[Mne_analysis] ICA failing to exclude bad channels

[Phillip Alday]

I suspect the problem may be in the definition of 'bads' -- Lyam are
you explicitly marking channels 'bad' or you expecting automatic
detection of bad channels (as e.g. some EEGLAB functions do)?

Phillip

On Tue, 2017-05-30 at 11:33 +0200, Alexandre Gramfort wrote:
> Dear Lyam,
> 
> ICA does ignore the bad channels see for example:
> 
> https://github.com/mne-tools/mne-python/blob/master/mne/preprocessing
> /ica.py#L408
> 
> can you share a full gist of code to replicate the problem?
> 
> Alex
> 
> 
> On Mon, May 29, 2017 at 8:37 PM, Lyam Bailey <Lyam.Bailey at dal.ca>
> wrote:
> > 
> > Dear MNE users,
> > 
> > 
> > I'm trying to analyse some EEG data which contains a few very noisy
> > channels
> > (amplitude is often to the order of 1V). This seems to be causing
> > problems
> > with ICA, even after bad channels are excluded
> > 
> > 
> > I begin EEG preprocessing by excluding the bad channels, and then
> > re-referencing the data to the average of all remaining channels
> > with:
> > 
> > 
> > raw.info['bads'] = ['CP1',etc...]
> > raw, ref_data = set_eeg_reference(raw, ref_channels=None,
> > copy=False)
> > 
> > After filtering and trial-by-trial artifact rejection, I run ICA
> > with:
> > 
> > ica = mne.preprocessing.ICA(n_components=.99, method='fastica',
> >                             max_iter=500,
> > random_state=ica_random_state)
> > picks = mne.pick_types(epochs.info, meg=False,
> >                        eeg=True, eog=False, stim=False,
> > exclude='bads')
> > ica.fit(epochs)
> > 
> > This usually outputs a single IC component, and does nothing to
> > address
> > blinks/saccades etc that are clearly present in the raw data. My
> > feeling is
> > that ICA is somehow failing to exclude the bad channels, meaning
> > that (in
> > the presence of much higher variance, introduced by the noisy
> > channels) it
> > is relatively blind to 'normal' artifacts in the EEG.
> > 
> > Does anyone know why this might be happening? Any advice on the
> > problem
> > would be greatly appreciated!
> > 
> > Regards
> > Lyam
> > 
> > ---------------------------------------------------------
> > 
> > Lyam Bailey, BSc.
> > 
> > Graduate Student
> > Department of Psychology & Neuroscience
> > Dalhousie University
> > 
> > 
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