External Email - Use Caution THank you so much for your help!
Le lun. 18 mars 2019 à 16:32, Greve, Douglas N.,Ph.D. < dgr...@mgh.harvard.edu> a écrit : > The vertices chosen for the cluster depend only on the cluster forming > threshold (CFT). Once that is chosen, the vertices in the cluster are > fixed. The permutation judges how likely the cluster as a whole would be > seen by chance. There are other ways to do permutation, but this is the way > we do it. > > > On 3/18/19 11:25 AM, Giuliana Klencklen wrote: > > External Email - Use Caution > Ok, well then I do not understand the purpose of the permutation testing > if the number of permutation would not change the size of the clusters. > What is it doing if not refining what vertices are significant? Perhaps I > am just missing a key idea. > > Best, > > > On Thu, Mar 14, 2019 at 5:11 PM Greve, Douglas N.,Ph.D. < > dgr...@mgh.harvard.edu> wrote: > >> The size of the cluster is not going to be affected by the number of >> iterations (only by the threshold). Why would you think that the cluster >> size is affected by the number of iterations? >> >> On 3/14/19 5:45 AM, Giuliana Klencklen wrote: >> > >> > External Email - Use Caution >> > >> > Hi Douglas, >> > >> > According to your suggestion, I used the permutation simulation >> > approach. I chose a cluster forming threshold set at 0.05 and explored >> > how the number of iterations effects the data. For example, I used >> > this command for 1,000 iterations: >> > mri_glmfit-sim \ >> > --glmdir lh.longMRI.glmdir \ >> > --sim perm 1000 1.3 perm.abs.13 \ >> > --sim-sign abs\ >> > --cwpvalthresh 0.05 >> > >> > I did not observe any difference on the size of the cluster between >> > 1,000 vs 5,000 vs 10,000 iterations. As I thought the results were >> > pretty odd, I tried running the command with 5 permutations just to >> > make sure it's not also the same and I did not find any significant >> > clusters. >> > >> > Is the absence of cluster size difference between different number of >> > iterations expected? Just wanted to make sure with you that this >> > approach is working as it should. >> > >> > Thanks! >> > Regards, >> > >> > On Fri, Feb 22, 2019 at 6:50 PM Greve, Douglas N.,Ph.D. >> > <dgr...@mgh.harvard.edu <mailto:dgr...@mgh.harvard.edu>> wrote: >> > >> > 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: >> >> >> >> External Email - Use Caution >> >> >> >> 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 >> >> QdecGroupComparison.jpg >> >> >> >> On Fri, Feb 15, 2019 at 5:24 PM Greve, Douglas N.,Ph.D. >> >> <dgr...@mgh.harvard.edu <mailto:dgr...@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: >> >>> >> >>> External Email - Use Caution >> >>> >> >>> 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.klenck...@berkeley.edu >> >>> <mailto:giuliana.klenck...@berkeley.edu> >> >>> >> >>> _______________________________________________ >> >>> Freesurfer mailing list >> >>> Freesurfer@nmr.mgh.harvard.edu <mailto: >> Freesurfer@nmr.mgh.harvard.edu> >> >>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >> >> >> _______________________________________________ >> >> Freesurfer mailing list >> >> Freesurfer@nmr.mgh.harvard.edu >> >> <mailto:Freesurfer@nmr.mgh.harvard.edu> >> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >> >> >> >> >> >> >> -- >> >> Giuliana Klencklen, Ph.D. >> >> >> >> Helen Wills Neuroscience Institute >> >> University of California, Berkeley >> >> 118 Barker Hall >> >> Berkeley, CA 94720-3190 >> >> 510-395-0040 >> >> giuliana.klenck...@berkeley.edu >> >> <mailto:giuliana.klenck...@berkeley.edu> >> >> >> >> _______________________________________________ >> >> Freesurfer mailing list >> >> Freesurfer@nmr.mgh.harvard.edu <mailto: >> Freesurfer@nmr.mgh.harvard.edu> >> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> > >> > _______________________________________________ >> > Freesurfer mailing list >> > Freesurfer@nmr.mgh.harvard.edu <mailto: >> Freesurfer@nmr.mgh.harvard.edu> >> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> > >> > >> > >> > -- >> > Giuliana Klencklen, Ph.D. >> > >> > Helen Wills Neuroscience Institute >> > University of California, Berkeley >> > 118 Barker Hall >> > Berkeley, CA 94720-3190 >> > 510-395-0040 >> > giuliana.klenck...@berkeley.edu <mailto:giuliana.klenck...@berkeley.edu >> > >> > >> > _______________________________________________ >> > Freesurfer mailing list >> > Freesurfer@nmr.mgh.harvard.edu >> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer@nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > > -- > Giuliana Klencklen, Ph.D. > > Helen Wills Neuroscience Institute > University of California, Berkeley > 118 Barker Hall > Berkeley, CA 94720-3190 > 510-395-0040 > giuliana.klenck...@berkeley.edu > > _______________________________________________ > Freesurfer mailing > listfreesur...@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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