qEEG as Biomarker for Alzheimer's Disease: Investigating Relative PSD Difference and Coherence Analysis.
Alzheimer’s disease
coherence
electroencephalography
power spectral density
Journal
Neuropsychiatric disease and treatment
ISSN: 1176-6328
Titre abrégé: Neuropsychiatr Dis Treat
Pays: New Zealand
ID NLM: 101240304
Informations de publication
Date de publication:
2023
2023
Historique:
received:
31
07
2023
accepted:
04
11
2023
medline:
15
11
2023
pubmed:
15
11
2023
entrez:
15
11
2023
Statut:
epublish
Résumé
Electroencephalography (EEG) is a non-intrusive technique that provides comprehensive insights into the electrical activities of the brain's cerebral cortex. The brain signals obtained from EEGs can be used as a neuropsychological biomarker to detect different stages of Alzheimer's disease (AD) through quantitative EEG (qEEG) analysis. This paper investigates the difference in the abnormalities of resting state EEG (rEEG) signals between eyes-open (EOR) and eyes-closed (ECR) in AD by analyzing 19-scalp electrode EEG signals and making a comparison with healthy controls (HC). The rEEG data from 534 subjects (ages 40-90) consisting of 269 HC and 265 AD subjects in South Korea were used in this study. The qEEG for EOR and ECR states were performed separately for HC and AD subjects to measure the relative power spectrum density (PSD) and coherence with functional connectivity to evaluate abnormalities. The rEEG data were preprocessed and analyzed using EEGlab and Brainstorm toolboxes in MATLAB R2021a software, and statistical analyses were carried out using ANOVA. Based on the Welch method, the relative PSD of the EEG EOR and ECR states difference in the AD group showed a significant increase in the delta frequency band of 19 EEG channels, particularly in the frontal, parietal, and temporal, than the HC groups. The delta power band on the source level was increased for the AD group and decreased for the HC group. In contrast, the source activities of alpha, beta, and gamma frequency bands were significantly reduced in the AD group, with a high decrease in the beta frequency band in all brain areas. Furthermore, the coherence of rEEG among different EEG electrodes was analyzed in the beta frequency band. It showed that pair-wise coherence between different brain areas in the AD group is remarkably increased in the ECR state and decreased after subtracting out the EOR state. The findings suggest that examining PSD and functional connectivity through coherence analysis could serve as a promising and comprehensive approach to differentiate individuals with AD from normal, which may benefit our understanding of the disease.
Identifiants
pubmed: 37965528
doi: 10.2147/NDT.S433207
pii: 433207
pmc: PMC10642578
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2423-2437Informations de copyright
© 2023 Simfukwe et al.
Déclaration de conflit d'intérêts
The authors declare that they have no competing interests in this work.
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