[Mne_analysis] some questions regarding the source modelling of evoked potentials/fields

[Eric Larson]

        External Email - Use Caution        

If you just want to visualize these, you can use add_foci for the Brain
object in PySurfer:

https://pysurfer.github.io/generated/surfer.Brain.html#surfer.Brain.add_foci

But you'll probably want to plot using the `white` surface, assuming that's
what you used for source localization, otherwise the location won't make
much sense.

If you want the vertex number, you can load the fsaverage/surf/lh.white
and/or rh.white surfaces using `mne.read_surface`, and find the
index/vertex number of the nearest surface vertex to each of your x/y/z
points. Once you have this, you can use `add_foci` with
`coords_as_verts=True` and pass the vertex number -- and this will work
regardless of which surface you're using to plot.

Eric


On Tue, Dec 17, 2019 at 10:12 AM Irina Anurova <anurova.irina at gmail.com>
wrote:

>         External Email - Use Caution
>
> Dear Alexandre,
> Is there a way to convert MNI coordinates TO the vertex number? I have
> group mean x, y, z values for different experimental conditions, and I
> would like to show them on the standard (fsaverage) brain.
> Thank you very much for your kind help,
> Irina.
>
> On Wed, Nov 6, 2019 at 8:22 PM Irina Anurova <anurova.irina at gmail.com>
> wrote:
>
>> Thank you so much for your help!
>> Everything works fine.
>>
>> On Wed, Nov 6, 2019 at 3:09 PM Alexandre Gramfort <
>> alexandre.gramfort at inria.fr> wrote:
>>
>>>         External Email - Use Caution
>>>
>>> hi Irina,
>>>
>>> indeed. I thought it was STC objects. You need to apply the morph to the
>>> stcs
>>> to get the source estimates on fsaverage (or your average subject).
>>>
>>> maybe this can help
>>> https://mne.tools/stable/auto_examples/inverse/plot_morph_surface_stc.html?highlight=morph
>>>
>>> Alex
>>>
>>>
>>> On Wed, Nov 6, 2019 at 12:38 PM Irina Anurova <anurova.irina at gmail.com>
>>> wrote:
>>>
>>>>         External Email - Use Caution
>>>>
>>>> I am very sorry for bothering you again,
>>>> I tried both options, and got the same error message:
>>>> TypeError: unsupported operand type(s) for +: 'SourceMorph' and
>>>> 'SourceMorph'
>>>>
>>>> Possibly, there was a mistake in morphing procedure.
>>>>
>>>> 1. I downloaded individual stcs:
>>>> stc = mne.read_source_estimate()
>>>> 2. I computed morphed stcs:
>>>> morph = mne.compute_source_morph(stc, subject_from=subject_name,
>>>> subject_to='fsaverage', subjects_dir=subjects_dir)
>>>> 3. saved them as *.h5:
>>>> morph.save()
>>>> 4. Then I download all morphed stcs:
>>>> morphS1 = mne.read_source_morph(fileFolderSTC_morph + 'S1_stc-morph.h5')
>>>> morphS2=.........
>>>> 5. and then tried to average:
>>>> grand_average = (morphS1 + morphS2 + morphS3 + morphS4) / 4
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Tue, Nov 5, 2019 at 10:17 PM Alexandre Gramfort <
>>>> alexandre.gramfort at inria.fr> wrote:
>>>>
>>>>>         External Email - Use Caution
>>>>>
>>>>> hi Irina,
>>>>>
>>>>> I tried this:
>>>>>> morph_group = [morphS1, morphS2, morphS3, morphS4]
>>>>>> grand_average = mne.SourceEstimate.mean(morph_group)
>>>>>>
>>>>>> returns error: "AttributeError: 'list' object has no attribute 'sum'"
>>>>>>
>>>>>
>>>>> you can do arithmetic with stcs
>>>>>
>>>>> you can do:
>>>>>
>>>>> grand_average = (morphS1 + morphS2 + morphS3 + morphS4) / 4
>>>>>
>>>>> and this should work
>>>>>
>>>>> all_stcs = [morphS1, morphS2, morphS3, morphS4]
>>>>> grand_average = sum(all_stcs) / len(all_stcs)
>>>>>
>>>>> HTH
>>>>> Alex
>>>>>
>>>>> _______________________________________________
>>>>> Mne_analysis mailing list
>>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>>
>>>> _______________________________________________
>>>> Mne_analysis mailing list
>>>> Mne_analysis at nmr.mgh.harvard.edu
>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>>
>>> _______________________________________________
>>> Mne_analysis mailing list
>>> Mne_analysis at nmr.mgh.harvard.edu
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>>
>> _______________________________________________
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20191217/ad7029fb/attachment.html