Dear MNE experts,
I want to anticipate the spatial normalization, and perform source reconstruction for each subject on a subject-specific grid, that maps onto a template grid in spatially normalized space.However, I only saw distortion of the surface source space on the MNE Python website ( Use source space morphing — MNE 1.5.1 documentation). Is there a way to morph the volume source space?
Best wishes!
Hi @podaking
like this: Morph volumetric source estimate — MNE 1.5.1 documentation ?
Hope this helps,
Britta
Thank you very much for your reply.I learned about the content below from the Fieldtrip website（(Creating a sourcemodel for source reconstruction of MEG or EEG data - FieldTrip toolbox).
I would like to choose the second strategy, as shown in the figure below, instead of performing source estimation normalization after source estimation.
I have also seen the website you mentioned, but this seems to be the first strategy, and I am not sure if I understand correctly.Looking forward to receiving your reply.
Not only that, but when I ran the routine, I found that the file in the figure below does not exist, and it seems that the file name has been changed, right?
The new file seems to be ‘fsaverage vol7 nointerp src. fif’(https://github.com/mne-tools/mne-testing-data/tree/master/subjects/fsaverage/bem).
I’m not very sure if I’m right.
Looking forward to your reply! Thanks.
Hi @prodaking
please excuse the late reply - most of us are working on MNE-Python in their free time or as an extra work task, so we do not always have time to answer immediately. Thank you for your patience.
I cannot reproduce your error, for me the tutorial works fine. You seem to be looking at the testing data folder in your screenshot - but the code will look in mne_data/MNE-sample-data/subjects/fsaverage/bem, not mne_data/MNE-testing-data/subjects/fsaverage/bem. Can you share the specific error message with which the code fails?
As for the FieldTrip tutorial: we do not support the same approach as FieldTrip does AFAIK.
HTH,
Britta
