Before revision:  It includes a novel denoising approach based on  Marchenko-Pastur Principle Component Analysis (MP-PCA) method, FMRIB's ICA-based Xnoiseifier (FIX) for automatic artefact classification and cleaning, and global signal regression (GSR) . Our results show that: I) MP-PCA denoising substantially improves the temporal signal-to-noise ratio;
After revision:  It includes a novel denoising approach based on Marchenko-Pastur Principle Component Analysis (MP-PCA) method, FMRIB's ICA-based Xnoiseifier (FIX) for automatic artefact classification and cleaning, and global signal regression . Our results show that: I) MP-PCA denoising substantially improves the temporal signal-to-noise ratio;