Are the EEG microstates correlated with motor and non-motor parameters in patients with Parkinson's disease?

Biomarkers Brain waves Diagnostic techniques Neurodegenerative disease Parkinsonian disorders

Journal

Neurophysiologie clinique = Clinical neurophysiology
ISSN: 1769-7131
Titre abrégé: Neurophysiol Clin
Pays: France
ID NLM: 8804532

Informations de publication

Date de publication:
Feb 2023
Historique:
received: 19 09 2022
revised: 05 11 2022
accepted: 17 12 2022
medline: 26 6 2023
pubmed: 31 1 2023
entrez: 30 1 2023
Statut: ppublish

Résumé

This study compared electroencephalography microstates (EEG-MS) of patients with Parkinson's disease (PD) to healthy controls and correlated EEG-MS with motor and non-motor aspects of PD. This cross-sectional exploratory study was conducted with patients with PD (n = 10) and healthy controls (n = 10) matched by sex and age. We recorded EEG-MS using 32 channels during eyes-closed and eyes-open conditions and analyzed the four classic EEG-MS maps (A, B, C, D). Clinical information (e.g., disease duration, medications, levodopa equivalent daily dose), motor (Movement Disorder Society - Unified Parkinson Disease Rating Scale II and III, Timed Up and Go simple and dual-task, and Mini-Balance Evaluation Systems Test) and non-motor aspects (Mini-Mental State Exam [MMSE], verbal fluency, Hospital Anxiety and Depression Scale, and Parkinson's Disease Questionnaire-39 [PDQ-39]) were assessed in the PD group. Mann-Whitney U test was used to compare groups, and Spearman's correlation coefficient to analyze the correlations between coverage of EEG-MS and clinical aspects of PD. The PD group showed a shorter duration of EEG-MS C in the eyes-closed condition than the control group. We observed correlations (rho = 0.64 to 0.82) between EEG-MS B, C, and D and non-motor aspects of PD (MMSE, verbal fluency, PDQ-39, and levodopa equivalent daily dose). Alterations in EEG-MS and correlations between topographies and cognitive aspects, quality of life, and medication dose indicate that EEG could be used as a PD biomarker. Future studies should investigate these associations using a longitudinal design.

Identifiants

pubmed: 36716585
pii: S0987-7053(22)00123-X
doi: 10.1016/j.neucli.2022.102839
pii:
doi:

Substances chimiques

Levodopa 46627O600J

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102839

Informations de copyright

Copyright © 2022 Elsevier Masson SAS. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential

Auteurs

Thaísa Dias de Carvalho Costa (TDC)

Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil.

Camila Beatriz da Silva Machado (CBDS)

Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil.

Robson Prazeres Lemos Segundo (RP)

Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil.

Joyce Poláine Dos Santos Silva (JPDS)

Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil.

Ana Catarine Tavares Silva (ACT)

Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil.

Rafael de Souza Andrade (RS)

Division of Neurology, Lauro Wanderley University Hospital, Federal University of Paraíba, João Pessoa, Brazil.

Marine Raquel Diniz Rosa (MRD)

Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil.

Suhaila Mahmoud Smaili (SM)

Department of Physical Therapy, State University of Londrina, Londrina, Brazil.

Edgard Morya (E)

Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Natal, Brazil.

Adriana Costa-Ribeiro (A)

NeuroMove Laboratory, Department of Physiotherapy, Federal University of Paraíba, Joao Pessoa, Brazil.

Ana Raquel Rodrigues Lindquist (ARR)

Laboratory of Intervention and Analysis of Movement, Department of Physiotherapy, Federal University of Rio Grande do Norte, Natal, Brazil.

Suellen Marinho Andrade (SM)

Aging and Neuroscience Laboratory, Federal University of Paraíba, João Pessoa, Brazil; Graduate Program in Cognitive and Behavioural Neuroscience, Federal University of Paraíba, João Pessoa, Brazil.

Daniel Gomes da Silva Machado (DGDS)

Research Group in Neuroscience of Human Movement (NeuroMove), Department of Physical Education, Federal University of Rio Grande do Norte, Natal, RN, Brazil. Electronic address: profdmachado@gmail.com.

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Classifications MeSH