[Advances in methods and applications of electroencephalogram microstate analysis]

Area of Science:

• Neuroscience
• Computational Neuroscience
• Brain Imaging Analysis

Context:

• Electroencephalogram (EEG) analysis is rapidly evolving, with microstate analysis offering unique temporal and topological insights.
• EEG microstate analysis captures brain dynamics at the millisecond scale, reflecting discontinuous and nonlinear brain activity.
• With over 30 years of development, EEG microstate analysis is now integral to various brain science research fields.

Purpose:

• To summarize the fundamental principles of EEG microstate analysis.
• To describe characteristic parameter changes, relationships with brain functional networks, and advances in microstate feature extraction and classification.
• To provide a reference for researchers in brain science, particularly in the application of EEG microstate analysis.

Summary:

• This paper reviews EEG microstate analysis, a method providing high temporal resolution and topological distribution of EEG signals.
• It details the basic principles, characteristic parameter changes, and the link between microstates and brain functional networks.
• Key advances in applying microstate feature extraction and classification to brain diseases and cognition are systematically presented.

Impact:

• EEG microstate analysis provides a powerful tool for understanding brain function at a fine temporal scale.
• The method aids in characterizing brain dynamics relevant to neurological and cognitive processes.
• This review offers valuable insights for researchers investigating brain diseases and cognitive functions using EEG data.