[Eeglablist] ICA Misinformation (Marius Klug)
Barry Oken
oken at ohsu.edu
Tue Jul 11 10:34:42 PDT 2017
Hi everyone. I’ve been following this active discussion about “artifact-free” EEG and thought I’d point to a unique study to show that EMG artifact contaminates scalp EEG beta activity. https://doi.org/10.1016/j.clinph.2007.04.027
Not sure I have the Australian commitment to paralyze myself to prove it as well as they did but non-cerebral activity contributing to scalp EEG is the norm and everyone has already suggested some of the many approaches to deal with it.
Barry
Barry S. Oken, MD, PhD
Professor, Depts of Neurology, Behavioral Neuroscience and Biomedical Engineering
Oregon Health & Science University CR-120
3181 SW Sam Jackson Park Road
Portland, OR 97239
503-494-8873
503-494-9520 (fax)
From: eeglablist [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Marius Klug
Sent: Monday, July 10, 2017 3:15 AM
To: Joseph Dien <jdien07 at mac.com<mailto:jdien07 at mac.com>>
Cc: Clayton Hickey <cmhickey at gmail.com<mailto:cmhickey at gmail.com>>; eeglablist <eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>>
Subject: Re: [Eeglablist] ICA Misinformation (Marius Klug)
Hi everyone,
sorry for the late response!
Thanks a lot for the info, Clayton, this is really helpful and backs up the discussion to a great degree! It would be nice to have something published with all the biological artifacts (eye, muscle, heart, skin) that finally can put the idea of an "artifact-free" EEG at rest... More projects on the endless to-do list ;-)
Cheers,
Marius
2017-07-07 21:47 GMT+02:00 Joseph Dien <jdien07 at mac.com<mailto:jdien07 at mac.com>>:
I’ve been working on an artifact correction manuscript with an EEG plus eye-tracker dataset. The corneo-retinal dipole (CRD) artifact reflects eye position not eye movement so it’ll be constantly present even if the eyes maintain fixation. My take is that each artifact is best corrected with a method tailored to its unique characteristics. I’ve got a working algorithm (Multiple Algorithm Artifact Correction or MAAC) implemented in my EP Toolkit (https://sourceforge.net/projects/erppcatoolkit/?source=navbar) but I need to finish testing and validation. Ideally it also needs to be tested out on different systems and montages to see how well it generalizes.
Cheers!
Joe
On Jul 5, 2017, at 07:37, Clayton Hickey <cmhickey at gmail.com<mailto:cmhickey at gmail.com>> wrote:
Hi Marius, Hi All,
In reading your message, Marius, it struck me that I might make a small contribution to this discussion.
The idea that EEG can be free of eye movement artifacts is something that can be empirically studied… what is needed is an independent measure of eye movements. Many of us have this in concurrent eye-tracking data.
In my group we use an eye-link 1000 and the wonderful EYE-EEG toolbox to co-register tracker data with concurrently recorded 64-channel EEG (Dimigen et al. & Kliegl, 2011, JEP:GEN). As per the pipeline suggested by Dimigen et al., we derive ICA components from the EEG data and identify artifactual components as those that strongly correlate with the tracker data. This removes some of the ambiguity inherent to identification of artifacts from EOG, topography etc, because the IR-camera-based tracker data is independent of the encephalic voltage data.
For the fun of it (procrastination, get thee behind me) I just had a quick look at a few datasets, extracting intervals where participants maintained fixation. I ran infomax ICA on this data and identified ‘artifactual’ components as those that correlated with the eye-tracking data. I consistently got at least a couple of components that strongly correlated with the tracker signal. This in spite of the fact that the data was putatively ‘artifact-free’ and collected during consistent maintenance of fixation.
Some of this variance may come from the brain. Dilation and microsaccades are likely to have related neural activity that could be confounded with muscle / rotation-of-eyeball activity by ICA. But the brain activity seems to be a very small source of variance. The components load heavily on frontal sensors close to the eyes, sharply tapering off along the anterior-to-posterior axis with very low or zero weights at posterior electrodes. I would expect microsaccades and dilation to elicit brain activity in subcortex (diffuse topography) or over early visual areas (posterior topography).
So... the eyes are doing something to the EEG signal during the maintenance of fixation, and ICA can pick this up. This seems to be primarily artifact from muscle / eyeball rotation.
best, clayton
8. Re: ICA Misinformation (Marius Klug)
From: Marius Klug <marius.s.klug at gmail.com<mailto:marius.s.klug at gmail.com>>
Subject: Re: [Eeglablist] ICA Misinformation
Date: June 30, 2017 at 3:02:52 PM GMT+2
To: otte georges <georges.otte at pandora.be<mailto:georges.otte at pandora.be>>
Cc: eeglablist <eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>>, pnunez at tulane.edu<mailto:pnunez at tulane.edu>, r.srinivasan at uci.edu<mailto:r.srinivasan at uci.edu>, Georges Otte <georges.otte at telenet.be<mailto:georges.otte at telenet.be>>
Dear Georges, all,
I am not sure if I missed something, this is the last email about the subject to my knowledge, so I'm answering to it now since I feel it should get one. My answers are in the text below, I think this will also be my first and last email on this topic. Everything I write is my own personal opinion.
