joao Batista Estombelo Montesco, Carlos Alberto Murta Junior, Luiz Otavio Martinoia, Sergio Chiappalone, Michela Marques, Suélen Moreira Neves, Amanda Ferreira |
author_role |
author |
author2 |
Estombelo Montesco, Carlos Alberto Murta Junior, Luiz Otavio Martinoia, Sergio Chiappalone, Michela Marques, Suélen Moreira Neves, Amanda Ferreira |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Destro Filho, Joao Batista Estombelo Montesco, Carlos Alberto Murta Junior, Luiz Otavio Martinoia, Sergio Chiappalone, Michela Marques, Suélen Moreira Neves, Amanda Ferreira |
dc.subject.por.fl_str_mv |
Stationarity time Neuronal spontaneous activity |
topic |
Stationarity time Neuronal spontaneous activity |
description |
The “stationarity time” (ST) of neuronal spontaneous activity signals of rat embryonic cortical cells, measured by means of a planar Multielectrode Array (MEA), was estimated based on the “Detrended Fluctuation Analysis” (DFA). The ST is defined as the mean time interval during which the signal under analysis keeps its statistical characteristics constant. An upgrade on the DFA method is proposed, leading to a more accurate procedure. Strong statistical correlation between the ST, estimated from the Absolute Amplitude of Neural Spontaneous Activity (AANSA) signals and the Mean Interburst Interval (MIB), calculated by classical spike sorting methods applied to the interspike interval time series, was obtained. In consequence, the MIB may be estimated by means of the ST, which further includes relevant biological information arising from basal activity. The results point out that the average ST of MEA signals lies between 2-3 seconds. Furthermore, it was shown that a neural culture presents signals that lead to different statistical behaviors, depending on the relative geometric position of each electrode and the cells. Such behaviors may disclose physiological phenomena, which are possibly associated with different adaptation/facilitation mechanisms. |
publishDate |
2010 |
dc.date.issued.fl_str_mv |
2010 |
dc.date.accessioned.fl_str_mv |
2016-05-19T12:58:59Z |
dc.date.available.fl_str_mv |
2016-05-19T12:58:59Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
DESTRO FILHO, J. B. et al. Quantitative estimation of the nonstationary behavior of neural spontaneous activity. Computational Intelligence and Neuroscience, v. 2010, 2010. Disponível em: <http://www.hindawi.com/journals/cin/2010/785919/>. Acesso em: 19 maio 2016. |
dc.identifier.uri.fl_str_mv |
https://ri.ufs.br/handle/riufs/1775 |
dc.identifier.issn.none.fl_str_mv |
1687-5273 |
dc.identifier.license.pt_BR.fl_str_mv |
Creative Commons Attribution License |
identifier_str_mv |
DESTRO FILHO, J. B. et al. Quantitative estimation of the nonstationary behavior of neural spontaneous activity. Computational Intelligence and Neuroscience, v. 2010, 2010. Disponível em: <http://www.hindawi.com/journals/cin/2010/785919/>. Acesso em: 19 maio 2016. 1687-5273 Creative Commons Attribution License |
url |
https://ri.ufs.br/handle/riufs/1775 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Hindawi Publishing Corporation |
publisher.none.fl_str_mv |
Hindawi Publishing Corporation |
dc.source.none.fl_str_mv |
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Universidade Federal de Sergipe (UFS) |
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UFS |
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UFS |
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Repositório Institucional da UFS |
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Repositório Institucional da UFS |
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