mne.channels.make_1020_channel_selections

mne.channels.make_1020_channel_selections(info, midline='z', *, return_ch_names=False)

Map hemisphere names to corresponding EEG channel names or indices.

This function uses a simple heuristic to separate channel names into three Region of Interest-based selections: Left, Midline and Right.

The heuristic is that any of the channel names ending with odd numbers are filed under Left; those ending with even numbers are filed under Right; and those ending with the character(s) specified in midline are filed under Midline. Other channels are ignored.

This is appropriate for 10/20, 10/10, 10/05, …, sensor arrangements, but not for other naming conventions.

Parameters:

infomne.Info

The mne.Info object with information about the sensors and methods of measurement. If channel locations are present, the channel lists will be sorted from posterior to anterior; otherwise, the order specified in info["ch_names"] will be kept.

midlinestr

Names ending in any of these characters are stored under the Midline key. Defaults to 'z'. Capitalization is ignored.

return_ch_namesbool

Whether to return channel names instead of channel indices.

New in v1.4.0.

Returns:

selectionsdict

A dictionary mapping from region of interest name to a list of channel indices (if return_ch_names=False) or to a list of channel names (if return_ch_names=True).

Examples using mne.channels.make_1020_channel_selections

Visualising statistical significance thresholds on EEG data

Visualising statistical significance thresholds on EEG data

Using contralateral referencing for EEG

Using contralateral referencing for EEG

Plot single trial activity, grouped by ROI and sorted by RT

Plot single trial activity, grouped by ROI and sorted by RT