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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
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Reliability of resting-state microstate features in electroencephalography.
Arjun Khanna1, Alvaro Pascual-Leone1, Faranak Farzan2
1Berenson-Allen Center for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States of America.
Plos One
|December 6, 2014
Summary
Electroencephalographic (EEG) microstate analysis shows high test-retest reliability, supporting its use as a neurophysiological biomarker. Consistent results were found across different analysis methods and electrode configurations.
Area of Science:
- Neuroscience
- Biomarker Discovery
- Brain Imaging
Background:
- Electroencephalographic (EEG) microstate analysis identifies functional brain states.
- These microstates are altered in neuropsychiatric disorders, indicating biomarker potential.
- Assessing test-retest reliability is crucial for clinical application of EEG microstates.
Purpose of the Study:
- To evaluate the test-retest reliability of EEG microstate analysis.
- To compare different microstate analysis approaches and clustering algorithms.
- To determine the reliability of microstate analysis with reduced electrode counts.
Main Methods:
- Resting-state EEG data from 10 healthy subjects across 3 sessions were analyzed.
- Four microstate classes were identified, with duration, frequency, and coverage fraction calculated.
- Reliability was assessed using Cronbach's alpha and SEM, with varying electrode numbers (30, 19, 8).
Main Results:
- Global microstate map identification demonstrated the highest reliability (Cronbach's α > 0.8).
- Analysis was most reliable when microstate maps were held constant across recordings.
- High consistency was observed across clustering methods (Cronbach's α > 0.9), and reliability was maintained with 19 and 8 electrodes.
Conclusions:
- EEG microstate features exhibit high test-retest reliability and cross-method consistency.
- These findings support the potential of EEG microstates as reliable biomarkers for neurophysiological health.
- The analysis remains reliable even with a reduced number of electrodes.
