[Eeglablist] Automatic ICs rejection from the EEG data in MNE Python

[Scott Makeig]

Rab -

Why not try running open source EEGLAB/Matlab tools on open source Octave?
Arno has worked to insure this is possible ...  I would recommend you try
Luca Pion-Tonacdhini's ICLabel.

Scott Makeig

On Wed, Feb 23, 2022 at 10:55 AM Rab Nawaz via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi EEGLABers,
>
>
>
> As in the EEGLAB we know there are multiple ICA classification methods
> available as a plugins (MARA (Winkler et al., 2011), ADJUST (Mognon et al.,
> 2011), SASICA, IC-MARC) for some near-automatic methods for removing
> unhealthy ICs to clean the data from artifacts.
>
>
>
> I am restricted to use an open-source tool therefore I choose Python. I am
> trying to perform data cleaning based on the ICA in MNE Python and looking
> for something automatic that helps in automatic ICs rejection. In MNE
> Python, there is a template matching method that uses the artifacted ICs
> from one person as ground and correlates it with the ICs of new EEG to pick
> the ICs which have strong correlation with the artifacted one. But, I am
> looking for something similar to the implementation of MARA or ADJUST in
> MNE Python. Do you know any materials that can help me in this regard? Or
> something else (other than template matching) that can help in selecting
> the artifacted ICs automatically in Python?
>
>
>
> Thanks
>
> Rab
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-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott