Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study
Q1
- Autores:
-
Moguilner, Sebastian
García, Adolfo M.
Sanz Perl, Yonatan
Tagliazucchi, Enzo
Piguet, Olivier
Kumfor, Fiona
Reyes, Pablo
Matallana-Eslava, Diana L.
Sedeño, Lucas
Ibáñez, Agustín
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2021
- Institución:
- Pontificia Universidad Javeriana
- Repositorio:
- Repositorio Universidad Javeriana
- Idioma:
- eng
- OAI Identifier:
- oai:repository.javeriana.edu.co:10554/53642
- Acceso en línea:
- https://login.ezproxy.javeriana.edu.co/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1053811920310077&lang=es&site=eds-live
http://hdl.handle.net/10554/53642
https://doi.org/10.1016/j.neuroimage.2020.117522
- Palabra clave:
- Dynamic functional connectivity
AD
bvFTD
fMRI resting-state connectivity
Copula-based dependence measure
- Rights
- License
- Atribución-NoComercial 4.0 Internacional
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|
dc.title.spa.fl_str_mv |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
title |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
spellingShingle |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study Dynamic functional connectivity AD bvFTD fMRI resting-state connectivity Copula-based dependence measure |
title_short |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
title_full |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
title_fullStr |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
title_full_unstemmed |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
title_sort |
Dynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter study |
dc.creator.fl_str_mv |
Moguilner, Sebastian García, Adolfo M. Sanz Perl, Yonatan Tagliazucchi, Enzo Piguet, Olivier Kumfor, Fiona Reyes, Pablo Matallana-Eslava, Diana L. Sedeño, Lucas Ibáñez, Agustín |
dc.contributor.author.none.fl_str_mv |
Moguilner, Sebastian García, Adolfo M. Sanz Perl, Yonatan Tagliazucchi, Enzo Piguet, Olivier Kumfor, Fiona Reyes, Pablo Matallana-Eslava, Diana L. Sedeño, Lucas Ibáñez, Agustín |
dc.contributor.corporatename.none.fl_str_mv |
Pontificia Universidad Javeriana. Facultad de Medicina. Instituto de Envejecimiento |
dc.subject.keyword.spa.fl_str_mv |
Dynamic functional connectivity AD bvFTD fMRI resting-state connectivity Copula-based dependence measure |
topic |
Dynamic functional connectivity AD bvFTD fMRI resting-state connectivity Copula-based dependence measure |
description |
Q1 |
publishDate |
2021 |
dc.date.accessioned.none.fl_str_mv |
2021-04-20T20:57:31Z |
dc.date.available.none.fl_str_mv |
2021-04-20T20:57:31Z |
dc.date.created.none.fl_str_mv |
2021-01-15 |
dc.type.local.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
format |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.identifier.spa.fl_str_mv |
https://login.ezproxy.javeriana.edu.co/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1053811920310077&lang=es&site=eds-live |
dc.identifier.issn.spa.fl_str_mv |
1053-8119 / 1095-9572 (Electrónico) |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10554/53642 |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.neuroimage.2020.117522 |
dc.identifier.instname.spa.fl_str_mv |
instname:Pontificia Universidad Javeriana |
dc.identifier.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional - Pontificia Universidad Javeriana |
dc.identifier.repourl.spa.fl_str_mv |
repourl:https://repository.javeriana.edu.co |
url |
https://login.ezproxy.javeriana.edu.co/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1053811920310077&lang=es&site=eds-live http://hdl.handle.net/10554/53642 https://doi.org/10.1016/j.neuroimage.2020.117522 |
identifier_str_mv |
1053-8119 / 1095-9572 (Electrónico) instname:Pontificia Universidad Javeriana reponame:Repositorio Institucional - Pontificia Universidad Javeriana repourl:https://repository.javeriana.edu.co |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofjournal.spa.fl_str_mv |
NeuroImage |
dc.relation.citationvolume.spa.fl_str_mv |
225 |
dc.rights.licence.*.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
dc.format.spa.fl_str_mv |
PDF |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
