<p>EEG microstates provides a unique perspective on the dynamic functional organization of the brain, has attracted considerable attention. This study conducted a bibliometric analysis of 441 articles retrieved from the Web of Science database using CiteSpace. The analysis focused on four key areas of EEG microstates: The academic network, classification and function, reliability of parameter, and primary research topics. Results revealed a steady increase in annual publications within this field. The academic network was dominated by the countries (including Switzerland, the United States, and China), the journal <i>NeuroImage</i>, and prominent researchers such as Koenig, Michel, and Lehmann. Determining the optimal number and the functions of EEG microstate classes were attributed to the clustering algorithms and validation criteria. The reliability of EEG microstate parameters varied, with mean duration demonstrating high reliability while the lower reliability was observed for transition probabilities (TP). Primary research topics that showed the trends in microstate studies encompassed cognitive function exploration, developmental changes, psychiatric disorder diagnosis, and emotion recognition. We recommend that future research focus on promoting international collaboration and establishing standardized labeling systems for EEG microstate classes. Greater attention should be directed towards employing robust metrics, such as mean duration (MD), while adopting a cautious approach to the use of TP. Furthermore, advancing task-based investigations and prioritizing clinical applications are essential for driving progress and fostering meaningful developments in EEG microstate research.</p>