2017-06-25 22:18 GMT+02:00 otte georges <georges.otte at pandora.be<mailto:georges.otte at pandora.be>>:
Dear all
Although I find the subject very interesting, the "cynicism" embedded in some responses feels a bit vexatious and this is something that we should try to avoid in important scientific discussions not unlike this on concerning the possible side effects of ICA signal reconstruction and the model that ICA approach of EEG is based upon
I find it strange that you attribute non-scientific way of arguing mostly to the ICA experts' side, having followed the complete discussion. I found Robert to be rather bold in his statements and kind of immune to well-formulated and thought through counter-arguments to his statements, even if they are backed up by data and plots. No wonder the tone in the discussion has turned a bit darker after a while, if you ask me. We all have a lot of things on our plate and must allocate our resources, some of the writers have allocated a lot of theirs to the topic and their time and reasoning has been met with denial disguised as interest, and statements have been repeated even though they were addressed already.
An example: In Prof Debners reply to Dr. Thatcher he invokes the question of the possibility of invisible ECG artefact contamination of the EEG recordings and then continues by saying " because you don't see heart-electrical activity in your "original" 19-ch 10/20 recordings, can you seriously claim that the heart of your participant was not beating during recording?" Ha.. Ha ... ha
I suspect that not even to be specifically humorous, but an actual argument. Robert and other in his side of argument several times spoke of "artifact-free data segments" which would be distorted by taking out an ICA component, even if it was artifact-free. The argument here is, and I can't believe that I have to write this again, since it's been written so often already, that no such data exists, end of story. EEG is just an electrical recording. Electrical signals are abundant and generated constantly during the recording by a wide number of sources, not only the brain. One example here being heart beats. Now obviously those signals do have an amplitude and a phase, and since they are superpositioning the brain signals and thus part of the EEG recording, they will - no way around this! - have an impact on the phase (and amplitude) of the data set. The data set is thus _continuously_ distorted by the artifact. So by saying that a data set has artifact-free time periods, Robert implies that the heart has stopped beating, which - as Stefan pointed out - is rather unlikely (now here is a bit of humor on my side, I admit ;-) ).
The thing is: This applies not only to heart beats but to each and every single artifact source that can be recorded by the EEG! So, even if you have no super strong eye blink artifacts, the eyeballs and eye muscles will still continuously contaminate the data - a bit at least. Since the IC for eyes in a 19 channel data set does likely contain both blinks and movements, taking it out will also take out the continuous eye movement artifacts produced by all kinds of drifts, saccades, and microsaccades, so it will take out parts of the data in the complete set! Now, since the eye signal again has a phase and an amplitude, the resulting signal will be distorted - but to the better, not to the worse! The new signal does not contain the artifacts of the eyes, AT ALL TIME POINTS, at least to the degree that ICA was able to separate them. So yes, the phase will be distorted, AND THAT IS A GOOD THING! The IC topography should, however, not extend to the parietal regions, so there should not be any distortions there. You can also check the continuous IC activity (meaning eye activity) and at times where it is very low, the distortion in the reconstructed sensor channels should be equally low.
The question of possible ECG contamination that Stefan raioses is indeed very important but instead of just joking about it, perhaps it would be even better to (also) propose a possible way to solve this question.
The proposed way is to take out the artifact via ICA. That's doable with high-density EEG, I find ECG ICs in my subjects without trouble usually. We use a neck band with electrodes in addition, that does help a lot, I suppose...
I am not in the same scientific league that Prof Debner is in but should that question pop up I would try to search for a test or setup that could clarify it or lead to a solution. Is that not the core of science? I can imagine that at Stefan's university, open hart operations are being performed and it would perhaps be feasible to record EEG before and during the period that the heart function is stopped and a heart-lung machine takes over. I agree that this is not a trivial task due to -among others- the electrical and other potential interferences in the operational theatre and it would require a good research capacity but I am confident that Stefan is up to that task.
This is indeed a non-trivial task and you must be joking to casually assume that Stefan will just lay down other projects at hand to have an experiment to prove small subleties of heart beat artifact attenuation via ICA - that are obvious to the skilled user and will likely not convince Robert anyway - in a setup that is likely to contain artifacts from all the machines around that are so strong that not much else can be recorded as a start. I can see the heart beat in the neck electrodes even visually WHILE RECORDING without any preprocessing and ICA, there is no way to deny this.
