Hi Knut
There are a few confusing things in
your question post. First, it seems that your attached images are
depicting p-values. We usually use -log10(pvalue) format for visualization in
tksurfer. The sig.mgh file saved by lme should
be in that format. However we didn't use tksurfer to build the
figures for the paper you mentioned. We instead just used
matlab-based geometric objects and figures. Second, for mass-univariate
analyses the contrast
matrix is given to lme as a matlab structure CM.C = [0 0 1 0 0 0] not a plain
matrix C. Perhaps
you should try first the vertex-wise lme model to ensure that all
your parameters (design matrix, data matrix, contrast matrix, etc...) are
right and then give it a try to the more complex spatio-temporal lme model using
the same parameters.
eg.lhstats = lme_mass_fit_vw(X,[1
2],Y,ni,lhcortex);
Then
you can compare the results to have a better idea about what is going on.
Best
-Jorge
El Jueves 5 de diciembre de 2013 13:29, Martin Reuter
<mreu...@nmr.mgh.harvard.edu> escribió:
Hi Jorge,
>
>this was on the freesurfer list. Do you know what is going on ?
>
>Best, Martin
>
>
>
>
>-------- Original Message --------
>Subject: [Freesurfer] Problems with longitudinal analysis
>Date: Wed, 4 Dec 2013 22:04:07 +0100
>From: Knut J Bjuland <knutjor...@outlook.com>
>To: freesurfer <freesurfer@nmr.mgh.harvard.edu>
>
>
>Hi, I have used a linear mixed model for longitudinal data analysis on a
FreeSurfer 5.3, Matlab 2013b on a system with Ubuntu 12.04. I used mris_preproc
--qdec-long qdec.table.dat --target fsaverage --hemi
lh --meas thickness --out lh.thickness.mgh to concatenate thickness surf
files, and smoothed with mri_surf2surf --hemi lh --s fsaverage --sval
lh.thickness.mgh --tval lh.thickness_sm30.mgh --fwhm-trg 30 --cortex
–noreshape. I then used the same command and options in a Matlab script, as
shown at http://freesurfer.net/fswiki/LinearMixedEffectsModel found in the
example for mass-univariate data analyses. . I used this design matrix:
interception, time, group, group*time,
gender, gender*time, and I used two random effect on interception and
time. I did not compare the two random effect models with one random
effect model. I used this contrast vector C=[0 0 1 0 0] for these images which
are
included in the email. The script ran fine but when I looked at sig.mgh, it
contained many
visible quadrate shapes boxes even after FDR correction, and the
image looks quite different than the image in the paper in Neuroimage
(Spatiotemporal Linear Mixed Effects Modeling for the Mass-univariate
Analysis of Longitudinal ). Any idea what went wrong here? Thank you! Best
regards,
Knut Jørgen
>
>
>
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