[Eeglablist] Beyond good and evil of ICA

Robert Thatcher rwthatcher2 at yahoo.com
Wed Jul 26 12:06:22 PDT 2017

Dear Makoto,   I think your criticisms are important and note that there are traveling waves in the EEG and also there is nonlinearity in the form of wave dispersion as noted by Nunez, 1981 and demonstrated in the paper that can be downloaded at this url (see Table IV):
It seems that your 3rd criticism does not recognize that ICA reconstruction of a new time series violates the "Reciprocity" theorem of Helmoltz and the "Lead Field" necessary for a valid inverse solution.
You mentioned a recent criticism on ICA that you stated is "technically invalid".   I doubt that you are referring to the criticism about ICA reconstruction adulterating phase differences between EEG channels?   The issue of ICA reconstruction and phase alteration is a settled issue based on math (not the separation of mixtures of phase or frequencies but rather the cross-spectrum at the same frequency at different locations) as well as multiple empirical demonstrations and tutorial demonstrations that anyone can verify for themselves.  Also, I am copying from the Eelablist statements by yourself and five others agreeing that ICA reconstruction alters phase differences.  
“If you remove IC andreconstruct channel EEG by back projecting the remaining ICs, of course itchanges channel EEG phase!” (Makoto Miyakoshi, Eeglablist ICA and signal phasecontent, Sept. 16, 2014) 

“The EEGreconstruction after removing bad components/sources MAY change the phase valueof the signal at any electrode.” (M. Rezazadeh Eeglablist ICA and signal phasecontent, Sept. 18, 2014).

“Thereconstructed data after removing spurious ICA components differs from theoriginal time series, and because of that there are phase differences.” (ArnaudDelorme, EeglablistICA misinformation, June 10, 2017).


  “I first noticed the problem with phase distortion more than adecade ago” (Robert Lawson, Eeglablist ICA misinformation, June 14, 2017).

“Ithink Bob is right that the relative phase will be changed by deleting 1 or 2artifact components.” (Ramesh Srinivasan, Eeglablist ICA misinformation, June 14, 2017).

“Wefound phase distortions in the 8-10 Hz alfa band (greatest near the source ofartefact) but also on more remote electrodes such as occipital and also inartefact free strokes of EEG.” (Georges Otte, Eeglablist ICA misinformation, June 15,2017).
Best regards,
On Wednesday, July 26, 2017, 2:01:59 PM EDT, Makoto Miyakoshi <mmiyakoshi at ucsd.edu> wrote:

Dear List,
Recently there was a criticism against ICA on the list. Unfortunately it is technically invalid so I remained unsatisfied. Let me share real problems of the ICA model (Onton and Makeig 2006) to re-do it. This is a continued discussion from the one titled 'How phase is calculated in linear decomposition' and now this is my turn to criticize ICA!
As far as I know, there are three known limitations in ICA model.   
   - Spatial stationarity. I have seen a nice traveling waves in ECoG grid data during Joaquin Repela's presentation at SCCN. This clearly violates the assumptions of spatial stationarity in ICA.
   - Temporal stationarity. Shawn Hsu at SCCN presented time-series data of ICA model likelihood during drowsy driving task. Also, Jason Palmer's AMICA also demonstrated temporal changes in model likelihood. So one model per data does not fit the truth (unless the task has a strong control over a subject's cognitive and behavioral states).   

   - Dipolar source model. Although most of ICA results are fit with dipole models, it seems ICA also returns (probably) non-point sources. When one fits a dipole model to such a non-point source, the location tend to end up with physiologically invalid depth (this is the most annoying thing about ICA today)
I'd like to hear detailed criticism about these points. Note I saw these critical counterevidence in SCCN; we are not a boring ICA cult who have blind belief in it.
Nonetheless, ICA model has a critical merit. I named it Independence-Dipolarity Identity (I-D Identity, or IDId). I-D Identity means that when ICA solves temporally problem, it also solves spatial problem at the same time without using ANY spatial constraint. Dipolarity can be thought of, in short, biophysical origin-ness. Hence I believe that this is evidence that ICA hits some physiological truth of EEG generation.
There could be multiple criticisms against the limitations of ICA model, but at the same time any criticism, at least so far, was NOT strong enough to deny I-D Identity of the ICA model. After all, because of this I-D Identity, I still advocate ICA (but similar dipolarity can be achieved by using very different approach, such as SOBI... so independence is not the only requirement to reach the biophysical validity. It's still a mystery to me.)
All models are wrong, but some are useful... but I want to go beyond this statement to reach the ground truth of EEG!
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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