On 6/20/2022 3:42 PM, Julian Macoveanu wrote:

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Dear Freesurfers,

I have a simple design with patients and controls and would like to find regions showing group differences in cortical volume and thickness. I also remove the effect of age, sex and ICV. Running the GLM group analysis by the book I get a few clusters showing significant differences in intercept.

1. I interpret this like patients have smaller “predicted” regional

volume at age 0, or at mean age of the group (if demeaned age covariate) compared to controls. How can this finding be described in a more clinically meaningful way?

I'm not sure what you mean here. It seems like you have the interpretation correct.

2. Related to the above, how do I visualize what is going on in the

significant clusters? The extracted values from these clusters (ocn.dat) show no group differences in volume when displaying the group means in SPSS (using either age/sex/ICV adjusted or non-adjusted values). Maybe I am misunderstanding something, how can there be differences in intercept but no differences between group means? (slopes not significantly different). How do I best describe and visualize this group difference in a paper?

You are probably not using the same model as mri_glmfit is using. You can try to feed the ocn.dat into the same mri_glmfit command with the --table option instead of --y. If you are going to do this, you will need to create a new table with the first column being the subject name and the first row being the clustername (eg, Cluster1, Cluster2, etc). The very first element (col=1 row=1) can be a dummy string (eg, "dummy") so that the table is complete.

Julian

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