- MNE-Python version: 0.23.1
- operating system: Ubuntu 18.04.5 LTS as server running Jupyter and macbook BigSur 11.5 as client (with firefox 91.0.2).
Dear MNE community,
After performing source localization in my data, I extracted the time series per label using stc.in_label() and performed some analysis outside MNE, ending up with 68 values (one per region), stored in the some array external_computations. Now I would like to plot these values in source space. What would be the easiest way to do that in MNE? I couldn’t find anything similar in the tutorials or in the discussions here.
I did hack something up after inspecting the mne.SourceEstimate class, which seems to be working, but it just looks… wrong
Here is the snippet that seems to do what I want, but I hope there is a better way of doing that:
# Load original source estimates labels = mne.read_labels_from_annot(subject, parc='aparc', hemi='both', subjects_dir=freesurfer_path) stclh = read_source_estimate('./sources_sLORETA-lh.stc') stcrh = read_source_estimate('./sources_sLORETA-rh.stc') # Crop to get only one sample stclh = stclh.crop(0, .0001) stcrh = stcrh.crop(0, .0001) # Set original source estimate values to zero stclh.data[:] = 0 stcrh.data[:] = 0 # Update the values in each dipole of each region with the external computations in "external_computations", which is an array with 68 values, one per region for (il, l) in enumerate(labels): if (l.name[-2:] == 'lh'): lvert = stclh.in_label(l).vertices inter = np.intersect1d(lvert, stclh.vertices, return_indices=True) stclh.data[inter, 0] = external_computations[il] if (l.name[-2:] == 'rh'): lvert = stcrh.in_label(l).vertices inter = np.intersect1d(lvert, stcrh.vertices, return_indices=True) stcrh.data[inter+len(stclh.vertices), 0] = external_computations[il]
Now in theory I can do the plots with stclh.plot() and stcrh.plot(). But I’m not sure this is correct, and it looks overly complicated. For instance I have to sum the number of vertices in left hemisphere (len(stclh.vertices)) to the positions identified in the right hemisphere (stcrh.in_label(l).vertices) before indexing the actual data (stcrh.data). Is this the correct way to access the data of a particular region in the right hemisphere?