Source space analysis without subject MRI

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Dear mne community,

I would like to perform source space analysis for a subject for which I do not have an MRI scan.

I followed the steps for coregistration without subject MRI scan in this presentation<https://de.slideshare.net/mne-python/mne-pythyon-coregistration> and got a bem, label, and surf folder as well as a -trans.fif file and an 'MRI scaling parameters.cfg' file for my subject.

However, how I am to proceed with these files is unclear to me.

Assuming the subject ID is 100000, I would normally load the following files disregarding the folder path:

src_fname = '100000-ico-4-src.fif'
bem_fname = '100000-5120-5120-5129-bem-sol.fif'
trans_fname = '100000-trans.fif'

Then I would plug these files into mne.make_forward_solution(). Since I do not have the subject MRI scan do I simply use the fsaverage files whenever necessary, e.g., replace '100000' with 'fsaverage' in src_fname and bem_fname? What do I do with the multitude of files in the bem, label, and surf folders?

Furthermore, how do I take the scaling into account? There does not seem to be an option to use 'MRI scaling parameters.cfg' as input.

Best,

Chris

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Hi Chris,

If you used scaling during coregistration you should now have a subject folder for the scaled subject (and since you say you have a bem, label and surf folders that seems to be the case). You can use the files in this folders as if it were a normal MRI subject. Don?t use any files from fsaverage directly unless they are scale-independent (such as *.annot files). If you generate additional source-spaces I would recommend to generate them for fsaverage and then use mne.scale_source_space(), that way the same vertices are used for different subjects.

Hope that helps,

Christian