[FieldTrip] MaxFilter and ICA preprocessing

[Frédéric Roux]

Problem solved.

I am posting below the solution with what I think may be 
the explanation, in case someone else might experience a similar
issue.

cfg = [];
cfg.method = 'runica';
cfg.numcomponent = rank(meg_data.trial{1}*meg_data.trial{1}');

ic_data = ft_componentanalysis(cfg,meg_data);

Most likely, this reduces the complexity of the solution the algorithm
searches for. Insead of searching for n1 = length(meg_data.label) ICs 
the algorithm searches for n2 = rank(meg_data.trial{1}*meg_data.trial{1}') ICs.
The slowing down of the ICA arises because the data has rank n2 and not n1, but
still the algorithm tries to search for a solution satisfying rank = n1.

Remains the question why cfg.runica.pca =  rank(meg_data.trial{1}*meg_data.trial{1}') didn't 
have any effect. Has this option become obsolete in more recent versions of FT?

Best,

Fred


Frédéric Roux

----- Original Message -----
From: "Frédéric Roux" <f.roux at bcbl.eu>
To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>, "Discussion list for international MEG community" <megcommunity at jiscmail.ac.uk>
Sent: Thursday, January 15, 2015 4:41:42 PM
Subject: MaxFilter and ICA preprocessing

Dear all,

after preprocessing my MEG data (Elekta Neuromag) with MaxFilter, I noticed that the ICA decomposition
takes longer than if the data hasn't been preprocessed with MF.

As a side note: I've taken care of reducing the dimensionality of the data to cfg.runica.pca = rank(data.trial{1}*data.trial{1}'), as I've read in previous posts that otherwise the results of the ICA decomposition can contain complex values.

My questions are: 

1) is the fact that the ICA training takes longer normal?

2) why does the ICA training take longer in the case of MF preprocessing?

Sorry for cross-posting on both lists, I'm just hoping to get an answer asap.


Best,
Fred


---------------------------------------------------------------------------