[Mne_analysis] a junior question on mne_setup_source_space

dgw dgwakeman at gmail.com
Thu May 1 11:29:46 EDT 2014
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Hi Peng,

Please see response in text.

On Thu, May 1, 2014 at 11:05 AM, peng <prion.w at gmail.com> wrote:
> Thanks for the reply, dgw. Do you mean the segmentation is made in fsaverage
> and then project to subject by
> ====
> mne_setup_source_space --subject subj1 --ico 2 --morph fsaverage
> ====
> I tried this way before and it always failed with the error message that
> vertex XXX was used multiple times, no matter which resolution I use (ico 2,
> 3, 4 or 5). It seemed the resolution of fsaverage is not so high (2 mm),
> thus I tried icbm152 and colin27 (both 1 mm resolution), and it did not work
> either. Do you have any idea on possible reasons?

Well, we would need to get an error report to try and track this down.
There is a useful chart in the morphing and averaging chapter which
describes the pipeline you are trying to use. Essentially, it is a
multistep process. Because MNE tries to provide you the best possible
estimates, you first analyze the data in the individuals space
(vertices don't match). Then you morph that data for each individual
to a shared space (e.g. fsaverage). Each individuals morphed data will
then have a one to one mapping.

> I just made ico 2 here as an example. Of course I am also interested to know
> what is the minimum number you think appropriate for reasonable mapping?

This depends on your application of the "loose" ness of your
orientation constraint. Something like --ico 5 and --loose .2

