Tracking dynamic resting-state networks at higher frequencies using MR-encephalography

Current resting-state network analysis often looks for coherent spontaneous BOLD signal fluctuations at frequencies below 0.1 Hz in a multiple-minutes scan. However hemodynamic signal variation can occur at a faster rate, causing changes in functional connectivity at a smaller time scale. In this study we proposed to use MREG technique to increase the temporal resolution of resting-state fMRI. A three-dimensional single-shot concentric shells trajectory was used instead of conventional EPI, with a TR of 100 ms and a nominal spatial resolution of 4 × 4 × 4 mm3. With this high sampling rate we were able to resolve frequency components up to 5 Hz, which prevents major physiological noises from aliasing with the BOLD signal of interest. We used a sliding-window method on signal components at different frequency bands, to look at the non-stationary connectivity maps over the course of each scan session. The aim of the study paradigm was to specifically observe visual and motor resting-state networks. Preliminary results have found corresponding networks at frequencies above 0.1 Hz. These networks at higher frequencies showed better stability in both spatial and temporal dimensions from the sliding-window analysis of the time series, which suggests the potential of using high temporal resolution MREG sequences to track dynamic resting-state networks at sub-minute time scale.