Are you setting the cwp to .01? The cwp controls the threshold for cluster significance. The number after "--cache" controls the cluster-forming threshold
Antonella Kis wrote:
Hi Doug,
Since running mri_glmfit-sim will do a correction by multiple comparison (I suppose is doing a Monte Carlo to remove areas that are not statically significant) I wonder why I still get clusters with p>0.01? Do I need to apply FDR before -sim?
Thank you for your time and help. Antonella
*From:* Douglas N Greve greve@nmr.mgh.harvard.edu *To:* Bruce Fischl fischl@nmr.mgh.harvard.edu *Cc:* Antonella Kis atorok9@yahoo.com; "freesurfer@nmr.mgh.harvard.edu" freesurfer@nmr.mgh.harvard.edu *Sent:* Thursday, August 25, 2011 12:23 PM *Subject:* Re: [Freesurfer] Fw: fsaverage
That "2" is a voxel-wise threshold used to form the cluster. The cwp is a cluster-wise threshold used to eliminate non-significant clusters from the output.
Bruce Fischl wrote:
I'll leave that for Doug On Thu, 25 Aug 2011, Antonella Kis wrote:
Hi Bruce,
Thank you very much for your prompt and helpful answer.
I have one more question, please: I do not understand what's the role of adding the threshold value while running the mri_glmfit-sim with --cache since after adding the threshold 2, I still get clusters with cwp>.01. This is what I was running:
mri_glmfit-sim \ --glmdir rh.age.glmdir \ --cache 2 neg \ --cwpvalthresh .025 \ --overwrite
And this is my output:
# ClusterNo Max VtxMax Size(mm^2) MNIX MNIY MNIZ CWP CWPLow CWPHi NVtxs Annot
1 -6.24 104279 2004.41 6.4 -83.6 34.4 0.0001 0 0 3539 cuneus
2 -5.71 56656 2923.03 24.4 25.4 37.1 0.0001 0 0 5020 superiorfrontal
3 -4.89 156133 1826.82 5.1 -29.7 38.6 0.0001 0 0 4324 posteriorcingulate
4 -4.57 117278 1917.42 43.2 43.4 -8.2 0.0001 0 0 3393 parsorbitalis
5 -4.32 134603 910.13 10.5 45.7 -9.2 0.0009 0 0 1597 medialorbitofrontal
6 -4.01 47845 1018.06 38.9 -73.9 34.6 0.0003 0 0 1802 inferiorparietal
7 -3.97 12268 580.81 14.2 -51 63.3 0.0132 0.01 0.01 1415 superiorparietal
8 -3.78 54798 871.02 53 -39.7 -5.1 0.0010 0 0 1969 bankssts
9 -3.78 21941 555.51 45.8 -28.2 6.4 0.0175 0.02 0.02 1369 superiortemporal
10 -2.91 86118 884.25 10.1 -98.9 11.7 0.0010 0 0 1089 lateraloccipital
11 -2.86 13271 674.26 21.5 -65.4 -6.1 0.0056 0 0.01 722 lingual
Is this right?
Also, by adding for the lh --cwpvalthresh .025 what exactly means or how the corrections are made for both hemispheres. I know --cwpvalthresh .025 shows only clusters p<.025 but then what means cluster significance values not corrected for 2 spaces? Please advise.
Thank you. Antonella
From: Douglas N Greve <greve@nmr.mgh.harvard.edu
mailto:greve@nmr.mgh.harvard.edu>
To: Antonella Kis <atorok9@yahoo.com mailto:atorok9@yahoo.com> Cc: "freesurfer@nmr.mgh.harvard.edu
mailto:freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu mailto:freesurfer@nmr.mgh.harvard.edu>
Sent: Tuesday, August 23, 2011 4:33 PM Subject: Re: [Freesurfer] correction for multiple comparisons
Yes, that is correct, you should use .025 if you are correcting for
both
hemispheres. doug
Antonella Kis wrote:
Hi Doug,
I would like to run the correction for multiple comparisons. I know glmfit-sim corrects for multiple comparisons. My question is:
the corrections for multiple comparisons will be done while running
mri_glmfit-sim \ --glmdir rh.age.glmdir \ --cache 2 neg \ --overwrite
or I need to add --cwpvalthresh .025 before --overwrite. I found on-line that setting a treshold = 2 means p < 0.05 but adding --cwpvalthresh .025 will do the correction across 2 spaces: lh
and rh:
.025 = .05/2 Bonferroni Correction and will show only the clusters with p<.025.
Is this right? So to run for multiple corrections in fact I will need to run:
mri_glmfit-sim \ --glmdir rh.age.glmdir \ --cache 2 neg \ --cwpvalthresh .025 --overwrite
Please advise me.
Thank you for your time and help. Antonella
*From:* Douglas N Greve <greve@nmr.mgh.harvard.edu
mailto:greve@nmr.mgh.harvard.edu>
*To:* Antonella Kis <atorok9@yahoo.com mailto:atorok9@yahoo.com> *Cc:* "freesurfer@nmr.mgh.harvard.edu
mailto:freesurfer@nmr.mgh.harvard.edu"
<freesurfer@nmr.mgh.harvard.edu
mailto:freesurfer@nmr.mgh.harvard.edu>
*Sent:* Monday, August 22, 2011 2:28 PM *Subject:* Re: [Freesurfer] GLM or Qdec ?
Antonella Kis wrote:
Dear FS experts,
I finished running the GLM and I wonder what is the best way to further analyse my data in order to see if there is any relation between age (at seizure onset) and cortical thickness for my
patients
versus control group.
1). Why when I overlay the sig.mgh in tksurfer lh inflated, I get more clusters than the number of clusters obtained from
mri_glmfit-sim?
When you look at it in tksurfer, you are looking at uncorrected data. glmfit-sim corrects for multiple comparisons. Some of the clusters
don't
survive.
2). What sig.mgh represents?
-log10(p)
- What's the real significance of a cluster (how a cluster is
formed)?
It is based on the likelihood of getting a cluster of that size by chance given the search space (cortical surface area), smoothness (FWHM), and cluster-forming threshold (eg, p<.05).
4). Why my thickness value in clusters (eg cluster no. 1 which coresponds to the posteriorcingulate) for subject no.1 is different that the thickness value obtained for the same region in the lh.aparc.stats while running recon-all?
5). After running the GLM should I use visualizing and plotting
method
to further analyse my data and load FSGD file lh.gender_age.glmdir/y.fsgd?
6). Should my ROI's be defined or be the same with my clusters?
I don't know what you mean by that.
7). What is the difference between GLM and Qdec? What method is the best to analyse the relation between age and cortical
thickness for
my patients versus control group?
They are the same statistically. They are just different ways to
provide
information about your design and contrasts. QDEC is graphical (point and click). mri_glmfit you create FSGD files and run it from the command-line. QDEC actually creates FSGD files and contrast files and runs mri_glmfit.
8). Why when analysing with Qdec I get more clusters? Are this defining or representing the sig.mgh as in GLM?
They should give identical results when run in the same way. My
guess is
that you have created two different designs and so are getting
different
answers.
9). When using Qdec were I can find as an output of results the number of clusters and the cortical thickness value?
You'll have to run the correction for multiple comparisons
(interface on
the results page). This simply runs mri_glmfit-sim.
doug
Thank you and have a great day! Antonella
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Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: www.nmr.mgh.harvard.edu/facility/filedrop/index.html