I think the results would seriously help the community to come closer to a more definite answer. The same could be done for eye movement artefacts. In ophthalmologic clinics all kind of eye diseased are treated. What about people with no corpus vitreum: do they have other eye movement artefacts before and after operation? It is often repeated that eye movement potentials are caused by the cornea-retina dipole. Is that so? Have You people tested this or do You just assumed this is so because it sounds so very plausible. I heard at least one ICA specialist state that this is a mémé and that the corpus vitreous is the originator of those eye movement potentials. I know that all handbooks of EEG claim otherwise so why not test this? We should be very critical with plausible models and try to test the stuff that we all take for granted.
Inhowfar does it matter if the eye ball movement artifact is generated in to corpus vitreum? I don't see this to be a counter to the notion of a dipolar eye ball, it's just a specification. It doesn't matter. The eye moves -> signals detectable in the EEG which should be taken out. You're giving a straw man argument here.
Scientists with access to large university hospital facilities are empowered to solve these kinds of question. They s are the people we clinicians need to get questions solved and personal beliefs or opinions are less relevant in those matters. I can of course understand humor even with a sniff of cynicism but it should not stop there. Humor should not serve to avoid tricky questions as a rapier in a duel but should be followed by an indepth endeavor to prove one point of view in a way that everybody can agree as solid evidence.. I do not want to start a flame war nor do I have revendicate intentions but as a clinician I feel that we deserve a more serious solution from the side of You scientists.
The challenge is open and until now unmet.
Rest assured that the majority of "us scientists" are giving our best to investigate our own methods and continuously try to find better ways to analyze our data, since we are usually our own most harsh critic and overthink everything (at least I am and do)... You however should not have stopped with your assessment of cynical humor above but thought further why this assumed humorous argument was indeed spot on.
Our serious solution is right there: High-density EEG with spatial filtering of some kind (ICA, spatiospectral decomposition, joint decorrelation, ...), source localization, source-level analysis or back-projection of sources of interest (without artifacts) into the sensor-level. Investigating all ICs and seeing the obvious: There are noise and artifact signals in the EEG data all the time. Of course it would be nice to have and provide you with a really fancy way to have perfect brain-only data with 19 electrodes, but at least for the time being, that is not possible. Also, I am wondering if you would then still say that it is different from the raw data and thus bad, ignoring the arguments given... Which brings me to my last point:
When Dr Thatcher launches a potential serious problem, it did not help me very much to hear his data being considered flawed, to hear preemptive suppositions that his choice of ICA algorithm was wrong, that his selection was maybe erroneous etc. One cannot solve a question or a problem by attacking the man who asks the question. It feels like shooting at the pianist because one dislikes the melody. Please bring forward more sturdy arguments and proof that ICA reconstruction does not alter phase.
I don't remember anyone attacking Robert as a person, except for the harsh tone and bold statements. The "preemptive suppositions" were indeed important and correct: He did not provide any information about the ICA decomposition and the ICs that were taken out. Since eye movements should not extend to the parietal parts of the EEG, but the phase has been altered in those channels after back projection, there must have been other ICs taken out (possibly containing brain signals) or the decomposition was seriously bad (mixing eye and brain signals), which led to doubts of the decomposition algorithm, the choice of ICs, and to the general statement that 19 channels are rather few for a good ICA decomposition in general. In fact, the discussion about his data began when Arno could clearly show that taking out eye movement artifacts did NOT distort phase to a relevant degree in times other than eye artifacts occurring in one of his earlier emails. How Robert can interpret those figures to suit his own argument is a mystery to me. Arno was, so to say, not able to replicate your bug and then the list proceeded to search for other reasons, but we were stuck by the fact, that there was no movement on Roberts side, no careful examination of the facts and arguments that have been laid out.
And, again, I can't believe that I have to write this again: YES, TAKING OUT ICs WILL ALTER PHASE! This is not even an argument! The thing is a) that this is something good for the time points where the artifacts occur, because in fact the original data has been distorted by a the artifacts, eye in this case, and taking out the artifacts will restore the more correct brain signal phases and b) the extent and spatial distribution of the distortion presented by Robert led to the conclusion that something must have been done incorrectly or at least not with a lot of scrutiny. Who knows... workshop participants might make mistakes, they learn, that's what they are there for. But this was not addressed by Robert at all.
The arguments and proof have been as sturdy as it can get and the fact that you and Robert don't see this just proves that your heads are sturdier, sorry to be so clear in my expression. I have nothing personal against either you or Robert, I don't know you at all and I don't judge you as persons, to be clear, we might get along well over a beer in a bar. I just judge the facts and your reactions to them in the emails I read.
Considering the EEG as a chaotic multivariate time series continuously contaminated by visible and invisible artefacts is a model that if true justifies the use of ICA but as such a model that needs rock solid scientific confirmation and not just authority based replication of opinions.
