Perfect, thanks so much for the quick response!

 

 

 

 

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Dear Freesurfer experts,

I have what seems like a simple problem, and I’m sure there is a method for doing this, hoping someone can give me some guidance.

We have results from an LME model run on surface data, and then run through PALM to calculate FWE-corrected p-values from the LME.  We now would like to extract the mean beta values from each anatomical label region, within regions that were significant at p-corrected < 0.05.  The beta values (as well as the PALM p-values) are contained in an mgz surface file.

So, what I think is needed is:

1)     Create mask images for each individual label index, e.g. lh.caudalmiddlefrontal

You can do this in one of two ways:
A. Use mri_annotation2label to create a "segmentation", then use mri_binarize with --match to pull out each label as a mask
B. Use mri_annotation2label to break the annotation into separate labels, then use mri_label2label to create a binary mask

2)     Create mask image from PALM results, for p < 0.05

Not sure about this, but you might be able to use mri_binarize with --max .05

3)     Multiply mask * label * beta, and calculate mean value in that region

fscalc mask.mgz mul labelmask.mgz mul beta.mgz -o result.mgz

So, my simple question is what are the appropriate FS commands for performing this (or alternatively Matlab commands), or is there a simpler way or extracting these values?

Thanks for any advice you can give us on this.

 

Mark

 

____________________
Mark Wagshul, PhD
Associate Professor
Gruss Magnetic Resonance Research Center
Albert Einstein College of Medicine
Bronx, NY 10461

Ph: 718-430-4011

FAX: 718-430-3399

Email: mark.wagshul@einsteinmed.org

 

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