morph_equiv.py

import os
import mne
from mne.datasets import sample
from mne.minimum_norm import apply_inverse, read_inverse_operator
import numpy as np

sample_dir_raw = sample.data_path()
sample_dir = os.path.join(sample_dir_raw, 'MEG', 'sample')
subjects_dir = os.path.join(sample_dir_raw, 'subjects')
fname_evoked = os.path.join(sample_dir, 'sample_audvis-ave.fif')
fname_inv = os.path.join(sample_dir, 'sample_audvis-meg-vol-7-meg-inv.fif')
evoked = mne.read_evokeds(fname_evoked, condition=0, baseline=(None, 0))
inverse_operator = read_inverse_operator(fname_inv)
stc = apply_inverse(evoked, inverse_operator, 1.0 / 3.0 ** 2, "dSPM")
stc.crop(0.09, 0.09)

# Use a sphere that creates a domain of the same shape (51, 51, 51)
pos = 5.
sphere_radius = 123.
sphere=(0., 0., 0., sphere_radius)
src_fs_vol_5mm = mne.setup_volume_source_space(
    'fsaverage', subjects_dir=subjects_dir,  pos=pos, sphere=sphere,
    verbose=True)
assert (src_fs_vol_5mm[0]['shape'] == 51).all()

morph = mne.compute_source_morph(
    inverse_operator['src'], subject_from='sample', subject_to='fsaverage',
    zooms=pos, niter_affine=(10, 10, 1), niter_sdr=(2, 2, 1),
    subjects_dir=subjects_dir, verbose=True)
stc_fsaverage = morph.apply(stc)
# Hack our fsaverage source space so that the vertices match
src_fs_vol_5mm[0]['inuse'].fill(0.)
src_fs_vol_5mm[0]['inuse'][stc_fsaverage.vertices] = 1
# And so that the affine corresponds to that of our morph
src_fs_vol_5mm[0]['src_mri_t']['trans'] = morph.affine.copy()
src_fs_vol_5mm[0]['src_mri_t']['trans'][:3] /= 1000.

# All three of these are now equivalent
stc.plot(inverse_operator['src'], subject='sample', subjects_dir=subjects_dir)
stc.plot(morph, subjects_dir=subjects_dir)
stc_fsaverage.plot(src_fs_vol_5mm, subjects_dir=subjects_dir)

Figure 1:

Figure 2:

Figure 3: