This file is created when you run reg-feat2anat and should be the one
that gets changed with --manxfm func2anat. You can handle this
differently if you
1. Manually edit the anat2exf.register.dat so that it is relatively
close (no need to be perfect)
cd feat/reg/freesurfer
tkregister2 --mov
Hi,
I have generated two different functional connectivity maps for two
different ROI-based seeds. These maps are based on group-average of the same
subjects (generated by using separate isxconcat-sess commands ), and now I
want to see the difference map. To do so, I used mris_calc as below.
Hi Shahin, it is not as simple as doing a subtraction of the cesvar
files. What you are trying to get is the expected variance of your
difference between the ces files (as a variance, it must be positive).
To get this you need
cesvardiff = (cesvar1+cesvar2)/(2^2)
The 2^2 is the number of
Hi Ping - Do the corresponding brain masks in diffusion space
(dlabel/diff/aparc+aseg_mask.bbr.nii.gz and aparc+aseg_mask.flt.nii.gz)
now cover the entire brain well, after the aparc+aseg fixes?
a.y
On Tue, 18 Oct 2011, Ping-Hong Yeh wrote:
Hi Anastasia,
I got fixed of the aparc+aseg
Thanks Doug. Just one related question. Should I also generate a new
ffxdof.dat file for this map? I assumed that ffxdof depends on the number of
subjects (session) and since number of subjects (sessions) is the same
between the two groups then I can use those values, generated by
It should be roughly the sum of the dofs of the individual subjects. Why
are you using a fixed-effects model?
doug
SHAHIN NASR wrote:
Thanks Doug. Just one related question. Should I also generate a
new ffxdof.dat file for this map? I assumed that ffxdof depends on the
number of
Do you suggest using random-effect model? Is there any problem with using a
fix-effect model (other than the fact that by using this model we can not
predict response of subjects outside our population)?
On Wed, Oct 19, 2011 at 3:07 PM, Douglas N Greve
gr...@nmr.mgh.harvard.eduwrote:
It should
If you don't care about extending your results beyond your sample, then
an FFx is fine.
doug
SHAHIN NASR wrote:
Do you suggest using random-effect model? Is there any problem with
using a fix-effect model (other than the fact that by using this model
we can not predict response of subjects
The mask sort of covers the whole brain (see attached). It may be due
to the display thresholding, when I viewed the path.pd.nii.gz using
fslview, the tract actually has been recovered as compared to the
previous one (old_path.png).
However, the path.pd still does seem normal, i.e. with quite a
Dear FreeSurfer Gurus,
We are looking for a way to normalize the intensity histogram for our
subjects. In the past we have used Brain Image Java, using FSL-Fast
inhomogeneity corrections. Unfortunately we are unable to open the output
files (.img, .hdr) in FreeSurfer. When trying to import the
Hi Christopher
try outputing nifti from FSL instead of analyze and see if that helps.
Don't go through analyze at all.
cheers,
Bruce
On Wed, 19 Oct 2011,
Christopher McCarthy wrote:
Dear FreeSurfer Gurus,
We are looking for a way to normalize the intensity histogram for our
subjects.
Glad things are moving in the right direction. Now it looks like maybe one
of the control points of the path is not moving around, which is why you
get that very bright thin spot in the distribution. I can't tell by
looking at that one slice of the mask only, but could it be that there
Hi Michelle, try this:
isxconcat-sess -sf sessidlist -a rtopy.fsaverage.lh -call -o retgroup
cd retgroup/rtopy.fsaverage.lh
mri_glmfit --y eccen/ces.000.nii.gz --osgm --o eccen/glm.real --surface
fsaverage lh
mri_glmfit --y eccen/ces.001.nii.gz --osgm --o eccen/glm.imag --surface
fsaverage lh
Hi Doug,
Thank you for your help with this. So when I looked at the maps, two issues
arose.
1) The fieldsign map looks like it needs lots of smoothing. When I ran the
individual subjects on the surface, I smoothed by 20 during fieldsign-sess.
Is it still appropriate/can one smooth at the
Hello,
I am working on comparing hand-drawn subcortical volumes to those output
automatically by FreeSurfer. While reading about the segmentation process on
the wiki, I came across this line:
The final segmentation is based on both a subject-independent probabilistic
atlas and
no, we created our own atlas by manually labeling 39 subjects according
to the CMA conventions, then iteratively going back over them to correct
for consistent inaccuracies in the manual labelings. It's still an ongoing
process as we are currently working on improving the manual putamen labels.
16 matches
Mail list logo
