Visualize channel over epochs as an imageΒΆ

This will produce what is sometimes called an event related potential / field (ERP/ERF) image.

2 images are produced. One with a good channel and one with a channel that does not see any evoked field.

It is also demonstrated how to reorder the epochs using a 1d spectral embedding as described in:

Graph-based variability estimation in single-trial event-related neural responses A. Gramfort, R. Keriven, M. Clerc, 2010, Biomedical Engineering, IEEE Trans. on, vol. 57 (5), 1051-1061

# Authors: Alexandre Gramfort <>
# License: BSD (3-clause)

import numpy as np
import matplotlib.pyplot as plt

import mne
from mne import io
from mne.datasets import sample


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, tmin, tmax = 1, -0.2, 0.5

# Setup for reading the raw data
raw = io.Raw(raw_fname)
events = mne.read_events(event_fname)

# Set up pick list: EEG + MEG - bad channels (modify to your needs)['bads'] = ['MEG 2443', 'EEG 053']
picks = mne.pick_types(, meg='grad', eeg=False, stim=True, eog=True,

# 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, eog=150e-6))

Show event related fields images

# and order with spectral reordering
# If you don't have scikit-learn installed set order_func to None
from sklearn.cluster.spectral import spectral_embedding  # noqa
from sklearn.metrics.pairwise import rbf_kernel   # noqa

def order_func(times, data):
    this_data = data[:, (times > 0.0) & (times < 0.350)]
    this_data /= np.sqrt(np.sum(this_data ** 2, axis=1))[:, np.newaxis]
    return np.argsort(spectral_embedding(rbf_kernel(this_data, gamma=1.),
                      n_components=1, random_state=0).ravel())

good_pick = 97  # channel with a clear evoked response
bad_pick = 98  # channel with no evoked response

mne.viz.plot_epochs_image(epochs, [good_pick, bad_pick], sigma=0.5, vmin=-100,
                          vmax=250, colorbar=True, order=order_func, show=True)
  • ../../_images/sphx_glr_plot_channel_epochs_image_001.png
  • ../../_images/sphx_glr_plot_channel_epochs_image_002.png

Total running time of the script: (0 minutes 30.841 seconds)

Download Python source code: