Regarding multiband artifacts, our recent paper may be of interest: Characterization and Mitigation of a Simultaneous Multi-Slice fMRI Artifact: Multiband Artifact Regression in Simultaneous Slices
We developed a regression-based technique, MARSS, that successfully removes an artifact manifesting as elevated signal correlations in simultaneously acquired slices. The removal method is run directly on unprocessed data (i.e., before any spatial normalization or SDC). We also showed that ICA-FIX does not fully mitigate the same artifact, so it may be advantageous to use MARSS prior to ICA-FIX for optimal denoising. The source code is here if interested (we have MATLAB and Python implementations): GitHub - CNaP-Lab/MARSS: Multiband Artifact Regression in Simultaneous Slices (MARSS)