AUTHOR=Yuan Bin-Ke , Zang Yu-Feng , Liu Dong-Qiang TITLE=Influences of Head Motion Regression on High-Frequency Oscillation Amplitudes of Resting-State fMRI Signals JOURNAL=Frontiers in Human Neuroscience VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2016.00243 DOI=10.3389/fnhum.2016.00243 ISSN=1662-5161 ABSTRACT=

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.