institution |
Pontificia Universidad Javeriana |
bitstream.url.fl_str_mv |
http://repository.javeriana.edu.co/bitstream/10554/53642/2/license.txt http://repository.javeriana.edu.co/bitstream/10554/53642/1/Dynamic%20brain%20fluctations.pdf http://repository.javeriana.edu.co/bitstream/10554/53642/3/Dynamic%20brain%20fluctations.pdf.jpg |
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MD5 MD5 MD5 |
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Repositorio Institucional - Pontificia Universidad Javeriana |
repository.mail.fl_str_mv |
repositorio@javeriana.edu.co |
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spelling |
Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/http://purl.org/coar/access_right/c_abf2Moguilner, SebastianGarcía, Adolfo M.Sanz Perl, YonatanTagliazucchi, EnzoPiguet, OlivierKumfor, FionaReyes, PabloMatallana-Eslava, Diana L.Sedeño, LucasIbáñez, AgustínPontificia Universidad Javeriana. Facultad de Medicina. Instituto de Envejecimiento2021-04-20T20:57:31Z2021-04-20T20:57:31Z2021-01-15https://login.ezproxy.javeriana.edu.co/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1053811920310077&lang=es&site=eds-live1053-8119 / 1095-9572 (Electrónico)http://hdl.handle.net/10554/53642https://doi.org/10.1016/j.neuroimage.2020.117522instname:Pontificia Universidad Javerianareponame:Repositorio Institucional - Pontificia Universidad Javerianarepourl:https://repository.javeriana.edu.coPDFapplication/pdfengDynamic brain fluctuations outperform connectivity measures and mirror pathophysiological profiles across dementia subtypes : a multicenter studyArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Q1Q1From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network (EN), partially compromised in both conditions; the motor network (MN); and the visual network (VN). These RSNs were entered as features for dementia classification using a recent robust machine learning approach (a Bayesian hyperparameter tuned Gradient Boosting Machines (GBM) algorithm), across four independent datasets with different MR scanners and recording parameters. The machine learning classification accuracy analysis revealed a systematic and unique tailored architecture of RSN disruption. The classification accuracy ranking showed that the most affected networks for bvFTD were the SN + EN network pair (mean accuracy = 86.43%, AUC = 0.91, sensitivity = 86.45%, specificity = 87.54%); for AD, the DMN + EN network pair (mean accuracy = 86.63%, AUC = 0.89, sensitivity = 88.37%, specificity = 84.62%); and for the bvFTD vs. AD classification, the DMN + SN network pair (mean accuracy = 82.67%, AUC = 0.86, sensitivity = 81.27%, specificity = 83.01%). Moreover, the DFCA classification systematically outperformed canonical connectivity approaches (including both static and linear dynamic connectivity). Our findings suggest that non-linear dynamical fluctuations surpass two traditional seed-based functional connectivity approaches and provide a pathophysiological characterization of global brain networks in neurodegenerative conditions (AD and bvFTD) across multicenter data.Revista Internacional - IndexadaDynamic functional connectivityADbvFTDfMRI resting-state connectivityCopula-based dependence measureNeuroImage225LICENSElicense.txtlicense.txttext/plain; charset=utf-82603http://repository.javeriana.edu.co/bitstream/10554/53642/2/license.txt2070d280cc89439d983d9eee1b17df53MD52open accessORIGINALDynamic brain fluctations.pdfDynamic brain fluctations.pdfArtículoapplication/pdf3516519http://repository.javeriana.edu.co/bitstream/10554/53642/1/Dynamic%20brain%20fluctations.pdfc809a3fbea16765856ed7fd3f2f48703MD51embargoed access|||9999-04-11THUMBNAILDynamic brain fluctations.pdf.jpgDynamic brain fluctations.pdf.jpgIM Thumbnailimage/jpeg9566http://repository.javeriana.edu.co/bitstream/10554/53642/3/Dynamic%20brain%20fluctations.pdf.jpg6f1958953320aa5a8ee24bb45974d78fMD53open access10554/53642oai:repository.javeriana.edu.co:10554/536422021-07-14 16:30:49.153Repositorio Institucional - Pontificia Universidad Javerianarepositorio@javeriana.edu.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 |