Hello,
I am trying to morph a sparse volume source estimate obtained with mne.inverse_sparse.mixed_norm
to fsaverage
but there seems to be a problem with the number of vertices.
After having processed the data and computed the forward operator, I run the following code:
sources, residual = mne.inverse_sparse.mixed_norm(
evokeds, fwd, noise_cov, alpha, loose=loose, depth=depth, maxit=3000,
tol=1e-4, active_set_size=None, debias=True, n_mxne_iter=1, return_residual=True,
return_as_dipoles=False, verbose=True)
src_fs = mne.read_source_spaces(fname_src_fsaverage)
morph = mne.compute_source_morph(fwd["src"], subject_from='CC110033',
subject_to='fsaverage', src_to=src_fs,
subjects_dir=BEM_DIR)
stc_fsaverage = morph.apply(sources)
I get the following error:
ValueError: vertices do not match between morph (11192) and stc (19) for volume[0]:
[ 2680 2681 2682 ... 32318 32319 32320]
[13018 13324 13383 14987 15016 15309 16440 18417 18730 19861 24179 24180
24208 24209 25310 25340 27699 28802 28832]
Perhaps src_to=fwd["src"] needs to be passed when calling compute_source_morph. Vertices were likely excluded during forward computation.
sources
contains:
<VolSourceEstimate | 19 vertices, tmin : -1700.0 (ms), tmax : 1700.0 (ms), tstep : 1.0 (ms), data shape : (19, 3401), ~253 kB>
whereas the source space fwd['src']
contains:
<SourceSpaces: [<volume, shape=(29, 39, 31), n_used=11192>] head coords, subject 'CC110033', ~73.2 MB>
- MNE-Python version: 0.23.4
- operating system: Ubuntu 18.04.5 LTS
Is there a way to add missing vertices to volume source estimates or should I do something differently ?
Thank you