[Mne_analysis] Calculate forward model using digitization from eximia system

Wed Oct 26 12:59:36 EDT 2016

I suspect the point digitized was not actually on the scalp. I have
seen other groups have systematic issues like this, when they don't
place the digitizer pen directly on the scalp (typically on top of an
electrode: which is often a bad idea for multiple reasons; although
occasionally unavoidable). MNE should handle this fine and use the
closest point on the scalp, but I would recommend for future data
collection that the pen is put inside the electrode on the scalp
itself (be careful, some digitizer pens are sharp).

hth
d

On Wed, Oct 26, 2016 at 12:44 PM, Leonardo Barbosa <lsbarbosa at gmail.com> wrote:
> I know it has been a while, but I finally went back to this project and
> managed to create the DigMontage using the mne.channels.read_dig_montage
>
>         digitization = read_dig_montage(hsp=positions.copy(),
> elp=positions.copy(), point_names=labels, unit='mm')
>
> positions is a ndarray (N,3) and labels is a list (N), where N is the number
> of entries in the digitization file: 257 electrodes + 3 fiducials
> here is an example of .sfp file I get from the digitization process and used
> to generate the position and labels objects through csv.reader() :
>
> https://drive.google.com/open?id=0B0p7WZ2wlTFSazJWbENnN0JnMkU
>
> I then used set_montage to update the info['dig'] entry ( knowing that I
> already called this function before with a normal Montage, to set the
> electrodes positions, since info['ch_names'] is not updated by
> read_dig_montage)
>
>         raw.set_montage(digitization)
>
> It works, but I'm not sure if this is the correct way to do it.
> Is it ok to use electrodes as head points?
> Is it not enough to use the fiducials alone?
>
> Perhaps I should open a new thread less specific about eximia, since my
> question is more generic: how can I align electrodes to individual MRIs just
> having the fiducials from the digitization process in a text file?
>
> I found this thread, but no it is not quite the same since I do have the
> MRI, but the co-registration is not in any supported format (Polhemus, etc)
>
> https://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/2016-June/003414.html
>
> In any case, now I can save the raw with the info['dig'] information (lpa,
> rpa and nasion) and use it to create the trans file using the
> mne.gui.coregistration (through "mne coreg" in the command line,
> http://www.slideshare.net/mne-python/mnepython-coregistration)
>
> However, for some reason all the electrodes are quite far from the scalp,
> even though the fiducials were aligned:
>
> https://drive.google.com/open?id=0B0p7WZ2wlTFSNklmcTlPakJERXc
> https://drive.google.com/open?id=0B0p7WZ2wlTFScXF4NGMtNXBiZ2M
>
> since it happened with 5 subjects, and the error is always similar, I think
> it is unlikely to be a simple switch between subjects digitization (I double
> checked the origin of the files in any case)
> it could be, however, a systematic error in the acquisition... But this
> system was successfully used with brainstorm, so I would not start with this
> hypothesis.
>
> Does anybody have another idea why this could be happening?
> Or how could I fix that?
>
> I could morph the MRI if needed, but since I'm using individual MRIs with
> the co-registration, wouldn't that be a waste and similar to using
> generic/fsaverage MRI?
>
> Thank you for any help,
> Leonardo
>
>
> 2016-09-09 8:07 GMT-05:00 Alexandre Gramfort
> <alexandre.gramfort at telecom-paristech.fr>:
>>
>> Hi Leonardo,
>>
>> > I'm following this tutorial
>> >
>> > http://martinos.org/mne/stable/auto_tutorials/plot_forward.html
>> >
>> > and trying to compute the forward model using individual anatomical
>> > information.
>> >
>> > So far I got the skull/skin surfaces using mne watershed_bem, and now
>> > I'm
>> > trying to use the mne.gui.coregistration the generate the -trans file.
>> >
>> > However, the digitization information is an eximia .nbe file. I found a
>> > thread about converting it to FIF
>> >
>> >
>> > https://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/2013-March/001465.html
>> >
>> > but it suggests using the mne_eximia2fif, and my eeg data is not
>> > acquired
>> > with the eximia system, only the digitization.
>> >
>> > The digitization consists of 3D positions for each electrodes +
>> > fiducial,
>> > which I have imported into python as numpy.array.
>> >
>> > Should I use mne.channels.read_dig_montage and update info['dig']
>> > manually?
>>
>> yes that's the entry point.
>>
>> see the structure of a DigMontage object and maybe see if you can create
>> one
>> directly.
>>
>> let us know if it works
>>
>> Alex
>>
>> > I tried
>> >
>> > import mne.channels.read_dig_montage
>> > digitization = read_dig_montage(elp=my_data[:, 1:],
>> > point_names=ch_names)
>> >
>> > where my_data[:, 1:] are the coordinates of the electrodes in mm, and
>> > the
>> > first 3 lines are ['nasion', 'lpa', 'rpa'] (ch_names has the strings
>> > with
>> > the fiducial and electrodes names)
>> >
>> > However I get this error:
>> >
>> > ===========================================
>> >
>> > In [48]: read_dig_montage(elp=my_data[:, 1:],
>> > point_names=montage.ch_names)
>> >
>> > ---------------------------------------------------------------------------
>> > TypeError                                 Traceback (most recent call
>> > last)
>> > <ipython-input-48-c58c337206f3> in <module>()
>> > ----> 1 read_dig_montage(hsp=None, elp=my_data[:, 1:],
>> > point_names=montage.ch_names)
>> >
>> > /home/leonardo/projects/mne-python/mne/channels/montage.pyc in
>> > read_dig_montage(hsp, hpi, elp, point_names, unit, fif, transform,
>> > dev_head_t)
>> >     608             fids = apply_trans(neuromag_trans, [nasion, lpa,
>> > rpa])
>> >     609             elp = apply_trans(neuromag_trans, elp)
>> > --> 610             hsp = apply_trans(neuromag_trans, hsp)
>> >     611         else:
>> >     612             fids = [None] * 3
>> >
>> > /home/leonardo/projects/mne-python/mne/transforms.pyc in
>> > apply_trans(trans,
>> > pts, move)
>> >     172
>> >     173     # apply rotation & scale
>> > --> 174     out_pts = np.dot(pts, trans[:3, :3].T)
>> >     175     # apply translation
>> >     176     if move is True:
>> >
>> > TypeError: unsupported operand type(s) for *: 'NoneType' and 'float'
>> >
>> > ===========================================
>> >
>> > Looks like hsp is mandatory, but I don't have the Polhemus
>> > information...
>> >
>> > Is there an easier way to create the -trans file and calculate the
>> > forward
>> > model using individual electrodes positions from the eximia system (or
>> > np.array with the electrodes coordinates for that matter)?
>> >
>> > Thank you very much in advance for any help,
>> >
>> > Leonardo
>> >
>> >
>> >
>> >
>> >
>> >
>> >
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