Hi Corinna,
You can download here: https://www.dropbox.com/s/yj1gbpmpgho7wtm/Yeo_JNeurophysiol11_SplitLabels.zi...
Regards, Thomas
On Thu, Jun 29, 2017 at 5:45 AM, Corinna Bauer corinnab83@gmail.com wrote:
Dear Dr. Yeo,
Our research group is currently trying to segment the Yeo atlas into separate labels, but just came across this thread which indicates that you have already done this. Would you be willing to re-share the link to your previously extracted individual labels from your 7 and 17 networks?
Thank you!
Corinna
On Thu, May 14, 2015 at 4:54 AM, Thomas Yeo ythomas@csail.mit.edu wrote:
Hi Annie,
I have previously extracted individual regions from the 7 and 17 networks. You can download them here (https://www.dropbox.com/s/u23nn3ov18tlhfs/Yeo_JNeurophysiol 11_SplitLabels.zip?dl=0). Please see the README in the folder for more explanations. There should be a precuneus DMN region.
The 17 networks consist of 114 regions that have been previously published:
- Krienen et al., Reconfigurable state-dependent functional coupling
modes cluster around a core functional architecture. Philosophical Transactions of the Royal Society B, 369:20130526, 2014
- Yeo et al., Functional connectivity during rested wakefulness
predicts vulnerability to sleep deprivation. Neuroimage 111:147-158, 2015
Hope this helps.
Cheers, Thomas
On Thu, May 14, 2015 at 3:08 PM, 陳昱潔 poohann1122@gmail.com wrote:
Hello Dr. Yeo,
Thank you for your previous help and reply. We've worked out the way to switch the resolution of parcellation and successfully extracted the anatomical information using your mask derived from iFC work.
However, we came across a new problem to apply the cortical mask and
need
your kind help again. We aim to conduct a seed-based analysis to
investigate
structural covariance based on the network defined by iFC, and find your work of cortical parcellation conceptually perfectly suit our research question. Based on the current approach, however, it seemed that we
could
only extract the anatomical information from the whole well-defined
network,
but not the specific hub within the network (e.g., the anatomical information of the precuneus from the DMN). We wonder if you have any suggestion to resolve our problem, ie, to be specific, is there any way
to
only extract the discrete hub information rather than the whole network?
We really appreciate your generous help. Thank you very much.
p.s. This email would also forward to my senior colleague, Dr.
Hsiang-Yuan
Lin, who is a child and adolescent psychiatrist doing imaging research
in
Taiwan.
2015-05-13 19:15 GMT+08:00 陳昱潔 poohann1122@gmail.com:
Hi Professor Yeo :
Thank you for helping us so much! After mris_anatomical_stat I tried aparcstats2table to extract the
table.
But I failed with generating the table.
Best wishes, Annie
2015-05-12 8:29 GMT-04:00 Thomas Yeo ythomas@csail.mit.edu:
Hi Annie,
I assume this means 5202 is your subject ID? Maybe you should check if /home/annie/test_run_allindex/5202/label/lh.Yeo2011_7Network
s_N1000.annot
exist?
If so, you can run mris_anatomical_stats to generate statistics for the parcellation.
Cheers, Thomas
On Tue, May 12, 2015 at 6:29 PM, 陳昱潔 poohann1122@gmail.com wrote:
Hi Professor Yeo : After I rechecked the directory and run again mri_surf2surf I got the result: "Saving target data Converting to target annot Saving to target annot
/home/annie/test_run_allindex/5202/label/lh.Yeo2011_7Network
s_N1000.annot"
The file of 5202/label didn't come out with lh.Yeo2011_7Networks_N1000.annot But it seems succeed, right? How can I get the stat of this parcellation ?
Thank you very much!
Best wishes, Annie
2015-05-12 6:06 GMT-04:00 Thomas Yeo ythomas@csail.mit.edu:
> Hi Annie, > > mri_surf2surf is complaining that it cannot write out the
annotation.
> > Just to clarify, is your subject called test_run_allindex? In other > words, is the variable s equal to test_run_allindex? > > Does the directory "/home/annie/test_run_allindex/label/" exist?
