Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos

[EN] Resting state electroencephalography (EEG) has proved useful in studying electrophysiological changes in neurodegenerative diseases. In many neuropathologies, microstate analysis of the eyes-closed (EC) scalp EEG is a robust and highly reproducible technique for assessing topological changes wi...

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Autores: Giménez-Aparisi, Guillem, Chornet-Lurbe, A., Cervero-Albert, D., Hao, Dongmei, Li, Guangfei, Guijarro Estelles, Enrique|||0000-0003-0606-2352, Ye Lin, Yiyao|||0000-0003-2929-181X
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/229242
Acceso en línea:https://riunet.upv.es/handle/10251/229242
Access Level:acceso abierto
Palabra clave:Resting state electroencephalography
Parkinson
Microstate
Eyes influence
Dynamic features
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
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repository_id_str
spelling Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&aposs disease by resting-state electroencephalography: Systematic analysis of the influence of eye conditionGiménez-Aparisi, GuillemChornet-Lurbe, A.Cervero-Albert, D.Hao, DongmeiLi, GuangfeiGuijarro Estelles, Enrique|||0000-0003-0606-2352Ye Lin, Yiyao|||0000-0003-2929-181XResting state electroencephalographyParkinsonMicrostateEyes influenceDynamic features03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades[EN] Resting state electroencephalography (EEG) has proved useful in studying electrophysiological changes in neurodegenerative diseases. In many neuropathologies, microstate analysis of the eyes-closed (EC) scalp EEG is a robust and highly reproducible technique for assessing topological changes with high temporal resolution. However, scalp EEG microstate maps tend to underestimate the non-occipital or non-alpha-band networks, which can also be used to detect neuropathological changes. Recent evidence has shown that the source-space microstates can characterize distinct functional connectivity patterns but its clinical ability to detect neuropathological changes has not been demonstrated so far. It should also be remembered that the eye condition may play an important role in neural activity dynamics. The aim of this study was to systematically characterize the dynamic neuropathological features of sensor-space and source-space EEG microstates in PD patients with no cognitive impairment in both EC and EO conditions with the aim of identifying potential biomarkers that could be used as a complementary clinical screening method for early PD detection. We found that the dynamic features of the source-space microstates were more sensitive in detecting PD than the sensor-space microstates, while EO was able to detect neuropathological changes in PD patients better than EC. In EO, PD disease exhibited significantly higher occurrence and coverage in visual-network related source-space microstates and abnormally high duration in sensorimotor network-related microstates. Our results suggest that the source-space microstate analysis of resting-state EEG could provide robust biomarkers to detect early-stage PD, which would allow the development of patient-oriented strategies to prevent the disease and improve the patients¿ quality of life.This work was supported by the European Union NextGenerationEU under the Investigo program (INVEST/2022/67) and Polisabio (Polisabio 2021/A04). Funding for open access charge: CRUE-Universitat Politecnica de Valencia.for open acceunding for open acc`e`ElsevierDepartamento de Ingeniería ElectrónicaEscuela Técnica Superior de Ingeniería IndustrialCentro de Investigación e Innovación en BioingenieríaEuropean CommissionUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20252025-01-15journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/229242reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengUniversitat Politècnica de València https://doi.org/10.13039/501100004233 PI2021_25 POLISABIOEuropean Commission https://doi.org/10.13039/501100000780 Invest%2F2022%2F67open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial (by-nc) http://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2292422026-06-13T07:49:27Z
dc.title.none.fl_str_mv Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
s disease by resting-state electroencephalography: Systematic analysis of the influence of eye condition
title Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
spellingShingle Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
Giménez-Aparisi, Guillem
Resting state electroencephalography
Parkinson
Microstate
Eyes influence
Dynamic features
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
title_short Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
title_full Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
title_fullStr Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
title_full_unstemmed Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
title_sort Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson&apos
dc.creator.none.fl_str_mv Giménez-Aparisi, Guillem
Chornet-Lurbe, A.
Cervero-Albert, D.
Hao, Dongmei
Li, Guangfei
Guijarro Estelles, Enrique|||0000-0003-0606-2352
Ye Lin, Yiyao|||0000-0003-2929-181X
author Giménez-Aparisi, Guillem
author_facet Giménez-Aparisi, Guillem
Chornet-Lurbe, A.
Cervero-Albert, D.
Hao, Dongmei
Li, Guangfei
Guijarro Estelles, Enrique|||0000-0003-0606-2352
Ye Lin, Yiyao|||0000-0003-2929-181X
author_role author
author2 Chornet-Lurbe, A.
Cervero-Albert, D.
Hao, Dongmei
Li, Guangfei
Guijarro Estelles, Enrique|||0000-0003-0606-2352
Ye Lin, Yiyao|||0000-0003-2929-181X
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Electrónica
Escuela Técnica Superior de Ingeniería Industrial
Centro de Investigación e Innovación en Bioingeniería
European Commission
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Resting state electroencephalography
Parkinson
Microstate
Eyes influence
Dynamic features
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
topic Resting state electroencephalography
Parkinson
Microstate
Eyes influence
Dynamic features
03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades
description [EN] Resting state electroencephalography (EEG) has proved useful in studying electrophysiological changes in neurodegenerative diseases. In many neuropathologies, microstate analysis of the eyes-closed (EC) scalp EEG is a robust and highly reproducible technique for assessing topological changes with high temporal resolution. However, scalp EEG microstate maps tend to underestimate the non-occipital or non-alpha-band networks, which can also be used to detect neuropathological changes. Recent evidence has shown that the source-space microstates can characterize distinct functional connectivity patterns but its clinical ability to detect neuropathological changes has not been demonstrated so far. It should also be remembered that the eye condition may play an important role in neural activity dynamics. The aim of this study was to systematically characterize the dynamic neuropathological features of sensor-space and source-space EEG microstates in PD patients with no cognitive impairment in both EC and EO conditions with the aim of identifying potential biomarkers that could be used as a complementary clinical screening method for early PD detection. We found that the dynamic features of the source-space microstates were more sensitive in detecting PD than the sensor-space microstates, while EO was able to detect neuropathological changes in PD patients better than EC. In EO, PD disease exhibited significantly higher occurrence and coverage in visual-network related source-space microstates and abnormally high duration in sensorimotor network-related microstates. Our results suggest that the source-space microstate analysis of resting-state EEG could provide robust biomarkers to detect early-stage PD, which would allow the development of patient-oriented strategies to prevent the disease and improve the patients¿ quality of life.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-01-15
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/229242
url https://riunet.upv.es/handle/10251/229242
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Universitat Politècnica de València https://doi.org/10.13039/501100004233 PI2021_25 POLISABIO
European Commission https://doi.org/10.13039/501100000780 Invest%2F2022%2F67
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial (by-nc)
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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