""" ================================================= Compare evoked responses for different conditions ================================================= In this example, an Epochs object for visual and auditory responses is created. Both conditions are then accessed by their respective names to create a sensor layout plot of the related evoked responses. """ # Authors: Denis Engemann # Alexandre Gramfort # License: BSD (3-clause) import matplotlib.pyplot as plt import mne from mne.viz import plot_evoked_topo from mne.datasets import sample print(__doc__) data_path = sample.data_path() ############################################################################### # Set parameters raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif' event_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw-eve.fif' event_id = 1 tmin = -0.2 tmax = 0.5 # Setup for reading the raw data raw = mne.io.read_raw_fif(raw_fname) events = mne.read_events(event_fname) # Set up pick list: MEG + STI 014 - bad channels (modify to your needs) include = [] # or stim channels ['STI 014'] # bad channels in raw.info['bads'] will be automatically excluded # Set up amplitude-peak rejection values for MEG channels reject = dict(grad=4000e-13, mag=4e-12) # pick MEG channels picks = mne.pick_types(raw.info, meg=True, eeg=False, stim=False, eog=True, include=include, exclude='bads') # Create epochs including different events event_id = {'audio/left': 1, 'audio/right': 2, 'visual/left': 3, 'visual/right': 4} epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks, baseline=(None, 0), reject=reject) # Generate list of evoked objects from conditions names evokeds = [epochs[name].average() for name in ('left', 'right')] ############################################################################### # Show topography for two different conditions colors = 'yellow', 'green' title = 'MNE sample data - left vs right (A/V combined)' plot_evoked_topo(evokeds, color=colors, title=title) plt.show()