mris_glm does not correct for multiple comparisons itself. However, you
can use fdr inside of tksurfer, or ...
Steve Smith and I just worked out how to use the FSL randomise program
to compute the vertex-wise threshold. Randomise implements permutation
testing, which is much less conservative than FDR or GRF.
When you run mris_glm, make sure to specify the --y output (something
like --y y-lh.mgh). then run mri_surf2surf to convert it to nifit,
something like:
mri_surf2surf --srcsubject average7 --trgsubject average7 \
--srcsurfval y-lh.mgh --src_type mgh \
--trg_type nii --trgsurfval y-lh.nii --hemi lh
You will also need to convert the design matrix produced by mris_glm
(something like y.X.mat) into ascii. This can be done in matlab with
something like:
load y.X.mat
save('X.asc','X','-ascii')
Then run:
randomise -i y-lh -o y-lh \
-d X.asc -t design.con -n 5000 -V
Where design.con has your contrasts
The output will be something like: y-lh_max_tstat1.mgh, which you can
view with tksurfer with something like:
tksurfer average7 lh inflated -overlay y-lh_max_tstat1.mgh
We're still working out the details on this (obviously:), you may have
to play with this a little to get the command lines exactly correct.
Note that randomise program cannot do cluster-based thresholding because
it is not aware that these values are really on the surface (not in a
volume), but the max stat will work.
doug
Antao Du wrote:
Hi,
I am running mris_glm to compare the cortical thickness between two groups.
I have a question, which method is used for correcting multiple comparison
in the analysis? Thanks,
Antao
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Douglas N. Greve, Ph.D.
MGH-NMR Center
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