This is the thing. That's what Stefan meant with his "cynical humor argument": You cannot seriously argue that physiological signals all of a sudden cease to exist every now and then and then come back to life again later. Let me be clear:
As long as your subjects have eyes that move, muscles that work, sweat glands on their skin, and a beating heart, there are biological artifacts in your EEG that continuously contaminate your data by superpositioning with the brain signals. And as long as you have electricity in the house that you record in, especially if it is close to the electrodes, and no faraday cage, you have other noise and artifacts that continuously contaminate your signals. This is as true as water is wet and Evolution is a thing.
And the best thing is: In times where this is not the case, the continuous activation of the IC components would be zero (as long as the decomposition is perfect - otherwise at least very low) and there would be no data alteration at those times if you subtract that IC! I feel like there should be a bit more in-depth understanding ofbiophysics of EEG, ICA, spatial filters as a method in general, linear mixture models, etc., before such a strong critique against this methods is put forward. Robert may or may not have this, but at least to me, from his arguments, it doesn't look like it. I don't say this as an attack but rather with the last spark of hope that spatial filtering as a useful method gets more understood and not bashed into oblivion in the clinics and diagnostics and in the end patients can benefit from the advances neuroscience has made in the last 30 years.
Frankly, I am kinda sad about this discussion: It could have been really intersting and fruitful, and brought the investigation of ICA as a method forward (which would be good, since it's far from perfect and many things still need to be tested and learned!) but as someone stated earlier, it's mostly interesting from a sociological point of view...
I wish you all the best,
Marius
Sincerely
Georges Otte
-----Original Message-----
From: eeglablist [mailto:eeglablist-bounces at sccn.ucsd.edu<mailto:eeglablist-bounces at sccn.ucsd.edu>] On Behalf Of Stefan Debener
Sent: Saturday, June 24, 2017 12:53 PM
To: Robert Thatcher <rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com>>; Arnaud Delorme <arno at ucsd.edu<mailto:arno at ucsd.edu>>
Cc: eeglablist <eeglablist at sccn.ucsd.edu<mailto:eeglablist at sccn.ucsd.edu>>; pnunez at tulane.edu<mailto:pnunez at tulane.edu>; r.srinivasan at uci.edu<mailto:r.srinivasan at uci.edu>; Georges Otte <georges.otte at telenet.be<mailto:georges.otte at telenet.be>>
Subject: Re: [Eeglablist] ICA Misinformation
Dear Robert,
Ok, I guess I have to give up on you. Of course you ascribe the "original" times series some magic, and this is one of several flaws in your reasoning. To cite your own published paper:
" PROBLEMS WITH RE-MONTAGING AND DISTORTIONS OF THE ORIGINAL TIME SERIES If the original EEG/event-related potential (ERP) time series is transformed into a second time series by using the average reference then the original phase differences from three electrode locations may be scrambled and lost. For example, with an average reference the entire surface of the brain is not measured, thus the averaging does not create a true zero potential at each instant of time." (citation taken from http://www.appliedneuroscience.com/Coh_phasediff&phase_resetinEEG-ERP.pdf).
Your phrase "distortion of the original time series" does make sense only if you believe that the original time series represents somehow a gold standard, something special (something "magic", forgive my poor use of English) that is magically close to the contributions from brain generators to the surface-recorded signal. In my view this is not justified, for instance because it disregards the fact that recording settings will influence how the data will be recorded, that is, they determine phase and amplitude! I argued before that attributing something special to the "original" time series is highly misleading, the "original" time series is not closer to the brain signal, in contrast it may be pretty far away from it, not only because phase of mixed brain generators does not make much sense, but also becasue of all the artifactual influences not accounted for. Now if you really believe that one particular reference scheme is appropriate in bringing the original data close to the brain while all others are rubbish, then I wish you good luck in trying to convince the community. I predict that nobody will take you serious. The reference discussion has been going on for ages, and there are good reasons to change the reference (online or
offline) depending on what the purpose of the study/analysis is.
I argue that any post-recording signal processing that changes the morphology of a time series will change the phase values as well, NOT just the average reference, and NOT just ICA. In your case, the average reference is far from zero because 19 10-20 channels, which are located on the top half of the head sphere, can hardly sum up to zero. Only a full equidistant spatial coverage of the head sphere would make the spatial average approximate zero potential. Check this paper for in-depth discussion on the average reference and the bias it introduces:
https://www.ncbi.nlm.nih.gov/pubmed/10402104). If you don't like the average reference, fair enough, then simply take any other reference, but you will observe the same "distortion" on phase values. By the way, non-invasive EEG does not measure signals from the brain, there is a skull in between and a couple other layers, all with different conductivies...just another reason to be aware of the inverse problem and trat signals originally recorded from the scalp with great care.
