[Eeglablist] Questions about AMICA
Thomas mas
thomasmas at gmail.com
Wed Jan 16 06:54:29 PST 2019
Dear all,
I would like to avoid the issues associated with data rank when running
AMICA.
I know that interpolating bad channels and average re-referencing are
common operations that could make the data rank deficient. I also know that
the Matlab 'rank' function is not always reliable.
I am asking whether the following approach is correct.
After interpolating bad channels and re-referencing to the average, I
estimate data rank by using the following snippet of code:
% Estimating data rank
dataRank = EEG.nbchan;
if strcmp(EEG.ref,'averef')
dataRank = dataRank - 1;
end
if isfield(EEG.etc,'clean_channel_mask') % using ASR to remove bad channels
dataRank = dataRank - length(find(~EEG.etc.clean_channel_mask));
end
dataRank = min([rank(double(EEG.data')) dataRank]);
Next, I enter dataRank in the field named '# PCA Dims' of the
pop_runamica() window. In this way, I get exactly dataRank independent
components, keeping all the channels (remember that this step occurs after
channel interpolation).
Is this approach correct?
Thank you in advance.
All the best,
Thomas
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