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Thank Sheraz, this is exactly what I was searching for!
Le ven. 21 sept. 2018 ? 00:50, Sheraz Khan, PhD <sheraz at nmr.mgh.harvard.edu>
a ?crit :
Hi Laetitia,
Please see the code below, neighbours_list contains the list of the
neighbours of each vertex.
import mne
from mne.source_estimate import spatial_tris_connectivity
import numpy as np
surf = mne.surface._get_ico_surface(5)
connectivity = spatial_tris_connectivity(surf['tris'])
connectivity = connectivity.todense()
neighbours_list = [np.where(row==1)[1] for row in connectivity]
#neighbours_list contains the list of the neighbours of each vertex
Thanks
Sheraz
> External Email - Use Caution
>
> Dear MNE users,
>
> I would like to implement a searchlight-based generalized linear model on
> source space data. To do so, I need to select the nearest neighbors of
> each
> vertex but I'm unsure of how to do that in practice.
> I have source estimates morphed to the fsaverage brain using ico5 spacing
> (10241 vertices per hemisphere) as well as the connectivity matrices and
> source spaces. I search in the methods of each of these classes, but did
> not find anything that could help me. How can I determine which are the x
> nearest neighbors of the nth vertex?
>
> Thank you for your help,
> Cheers,
> Laetitia
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> Mne_analysis at nmr.mgh.harvard.edu
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-------------------------
Sheraz Khan, M.Eng, Ph.D.
Instructor in Radiology
Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School
McGovern Institute for Brain Research
Massachusetts Institute of Technology
Tel: +1 617-643-5634
Fax: +1 617-948-5966
Email: sheraz at nmr.mgh.harvard.edu
sheraz at mit.edu
Web: http://sheraz.mit.edu
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