The second flaw in your reasoning is that you believe there are "artifact-free" intervals. The report I included showed (far from perfect, but clearly evident!) heart-electrical activity. Recording parameters strongly determine whether such "EKG" contributions show up in ICA decompositions or not (such as sub-10/20 spatial coverage). Now, only because you don't see heart-electrical activity in your "original"
19-ch 10/20 recordings, can you seriously claim that the heart of your participant was not beating during recording? Of course not! All it says is that the influcene may be stronger or weaker represented in your recordings (depending on individual differences, and, again, recording parameters). With your philosophy, you gonna miss it if it does not jump into your eyes.
Anyway, I hope others join the discussion, I am giving up.
Best,
Stefan
Am 23.06.17 um 19:16 schrieb Robert Thatcher:
>
> Dear Stefan,
>
> Thank you for your dilligence and dedication to this important
> issue. I am pleased that you are in agreement with myself and
> Georges and Gert and scienific publications that "a spatial filter
> operation such as ICA or other, the phase differences may indeed be
> different." I would add that we have not yet found an instance where
> ICA reconstruction did not alter phase differences between channel and
> there I would change the word "may" and phrase to "are indeed different".
>
> You sated: "As a toy example I include the common average reference. "
>
> In Neuroguide we do not allow one to compute phase diffferences or
> coherence when using a common reference. We found with simulation and
> real data that the common reference mixes the phases differences
> between all channels and itself distorts phase differences and often
> in strange ways, for example, if one or two channels has a suddent
> large amplitude alpha or theta rhythm then the phase differences
> between channels that do not have a alpha or beta or theta rhythm are
> altered. If one uses a single common reference then if an alpha
> rhythm appeas for example in O1/2 then there is not change in phase
> differences in channels where there is no alpha. We also compared two
> sine waves at different phase differences, e.g., 30 deg, 60 deg, 90
> deg, etc and mixed different amounts of white noise in one of the
> channels we found linear reductions in coherence (i.e., the phase
> stability over time) as a function of the SNR and the mean phase
> differences were stable until the noise was too high and when
> coherencer was near zero. In contrast, uses the averge refence and
> repeats the same signal and noise test with different phase
> differences then the mean phase difference is quickly lost and there
> is no valid measure of coherence. Here is a url to a publication
> that discusses this topic:
> http://www.appliedneuroscience.com/Coh_phasediff&phase_resetinEEG-ERP.
> pdf
>
> You stated: "Your claim that ICA has somehow corrupted the data such
> that previously super reliable clinical effects all over a sudden
> vanished is not convincing either."
>
> I never said this. There is no ICA reconstruction in NeuroGuide and
> the over 3,000 users of Neuroguide have not complained about coherence
> or phase and they always obtain repeatable measures when the retest
> patients. It was only the WinEEG users that are worried about ICA
> and they never said that they got "super reliable clinical effects".
> They just noticed that coherence using the WinEEG after ICA
> reconstruction was totally different than when they use NxLink or SKIL
> or Neurorep or Neuroguide or Brindx or other software, etc.
>
> You stated: "Now which phase values are valid, those obtained by one
> particular reference scheme or those by another? In my view they are
> both arbitraty"
>
> See my earlier reply regarding average references and the Laplacian
> reference in regard to the accurate and reproducible measures of phase
> differences as opposed to using a single common reference. I am
> recopying the link here:
> http://www.appliedneuroscience.com/Coh_phasediff&phase_resetinEEG-ERP.
> pdf here is another review on this topic:
> http://www.appliedneuroscience.com/Brain%20Connectivity-A%20Tutorial.p
> df
>
> You stated: “there is no such magically clean raw brainsignal
> available in the first place!”
>
> No one says that “magic” is involved in the EEG. However, the physics
> of EEG is involved and during a 5 minute to 20 minute EEG recording
> there is plenty of artifact free data. There are over 100,000 QEEG
> publications in the National Library of Medicine with high effect
> sizes and high test retest reliability and highly reproducible
> findings. My concern and the concern of many others is that ICA
> reconstruction alters phase differences in an entire EEG recording
> even if there are only a few instances of artifact. The reason that
> QEEG has been so successful and so widely used since the late 1950s is
> because people have been successful in avoiding or deleting artifact
> and selecting multiple artifact free parts of the record and achieving
> 0.95 or higher test retest reliability. Over reaction to the
> presence of small amounts of artifact is not a justification for
> altering the electricity of the brain including network dynamics such
> as average synaptic rise times and conduction velocities and couplings
> between groups of neurons.
>
> You stated: “Artifacts not accounted for adulterate EEG phase values”
>
> We agree on this but this is not what the discussion is about. The
> concerns of many is that the phase differences in the artifact free
> sections are altered. Rarely if ever do clinicians/scientists bother
> computing the phase differences during an eye movement artifact.
> Usually phase differences are zero and this physics fact plus the
> electrical gradients from the eyes is how many people detect eye
> movement artifact and then omit the artifact from analyses without
> using ICA. The main focus in QEEG is the parts of the recording
> where there is no artifact and the electrical potentials are generated
> by the brain inside the skull.
