eelbrain.pipeline.MneExperiment.make_bad_channels_neighbor_correlation
- MneExperiment.make_bad_channels_neighbor_correlation(r, epoch=None, add_bads=True, save=True, **state)
Iteratively exclude bad channels based on low average neighbor-correlation
- Parameters:
r (float) – Minimum admissible neighbor correlation. Any channel whose average correlation with its neighbors is below this value is added to the list of bad channels (e.g., 0.3).
epoch (str) – Epoch to use for computing neighbor-correlation (by default, the whole session is used).
add_bads (bool) – Reject bad channels first.
save (bool) – Save the bad channels to the bad channel specification file. Set
save=False
to examine the result without actually changing the bad channels.... – State parameters.
- Returns:
neighbor_correlation – Head-map with the neighbor correlation for each sensor.
bad_channels – Channels that are excluded based on criteria.
- Return type:
Notes
Algorithm:
Load the corresponding data
Calculate the pairwise correlation between each neighboring sensor pair
Assign to each sensor the average correlation with its neighbors
If the sensor with the lowest correlation is <
r
, exclude it and go back to 2.
Warning
Data is loaded for the currently specified
raw
setting, but bad channels apply to allraw
settings equally. Hence, when using this method with multiple subjects, it is important to setraw
to the same value.