You can make the bonferroni correction from of mri_glmfit-sim the same as qdec by not including --2spaces (the bonferroni correction in qdec is actually 1, not 0). Also, if you want to use such a low cluster forming threshold (1.3=p<.05), then you should use permutation and not MC (MC is not valid at such low thresholds).

On 2/22/19 7:49 AM, Giuliana Klencklen wrote:

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Thanks Douglas, that makes sense. I have run mri_glmfit-sim and have that table file.

However, the cortical thickness values for each cluster displayed in that table can’t be used because the clusters (something.sig.cluster.mgh opened with tksurfer) do not match exactly (but are very similar to) those previously generated with QDEC. I do not understand the cause of this issue because all the stats I used, i.e., threshold, statistical correction, level of smooting, seem to be the same between both qdec and mri_glmfit-sim. 

I send you here a typical example of the problematic clusters, as well as the summary for both qdec and mri_glmfit-sim. They appear similar except for the Bonferroni correction that is set at 2 for the mri_glmfit-sim while it is set at 0 for the qdec version? If it is the source of the current issue, how can I configure the Bonferroni correction? If not, do you have any idea how I can resolve the problem?

Many thanks in advance.

Regards,

Giuliana Klencklen

On Fri, Feb 15, 2019 at 5:24 PM Greve, Douglas N.,Ph.D. <DGREVE@mgh.harvard.edu> wrote:

This can happen if the label is small and/or you've used a lot of smoothing. It is better to do this kind of thing in fsaverage space rather than moving the labels back to the individual space. If you've run mri_glmfit-sim, then it should have created a table file  (something.y.ocn.dat). This file will have a row for each subject and a column for each cluster. The value will be the mean for that subject in that cluster.

On 2/15/19 6:23 AM, Giuliana Klencklen wrote:

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Hi FS experts,

I did group-level, surface-based, vertex-wise analysis for baseline and longitudinal data. I used Qdec and do the same work with the fsgd version (mri_glmfit-sim command) to double-check the data. 

I created label files with tksurfer for each of the clusters showing a significant between-group difference. Then, I used the following command stream to extract the cortical thickness values for each subject and cluster: mri_label2label, mris_anatomical_stats, and aparcstats2table.

E.g.,

mri_label2label --srcsubject fsaverage --srclabel /home/jagust/gklenck/Long_MRI/lh.ac-baseline-rostralmiddlefrontal.label --trgsubject ${s}_tp1 --trglabel ${s}_tp1/label/lh.ac-baseline-rostralmiddlefrontal.label --hemi lh --regmethod surface

mris_anatomical_stats -l lh.ac-baseline-rostralmiddlefrontal.label -t lh.thickness -b -f ${s}_tp1/stats/lh.ac-baseline-rostralmiddlefrontal.stats ${s}_tp1 lh

aparcstats2table --subjects ${s}_tp1 --hemi lh --parc ac-baseline-rostralmiddlefrontal --meas thickness --tablefile ${out_dir}/lh.ac-baseline-rostralmiddlefrontal.aparc_stats.txt

Subsequently, when I conducted between-group comparisons for each cluster, a couple of clusters (7 out of 16) do not show a significant difference - which does not make sense. This problem seems to appear randomly. 

Help to the FS archives, I tried to use mri_segstats command but was not able to find a correct combination of arguments. If this is the right track to solve this problem, what combination of arguments should I use? And if this is not, do you have any idea how I can solve this problem?

Many thanks in advance.

Regards,

Giuliana

--

Giuliana Klencklen, Ph.D.

Helen Wills Neuroscience Institute

University of California, Berkeley

118 Barker Hall 

Berkeley, CA 94720-3190
510-395-0040

giuliana.klencklen@berkeley.edu

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--

Giuliana Klencklen, Ph.D.

Helen Wills Neuroscience Institute

University of California, Berkeley

118 Barker Hall 

Berkeley, CA 94720-3190
510-395-0040

giuliana.klencklen@berkeley.edu

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Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

_______________________________________________
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Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer