[Mne_analysis] How to set atlas

[Vivek Sharma]

        External Email - Use Caution        

When I run this command, label = mne.read_labels_from_annot(subject,
hemi=hemi, parc='aparc', subjects_dir=subjects_dir, regexp=regexp)[0], with
[0] at the end I could run the next command stc = stc.in_label(label),
successfully but it reduces the number of vertices to 35, whereas when I do
not use '[0]' at the end of command, I could not run the next command, it
gives the following error:
>>> label = mne.read_labels_from_annot('sub-CC721377_T1w', hemi='both',
parc='aparc', subjects_dir=subjects_dir, regexp=None)
Reading labels from parcellation...
   read 34 labels from
/home/vivek/Downloads/freesurfer/subjects/sub-CC721377_T1w/label/lh.aparc.annot
   read 34 labels from
/home/vivek/Downloads/freesurfer/subjects/sub-CC721377_T1w/label/rh.aparc.annot
>>> stc_label.in_label(label)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File
"/home/vivek/anaconda3/lib/python3.7/site-packages/mne/source_estimate.py",
line 1197, in in_label
    if label.subject is not None and self.subject is not None \
AttributeError: 'list' object has no attribute 'subject'


On Wed, Jan 23, 2019 at 6:52 PM Diptyajit Das <bmedasdiptyajit at gmail.com>
wrote:

>         External Email - Use Caution
>
> Follow this:
> https://github.com/mne-tools/mne-python/issues/5850
>
> best,
>
> On Tue, Jan 22, 2019 at 11:18 AM Vivek Sharma <vivek.sharma1510 at gmail.com>
> wrote:
>
>>         External Email - Use Caution
>>
>> Hi,
>> Thanks for the code.
>> I tried with this method but it reduces the number of vertices to 35, I
>> want it to be 68 according to Desikan atlas.
>>
>> On Thu, Jan 17, 2019 at 5:12 PM Diptyajit Das <bmedasdiptyajit at gmail.com>
>> wrote:
>>
>>>         External Email - Use Caution
>>>
>>> Hi,
>>>
>>> You do cortical parcellation by using some atlas. I think what you meant
>>> is to restrict the dipoles activity to some particular brain regions. For
>>> that,  you need to pass the 'label'  during source estimation or you can do
>>> something like this after the source estimate:
>>>
>>> code:
>>> regexp = 'bankssts'     # name the brain region that you are interested
>>> in
>>> hemi = 'both'  # taking both hemisphere
>>> label = mne.read_labels_from_annot(subject, hemi=hemi, parc='aparc',
>>> subjects_dir=subjects_dir, regexp=regexp)[0]    # read the label of the
>>> particular region based on Desikan atlas (i.e., defined by 'aparc')
>>> stc = stc.in_label(label)  # restrict the dipoles to that particular
>>> label
>>>
>>>
>>> best,
>>>
>>> Dip
>>>
>>> On Thu, Jan 17, 2019 at 12:05 PM Vivek Sharma <
>>> vivek.sharma1510 at gmail.com> wrote:
>>>
>>>>         External Email - Use Caution
>>>>
>>>> Okay.
>>>> The source estimate file I'm getting consists of 8175 vertices
>>>> (SourceEstimate  |  8175 vertices) , I wanted to reduce the number of
>>>> vertices to the ROIs, in my case I wanted to use Desikan atlas.
>>>> How can I reduce the number of vertices, specific to certain atlases?
>>>>
>>>> On Thu, Jan 17, 2019 at 2:10 PM Alexandre Gramfort <
>>>> alexandre.gramfort at inria.fr> wrote:
>>>>
>>>>>         External Email - Use Caution
>>>>>
>>>>> make_watershed_bem uses an atlas to get a good skull segmentation
>>>>>
>>>>> it's not an atlas of the cortical surface as you suggest
>>>>>
>>>>> HTH
>>>>> A
>>>>>
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>>>>>
>>>>
>>>>
>>>> --
>>>> Vivek Sharma
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>>
>>
>>
>> --
>> Vivek Sharma
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>
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-- 
Vivek Sharma
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