How to choose MNI space resolution when doing normalization?

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Hi,
I have a question about the choice MNI space resolution. I found that for a typical fMRI scan for about 3 mm resolution and T1w 1 mm resolution, MNI for T1 would be 1mm and for fMRI would be ~2 mm.

However, my images have much higher resolution (0.6 mm for T1w and 1.3 mm for fMRI). Could you suggest what resolution of MNI should I choose when doing normalization? Because I assumed that by choosing a higher resolution I can retain more information afforded by the high-res scans. Is this correct?

Thank you very much!
Best
Xinyu

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Hi,

With such high resolution, you would not want to normalize you data to “classical” resolutions (1mm for anatomy, 3mm for functional). In tools such as FMRIPREP, you can keep your native resolution for your normalized data in MNI space.

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Hi @jsein , thank you very much for the suggestion! Unfortunately I am unable to use fmriprep because of a slicing timing error in my DICOM files. I was wondering if there are any alternatives I could look into?

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@Meteorxy You can ignore slice timing (--ignore slicetiming). Is the error not fixable?

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There is afni_proc.py (AP) which you can use to set up an FMRI processing pipeline:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/programs/alpha/afni_proc.py_sphx.html#ahelp-afni-proc-py
… and you can control features like blurring or not (whether you are doing voxelwise or ROI-based analysis, respectively), volumetric or surface analysis, choosing a particular template, etc. The option for specifying the final output resolution is:

-volreg_warp_dxyz         SIZE

There are some examples of AP commands from particular papers here:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/codex/fmri/main_toc.html
for example.

–pt

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