The first command sets the voxel-wise threshold to p<.0001, which is
pretty strict by itself. Is that what you wanted? Do voxels survive
uncorrected at that level? The 2nd sets the voxelwise threshold at about
.05. In both cases the clusterwise correction is .05 (ie, neither are
0.9), so I'm not what it is that is going wrong.
doug
On 3/9/15 7:54 AM, Sofia Rodriguez Penuela wrote:
Dear all,
I’m trying to perform vertex-wise surface analysis on some PET data.
After performing the group contrast, significant differences
(uncorrected) are observed in a few clusters.These results apparently
do not survive the Monte Carlo method. In order to ensure that the
MC-z is working fine, I have repeated the MC-z only with two
simulations and have set the statistical threshold to either p < 0.05
or p < 0.9. I found no significant results in any case. So, I assume
that something must be wrong in the command line. I’m also planning to
do regression analyses, and perhaps I should do something different
when correcting for multiple comparisons with Monte Carlo.
Here are the commands used:
Command to create average subject:
make_average_subject --out avgsubject --subjects subj1 subj2 subj3 subj4
Commandtocreatetheaveragesurface:
mris_preproc --fsgd fsgd_variables.txt –target s00x_average --hemi
lh--meas SurfPet.mgh –out /ruta/lh.SurfPETpromedio.mgh
Commandtosmooththeavgsurface:
mri_surf2surf --hemi lh --s s00X_average --sval
/ruta/lh.SurfPETpromedio.mgh --fwhm 10 --cortex --tval
/ruta/lh.SurfPETpromedio_10mm.mgh
**
Commandtoperform GLM analysis
mri_glmfit--y $FS_HOME/mySubj_average
/my_lh_stats_dir/lh.SurfPETpromedio_10mm.mgh --fsgd
$FS_HOME/mySubj_average/my_lh_stats_dir/ fsgd_variables.txt dods --C
$FS_HOME/mySubj_average /my_lh_stats_dir/lh_contrast.mat --surf
mySubj_averagelh --label
$FS_HOME/mySubj_average/label/lh.cortex.label--no-prune
--glmdir$FS_HOME/mySubj_average/my_lh_stats_dir
Commandtocorrectformultiplecomparisonswith Monte Carlo as in theFSwiki:
mri_glmfit-sim --glmdir ruta\directorio --sim-sign pos --sim mc-z
10000 4 mcz-sim --cwp 0.05
Modifiedcommandtocorrectformultiplecomparisonswith Monte Carlo:
mri_glmfit-sim --glmdir ruta\directorio --sim-sign pos --sim mc-z
10000 1.3010 mcz-sim --cwpvalthresh 0.05 --seed 1297708255
Anyhelpwill behighlyappreciated.
Manythanks in advance,
Sofía Rodríguez Peñuela, Técnico de Laboratorio.
Laboratorio de Neurociencia Funcional
Departamento de Fisiología, Anatomía y Biología Celular.
Universidad Pablo de Olavide
Ctra. de Utrera, Km.1
41013 - Sevilla
- España -
Movil: 627273085
Email: srod...@upo.es
http://www.upo.es/neuroaging/es/
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