Visualize Epochs data

This tutorial focuses on visualization of epoched data. All of the functions introduced here are basically high level matplotlib functions with built in intelligence to work with epoched data. All the methods return a handle to matplotlib figure instance.

Events used for constructing the epochs here are the triggers for subject being presented a smiley face at the center of the visual field. More of the paradigm at sample-dataset.

All plotting functions start with plot. Let's start with the most obvious. :func:mne.Epochs.plot offers an interactive browser that allows rejection by hand when called in combination with a keyword block=True. This blocks the execution of the script until the browser window is closed.

The numbers at the top refer to the event id of the epoch. The number at the bottom is the running numbering for the epochs.

Since we did no artifact correction or rejection, there are epochs contaminated with blinks and saccades. For instance, epoch number 1 seems to be contaminated by a blink (scroll to the bottom to view the EOG channel). This epoch can be marked for rejection by clicking on top of the browser window. The epoch should turn red when you click it. This means that it will be dropped as the browser window is closed.

It is possible to plot event markers on epoched data by passing events keyword to the epochs plotter. The events are plotted as vertical lines and they follow the same coloring scheme as :func:mne.viz.plot_events. The events plotter gives you all the events with a rough idea of the timing. Since the colors are the same, the event plotter can also function as a legend for the epochs plotter events. It is also possible to pass your own colors via event_colors keyword. Here we can plot the reaction times between seeing the smiley face and the button press (event 32).

When events are passed, the epoch numbering at the bottom is switched off by default to avoid overlaps. You can turn it back on via settings dialog by pressing o key. You should check out help at the lower left corner of the window for more information about the interactive features.

To plot individual channels as an image, where you see all the epochs at one glance, you can use function :func:mne.Epochs.plot_image. It shows the amplitude of the signal over all the epochs plus an average (evoked response) of the activation. We explicitly set interactive colorbar on (it is also on by default for plotting functions with a colorbar except the topo plots). In interactive mode you can scale and change the colormap with mouse scroll and up/down arrow keys. You can also drag the colorbar with left/right mouse button. Hitting space bar resets the scale.

We can also give an overview of all channels by calculating the global field power (or other other aggregation methods). However, combining multiple channel types (e.g., MEG and EEG) in this way is not sensible, so by default if you don't specify specific channel picks the :meth:~mne.Epochs.plot_image method will generate a separate figure for each channel type.

You also have functions for plotting channelwise information arranged into a shape of the channel array. The image plotting uses automatic scaling by default, but noisy channels and different channel types can cause the scaling to be a bit off. Here we define the limits by hand.