[Mne_analysis] Applying ICA with No Components Selected out but Signal Changes Using Default Parameters

Mainak Jas mainakjas at gmail.com
Tue Jul 2 17:27:57 EDT 2019
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Hi Alex,

Could you provide us a full script on the MNE sample data that we can run?

Mainak

On Tue, Jul 2, 2019 at 5:14 PM Rockhill, Alexander P. <
AROCKHILL at mgh.harvard.edu> wrote:

> Also, of note the ica scale is off by quite a lot in the plot_sources
> plot, it is way too zoomed in.
>
> Alex
>
> Translational NeuroEngineering Laboratory
> Division of Neurotherapeutics, Department of Psychiatry
> Massachusetts General Hospital, Martinos Center
> 149 13th St Charlestown #2301, Boston, MA 02129
> ------------------------------
> *From:* mne_analysis-bounces at nmr.mgh.harvard.edu <
> mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Rockhill,
> Alexander P. <AROCKHILL at mgh.harvard.edu>
> *Sent:* Tuesday, July 2, 2019 3:25 PM
> *To:* mne_analysis at nmr.mgh.harvard.edu
> *Subject:* [Mne_analysis] Applying ICA with No Components Selected out
> but Signal Changes Using Default Parameters
>
> Hi,
>
>     In an analysis, I am running:
>
> ica = ICA(method='fastica', n_components=n_components,  # n_components=None
>           random_state=seed)
> ica.fit(inst2)
> ...
> inst2 = ica.apply(inst2, exclude=ica.exclude)
>
>     and when I skip all intermediate steps and just fit the ICA and apply
> it with an empty list for ica.exclude the signal still changes, quite a
> bit. I thought if no components were selected out and all the max PCA
> components were used the signal would be unchanged or basically unchanged.
> Is this a bug or something with my implementation?
>
> Thanks,
>
> Alex
>
> Translational NeuroEngineering Laboratory
> Division of Neurotherapeutics, Department of Psychiatry
> Massachusetts General Hospital, Martinos Center
> 149 13th St Charlestown #2301, Boston, MA 02129
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> Mne_analysis at nmr.mgh.harvard.edu
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