[Eeglablist] Beyond good and evil of ICA

[Makoto Miyakoshi]

Dear Robert,

I want to know all publications that makes a clear claim that 'ICA distorts
phase'. I will include all of them for our clarification paper. So far I
know Montefusco-Siegmunt et al. (2013) is the only paper that makes this
invalid claim. If you know other papers, please let me know.

Again, you are calling the difference between 18 Bitcoins and 19 Bitcoins
'distortion'. It's a due change. See the pages below.
https://sccn.ucsd.edu/wiki/How_phase_is_calculated_in_linear_decomposition
https://sccn.ucsd.edu/wiki/ICA_phase_distortion

Georges, Ramon told me that all the posts were published on the list. If
otherwise, please let us know. Sorry for the trouble.

Makoto

On Wed, Jul 26, 2017 at 12:06 PM, Robert Thatcher <rwthatcher2 at yahoo.com>
wrote:

> 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):
>
> http://www.appliedneuroscience.com/TWO-COMPARTMENTAL_MODEL_EEG_
> COHERENCE.pdf
>
> 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 and reconstruct channel EEG by back projecting the
> remaining ICs, of course it changes channel EEG phase!” (Makoto Miyakoshi,
> Eeglablist ICA and signal phase content, Sept. 16, 2014)
>
>
> “The EEG reconstruction after removing bad components/sources MAY change
> the phase value of the signal at any electrode.” (M. Rezazadeh Eeglablist
> ICA and signal phase content, Sept. 18, 2014).
>
> “The reconstructed data after removing spurious ICA components differs
> from the original time series, and because of that there are phase
> differences.” (Arnaud Delorme, Eeglablist ICA misinformation, June 10,
> 2017).
>
>
>
>   “I first noticed the problem with phase distortion more than a decade
> ago” (Robert Lawson, Eeglablist ICA misinformation, June 14, 2017).
>
>
> “I think Bob is right that the relative phase will be changed by deleting
> 1 or 2 artifact components.” (Ramesh Srinivasan, Eeglablist ICA
> misinformation, June 14, 2017).
>
> “We found phase distortions in the 8-10 Hz alfa band (greatest near the
> source of artefact) but also on more remote electrodes such as occipital
> and also in artefact free strokes of EEG.” (Georges Otte, Eeglablist ICA
> misinformation, June 15, 2017).
> Best regards,
>
> Robert
>
> 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.
>
>    1. 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.
>    2. 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).
>    3. 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
>



-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://sccn.ucsd.edu/pipermail/eeglablist/attachments/20170726/32686514/attachment.html>