Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomedical Engineering

Background:

• Electroencephalography (EEG) is crucial for studying brain activity.
• Traditional EEG analysis methods often suffer from reference-dependency.
• Investigating neural mechanisms in brain disorders requires robust complexity measures.

Purpose of the Study:

• To provide a step-by-step protocol for EEG microstate and omega complexity analyses.
• To highlight the advantages of these reference-free EEG measures.
• To demonstrate their complementary roles in assessing brain complexity.

Main Methods:

• Detailed protocol for EEG microstate analysis.
• Step-by-step guide for omega complexity analysis.
• Emphasis on reference-free data processing.

Main Results:

• Microstate analysis captures temporal complexity and links to resting-state networks.
• Omega complexity quantifies spatial complexity across the whole brain or specific regions.
• Both methods overcome limitations of traditional spectrum analysis.

Conclusions:

• EEG microstate and omega complexity offer comprehensive, reference-free assessments of brain dynamics.
• These methods provide complementary temporal and spatial insights into neural mechanisms.
• They are valuable tools for investigating brain disorders.