Influences of Head Motion Regression on High-Frequency Oscillation Amplitudes of Resting-State fMRI Signals.

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.

journal_name

Front Hum Neurosci

authors

Yuan BK,Zang YF,Liu DQ

doi

10.3389/fnhum.2016.00243

subject

Has Abstract

pub_date

2016-05-26 00:00:00

pages

243

issn

1662-5161

journal_volume

10

pub_type

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