[Eeglablist] FW: Beyond good and evil of ICA

Tue Aug 1 14:18:25 PDT 2017

Dear Robert,

I paste a link below to show* mathematical process of how phase CHANGES
after rejecting a component* obtained by a linear method.
You are calling the difference between 18 Bitcoins and 19 Bitcoins
'distortion'. It's a due change.
https://sccn.ucsd.edu/wiki/How_phase_is_calculated_in_linear_decomposition

If your understanding is different, *please show it in math*.

Makoto

On Thu, Jul 27, 2017 at 12:30 PM, Robert Thatcher <rwthatcher2 at yahoo.com>
wrote:

> Dear Makoto,
>
> You stated: "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."
>
> The phase distortion by ICA reconstruction was only discovered in 2014 so
> there are not a lot of publications on this topic.  However, you are the
> author of one publication yourself on this Eeglablist.
>
> For example: “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 proof of the distortion was discovered and validated by comparing the
> phase differences of the original EEG to the ICA reconstruction time series
> thereby invalidating the cross-spectrum which is essential for network
> analyses and also inverse source solutions.  The proof is by observation
> and mathematics for example by yourself and the following other Eeglablist
> publishers:
>
> “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).
>
> Additional proof is by direct comparisons like Arno did showing about 98%
> of the phase differences are statistically significantly altered at P <
> 0.0001. Here is a url to some of the statistics and tutorial demonstrations
> that allow one to verify for themselves:
> http://www.appliedneuroscience.com/Tutorial_Adulteration_Phase_
> Relations_when_using_ICA.pdf
>
> Myself and colleaques will be publishing more statistical comparisons and
> also show how ICA reconstruction distorts other network measures such as
> the Phase Slope Index and phase shift and phase lock duration and
> phase-amplitude coupling and cross-frequency coupling, etc.
>
> Other publications are:
>  Bridwell et al (2016) *Spatiospectral Decomposition of Multi-subject
> EEG: Evaluating Blind Source Separation Algorithms on Real and Realistic
> Simulated Data*. Brain Topogr DOI 10.1007/s10548-016-0479-1 Feb 2016 -
> see page 13 where they state: “The current group spatiospectral BSS
> approach discards phase information …” (Pg 13).
>
> R.W. Thatcher (2012) "Handbook of QEEG and EEG Biofeedback" ,
> Anipublishing Co., St. Petersburg, Fl
>
> Otte, G. "ICA Reconstruction"  Presented at the ANT workshop, Beaune,
> France
>
> I hope that this is helpful.
>
> Best wishes,
>
> Robert
>
> On Thursday, July 27, 2017, 1:58:05 AM EDT, otte georges <
> georges.otte at pandora.be> wrote:
>
>
> Dear Bob
>
>
>
> I reposted thismessage below  to the EEGLablist and asked Makoko what
> caused his opinion switch since 2014 ….
>
>
>
> Maybe another mail that will get “lost”….   ?  We’ll wait and see….
>
>
>
> Sincerely
>
>
>
>
>
> Georges
>
>
>
>
>
>
>
> *From:* otte georges [mailto:georges.otte at pandora.be]
> *Sent:* Thursday, July 27, 2017 7:55 AM
> *To:* 'mmiyakoshi at ucsd.edu' <mmiyakoshi at ucsd.edu>
> *Subject:* RE: Beyond good and evil of ICA
>
>
>
> Dear Makoto
>
>
>
> Below is the mail I have send to the EEGLab list and that could maybe also
> be relevant as a reply to Mr. Andrew Smart.
>
>
>
> I can imagine that managing a busy list in extra time is quite a hard task
> so therefore I can understand that messages get lost in transit. No offense
> taken.
>
>
>
> PS the bitcoin image (a string of chars) is mine. It reflects to the fact
> that if one has 19 strings or components and omits 4  or 5 the
> reconstructed ones will not be accepted as true bitcoins. In case I am
> wrong I will send you my sincere apologies and some char strings (just
> joking)
>
>
>
> Sincerely
>
>
>
> PS: (no joke) in a mail You send me in 2014 when we had this discussion
> again you did state that ICA reconstruction does indeed change phase
> relations between channels. What causes Your switch of opinion ?
>
>
>
> Sincerely
>
>
>
> Georges
>
>
>
> Mail of july
>
>
>
> There is a major evolution in modern neuropsychiatry that aims at linking
> clinical symptoms to brain network dysfunctions. While this approach was
> successful in grounding neurological symptoms to structural pathologic
> alternations in brain networks, in psychiatry the main momentum was not
> structural but functional network dysfunctions. While fMRI was the pioneer,
> the much better time resolution of MEG and EEG made them the preferred
> tools. Their output ( time series) is but a means to further construct a
> functional image of the networks involved where phase dynamics teach us the
> directionality of the information flow in the network nodes and allows us
> by comparison with a database of normal values what functional
> abnormalities can be detected. For me phase integrity in the data is thus
> very important to be able to construct valuable graph theory models of
> those networks be them dysfunctional or compensatory. Much work has been
> devoted on this topic since many decades by DrThatcher but also by many
> other authors such as Vinod Menon ( Stanford) linking psychiatric symptoms
> to specific network dysfunctions. For us, clinicians this introduces a new
> approach to neuroscientific psychiatry that links psychiatry back to it's
> neurobiological roots and can hopefully one day send the DSM categorization
> to the museum of the history of psychiatry.
>
> As phase is IMHO a most important parameter in order to establish the
> network internode information flow, it should not come as a surprise to
> hear that some find phase unimportant as contaminated by continuous
> artefact or hear about ICA’ s a signal reconstruction method that presents
> the danger of changing the phase dynamics in the original time series
> especially in low channel (19ch) recordings with perhaps more prominent
> effect due to overcompleteness.
>
> If in a 19 ch. EEG a clinician rejects (nulls out the rows of the mixing
> matrix ) ICAas components for blinks EMG, pletysmo and ecg ( 4 ) and then
> does a "reconstruction"  ( creating 19 channels  out of 15 ??) what we then
> get might look nice but is IMHO  not a valid base for a graph theoretical
> model of the underlying brain network.
>
> I think this is the reason this discussion is important and certainly not
> a trivial pro or contra ICA pugilism.
>
>
>
> Sincerely
>
>
>
> Georges
>
>
>
>
>
> *From:* Makoto Miyakoshi [mailto:mmiyakoshi at ucsd.edu <mmiyakoshi at ucsd.edu>]
>
> *Sent:* Wednesday, July 26, 2017 11:40 PM
> *To:* Robert Thatcher <rwthatcher2 at yahoo.com>
> *Cc:* EEGLAB List <eeglablist at sccn.ucsd.edu>; Georges Otte <
> georges.otte at telenet.be>
> *Subject:* Re: Beyond good and evil of ICA
>
>
>
> 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
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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