Location of bold reference image in fmriprep 1.0.6?

Hi, all. We’d like to do some analyses on the bold reference images across our studies (to see if we can classify the originating scanner), but I don’t see that the reference images are output.

I think I should be able to fetch them from the working directory, but I wanted to confirm the correct location. If I use:

will I be getting the reference image I’m looking for?


I think this is it, but we should probably output those with other results.

That is the initial reference image, but some additional steps are done to improve the gray/white contrast (for boundary-based registration).

The enhanced image is: bold_reference_wf/enhance_and_skullstrip_bold_wf/n4_correct/*.nii.gz
The skull-stripped enhanced image is: bold_reference_wf/enhance_and_skullstrip_bold_wf/apply_mask/*.nii.gz

Those are the images actually used for further processing.

Thanks, Chris(es),

My RA pointed out to me that we actually want the reference image in MNI space to run the classification algorithm on.

Seems like I might want:
/fmriprep_wf/single_subject_sub_wf/func_preproc_task_task_run_001_wf/ bold_reference_wf/enhance_and_skullstrip_bold_wf/apply_mask/uni_xform_masked.nii.gz

Is that correct?

Thanks so much, again,

I don’t think we actually apply the full set of transforms to the reference image so this file is not available.

Why not take an average of 10 first volumes of your _preproc outputs in the MNI space?

My backup plan was to take the overall average of the timecourse, but I was thinking that the way fmriprep identifies the representative image might be slightly better than a simple average.

Is there any reason that the average of the first 10 images would be better than a whole timecourse average? (This is a block design experiment, so there are going to be time-varying differences in some ROIs.)

You want to average over some TRs (so you would remove noise), but you expect variance over a large number of TRs (so it’s a trade off). I would also skip some TRs in the beginning to avoid catching the non-steady state effects.