Influences of head motion regression on high-frequency oscillation amplitudes of resting-state fMRI signals

High-frequency oscillations (hfos,>0.1 hz) of resting-state fmri (rs-fmri) signals have received much attention in recent years. denoising is critical for hfo studies. previous work indicated that head motion (hm) has remarkable influences on a variety of rs-fmri metrics,but its influences on rs-fmri hfos are still unknown. in this study,we investigated the impacts of hm regression (hmr) on hfo results using a fast sampling rs-fmri dataset. we demonstrated that apparent high-frequency (~0.2-0.4 hz) components existed in the hm trajectories in almost all subjects. in addition,we found that individual-level hmr could robustly reveal more between-condition (eye-open vs. eye-closed) amplitude differences in high-frequency bands. although regression of mean framewise displacement (fd) at the group level had little impact on the results,mean fd could significantly account for inter-subject variance of hfos even after individual-level hmr. our findings suggest that hm artifacts should not be ignored in hfo studies,and hmr is necessary for detecting hfo between-condition differences. © 2016 yuan,zangand liu.