>
> Also, thank you for your use of the Hilbert transform, this is only of
> the tools that we use and it allows one to evaluate phase differences
> in every individual time sample in the artifact free sections and
> prove that each and every one of the phase differences for all
> channel combinations is altered by ICA reconstruction. You may be
> interested that we use the Hilbert transform to measure phase shift
> and phase lock duration that have a high correlation with Autism and
> intelligence in short distance connections and with use the Hilbert
> transform to measure the magnitude of information flow (phase slope
> index) and intelligence. Here are some hyperlinks to these studies:
> http://www.appliedneuroscience.com/Intelligence-phase_reset_Nature.pdf
>
> http://www.appliedneuroscience.com/Autism%20Thatcher%20et%20al.pdf
>
> http://www.appliedneuroscience.com/Default_Network_LORETA_Phase_Reset-
> Thatcher_et_al.pdf
>
> http://www.appliedneuroscience.com/Intelligence%20&%20information%20fl
> ow-Thatcher%20et%20al%202016.pdf
>
> We are also using the Hilbert transforms for cross-frequency network
> dynamics including phase-amplitude coupling. I do not believe that
> we would have discovered these important network correlations if we
> had used ICA reconstruction.
>
> Robert
>
>
> On Friday, June 23, 2017, 9:53:01 AM EDT, Stefan Debener
> <stefan.debener at uni-oldenburg.de<mailto:stefan.debener at uni-oldenburg.de>> wrote:
>
>
> Dear Robert,
>
> I have expanded my illustration and now consider the phase differences
> between two channels, slides 13 to 16 of the updated pdf:
> https://www.dropbox.com/s/e70qhf91dgc5anu/Thatcher_summary_2.pdf?dl=0
>
> Note that phase values were derived by the Hilbert transform of the
> bandpass filtered signal, as explained by W Freeman here:
> http://www.scholarpedia.org/article/Hilbert_transform_for_brain_waves
>
> More details on the particular implementation I used are here:
> https://de.mathworks.com/help/signal/ref/hilbert.html
>
> If you measure phase differences between two channels, consider the
> result as your gold standard, and then apply a spatial filter
> operation such as ICA or other, the phase differences may indeed be
> different. I assume any spatial filter (that effectively spatially
> filters the data) changes phase values and phase difference values. As
> a toy example I include the common average reference. If you apply a
> common average reference to the raw data, then bandpass filter as
> before, and compare the phase difference values to your "gold
> standard", then the phase differences will change as well. Now which
> phase values are valid, those obtained by one particular reference
> scheme or those by another? In my view they are both arbitraty, since
> recording settings as well as preprocessing steps may have a strong
> impact on the actually measured phase. There is no reason to assume
> that a change in phase, or in phase differences, "adulterates" a
> magically clean phase signal obtained from the raw data - simply
> because there is no such magically clean raw brain signal available in the first place!
>
> Your claim that ICA has somehow corrupted the data such that
> previously super reliable clinical effects all over a sudden vanished
> is not convincing either. Artifacts such as eye blinks and lateral eye
> movements are very common, I hope you can agree at least here. Now,
> keep in mind that they contribute fixed spatial patterns - as long as
> the electrodes cap does not shift during acquisition the projections
> of the sources of those artifacts do not change. My illustrations
> above show very clearly how artifacs indeed adulterate phase values,
> just as Arnos illustrations do! Now, if you disregard artifactual
> influences you may end up with highly reliable connectivity effects -
> but they tell you very little about brain function! Even more
> troubling, if you compare two individuals EEGs (say, one "healthy",
> one "abnormal"), then a different amount of artifacts in the data, if
> not carefully taken care of during preprocessing, will produce
> spurious results that are falsely attributed to differences in brain
> function. Actually, given that many artifacts often contribute much
> more variance to that raw signals than (reasonably well validated)
> brain signals, such as fronto-midline theta, this is actually very likely! So, what we learn is that:
>
> Artifacts not accounted for adulterate EEG phase values
>
> Best,
>
> Stefan
>
>
>
> Am 22.06.17 um 20:30 schrieb Robert Thatcher:
> > Dear Stefan,
> > The attachment did not contain any measures of phase differences
> > between channels. It is very difficult to visually see differences
> > in phase differences. One must use the cross-spectrum to calculate
> > phase differences and compare phase differences in degrees. Phase
> > difference varies from -180 to 180 degrees and one must look at the
> > numbers. Below is a url to the two power points that also show
> > visually similar EEG tracings but also computed the instantaneous
> > phase differences using the Hilbert transform (complex demodulation).