>
> btw: I hope it is OK when I address you as dgw; that's what I saw as the
> email sender. Please correct me if it is not what you like.
>
> best
> Peng
>
>
> On Thu, May 1, 2014 at 4:12 PM, dgw <dgwakeman at gmail.com> wrote:
>>
>> Hi Peng,
>>
>> I think the basic point here is you have the logic reversed. The idea
>> behind the morph option is that you would use  --subject subj1 and
>> --morph fsaverage. You would then do this for all of your subjects.
>> Although with such a tiny number of sources (--ico 2), I wouldn't
>> expect to get very good results.
>>
>> HTH,
>> D
>>
>> On Tue, Apr 29, 2014 at 12:44 PM, peng <prion.w at gmail.com> wrote:
>> > Hi dgw,
>> >
>> >    First thanks you for help in previous discussions, also thanks alex,
>> > martin, junpeng and many others for helps.
>> >    I have played with the commands for a while and now understand more.
>> > However, I am still not sure how this "morph" works. For example, in the
>> > following command,
>> >    mne_setup_source_space --subject fsaverage --ico 2 --morph subj1
>> > --overwrite
>> >    Previously, I thought with this command, it would took some locations
>> > in
>> > the template fsaverage, and then projected them into subj1 based on
>> > their
>> > anatomical similarity (e.g. shape of white matter). Or in another words,
>> > I
>> > expected that if I repeated this command many times by changing the
>> > subjects, I would have all subjects share the same or at least very
>> > close
>> > locations (in cortex level) for the same vertex id. This is interesting
>> > for
>> > me because it would give much convenience in later group analysis. e.g.
>> > location #100 of subject 1 and location #100 of subject 2 means the same
>> > thing in group level. However, later I applied the labels in freesurfer
>> > and
>> > found out that for the same id (e.g. #100) may belong to different brain
>> > areas (as indicated by labels). I am a little confused then. Is this
>> > difference cause by small variations; or I was wrong in the root : This
>> > morph does not grantee a one-to-one mapping between template and each
>> > subject?
>> >    Thanks a lot for the help!
>> >
>> > best
>> > Peng
>> >
>> >
>> >
>> > On Fri, Mar 28, 2014 at 3:08 PM, dgw <dgwakeman at gmail.com> wrote:
>> >>
>> >> That certainly is the basic workflow in terms of commands, but I don't
>> >> think you want to use the "tmp" subject. You also don't morph the data
>> >> until later in the process.
>> >>
>> >> Can I recommend that you start off by doing the example in the
>> >> "Cookbook" chapter? It does not take very long, and it will help you
>> >> be more familiar with how the process works in one individual. Then
>> >> you can try to take what you learn from that and apply it directly to
>> >> your data.
>> >>
>> >> HTH,
>> >> D
>> >> .
>> >>
>> >> On Fri, Mar 28, 2014 at 9:52 AM, peng <prion.w at gmail.com> wrote:
>> >> > Dear Alex, Martin and other MNE users,
>> >> >
>> >> > I have my MEG raw data in CTF .ds format and raw MRI image with dicom
>> >> > format. I wish to use MNE to compute the leadfield (source space
>> >> > based
>> >> > on
>> >> > surface).
>> >> > With your help, I wish to summarise a possible pipeline as a
>> >> > following:
>> >> > 1. recon-all --subject test1 #use  in freesurfer to generate the
>> >> > brain
>> >> > surfaces and other needed files.
>> >> > 2. mne_watershed_bem --subject test1 --overwrite --atlas #generate
>> >> > surfaces
>> >> > for bem model
>> >> > 3. mne_ctf2fiff --ds test1.ds --fif test1.fif --infoonly #generate
>> >> > MEG
>> >> > information (sensor locations etc.)
>> >> > 4. #use MNE_analyze with test1.fif and inflated.surf to generate
>> >> > test1-trans.fif which contains the transformation matrix;
>> >> >     #or use a previous calculated transformation matrix and convert
>> >> > it
>> >> > to
>> >> > fif format
>> >> > 5. mne_setup_source_space --subject tmp --ico 5 --morph test1 #tmp is
>> >> > name
>> >> > of a template, could be fsaverage or icbm152...
>> >> > #This is to use locations on the surface of the template cortex
>> >> > (white
>> >> > matter?) as source space.
>> >> > #These locations was morphed to subject <test1> to generate leadfield
>> >> > for
>> >> > this subject later
>> >> > 6. mne_do_forward_solution --subject test1 \
>> >> >    --src test1-fsaverage-ico-5-src.fif \
>> >> >   --meas test1.fif \
>> >> >   --trans test1-trans.fif \
>> >> >   --megonly --overwrite \
>> >> >   --fwd test1-oct-5-fwd.fif
>> >> > # I can then find my leadfield (MxNx3 matrix, M=number of locations,
>> >> > N =
>> >> > number of sensors) by importing test1-oct-5-fwd.fif into matlab.
>> >> >
>> >> > Did I miss something?
>> >> > Thanks a lot for the help.
>> >> >
>> >> >
>> >> >
>> >> > On Fri, Mar 28, 2014 at 2:14 PM, peng <prion.w at gmail.com> wrote:
>> >> >>
>> >> >> Thank you Martin for the help.
>> >> >> 1. I re-run the command "mne_setup_forward_model" and it seemed
>> >> >> working
>> >> >> this time (maybe I did not set the environment correctly). Sorry for
>> >> >> the
>> >> >> confusion.
>> >> >> 2. I tried with MNE_analyze GUI and it was not easy for me. But I
>> >> >> saved
>> >> >> results from one subject successfully and it could be load by
>> >> >> MNE_analyze.
>> >> >> However I wanted to read it in matlab to check the real contents
>> >> >> (which
>> >> >> I
>> >> >> assume is a structure with the transformation matrix). I failed with
>> >> >> "x
>> >> >> =
>> >> >> fiff_read_mri(fname, 0). It complained "Could not find MRI data"...
>> >> >> Would
>> >> >> please let me know the function name to read and write *-src.fif
>> >> >> file
>> >> >> in
>> >> >> matlab?
>> >> >>
>> >> >>
>> >> >>
>> >> >> On Wed, Mar 26, 2014 at 9:28 PM, Martin Luessi
>> >> >> <mluessi at nmr.mgh.harvard.edu> wrote:
>> >> >>>
>> >> >>> On 03/26/14 16:00, peng wrote:
>> >> >>> > Thank you for the answers.
>> >> >>> > 1. Surprisingly I did not find any files were generated/saved
>> >> >>> > after
>> >> >>> > running mne_setup_forward_model.
>> >> >>>
>> >> >>> I assume there was an error, can you post the program output?
>> >> >>>
>> >> >>> > 2. I don't have a -trans.fif file. I tried to do it in GUI of
>> >> >>> > MNE_analyze, it was quite complicated. If I have a co-registered
>> >> >>> > mri
>> >> >>> > file (generated by CTF software with .mri extension), can it be
>> >> >>> > converted to fif format? If not, I can read the 4x4 head2mri
>> >> >>> > matrix
>> >> >>> > via
>> >> >>> > matlab, can this information be written to fif format with
>> >> >>> > certain
>> >> >>> > tools
>> >> >>> > in MNE?
>> >> >>>
>> >> >>> There is also a coreg GUI in MNE-Python, have a look here
>> >> >>>
>> >> >>> http://www.slideshare.net/mne-python/mnepython-coregistration
>> >> >>>
>> >> >>> You could write a .fif file with the transform in Matlab, but it
>> >> >>> seems
>> >> >>> to me that this wouldn't be easier than using the coregistration
>> >> >>> tools
>> >> >>> in mne_analyze or MNE-Python.
>> >> >>>
>> >> >>> HTH,
>> >> >>>
>> >> >>> Martin
>> >> >>>
>> >> >>>
>> >> >>> > Thanks again!
>> >> >>> >
>> >> >>> >
>> >> >>> > On Tue, Mar 25, 2014 at 11:39 PM, Alexandre Gramfort
>> >> >>> > <alexandre.gramfort at telecom-paristech.fr
>> >> >>> > <mailto:alexandre.gramfort at telecom-paristech.fr>> wrote:
>> >> >>> >
>> >> >>> >     hi,
>> >> >>> >
>> >> >>> >     >  Some additional questions.
>> >> >>> >     > 1 After I ran mne_setup_forward_model, I have no feedback
>> >> >>> > from
>> >> >>> > the
>> >> >>> >     command
>> >> >>> >     > line, is it normal?
>> >> >>> >
>> >> >>> >     it should print that it saved a file to disk
>> >> >>> >
>> >> >>> >     > 2 I am using CTF data, thus I converted the .ds folder from
>> >> >>> > CTF
>> >> >>> > to fif
>> >> >>> >     > format with mne_ctf2fiff command, with option --infoonly.
>> >> >>> > Here
>> >> >>> > I
>> >> >>> >     only want
>> >> >>> >     > to get the Leadfield thus I suppose data is not necessary.
>> >> >>> > However
>> >> >>> >     when I
>> >> >>> >     > try mne_do_forward_solution, it asked for mri description
>> >> >>> > file,
>> >> >>> >     which I
>> >> >>> >     > haven't. I have only a series of dicom files or the .mri
>> >> >>> > file
>> >> >>> >     generated by
>> >> >>> >     > ctf software from them. Can I still move on?
>> >> >>> >
>> >> >>> >     you need to do the coregistration and get a -trans.fif file.
>> >> >>> >
>> >> >>> >     A
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