[Mne_analysis] Selecting nearest neighbors of a vertex in source space

Laetitia Grabot laetitia.grabot at gmail.com
Mon Sep 24 10:40:43 EDT 2018
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Thank Sheraz, this is exactly what I was searching for!



Le ven. 21 sept. 2018 à 00:50, Sheraz Khan, PhD <sheraz at nmr.mgh.harvard.edu>
a écrit :

> 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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