Plot M/EEG field linesΒΆ

In this example, M/EEG data are remapped onto the MEG helmet (MEG) and subject’s head surface (EEG). This process can be computationally intensive.

  • ../../_images/sphx_glr_plot_meg_eeg_fields_3d_000.png
  • ../../_images/sphx_glr_plot_meg_eeg_fields_3d_001.png
# Authors: Eric Larson <>
#          Denis A. Engemann <>
#          Alexandre Gramfort <>

# License: BSD (3-clause)

from mne.datasets import sample
from mne import make_field_map, read_evokeds


data_path = sample.data_path()
subjects_dir = data_path + '/subjects'
evoked_fname = data_path + '/MEG/sample/sample_audvis-ave.fif'
trans_fname = data_path + '/MEG/sample/sample_audvis_raw-trans.fif'
# If trans_fname is set to None then only MEG estimates can be visualized

condition = 'Left Auditory'
evoked = read_evokeds(evoked_fname, condition=condition, baseline=(-0.2, 0.0))

# Compute the field maps to project MEG and EEG data to MEG helmet
# and scalp surface
maps = make_field_map(evoked, trans_fname, subject='sample',
                      subjects_dir=subjects_dir, n_jobs=1)

# Plot MEG and EEG fields in the helmet and scalp surface in the same figure.
evoked.plot_field(maps, time=0.11)

# Compute the MEG fields in the scalp surface
evoked.pick_types(meg=True, eeg=False)
maps_head = make_field_map(evoked, trans_fname, subject='sample',
                           subjects_dir=subjects_dir, n_jobs=1,

# Plot MEG fields both in scalp surface and the helmet in the same figure.
evoked.plot_field([maps_head[0], maps[1]], time=0.11)

Total running time of the script: (0 minutes 9.871 seconds)

Download Python source code: