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Abstract #2718

Depth-dependent effects of thermal and physiological noise reduction in BOLD fMRI

Maria Guidi1,2,3, Giovanni Giulietti4,5, Harald E. Moeller2, David G. Norris3, and Federico Giove1,4
1MARBILab, Enrico Fermi Research Center, Rome, Italy, 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands, 4Fondazione Santa Lucia IRCCS, Rome, Italy, 5SAIMLAL Department, Sapienza University, Rome, Italy

Synopsis

Keywords: Data Processing, Data Analysis, Denoising, LayersIn this study, we evaluated the effect of common denoising steps (NORDIC, regression for motion parameters, RETROICOR and aCompCor) on a high-resolution resting-state BOLD fMRI dataset. We extracted the temporal standard deviation and the spectral power density at different cortical depths in the primary motor cortex and found that each denoising algorithm had a distinct signature on the profile shape. We further estimated the effect of denoising by calculating the temporal signal-to-noise ratio and delta variation signal (DVARS) for different tissue types and found that NORDIC and aCompCor had the largest impacts on the metrics considered.

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Keywords