If
> not, then you first need to create the directory first, and then > mri_surf2surf can write the resulting annotation file into the > directory. > > Cheers, > Thomas > > On Tue, May 12, 2015 at 5:46 PM, 陳昱潔 poohann1122@gmail.com
wrote:
> > Hi Professor Yeo : > > > > We tried the code > >>> mri_surf2surf --srcsubject fsaverage --trgsubject $s --hemi lh > >>> --sval-annot > >>> > >>> > >>> > >>> $FREESURFER_HOME/subjects/fsaverage/label/lh.Yeo2011_7Networ
ks_N1000.annot
> >>> --tval $SUBJECTS_DIR/$s/label/lh.Yeo2011_7Networks_N1000.annot > > However there came an error of "could not write annot file > > /home/annie/test_run_allindex/label/lh.Yeo2011_7Networks_N10
00.annot
> > No such file or directory" > > And we checked our individual subject's label there isn't > > lh.Yeo2011_7Networks_N1000.annot > > Should we generate/import the lh.Yeo2011_7Networks_N1000.annot
into
> > our > > subjects/label first? > > What can we do ? > > Thank you very much! > > > > Best wishes, > > Annie > > > > > > 2015-05-05 8:36 GMT-04:00 Thomas Yeo ythomas@csail.mit.edu: > > > >> Hi Annie, > >> > >> Please cc the freesurfer list when you reply because there
might be
> >> other people more qualified to answer your question. > >> > >> Based on what you are saying, I think you can first use > >> mri_surf2surf > >> (with the "sval-annot" flag) to transform the 2011 functional > >> networks > >> .annot file from fsaverage space to the subject's native surface > >> space. Type "mri_surf2surf --help" to see examples. > >> > >> You can then use mris_anatomical_stats to compute thickness > >> statistics. > >> > >> Cheers, > >> Thomas > >> > >> On Tue, May 5, 2015 at 3:21 PM, 陳昱潔 poohann1122@gmail.com
wrote:
> >> > Dear Pro. Yeo: > >> > > >> > Very appreciate for your reply ! > >> > > >> > We are trying to use your definition of the functional network > >> > regions > >> > to > >> > re-parcellate our images > >> > and get the regions of volume or cortical thickness for our
study
> >> > interest > >> > of structural network. > >> > However, we did not want to re-run the first recon-all again
due
> >> > to > >> > it's > >> > spending to much time. > >> > And we are still can't find the way to solve this problem. > >> > Thank you very much for helping us! > >> > > >> > Best wishes, > >> > Annie Chen > >> > > >> > 2015-05-02 8:25 GMT+08:00 Thomas Yeo ythomas@csail.mit.edu: > >> >> > >> >> Hi Yu-Chieh, > >> >> > >> >> I am cc-ing the freesurfer list who may help you with your > >> >> issues. > >> >> > >> >> Can you explain what exactly you are trying do? The
parcellation
> >> >> is > >> >> released in different resolutions including fsaverage5. Why > >> >> can't > >> >> you > >> >> just use the fsaverage5 parcellation? > >> >> > >> >> Cheers, > >> >> Thomas > >> >> > >> >> On Fri, May 1, 2015 at 6:14 PM, 陳昱潔 poohann1122@gmail.com > >> >> wrote: > >> >> > Dear professor Yeo : > >> >> > > >> >> > My name is Yu-chieh Chen , I am a graduated student from > >> >> > National > >> >> > Taiwan > >> >> > University of medical school, and my supervisor is
professor
> >> >> > Susan > >> >> > Shur-Fen > >> >> > Gau from department of psychiatry, National Taiwan
University
> >> >> > Hospital & > >> >> > College of Medicine. We are very interesting about your
paper
> >> >> > published > >> >> > in > >> >> > 2011 which using resting MRI to separate brain regions to > >> >> > functional > >> >> > networks. We'd like to use your percellation to re-separate > >> >> > the > >> >> > brain > >> >> > regions based on your released data in Freesurfer( > >> >> > > >> >> > > >> >> > http://ftp.nmr.mgh.harvard.edu
/fswiki/CorticalParcellation_Yeo2011).
> >> >> > And > >> >> > use > >> >> > these volume of brain regions for our study, however, there > >> >> > comes > >> >> > the > >> >> > problem that we assumed that we can change the fsaverage
into
> >> >> > fsaverage5, > >> >> > thus we may get the new volume of the parcellation_Yeo.
But it
> >> >> > is > >> >> > not > >> >> > work. > >> >> > So I send this email for help. Last , I am very appreciate > >> >> > your > >> >> > kindness > >> >> > and > >> >> > very sorry for my inappropriate and rough. > >> >> > Thank you very much for read this email and sorry for
occupied
> >> >> > your > >> >> > time. > >> >> > > >> >> > Best wishes, > >> >> > Yu-chieh Chen > >> >> > > >> > > >> > > > > >
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