How to use MNIPediatricAsym with XCP-D?

Software Support
1

I processed my data aligning to MNIPediatricAsym (cohort-5) because that was the most appropriate template. However, I now see in the XCP-D docs:

The minimal inputs required to run XCP-D are:

  • A native-space preprocessed T1w or T2w image.
  • A preprocessed BOLD image in MNI152NLin6Asym, MNI152NLin2009cAsym, MNIInfant (nibabies derivatives), or fsLR (CIFTI processing) space.

I did not generate the MNI152 spaces, not realizing XCP-D didn’t include this template. What is the best way to approach this?

Should I work in adult space (i.e. rerun fMRIPREP, which I would prefer to avoid), or can I symlink the MNIPediatric data to MNI152NLin and fake it?

2

In order to make MNIPediatricAsym (or any currently unsupported volumetric template) work, we need high-quality transforms to MNI152NLin6Asym, MNI152NLin2009cAsym, or MNIInfant. I should note that the transforms we have for MNIInfant (e.g., to MNI152NLin6Asym) are low quality, which is one reason we typically run XCP-D on CIFTIs when working with infant data.

If you’re interested in helping, I’d recommend trying to build some solid transforms to the adult spaces and pushing them to TemplateFlow. I believe Mathias Goncalves has been doing similar work with MNIInfant.

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3

Thanks for the info. In the short term then, I should re-run fMRIPREP with the correct space?

Thanks for the quick reply.

4

If you run fMRIPrep with MNIInfant as the output space, XCP-D should work, but I should warn you that some derivatives, like the parcellated time series, won’t be very high quality, since they rely on a pretty bad MNI152NLin6Asym-to-MNIInfant transform. The denoised data will be fine though, since it doesn’t rely on that transform.

5

Cohort 5 is 10 - 14 y, so probably just using the adult space would be better (this doesn’t need to be the highest-quality analysis ever).

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