Thank you for your comments. Some more questions below:
On Mon, Aug 22, 2016 at 1:09 PM, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
- In NeuroVault users are asked to upload their statistical maps in
form of files. I'm planning to target outputs of mri_glmfit: preferably Z.mgh but also sig.mgh. Is this the most sensible thing to do?
Yes. You may also want the gamma.mgh file as that is the size of the effect (eg, thickness change in mm )
This would be very useful - an effect size in meaningful units is a rarity in neuroimaging!
- Finally NeuroVault gives users ability to compare maps and even
search through the whole repository to find statistical maps with similar patterns. This is currently implemented for volumetric data, but could be extended to surface data. The problem arises when one wants to compare MNI volumetric data with fsaverage surface data. So far I have been using mri_vol2surf with target subject being fsaverage (with a supplied affine correction matrix), but this solution is far from optimal since fsaverage folding patterns are quite different from MNI. I was thinking that maybe a more accurate way of dealing with this would be to reconstruct MNI152 cortical surface model, do surface registration of it to fsaverage, and use that to sample statistical maps in MNI space. What do you think?
I would probably go the other direction, ie, sample the MNI152 maps into surface space.
This is exactly what I want to do. The question is what is the most accurate way of sampling MNI152 maps to fsaverage?
Best, Chris
Thank you for any help feedback you can provide!
Best, Chris Gorgolewski
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