Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy?
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/jspui/handle/123456789/23219 |
Resumo: | Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy. |
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Onias, HeloisaViol, AlinePalhano-Fontes, FernandaAndrade, Katia C.Sturzbecher, MarcioViswanathan, GandhimohanAraújo, Dráulio Barros de2017-05-30T13:00:27Z2017-05-30T13:00:27Z2014https://repositorio.ufrn.br/jspui/handle/123456789/2321910.1016/j.yebeh.2013.11.019engComplex networkGraphfMRIResting stateEpilepsyBrain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy?info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFunctional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALBrain complex network analysis by means of resting state fMRI.pdfBrain complex network analysis by means of resting state fMRI.pdfDraulioAraujo_ICe_Brain complex network analysis_2014application/pdf1812436https://repositorio.ufrn.br/bitstream/123456789/23219/1/Brain%20complex%20network%20analysis%20by%20means%20of%20resting%20state%20fMRI.pdfb27de561a10e7b7a2b79ae73f18de2f5MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/23219/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTBrain complex network analysis by means of resting state fMRI.pdf.txtBrain complex network analysis by means of resting state fMRI.pdf.txtExtracted texttext/plain46652https://repositorio.ufrn.br/bitstream/123456789/23219/5/Brain%20complex%20network%20analysis%20by%20means%20of%20resting%20state%20fMRI.pdf.txt4a44c621f77c374fb60683f21a450734MD55THUMBNAILBrain complex network analysis by means of resting state fMRI.pdf.jpgBrain complex network analysis by means of resting state fMRI.pdf.jpgIM Thumbnailimage/jpeg11862https://repositorio.ufrn.br/bitstream/123456789/23219/6/Brain%20complex%20network%20analysis%20by%20means%20of%20resting%20state%20fMRI.pdf.jpg085eecffccad5926b6b37eb2bf263a29MD56123456789/232192021-07-08 15:39:00.177oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-07-08T18:39Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
title |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
spellingShingle |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? Onias, Heloisa Complex network Graph fMRI Resting state Epilepsy |
title_short |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
title_full |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
title_fullStr |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
title_full_unstemmed |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
title_sort |
Brain complex network analysis by means of resting state fMRI and graph analysis: Will it be helpful in clinical epilepsy? |
author |
Onias, Heloisa |
author_facet |
Onias, Heloisa Viol, Aline Palhano-Fontes, Fernanda Andrade, Katia C. Sturzbecher, Marcio Viswanathan, Gandhimohan Araújo, Dráulio Barros de |
author_role |
author |
author2 |
Viol, Aline Palhano-Fontes, Fernanda Andrade, Katia C. Sturzbecher, Marcio Viswanathan, Gandhimohan Araújo, Dráulio Barros de |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Onias, Heloisa Viol, Aline Palhano-Fontes, Fernanda Andrade, Katia C. Sturzbecher, Marcio Viswanathan, Gandhimohan Araújo, Dráulio Barros de |
dc.subject.por.fl_str_mv |
Complex network Graph fMRI Resting state Epilepsy |
topic |
Complex network Graph fMRI Resting state Epilepsy |
description |
Functional magnetic resonance imaging (fMRI) has just completed 20 years of existence. It currently serves as a research tool in a broad range of human brain studies in normal and pathological conditions, as is the case of epilepsy. To date, most fMRI studies aimed at characterizing brain activity in response to various active paradigms. More recently, a number of strategies have been used to characterize the low-frequency oscillations of the ongoing fMRI signals when individuals are at rest. These datasets have been largely analyzed in the context of functional connectivity, which inspects the covariance of fMRI signals from different areas of the brain. In addition, resting state fMRI is progressively being used to evaluate complex network features of the brain. These strategies have been applied to a number of different problems in neuroscience, which include diseases such as Alzheimer's, schizophrenia, and epilepsy. Hence, we herein aimed at introducing the subject of complex network and how to use it for the analysis of fMRI data. This appears to be a promising strategy to be used in clinical epilepsy. Therefore, we also review the recent literature that has applied these ideas to the analysis of fMRI data in patients with epilepsy. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2017-05-30T13:00:27Z |
dc.date.available.fl_str_mv |
2017-05-30T13:00:27Z |
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.uri.fl_str_mv |
https://repositorio.ufrn.br/jspui/handle/123456789/23219 |
dc.identifier.doi.none.fl_str_mv |
10.1016/j.yebeh.2013.11.019 |
url |
https://repositorio.ufrn.br/jspui/handle/123456789/23219 |
identifier_str_mv |
10.1016/j.yebeh.2013.11.019 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
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UFRN |
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Repositório Institucional da UFRN |
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