  Despite the decades of efforts, the choice of EEG reference is still a
debated fundamental issue. Non-neutral reference can inevitably inject the
uncontrolled temporal biases into all EEG recordings, which may influence the
spatiotemporal analysis of brain activity. A method, termed microstates,
identifying spatiotemporal EEG features as the quasi-stable topography states
in milliseconds, suggests its potential as biomarkers of neurophysiological
disease. As reference electrode standardization technique (REST) could
reconstruct an infinity reference approximately, it is a question whether REST
or the other references will be more reliable than average reference (AR) for
the microstates analysis. In this study, we design the microstate-based EEG
forward model, and apply different references for microstates analysis. The
spatial similarity between the generated and assumed cluster maps is mainly
investigated. Furthermore, the real EEG data by the parametric bootstrap method
is used to validate the performance of the references. Finally, we find that
REST is robust to recover more similar cluster maps to the assumption than AR
in the simulation, and the cluster maps between REST and AR on the real EEG
data are quite different. This study may indicate that REST contributes to
identifying more objective microstates features than AR.
