Dynamic functional connectivity (dFC) states have been identified in BOLD-fMRI data, but their electrophysiological underpinnings remain a matter of debate. The simultaneous acquisition of the EEG has previously allowed the identification of EEG signatures of dFC states. Here, we further investigated whether EEG microstates can be used to classify dFC states. We found that highly accurate classification could be achieved based on the three EEG microstates with the highest global explained variance, in simultaneous EEG-fMRI data acquired from eight epileptic patients. These results further support the electrophysiological underpinnings of fMRI dFC states, highlighting their relationship with EEG-derived microstates.