> > Four identical time points were selected and they demonstrated
> > totally different phase differences with respect to the O1 channel
> > and the other 18 channels. No matter what reference channel one
> > selects and no matter what identical time points one selects there
> > are always large differences in the phase difference between
> > channels in all frequency bands. I also computed the average phase
> > difference in the artifact free parts of the record and the averages
> > were statistically significantly different at P < 0.0001 and the same for the FFT.
> >
> > Proof of phase difference adulteration is in the power points. I am
> > again copying the hyperlink here:
> >
> >
> >
> http://www.appliedneuroscience.com/Phase_Diff-Original_&_Delorme-Post-
> ICA-4_time_points.zip
> >
> >
> > This cannot be explained by a low quality ICA reconstruction because
> > the ICA reconstruction was conducted by Arnu using EEGLab software.
> >
> > Robert
> > On Thursday, June 22, 2017, 2:00:19 PM EDT, Stefan Debener
> > <stefan.debener at uni-oldenburg.de<mailto:stefan.debener at uni-oldenburg.de>
> <mailto:stefan.debener at uni-oldenburg.de<mailto:stefan.debener at uni-oldenburg.de>>> wrote:
> >
> >
> > Dear Robert,
> >
> > I looked up some own data and find absolutely no evidence in favour
> > of your ICA phase adulteration claim, see the attached pdf report. I
> > guess you simply used a poor ICA implementation, and/or a poor
> > component selection. The attached example is in full accordance with
> > Arnos reply, with the difference that I zoom into a clearly visibile
> > alpha oscillation, to have a reference brain signal. The example
> > shows no evidence that occipital alpha phase is biased by ICA eye
> > blink correction. This is a very typical example and based on a
> > quick and dirty ICA decomposition, nothing fancy, to keep this demo
> > simple. Better preprocessing and component selection would easily
> > further improve the signal quality.
> >
> > Best,
> >
> > Stefan
> >
> >
> >
> > Am 20.06.17 um 19:53 schrieb Robert Thatcher:
> > >
> > > Dear Arno,
> > >
> > > 1)*On Phase Differences in the Original vs the Delorme ICA
> > > Reconstruction: *We can agree or disagree about whether or not
> > > some small eye movement artifact was in the hand selection that I
> > > did. But that misses the main point here. That is the ICA
> > > reconstruction alters each and every data point in the entire
> > > record including all artifact free portions no matter what one
> > > selects. For example, the record is 6 minutes and 51 seconds = 411
> > > seconds. The Mitsar sample rate was 250 samples per second =
> > > 102,750 data samples. Phase difference for each frequency band for
> > > each and every one of the
> > > 102,750 data samples has been altered by your own ICA
> > > reconstruction in the EDF file that you emailed to me. Unless you
> > > were to sit next to me or if we do a Team Viewer it is not
> > > possible for me to demonstrate this for all of the data points and
> > > then create a power point for all of these data samples. However,
> > > I can show some exemplars, for example, I have created two figures
> > > at 4 different time points (1 sec;
> > > 2:27 sec; 42 sec & 5:49 sec) that you can download. You can
> > > extract each screen capture and expand them so that you can see
> > > that the exact same time points were selected and the Hilbert
> > > transform JTFA for the
> > > 4 time points resulted in different phase differences in all
> > > channel combinations with respect to O1 for all frequencies. The
> > > same is true no matter which channel is selected to compute the
> > > phase differences in degrees. The same is true also if one
> > > computes averages of the instantaneous phase differences or if one
> > > uses the FFT. Here is the download URL:
> > >
> > >
> >
> http://www.appliedneuroscience.com/Phase_Diff-Original_&_Delorme-Post-
> ICA-4_time_points.zip
> > >
> > >
> > > 2)*On the WinEEG ICA Reconstruction: *I agree that having access
> > > to ICA components themselves and the topography is critical in
> > > understanding exactly what the WinEEG software did. Unfortunately,
> > > I personally do not have access to the WinEEG software.
> > > Clinician/Scientists in Australia use the WinEEG software and they
> > > were the ones that expressed concern about phase difference
> > > distortion at a workshop in Adelaide and gave me the original and
> > > the WinEEG ICA eye movement corrected files in EDF format. They
> > > explained that they removed only one ICA component for eye
> > > movement before they reconstructed a new time series. At first, I
> > > was impressed because the eye movements were absent in the
> > > reconstructed time series. I then was able to use JTFA (Hilbert
> > > transform) to compare the two edf files and discovered that all of
> > > the phase differences for all channels for all frequencies had
> > > been altered by the ICA reconstruction including artifact free
> > > periods. I could demonstrate this by individual time comparisons
> > > or averages of instantaneous phase differences or by the FFT. A
> > > user of WinEEG explained that they do not throw away the original
> > > raw digital data, however I was told that they believe that the
> > > ICA reconstructed times series is artifact free and therefore they
> > > compute means and standard deviations for their normative database
> > > using the ICA reconstructed data and not the hand edited or
> > > artifact deleted original data samples like other commercial
> > > companies do. Your ICA reconstructed time series is actually less
> > > different than the original phase difference in comparison to the
> > > WinEEG ICA. Nonetheless, both your ICA reconstruction and the
> > > WinEEG reconstructions are significantly different than the
> > > original
> recording.
