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%matplotlib inline
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# Author: Alan Leggitt <alan.leggitt@ucsf.edu>
#
# License: BSD (3-clause)
import mne
from mne import setup_source_space, setup_volume_source_space
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
subjects_dir = data_path + '/subjects'
subject = 'sample'
aseg_fname = subjects_dir + '/sample/mri/aseg.mgz'
Setup the source spaces
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# setup a cortical surface source space and extract left hemisphere
surf = setup_source_space(subject, subjects_dir=subjects_dir, add_dist=False)
lh_surf = surf[0]
# setup a volume source space of the left cerebellum cortex
volume_label = 'Left-Cerebellum-Cortex'
sphere = (0, 0, 0, 0.12)
lh_cereb = setup_volume_source_space(
subject, mri=aseg_fname, sphere=sphere, volume_label=volume_label,
subjects_dir=subjects_dir, sphere_units='m')
# Combine the source spaces
src = surf + lh_cereb
Plot the positions of each source space
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fig = mne.viz.plot_alignment(subject=subject, subjects_dir=subjects_dir,
surfaces='white', coord_frame='head',
src=src)
mne.viz.set_3d_view(fig, azimuth=173.78, elevation=101.75,
distance=0.30, focalpoint=(-0.03, -0.01, 0.03))
Compare volume source locations to segmentation file in freeview
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# Export source positions to nift file
nii_fname = data_path + '/MEG/sample/mne_sample_lh-cerebellum-cortex.nii'
src.export_volume(nii_fname, mri_resolution=True)
# Uncomment the following lines to display source positions in freeview.
'''
# display image in freeview
from mne.utils import run_subprocess
mri_fname = subjects_dir + '/sample/mri/brain.mgz'
run_subprocess(['freeview', '-v', mri_fname, '-v',
'%s:colormap=lut:opacity=0.5' % aseg_fname, '-v',
'%s:colormap=jet:colorscale=0,2' % nii_fname, '-slice',
'157 75 105'])
'''