[Eeglablist] ICA after PCA

[Iman Mohammad-Rezazadeh]

Hi Makoto,
My question is : does doing PCA before ICA helps for increasing K or in other words the quality of ICA output? Could you please describe it in a simple language ☺
Thanks
Iman
From: Makoto Miyakoshi [mailto:mmiyakoshi at ucsd.edu]
Sent: Wednesday, April 20, 2016 7:01 PM
To: Iman Mohammad-Rezazadeh <irezazadeh at UCDAVIS.EDU>
Cc: EEGLAB List <eeglablist at sccn.ucsd.edu>; Arnaud Delorme <arno at ucsd.edu>; Loo, Sandra <SLoo at mednet.ucla.edu>; Jeste, Shafali M.D. <SJeste at mednet.ucla.edu>; ADickinson at mednet.ucla.edu; Scott Makeig <smakeig at ucsd.edu>
Subject: Re: ICA after PCA

Dear Iman,

> I have found few papers and discussions about doing PCA and then ICA for increasing the K-factor and dimensionality reduction.

K-factor you mean is the term you see in the equation?

minimumDataPointsToRunICA = ((number of channels)^2) * K

> However, I cannot completely understand what is the meaning of the ICA outputs?

ICA output rotates PCA-dimension-reduced data. You can reconstruct full-channel (but now rank-deficient) data using PCA output.

Actually there is another rotation, sphering, as a preprocess for ICA. So you rotate data three times to find unmixing matrix using PCA rank-reduction option. That's why you feel dizzy :-)

Makoto



On Wed, Apr 13, 2016 at 11:59 PM, Iman Mohammad-Rezazadeh <irezazadeh at ucdavis.edu<mailto:irezazadeh at ucdavis.edu>> wrote:
Hi EEGLABers,
I have found few papers and discussions about doing PCA and then ICA for increasing the K-factor and dimensionality reduction. The (un)mixing matrix would be m x m which m is the number of PCA. Each row (column) is the weights for ICA sources.
However, I cannot completely understand what is the meaning of the ICA outputs? How are the IC maps (topo maps) constructed since we need the location of PCA components (similar to  the channels locations) to plot the spatial filters/IC maps.
In other words,  how can we plot the IC maps given the fact that we don’t have the spatial information about PCA components?
Best
Iman


============================================
Iman M.Rezazadeh, Ph.D
UCLA David Geffen School of Medicine
Semel Institute for Neuroscience and Human Behavior
760 Westwood Plaza, Ste 47-448
Los Angeles, CA  90095
http://www.linkedin.com/pub/iman-m-rezazadeh/10/859/840/







--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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