> > >
> > > Best regards,
> > >
> > > Robert
> > >
> > > Cp
> > >
> > >
> > > On Tuesday, June 20, 2017, 1:12:41 AM EDT, Arnaud Delorme
> > > <arno at ucsd.edu<mailto:arno at ucsd.edu> <mailto:arno at ucsd.edu<mailto:arno at ucsd.edu>> <mailto:arno at ucsd.edu<mailto:arno at ucsd.edu>
> <mailto:arno at ucsd.edu<mailto:arno at ucsd.edu>>>> wrote:
> > >
> > >
> > > Dear Robert,
> > >
> > > 1) *On my ICA decomposition analysis on your data.* You have
> > > selected a subset of the file where there is 1 minute and 41
> > > second data of eye free data. I was only able to select 40 seconds
> > > in the same file, and I also showed that even in this short file,
> > > there was some residual eye movements. Jason and Stefan agreed
> > > with me. This is the reason why ICA components power spectrum over
> > > frontal channels (and frontal channels only) was affected below 10
> > > Hz frequency band in my data analysis. So on my ICA decomposition,
> > > our disagreement comes from the interpretation. You feel that the
> > > power we remove at low frequency in frontal channel is not eye
> > > movement. In an attempt to convince you, I have picked up a clean
> > > region from your EDF dataset, and did some dipole localization at
> > > this latency. We see that in the clean data, the best dipolar fit
> > > (with 2 symmetrical dipoles) ends up near the eye balls with a
> > > residual variance of 6.9%. Hopefully this convinces you that your
> > > data is not free of eye movement artifacts. If you are willing to
> > > take a step further you might contemplate the idea that ICA can remove this residual spurious activity.
> > >
> > > 2) *On the WinEEG ICA decomposition analysis.* It is critical for
> > > us to see the scalp topography (and if possible continuous
> > > activity) of the components the people at the Australia workshop
> > > selected. Without this, it is not possible for us to comment on
> > > the cleaned data. I agree with you that there was some phase
> > > distortion in alpha (visible directly in the raw data in the first
> > > email you sent) and that this should not be the case. However,
> > > without seing the ICA decomposition, it is not possible for us to
> > > conclude as to wether people selected the wrong ICA components or
> > > if the ICA decomposition implemented in this software is buggy
> > > (ICA is not a simple algorithm and it is sensitive to numerical
> > > imprecision and a lot of other parameters - a suboptimal
> > > implementation could easily explain the WinEEG results). Also, you
> > > seem to imply that the WinEEG people were running ICA on their
> > > data then throwing away the raw data (which is why their ICA
> > > biased neurofeedback database is useless for practical purposes).
> > > Is that correct? One should never throw away the raw data. If they
> > > did throw away the raw data, it is an indication that the WinEEG
> > > are not rigorous in their approach and therefore might not have
> > > implemented ICA in an optimal way. If it is not the case, one may
> > > easily reconstruct the database of measures with or without ICA
> > > decomposition (assuming ICA is done right which does not seem to
> > > be the case) then assess data measure distoritions (power, phase index, etc…) in a statistical fashion.
> > >
> > > Best wishes,
> > >
> > > Arno
> > >
> > > http://sccn.ucsd.edu/~arno/download/clean_edf_file_analysis2.pdf<http://sccn.ucsd.edu/%7Earno/download/clean_edf_file_analysis2.pdf>
> <http://sccn.ucsd.edu/%7Earno/download/clean_edf_file_analysis2.pdf%20
> >
> > <http://sccn.ucsd.edu/%7Earno/download/clean_edf_file_analysis2.pdf%<http://sccn.ucsd.edu/%7Earno/download/clean_edf_file_analysis2.pdf%25>
> > 20>
> > > <http://sccn.ucsd.edu/%7Earno/download/clean_edf_file_analysis2.pd
> > > f>
> > >
> > >> On Jun 18, 2017, at 11:44 AM, Robert Thatcher
> > <rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com>>
> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com>>>
> > >> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com>>
> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com> <mailto:rwthatcher2 at yahoo.com<mailto:rwthatcher2 at yahoo.com>>>>> wrote:
>
> >
> > >>
> > >> <Pre-ICA-Hand Artifact free selections.edf>
> >
> > >
> > >
> > >
> > > Dieser Nachrichteninhalt wird auf Anfrage komplett heruntergeladen.
> >
> >
>
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--------------------------------------------------------------------------------
Joseph Dien, PhD
Senior Research Scientist
Maryland Neuroimaging Center
University of Maryland, College Park
http://joedien.com
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