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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
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Electroencephalography microstate alterations reflect potential double-edged cognitive adaptation in Ménière's
Yi-Ni Li1, Jie Li1, Peng-Jun Wang1
1Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
CNS Neuroscience & Therapeutics
|August 7, 2024
Summary
Electroencephalography (EEG) microstate analysis reveals distinct brain network patterns in Ménière
Area of Science:
- Neuroscience
- Clinical Neurology
- Biomarkers
Background:
- Ménière's disease (MD) is a complex inner ear disorder.
- Understanding the neurophysiological underpinnings of MD is crucial for diagnosis and treatment.
- High-density electroencephalography (EEG) offers a non-invasive method to study brain activity.
Purpose of the Study:
- To investigate EEG microstate characteristics in MD patients.
- To correlate microstate dynamics with clinical symptoms and dysfunction.
- To explore EEG microstates as potential neurobiomarkers for MD.
Main Methods:
- 32 MD patients and 29 healthy controls (HC) underwent 256-channel resting-state EEG.
- EEG data were analyzed for microstate classes (A, B, C, D) and their dynamic parameters.
- Support vector machine (SVM) classifier used microstate features to distinguish MD from HC.
Main Results:
- MD patients showed increased microstate C presence and altered A-B, A-D, and A-C transition frequencies.
- Specific microstate transitions correlated with postural control and vertigo symptom severity.
- SVM achieved 86.21% sensitivity and 90.61% specificity in classifying MD patients.
Conclusions:
- EEG microstate alterations are present in MD patients.
- These microstate features can differentiate MD patients from healthy controls.
- EEG microstates show potential as neurobiomarkers for MD and may inform cognitive compensation strategies.
