The label will be totally off because it was not created in the conformed anatomical space of fsaverage. Does the mask look ok? If you want to view the label, use something like
tkmedit -f $SUBJECTS_DIR/fsaverage/mri.2mm/orig.mgz -ov sig.mgh -seg $SUBJECTS_DIR/fsaverage/mri.2mm/aseg.mgz
doug
On 11/19/2013 08:41 AM, Suzanne Oosterwijk wrote:
Hi Doug,
I use the following command to open tkmedit and then I load the mask, the ocn.mgh file or the original label (created by mri_binarize) as a segmentation (through the tkmedit menu). In this case a label does open, but it is totally off.
tkmedit fsaverage orig.mgz -aux brain.mgz -bc-main-fsavg -overlay /home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_functional/ff_image/feedback_gamma_image_vol/omnibus/glm.amygdala/osgm/sig.mgh -fthresh 2.3 -fmax 4 -aparc+aseg
Thanks!
Suzanne
On Thu, Nov 14, 2013 at 8:48 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:
What is your tkmedit command used to view the segmentation?
doug
On 11/14/2013 07:10 AM, Suzanne Oosterwijk wrote:
Hi Doug,
Thanks for the code, this works. Nevertheless, I am a bit
unsure about whether the masks that are used as input into
this command are correct. I like to check all the stages of
the process and when I open the mask.mgh file within the
appropriate glm folder, the segmentation is totally off (the
putamen is somewhere in the OFC). Furthermore, even though the
file that holds the output cluster from the Monte Carlo
simulation (mc-z.pos.23.lh.sig.cluster.mgh) seems correct, the
segmentation file that I use as input into the mri_segstats
command is also totally off (mc-z.pos.23.lh.sig.ocn.mgh) when
I load it in tkmedit. Am I loading it incorrectly as a
segmentation? Does this have anything to do with the fact that
you advised me to use the 2mm version
fsaverage/mri.2mm/aseg.mgz? Should I adapt for that in my
tkmedit command?
Finally, I also run into a problem with the nucleus accumbens
specifically. For some reason I get an error when I run the
glmfit and mc simulation within this specific mask. First I
make the mask:
mri_binarize --match 26 --i
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/fsaverage/mri.2mm/aseg.mgz
--o
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/ROI_handmade_labels/accumb_lh.mgz
Then I run glmfit:
set labels = (accumb)
foreach label ($labels)
mri_glmfit --y ces.nii.gz --osgm --glmdir glm.${label} --mask
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/ROI_handmade_labels/${label}_lh.mgz
mri_glmfit-sim --glmdir glm.${label} --sim mc-z 10000 2.3
mc-z.pos.23.lh --sim-sign pos
end
But I get an error saying:
FWHM = -nan
ERROR: input FWHM is NaN (not a number).
Check the mask in the glm directory.
Any ideas what I am doing wrong?
Thanks again!
Suzanne
On Tue, Nov 5, 2013 at 12:04 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu><tel:617-726-7422 <tel:617-726-7422>> <tel:617-726-7422<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>> wrote:
Hi Suzanne, there is probably an easier way to do this. If you
create contrasts of each condition vs baseline then run
isxconcat-sess on each, you can then run something like
mri_segstats --seg mc-z.pos.23.lh.sig.ocn.mgh --i
condition1.nii.gz --avgwf condition1.table.dat --excludeid 0
where condition1.nii.gz is the output of isxconcat-sess for
condition 1. The output fo mri_segstats will be
condition1.table.dat which will have a row for each
subject and a
column for each of the clusters
doug
On 11/01/2013 09:51 AM, Suzanne Oosterwijk wrote:
Hello again,
I am stuck again in my analysis and I am not sure that
my code
is right. I want to do the following. With a Monte Carlo
simulation I search for significant clusters within a
particular ROI in my all conditions vs baseline
contrast. Then
I want to translate this functional cluster to each
individuals native space (as a label) and extract percent
signal change for each condition separately from that
label.
