Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy.
Recently, emerging studies have demonstrated the existence of brain resting-state spontaneous activity at frequencies higher than the conventional 0.1 Hz. A few groups utilizing accelerated acquisitions have reported persisting signals beyond 1 Hz, which seems too high to be accommodated by the sluggish hemodynamic process underpinning blood oxygen level-dependent contrasts (the upper limit of the canonical model is ∼0.3 Hz). It is thus questionable whether the observed high-frequency (HF) functional connectivity originates from alternative mechanisms (e.g., inflow effects, proton density changes in or near activated neural tissue) or rather is artificially introduced by improper preprocessing operations. In this study, we examined the influence of a common preprocessing step-whole-band linear nuisance regression (WB-LNR)-on resting-state functional connectivity (RSFC) and demonstrated through both simulation and analysis of real dataset that WB-LNR can introduce spurious network structures into the HF bands of functional magnetic resonance imaging (fMRI) signals. Findings of present study call into question whether published observations on HF-RSFC are partly attributable to improper data preprocessing instead of actual neural activities.
['Chen|Jingyuan E|JE|', 'Jahanian|Hesamoddin|H|', 'Glover|Gary H|GH|']
D000328:Adult D016477:Artifacts D001921:Brain D001931:Brain Mapping D003198:Computer Simulation D066264:Datasets as Topic D005260:Female D006801:Humans D007091:Image Processing, Computer-Assisted D008279:Magnetic Resonance Imaging D008297:Male D008875:Middle Aged D016571:Neural Networks, Computer D009434:Neural Pathways D010100:Oxygen D059629:Signal-To-Noise Ratio D013057:Spectrum Analysis D055815:Young Adult
linear nuisance regression spurious network structures fast acquisition high frequency resting state functional connectivity