Depression diagnosis based on electroencephalography power ratios.
alpha/beta ratio
depression
electroencephalography
neural network
Journal
Brain and behavior
ISSN: 2162-3279
Titre abrégé: Brain Behav
Pays: United States
ID NLM: 101570837
Informations de publication
Date de publication:
08 2023
08 2023
Historique:
revised:
14
06
2023
received:
30
04
2023
accepted:
08
07
2023
medline:
28
8
2023
pubmed:
22
7
2023
entrez:
21
7
2023
Statut:
ppublish
Résumé
Depression is a common mental disorder that impacts millions of people across the world. However, its diagnosis is difficult due to the dependence on subjective testing. Although quantitative electroencephalography (EEG) has been investigated as a promising diagnostic tool for depression, the associated results have proven contradictory. The current study determines whether the alpha/beta (ABR), alpha/theta (ATR), and theta/beta (TBR) ratios can serve as biological markers of depression. We used open-access EEG data from OpenNeuro to investigate power ratios in the resting state of 46 patients with depression and 75 healthy controls. Spectral data were extracted by fast Fourier transform at the theta band (4-8 Hz), alpha band (8-13 Hz), and beta band (13-32 Hz). Neural network, logistic regression, and receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracies of each suggested index. Additionally, the cutoff point, sensitivity, specificity, positive predictive value, and negative predictive value at the maximized Youden index were compared for each variable. Decreased anterior frontal, frontal, central, parietal, occipital, and temporal ABR and decreased central and parietal TBR were observed in the depression group. The area under the curve of the ROC curves further revealed that these ratios could all effectively differentiate depression. In particular, the central, frontal, and parietal ABR exhibited high discrimination scores. Multiple logistic regression analysis demonstrated that the Beck Depression Inventory and Spielberger Trait Anxiety Inventory scores, as well as the probability of depression, increased with a decrease in the central ABR. Moreover, neural network analysis revealed that the global ABR was the most effective index for diagnosing depression among the three global EEG power ratios. The central, frontal, and parietal ABR represent potential biomarkers to differentiate patients with depression from healthy controls.
Sections du résumé
BACKGROUND
Depression is a common mental disorder that impacts millions of people across the world. However, its diagnosis is difficult due to the dependence on subjective testing. Although quantitative electroencephalography (EEG) has been investigated as a promising diagnostic tool for depression, the associated results have proven contradictory. The current study determines whether the alpha/beta (ABR), alpha/theta (ATR), and theta/beta (TBR) ratios can serve as biological markers of depression.
METHODS
We used open-access EEG data from OpenNeuro to investigate power ratios in the resting state of 46 patients with depression and 75 healthy controls. Spectral data were extracted by fast Fourier transform at the theta band (4-8 Hz), alpha band (8-13 Hz), and beta band (13-32 Hz). Neural network, logistic regression, and receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracies of each suggested index. Additionally, the cutoff point, sensitivity, specificity, positive predictive value, and negative predictive value at the maximized Youden index were compared for each variable.
RESULTS
Decreased anterior frontal, frontal, central, parietal, occipital, and temporal ABR and decreased central and parietal TBR were observed in the depression group. The area under the curve of the ROC curves further revealed that these ratios could all effectively differentiate depression. In particular, the central, frontal, and parietal ABR exhibited high discrimination scores. Multiple logistic regression analysis demonstrated that the Beck Depression Inventory and Spielberger Trait Anxiety Inventory scores, as well as the probability of depression, increased with a decrease in the central ABR. Moreover, neural network analysis revealed that the global ABR was the most effective index for diagnosing depression among the three global EEG power ratios.
CONCLUSIONS
The central, frontal, and parietal ABR represent potential biomarkers to differentiate patients with depression from healthy controls.
Identifiants
pubmed: 37479962
doi: 10.1002/brb3.3173
pmc: PMC10454346
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e3173Informations de copyright
© 2023 The Authors. Brain and Behavior published by Wiley Periodicals LLC.
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