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Hi Doug,
For your questions:
1. "Not sure what you mean by in the ROI. Are you trying to permute
across space? That generally does not work because the points are not
exchangeable across space."
By "In the ROI", I mean for all vertices listed in the label file.
Here, I am talking about a test subject and n control subjects, they
are all considered in the same reference subject space - fsaverage. A
ROI is defined by a label file for the subject fsaverage. So, I am
comparing the test subject and control group on the same ROI region,
vertex by vertex. I want to permute points in the test subject and
points in all subjects in control groups.
I am not talking about permuting vertex locations; I am talking about
permuting values (thickness in my case) from subjects on each vertex.
For example, for vertex i, I have one value (v0) from test subject,
and n values (v1, v2,...vn) from control subjects:
test subject control subjects
v0 v1, v2, ...... vn
One way of permutation would be:
test subject control subjects
v1 v0, v2, ...... vn
Is this a reasonable way to do permutation?
2. "Not sure. You cannot discriminate between the groups when you are
doing permutation"
By doing the permutation many (say 1000) times, I want to get the
probability distribution of the sampling (observed or test) data
inside the ROI area, so that I can decide if I should reject or accept
null hypothesis based on cluster-wise significance level. What
problems do you think I have in this idea?
Thanks a lot!
On 7/21/2020 1:12 AM, Xiaojiang Yang wrote:
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Dear FS experts,
Instead of using mri_glmfit-sim, I am trying to implement a customized multiple
comparison correction algorithm using permutation. Before I implement my
own, I want to make sure my permutation idea is correct. So I was looking
at how mri_glmfit-sim does the permutation. The link here
http://freesurfer.net/fswiki/FsTutorial/MultipleComparisonsV6.0Perm has a
simple description for how to do permutation, but I don't quite understand
the 1st step: Permute the design matrix. To me, permute the design matrix
means permute the matrix rows here, but still hard to understand why
permuting matrix rows does the trick.
This is pretty standard in permutation. I think Tom Nichols has some basic
tutorials on how permutations work.
Anyway, I will not use any design matrix in my customized implementation,
so it does not matter for now. My problem can be described as follows: if I
have a ROI (a label file) on fsaverage, and I have a test subject and a
group of control subjects whose thickness values on every vertex in this
label are all known. (The test subject and control subjects are all using
fsaverage reference space). I want to compare this test subject's
thickness within
the ROI to a control group of subjects (within the same ROI). This is a
multiple-comparison problem, so I want to use permutation to get less FP
rate. My question is: How do I permute the test subject's points and
control subjects' points in ROI?
Not sure what you mean by in the ROI. Are you trying to permute across space?
That generally does not work because the points are not exchangeable across
space.
My understanding is that: for each point in the label, I randomly re-assign
all (1+n) values from (1+n) subjects to these (n+1) subjects (where n is
the number of subjects in control group). And when all points in the label
are done, this is only 1 permutation. I will need at least 1000 times of
permutation to get the comparison statistics.
Is my understanding right?
Not sure. You cannot discriminate between the groups when you are doing
permutation
Thank you!
Xiao
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