Hi Doug,

Thank you so much for your respond. Greatly appreciate it!!

I have one more question. If I run glm with FSGD and contrast file mentioned in my previous email, it should be DOSS, correct? However, when I tried to run it using the same FSGD, contrast and command mentioned in my previous email, the screen prints are telling me it is DODS as below:

INFO: gd2mtx_method is dods

I just want to confirm that I am using DOSS in this condition. And, if I want to use DODS, I will have to make two thickness file as -pvr inputs for each group, is this correct?

Thank you so much for your time.

Vicky

On Fri, Jan 10, 2020 at 11:22 AM Greve, Douglas N.,Ph.D. <DGREVE@mgh.harvard.edu> wrote:

Your FSGD and command look correct. As for whether it is a good idea or not, I'm not sure (you're probably the best person to decide that). One thing to keep in mind is that if there are true thickness differences you might see some differences due to partial voluming. I would also remove the mean of the thickness. You can so this with
mri_glmfit --surf fsaverage lh --osgm --y lh.thickness.sm10.mgz --o glm.osgm.lh --eres-save :
Then use glm.osgm.lh/eres.mgh as the PVR

On 1/8/2020 9:45 PM, Vicky Shi wrote:
External Email - Use Caution

Dear Freesurfer team,

I am running the glm analysis on CBF maps. I have two class and I want to see the group difference regressing out the cortex thickness. I know that I can add the average cortical thickness as one covariable in FSDG file. However, I think it might worth trying to do this with GLM by using a per vertex regressor (thickness).

My fsgd file is like below:

Class Patient

Class CTL

INPUT subj1 Patient

INPUT subj2 CTL

....

My command is below:

mri_glmfit --y lh.fsaverage.cbf.sm10.mgz --fsgd fsgd.txt --C contrast.mtx --glmdir lh.output.glmdir --surf fsaverage lh --pvr lh.thickness.sm10.mgz

My contrast matrix is -1 1 0.

I am wondering if what I do is correct or not. Does it make sense or I should use the mean thickness as regressor?

Thank you for your time!

Best regards,

Vicky
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