Hi Alfonso,

I am combining 8 resting state fMRI datasets for a mega-analysis. I'm using CONN25b / SPM25 / MATLAB 2026 through batch scripts on a remote server (without GUI). I greatly appreciate your expert opinion on a few decisions.
My plan is to apply the same preprocessing, denoising, and first-level analysis pipelines separately to each dataset, then pool the participant-level results for a combined second-level analysis.

I am using CONN's default MNI preprocessing pipeline with the following settings:
Preprocessing: Realignment/unwarping, STC (except one dataset), ART (0.9 mm/5 SD), direct normalization (2 mm MNI), smoothing (8 mm FWHM).
Denoising: aCompCor (10 WM + 10 CSF, with 1st derivatives), motion (6 + 1st derivatives), scrubbing, session effects, detrending, and band-pass filtering (0.008–0.09 Hz).

I have some questions.
1. TR=0.9 / multiband / no STC: slice-timing info for dataset 5 is missing. so I am skipping STC for this dataset only. Do you find it reasonable?
Do you think there are other adjustments I should consider? like in motion scrubbing or ART?

2. smoothing kernel size: Dataset 4 has a voxel size of 1×1×2 mm (TR=2), while the others are around 3-3.5 mm. Would you still recommend 8 mm FWHM, or would 6 mm be better in our case?
In your previous reply, you explained that smoothing mainly accounts for differences in functional localization rather than improving SNR, but I'm still concerned that an 8 mm kernel would lead to a greater loss of data in this dataset compared to others.

3. coregistration: Do you recommend using the first functional volume or the mean functional image for coregistration?

4. aCompCor: I am currently using 10 WM + 10 CSF components (with first derivatives). My rational is to remove as much noise as possibel. Do you think this is appropriate, or would you recommend keeping the default 5 + 5?

5. pipeline: And finally :) do you have any recommendations or changes to the preprocessing or denoising pipeline?

Here is the profile of my datasets:

Dataset    Scanner (3T)     Voxel (mm)        TR (s)     Slice order       Duration (min)
-------     ------------       --------------         ------       --------------      --------------
1           Siemens               3×3×3                2.0        Interleaved           10
2           Philips                 3.5×3.5×3.5        3.0        Ascending             5
3           Siemens              3.5×3.5×3           2.5        Interleaved            7
4           Siemens              1×1×2               2.0        Multiband               7
5           Philips                3.5×3.5×3.5        0.9        Multiband*             5
6           Siemens             3×3×3                2.0        Interleaved             8
7           Siemens             3×3×3                2.0        Interleaved             10
8           Siemens             3×3×3                2.0        Interleaved             10

Thank you very much for your time and guidance!
Best,
Shiva