# Extracting MNI coordinates of vertices in a specific parcel

**URL:** <https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108>\
**Category:** Support & Discussions\
**Tags:** source-localization, preprocessing, meg\
**Created:** [June 19, 2023, 10:10pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108 "2023-06-19T22:10:56Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![MateGy](https://avatars.discourse-cdn.com/v4/letter/m/b38774/32.png) [@MateGy](https://mne.discourse.group/u/MateGy)\
**Post date:** [June 19, 2023, 10:10pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/1 "2023-06-19T22:10:56Z")

</div>

Hi all,  
I am trying to solve two related problems during source localization. First, I’m trying to extract all vertices in a given parcel of a specific parcellation, convert into MNI coordinates, and then, I’m trying to find the centroid of the parcel. Based on code from another response on this forum, I have managed to extract all vertices in a given parcel, albeit I have some concerns whether I am doing that correctly. Please see the attached code below - could someone confirm whether version 1, 2, 3 or 4 is the appropriate approach?

Finally, I know that the way I am calculating the centroid of the parcel is incorrect - I’m simply taking the mean of all coordinates, even though the surface is curved, not flat. However, I am unsure how to find the centroid in a situation such as this. Could someone help? Thank you so much in advance.

```python
# Set up source space
 # sub here is the subject ID, and subjects_dir is the MRI folder
    src = mne.setup_source_space(
        subject=sub, subjects_dir=subjects_dir,
        spacing='oct6', add_dist=False)

    labels = mne.read_labels_from_annot(sub,parc ='parc2018yeo17_200',subjects_dir = subjects_dir)
    labelname = '17Networks_' + hemifield.upper() + '_' + roi + '-' + hemifield
    offset = src[0]['vertno'].shape[0] # this value will be used below, and is based on
    # code from this link:
    #https://mne.discourse.group/t/correspondence-of-sources-with-parcellation/1942/5
    for label in labels:
        if label.name == labelname:
            #print(label)
            this_hemi = 0 if (label.hemi == 'lh') else 1
            # identify vertices that are present in the src of the participant
            # AND belong to the vertices in a given parcellation based on the
            # label information:
            idx = np.intersect1d(label.vertices, src[this_hemi]['vertno']) 
            # not sure about why searchsorted is necessary:
            parc_hemi_idx = np.searchsorted(src[this_hemi]['vertno'], idx)
            # add offset if in right hemisphere:
            parc_idx = parc_hemi_idx + offset * this_hemi
            
            # different ways to get MNI coordinates:
            # 1) use the idx without the hemi specific index and simply specify the hemi
            # through the second argument in vertex_to_mni (this should only matter for rh)
            mnicoordA = mne.vertex_to_mni(parc_hemi_idx,this_hemi,sub,subjects_dir=subjects_dir)
            # 2) use the vertex info from the label, without reference to the src
            # I guesss this is problematic, because the label might have vertices that the src does not?
            mnicoordB = mne.vertex_to_mni(label.vertices,this_hemi,sub,subjects_dir=subjects_dir)
            # 3) use the idx of the vertices that overlap between the label and the src directly
            mnicoordC = mne.vertex_to_mni(idx,this_hemi,sub,subjects_dir=subjects_dir)
            # 4) index the src with the searchsorted idx, and look up these vertices
            mnicoordD = mne.vertex_to_mni(src[this_hemi]['vertno'][parc_hemi_idx],this_hemi,sub,subjects_dir=subjects_dir)
            # 3 and 4 seem to produce identical results so I assume they do the same thing
            
            # centroids coming from the diff methods:
            centroidA = np.mean(mnicoordA,axis=0)#
            centroidB = np.mean(mnicoordB,axis=0)
            centroidC = np.mean(mnicoordC,axis=0)
            centroidD = np.mean(mnicoordD,axis=0)
            # A seems way off, C and D are identical, B is comparable to C and D
            break

```

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<div class="post-metadata">

**Author:** ![MateGy](https://avatars.discourse-cdn.com/v4/letter/m/b38774/32.png) [@MateGy](https://mne.discourse.group/u/MateGy)\
**Post date:** [June 20, 2023, 9:27pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/2 "2023-06-20T21:27:00Z")

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- MNE version:1.1.1
- operating system: Windows 10

I have found this built-in function, could someone confirm that these two lines are indeed doing what I hope they are doing, i.e., identifying (roughly) the center of a parcel, and converting that point to MNI coordinates?

```python
mne_vert = label.center_of_mass(subject=sub,restrict_vertices=src,subjects_dir=subjects_dir)
centroidX = mne.vertex_to_mni(mne_vert,this_hemi,sub,subjects_dir=subjects_dir)

```

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<div class="post-metadata">

**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\
**Post date:** [June 26, 2023, 4:07pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/3 "2023-06-26T16:07:27Z")

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those lines look correct to me. resulting `centroidX` should be a 1x3 array of XYZ in millimeters.

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<div class="post-metadata">

**Author:** ![MateGy](https://avatars.discourse-cdn.com/v4/letter/m/b38774/32.png) [@MateGy](https://mne.discourse.group/u/MateGy)\
**Post date:** [June 26, 2023, 9:46pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/4 "2023-06-26T21:46:18Z")

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Thanks, Dan. Indeed, centroidX is an array of coordinates. Is my interpretation then correct that these lines will get the center of mass of all vertices within a label that are also present in the src, and then transform this vertex into regular old MNI coordinates (in mm)? Will mne\_vert in my example also always be part of the vertices in src?

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<div class="post-metadata">

**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\
**Post date:** [June 27, 2023, 3:54pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/5 "2023-06-27T15:54:39Z")

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`mne_vert` should be guaranteed to be one of the vertices in `src`, yes. But your description of how it’s found is I think a little inaccurate:

- I think you said “it will find all points in the label that are also in `src` and then compute the centroid of those points”
- I think the correct explanation is “it will calculate the centroid _based only on the vertices in the label_ and then pick the point in your `src` that is closest to that centroid”

but I’d have to double-check the code to be absolutely sure.

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<div class="post-metadata">

**Author:** ![MateGy](https://avatars.discourse-cdn.com/v4/letter/m/b38774/32.png) [@MateGy](https://mne.discourse.group/u/MateGy)\
**Post date:** [June 27, 2023, 9:05pm UTC](https://mne.discourse.group/t/extracting-mni-coordinates-of-vertices-in-a-specific-parcel/7108/6 "2023-06-27T21:05:57Z")

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Thanks, that makes perfect sense too.