Frequently asked questions

This section of the documentation provides a discussion-like format, answering “How-to” questions.

Should I apply ICA first or autoreject first?

Please read Preprocessing workflow with autoreject and ICA.

Is it dangerous to do source estimation with interpolated channels?

Interpolated data is no different from measured data. It’s what you would expect to see if there were no artifacts in the data. Interpolation is nothing magical. It simply takes a weighted average of the data in the neighboring good channels. Indeed, if the artifact was left in the data, it will bias the source estimate far more than any potential harm that interpolation may pose.

How do I manually set the n_interpolate and consensus parameter?

If you do not want autoreject to select a parameter for you, simply pass it as a list of a single element:

>>> ar = AutoReject(n_interpolate=[1], consensus_percs=[0.6])

Note this will still run a cross-validation loop to generate the validation score.

Is it possible to get only bad sensor annotations and not interpolate?

Yes! Simply do:

>>> ar.fit(epochs)
>>> reject_log = ar.get_reject_log(epochs)

No need to run ar.transform(epochs) in this case.