Functional significance of RSNs is examined via simultaneous EEG-fMRI studies on the basis of relation of RSNs with different frequency bands of EEG and EEG based microstate analysis. In this study we try to identify RSNs from microstates of cortical surface maps of BOLD signal. In addition the scale-free dynamics of these map sequences were also examined. The structural and resting state functional MRI images were acquired on a 3T scanner with three different fMRI acquisition protocols from 7 subjects. Microstate segmentations from EEG, fMRI and simulated data were performed using Cartool software for each subject separately. Wavelet-based fractal analysis was performed on map sequence time series and the Hurst exponent (H) was calculated. By using HRF deconvolved fMRI time series, the effect of HRF (Hemodynamic Response Function) was on fMRI-derived microstates was tested. fMRI map sequence has a system having a memory system smaller than 16s. When HRF was deconvolved, the duration of the memory of the system was reduced to 4s. On the other hand, the results of simulation data indicated that these systems are specific to resting state BOLD signal. Similar to EEG microstates, fMRI also has microstates and both of them have scale-free dynamics. fMRI microstates dynamics have 2 different components, one is related to HRF and the other independent from HRF. The significance of fMRI microstates and their relation with RSNs are needed to further studied.