Hi, I’m wondering why I would be getting this error: ValueError: Confound signal has an incorrect lengthSignal length: 150; confound length: 96 when running this:
I understand the error (my .tsv is 96 rows and the example data is (168, 39) but I don’t know how to run the pipeline with my data. I ran standard fmriprep with --use-aroma.
Instead of loading the example data, load your preprocessed bold image (corresponding to your confounds TSV file) with
nilearn.image.load_img($PATH_TO_BOLD), and pass that into
masker.fit_transform instead of the example data. The rest, assuming you are using the same atlases and plotting outputs as the tutorial, should be the same. Hope this helps.