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Hi Tom,
basically most of it looks OK to me, just a few remarks:
I assume that you deliberately chose the plain mass-univariate approach instead
of the potentially more powerful spatiotemporal mass-univariate approach.
For the interpretation of the intercepts, if desired, it may be advantageous to
code sex as 0 and 1, and de-mean age. But that's not strictly necessary.
I suspect that it's just a typo, so just for the sake of completeness: for
contrast estimation, I don't think that using CM.C1, CM.C2, etc. would work, as
the program expects a 'C' substructure. So instead, one would use CM1.C, CM2.C
etc for the different contrasts, if I am not mistaken.
About the mri_surfcluster command: if you want to do the FDR2 inference as
suggested by the LME tutorial, just use the 'pth' value as returned by the
lme_mass_FDR2 script for thresholding. I believe that you are mixing different
kinds of inference (traditional FDR, clusterwise) otherwise.
Finally, if you want to make corrected inferences for the whole cortex, it's
probably better to compute one (FDR2) threshold for both hemispheres at once
(see the very last part of the tutorial) instead of treating them separately.
And regarding your specific questions:
The order is fine.
You can visualize the 'spval_lh.mgh' by first loading e.g. the 'lh.inflated'
surface of the fsaverage template, and then adding 'spval_lh.mgh' as an
overlay. Same with e.g. 'rh.inflated' for the 'spval_rh.mgh' file.
About the Monte Carlo correction for this type of analysis others may know
better, sorry.
Best regards,
Kersten
On So, 2019-07-21 at 21:50 +0200, tom parker wrote:
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Dear all,
I am currently running a Mass-Univariate LME analysis in Freesurfer. I have
some doubts about the last steps and I was wondering whether someone could help
me figure them out and also check what I have done so far (sorry for the long
email).
My study has 2 time points (baseline, follow-up), 3 groups (controls, patients
without cognitive problems, patients with cognitive problems) and 2 covariates
of no interest (age, sex).
I am interested in looking at the interactions between group and time (mainly
whether the 2 patient groups show more cortical thinning over time compared to
controls).
These are the commands I have ran so far through terminal or in matlab:
1)
mris_preproc --qdec-long long.qdec.table.dat --target fsaverage --hemi lh
--meas thickness --out lh.thickness.mgh
mris_preproc --qdec-long long.qdec.table.dat --target fsaverage --hemi rh
--meas thickness --out rh.thickness.mgh
2)
mri_surf2surf --hemi lh --s fsaverage --sval lh.thickness.mgh --tval
lh.thickness_sm15.mgh --fwhm-trg 15 --cortex --noreshape
mri_surf2surf --hemi rh --s fsaverage --sval rh.thickness.mgh --tval
rh.thickness_sm15.mgh --fwhm-trg 15 --cortex --noreshape
3)
[Y,mri] = fs_read_Y('lh.thickness_sm15.mgh');
[Y,mri] = fs_read_Y('rh.thickness_sm15.mgh');
4)
lhsphere = fs_read_surf('fsaverage/surf/lh.sphere')
rhsphere = fs_read_surf('fsaverage/surf/rh.sphere')
lhcortex = fs_read_label('fsaverage/label/lh.cortex.label')
rhcortex = fs_read_label('fsaverage/label/rh.cortex.label')
5) Create X matrix in matlab, here is a sample:
intercept time group2 group2*time group3 group3*time age
sex
1 0 0 0 0
0 41 1
1 2.42 0 0 0
0 41 1
1 0 1 0 0
0 53 1
1 2.5 1 2.5 0
0 53 1
1 0 0 0 0
0 54 2
1 5.25 0 0 0
0 54 2
5)
lhstats = lme_mass_fit_vw(X, [1], Y, ni, lhcortex);
rhstats = lme_mass_fit_vw(X, [1], Y, ni, rhcortex);
6)
I entered 3 contrasts separately to check the interaction group*time.
CM.C1 = [0 0 0 1 0 0 0 0]; this contrast will show if group 1 and 2 show a
different cortical thinning pattern over time
CM.C2 = [0 0 0 0 0 1 0 0]; this contrast will show if group 1 and 3 show a
different cortical thinning pattern over time
CM.C3 = [0 0 0 -1 0 1 0 0]; this contrast will show if group 2 and 3 show a
different cortical thinning pattern over time
7)
For each of the previous contrasts, i did the following:
F_lhstats = lme_mass_F(lhstats, CM);
F_rhstats = lme_mass_F(rhstats, CM);
fs_write_fstats(F_lhstats, mri,' sigL.mgh', 'sig');
fs_write_fstats(F_rhstats, mri,' sigR.mgh', 'sig');
mri.volsz(4) = 1
[detvtx,sided_pval,pth] =
lme_mass_FDR2(F_lhstats.pval,F_lhstats.sgn,lhcortex,0.05,0);
[detvtx,sided_pval,pth] =
lme_mass_FDR2(F_rhstats.pval,F_rhstats.sgn,rhcortex,0.05,0);
8)
fs_write_Y(sided_pval,mri,'spval_lh.mgh');
fs_write_Y(sided_pval,mri,'spval_rh.mgh');
mri_surfcluster --subject fsaverage --hemi lh --in spval_lh.mgh --cwpvalthresh
0.05 --fdr 0.05 --sign pos --o lh_time_cluster --sum lh_time_cluster_sum
mri_surfcluster --subject fsaverage --hemi rh --in spval_rh.mgh --cwpvalthresh
0.05 --fdr 0.05 --sign pos --o rh_time_cluster --sum rh_time_cluster_sum
My questions are:
- Is the order of the steps (1-8) correct?
- How can I visualize the significant FDR-corrected results?
- Is there any way I can apply a Monte Carlo correction using the generated
files?
Thank you so much!
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