Dear Alfonso,

Thanks for your suggestions and reply.

We expect anatomical differences between baseline and follow-up due to AD development. Would you suggest option (2) in this case? For example, align both baseline and follow-up data to the same T1 images (the averaged T1 images or the baseline T1 images), then import baseline and follow-up data as different subjects.

I preprocess a few subjects again as longitudinal data (with --longitudinal flag) via fMRIprep. With the --longitudinal flag, T1w images are merged into a single template image using FreeSurfer’s mri_robust_template. This template may be unbiased, or equidistant from all source images, or aligned to the first image (determined lexicographically by session label). (Given that I preprocessed my data via fMRIprep, I'm not able to use the reference computed from the averaged functional data across all sessions.)

I examined the correlation matrices from the 4 options again. 

Option (3) generates the same correlation matrices as option (1), which only imports baseline data, and (4), which only imports follow-up data. However, option (2) still generates different correlation matrices compared with the other options.

For option (2), each subject has "func" and "anat" folders which contain either preprcoessed functional data or preprocessed T1 image. Different sessions (baseline and follow-up) have the same preprocessed T1 image. 

In addition, I noticed that options (3) and (4) automatically use "sub-xxx_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii" instead of "c0sub-xxx_ses-baseline_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii". On the other hand, option (2) load "c0sub-xxx_ses-baseline_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii". 

However, the results are the same if I replace structural images with "c0sub-xxx_ses-baseline_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii".

Best regards,

Chih-Hao