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commit cb426411559875d909f05e2b63a583cbfb03e6d1 Author: Alexandre Gramfort <[email protected]> Date: Wed Jul 25 11:48:01 2012 +0200 ENH : add example of LCMV on volume grid --- examples/inverse/plot_lcmv_beamformer_volume.py | 66 +++++++++++++++++++++++++ 1 file changed, 66 insertions(+) diff --git a/examples/inverse/plot_lcmv_beamformer_volume.py b/examples/inverse/plot_lcmv_beamformer_volume.py new file mode 100644 index 0000000..a7cba57 --- /dev/null +++ b/examples/inverse/plot_lcmv_beamformer_volume.py @@ -0,0 +1,66 @@ +""" +=================================================================== +Compute LCMV inverse solution on evoked data in volume source space +=================================================================== + +Compute LCMV inverse solution on an auditory evoked dataset in a volume source +space. It stores the solution in a nifti file for visualisation e.g. with +Freeview. + +""" + +# Author: Alexandre Gramfort <[email protected]> +# +# License: BSD (3-clause) + +print __doc__ + +import mne +from mne.datasets import sample +from mne.fiff import Raw, pick_types +from mne.beamformer import lcmv + + +data_path = sample.data_path('..') +raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif' +event_fname = data_path + '/MEG/sample/sample_audvis_raw-eve.fif' +fname_fwd = data_path + '/MEG/sample/sample_audvis-meg-vol-7-fwd.fif' +fname_cov = data_path + '/MEG/sample/sample_audvis-cov.fif' + +############################################################################### +# Get epochs +event_id, tmin, tmax = 1, -0.2, 0.5 + +# Setup for reading the raw data +raw = Raw(raw_fname) +raw.info['bads'] = ['MEG 2443', 'EEG 053'] # 2 bads channels +events = mne.read_events(event_fname) + +# Set up pick list: EEG + MEG - bad channels (modify to your needs) +left_temporal_channels = mne.read_selection('Left-temporal') +picks = pick_types(raw.info, meg=True, eeg=False, stim=True, eog=True, + exclude=raw.info['bads'], selection=left_temporal_channels) + +# Read epochs +epochs = mne.Epochs(raw, events, event_id, tmin, tmax, proj=True, + picks=picks, baseline=(None, 0), preload=True, + reject=dict(grad=4000e-13, mag=4e-12, eog=150e-6)) +evoked = epochs.average() + +forward = mne.read_forward_solution(fname_fwd) + +noise_cov = mne.read_cov(fname_cov) +noise_cov = mne.cov.regularize(noise_cov, evoked.info, + mag=0.05, grad=0.05, eeg=0.1, proj=True) + +data_cov = mne.compute_covariance(epochs, tmin=0.04, tmax=0.15) +stc = lcmv(evoked, forward, noise_cov, data_cov, reg=0.01) + +# Save result in stc files +stc.save('lcmv-vol') + +stc.crop(0.0, 0.2) + +# Save result in a 4D nifti file +img = mne.save_stc_as_volume('lcmv_inverse.nii.gz', stc, + forward['src'], mri_resolution=True) # True for full MRI resolution -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-med/python-mne.git _______________________________________________ debian-med-commit mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/debian-med-commit
