title: Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy.
abstract: 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.
authors.affiliation: 1 Department of Radiology, Stanford University , Stanford, California.|2 Department of Electrical Engineering, Stanford University , Stanford, California.
authors.forename: Jingyuan E
authors.initials: JE
authors.lastname: Chen
authors.affiliation: 1 Department of Radiology, Stanford University , Stanford, California.
authors.forename: Hesamoddin
authors.initials: H
authors.lastname: Jahanian
authors.affiliation: 1 Department of Radiology, Stanford University , Stanford, California.
authors.forename: Gary H
authors.initials: GH
authors.lastname: Glover
mesh_terms: D000328:Adult; D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods; 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 / Q000000981:diagnostic imaging; D010100:Oxygen / Q000097:blood; D059629:Signal-To-Noise Ratio; D013057:Spectrum Analysis; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: fast acquisition; high frequency; linear nuisance regression; resting state functional connectivity; spurious network structures