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

[Irina Anurova]

        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
>>>>
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