I’ve been using fmriprep with ica-aroma to analyze a multiband dataset from a 2 minute long continuous scan, and then applied a separate highpass filter. This procedure yielded an artifact, apparent when performing inter-subject correction of the full timecourses within each voxel. In the image below you can see unusual correlations in voxels that seem to include a lot of CSF, such as in sulci and ventricles (in addition to the expected higher correlations in auditory cortex). This artifact appears whether the filtering is applied using FSL or SPM.
However, when the inter-subject correlation is performed on the original fmriprep ica-aroma output (without the highpass), the artifacts disappear. Also no artifacts manifest when the entire preprocessing pipeline is performed in FSL (using MCFLIRT for motion correction), including the same highpass filter. In addition, no artifacts manifest when performing the same fmriprep+ica-aroma+highpass on a different, non-multiband dataset.
It seems to me like the artifacts are a result of the interaction between ica-aroma, the highpass filter, and multiband data. I read through most of this discussion, but I’m not sure how it will all translate into my specific use case. This is my first time using multiband and ica-aroma, so I might just be missing something obvious. Any leads would be appreciated!