[Mne_analysis] Autoreject

Mainak Jas mainakjas at gmail.com
Thu Feb 8 08:34:50 EST 2018
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Hi Luke,

You can supply the reject dictionary to ICA in mne-python after estimating
it using autoreject. Something like:

>>> from autoreject import get_rejection_threshold>>> reject = get_rejection_threshold(epochs)>>> ica.fit(epochs, picks=picks, reject=reject)

I’m not sure if it would help a lot though. It depends on your data.

As for running autoreject without interpolation, you can use
LocalAutoreject(n_interpolate=0,
...) so that it does not interpolate. Set n_consensus to something
reasonable like 0.8.

In terms of SSS, maybe look into Eric’s new method, oversampled temporal
projection <http://ieeexplore.ieee.org/document/7997929/>. It’s available
in the dev version of mne-python.

Mainak

On Thu, Feb 8, 2018 at 2:48 AM, Luke Bloy <luke.bloy at gmail.com> wrote:

Hi,
>
> I'm starting to investigate using autoreject and so far it looks quite
> promising. One thing I'm running into is using ICA and EOG/ECG projectors.
>
> In the paper it is suggested to "first run autoreject only for detection
> of bad channels but without interpolation" then exclude those channels from
> ssp, ica or sss computations.
>
> This seems like a sensible approach but from a practical stand point how
> is that done. Should I estimate the model first
> using
>
> ar.fit(epochs)
>
> and then look at ar.bad_segments to exclude any channel that is ever bad?
> Would it be better to do this on the epochs created using the EOG/ECG
> events as part of SSP determination?
>
> I assume a similar iterative approach would be recommended for dealing
> with motion correction?
>
> Thanks
> Luke
>
​
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