This is no problem in my surface analysis, but I am
not sure
how to do this in the volume. I ran the Monte Carlo
simulation
within the mask, which provides a segmentation called
mc-z.pos.23.lh.sig.ocn.mgh. I assume that this would
be the
label that would go into mri_vol2vol to translate the
cluster
to native space. I found on the website, however, that you
need to use tkregister first. So I used the following
code,
but I am doubtful about whether I am doing this right.
tkregister2 --mov
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_functional/ff_image/feedback_gamma_image_vol
/omnibus/glm.amygdala/osgm/mc-z.pos.23.lh.sig.ocn.mgh --s
ff_01_030512 --regheader --reg
ff_01_030512/register.dat --surf
The results of this command do not look good at
all....(see
attached image). The cluster in the -mov file does not
overlap
with the amygdala. For the next step, I assumed to use
mri_vol2vol to save the cluster as a native space label,
although I'd like to make sure the first step is correct
before continuing with this step.
mri_vol2vol --mov
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_functional/ff_image/feedback_gamma_image_vol
/omnibus/glm.amygdala/osgm/mc-z.pos.23.lh.sig.ocn.mgh
--reg
ff_01_030512/register.dat --fstarg --interp nearest --o
ff_01_030512/label/lh.amygdala.imact.mgz --s ff_01_030512
What am I missing? Is the translation off because I did
something wrong, or does that point to a deeper issue?
Any help is much appreciated!
Suzanne
On Tue, Oct 29, 2013 at 6:04 PM, Douglas N Greve
<greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>> wrote:
Hi suzanne, you'll need to use the 2mm version
fsaverage/mri.2mm/aseg.mgz
doug
On 10/29/2013 11:46 AM, Suzanne Oosterwijk wrote:
> Hello all,
>
> I want to run a Monte Carlo simulation within a
volume
ROI and I am
> running into a problem when I use the --mask
flag while
running
> glmfit. My question is very similar to the
question asked in
> "[Freesurfer] Volume-based Monte Carlo
Restricted to a
within mask
> area" but I could not find the response to this
question.
>
> Here is my code.
>
> First, I created a volume mask with mri_binarize:
>
> mri_binarize --match 18 --i
>
home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/fsaverage/mri/aseg.mgz
> --o
>
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/ROI_handmade_labels/amygdala_lh.mgz
>
> I checked the mask and it looked good. Then I
use the
mask in
glmfit.
>
> mri_glmfit --y ces.nii.gz --osgm --glmdir
glm.amygdala_lh --mask
>
/home/sooster1/Desktop/FALSE_FEEDBACK_imaging/DATA/feedback_structural/ROI_handmade_labels/amygdala_lh.mgz
>
> When I do this, I get the following error:
>
> ERROR: dimension mismatch 1 between y and mask
>
> I guess this means that the ces.nii.gz file and mask
file don't
match,
> but I have no idea how to solve this. Any thoughts?
>
> Thanks!
> Suzanne
>
>
> --
>
> Suzanne Oosterwijk, Ph.D.
>
> Postdoctoral Researcher
>
> Department of Social Psychology
>
> University of Amsterdam
>
> s.oosterwijk@u <mailto:s.oosterwijk@neu.edu
<mailto:s.oosterwijk@neu.edu>
<mailto:s.oosterwijk@neu.edu
<mailto:s.oosterwijk@neu.edu>>
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<mailto:s.oosterwijk@neu.edu>
<mailto:s.oosterwijk@neu.edu
<mailto:s.oosterwijk@neu.edu>>>>va.nl <http://va.nl>
<http://va.nl>
<http://va.nl> <http://va.nl>
>
> https://sites.google.com/site/suzanneoosterwijk/
>
>
>
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MGH-NMR Center
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Postdoctoral Researcher
Department of Social Psychology
University of Amsterdam
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-- Douglas N. Greve, Ph.D.
MGH-NMR Center
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--
Suzanne Oosterwijk, Ph.D.
Postdoctoral Researcher
Department of Social Psychology
University of Amsterdam
s.oosterwijk@u <mailto:s.oosterwijk@neu.edu
<mailto:s.oosterwijk@neu.edu>>va.nl <http://va.nl> <http://va.nl>
https://sites.google.com/site/suzanneoosterwijk/
-- Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>
Phone Number: 617-724-2358 <tel:617-724-2358>
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--
Suzanne Oosterwijk, Ph.D.
Postdoctoral Researcher
Department of Social Psychology
University of Amsterdam
s.oosterwijk@u <mailto:s.oosterwijk@neu.edu>va.nl <http://va.nl>
https://sites.google.com/site/suzanneoosterwijk/
--
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MGH-NMR Center
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Suzanne Oosterwijk, Ph.D.
Postdoctoral Researcher
Department of Social Psychology
University of Amsterdam