[FieldTrip] using cfg.runica.pca to reduce number of ICs

[Frédéric Roux]

Dear all,

I have a general question relating to the usage of cfg.runica.pca
during the call to ft_componentanalysis.

Is it correct to assume that cfg.runica.pca = length(meg_data.label) will
force the algorithm to return n = length(meg_data.label) ICs, and that as a
result artifacts can be "spread" across several ICs?

If that's true, then I imagine that cfg.runica.pac = n/4 will return less components
and reduce the "spread" of artifacts over several components.  

My question is how to choose the number of principal components to which the data
is reduced before ICA? 

Best,
Fred
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