[Eeglablist] Why most of good 'brain' ICs are 'dipolar' with show 'red'-centerd scalp topos, although 2/3 of the cortex is in sulci?

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Thu Dec 21 09:49:32 PST 2023


Hi Scott,

Thank you for your comment.
For a beautiful, variance-dominant, dipolar independent component, how many
electrodes are included within a FWHM? More than a dozen, in the case of
128-ch recording, right? Hence I wrote 'phases of major ERP components are
more or less the same across scalp electrodes'. The physical radius of such
synchronized (in the case of ICA, nearly 100% synchronized!) cortical
columns is not very local.

Or do you mean there is only a very small cortical patch right in the
center of the distribution, and the large FWHM is explained only by volume
conduction? Then you have to explain why 1 out of 4 'Brain' ICs are
localized in the subcortical regions. We have to consider the
possibility that ICA returns a broadly distributed source. Then we can also
explain why sometimes IC scalp topos shows somewhat square shape rather
than a perfectly dipolar--which is another evidence that ICA does not only
identify a local active patch.

Hiro Tanaka told me about the Koopman operator when I asked him how to
perform mode decomposition on the fluid dynamics of ECoG back in late
2010's. To apply it to scalp-recorded EEG, however, we need a different
type of spacial filter than ICA, something like spline Laplacian, that does
not rely on the assumption of spatial stationarity of the active sources
across time.

I understood traveling waves of EEG and the underlying brain's spatial
organization principle that seems different from the well-known other
principle, the functional brain mapping, by understanding the global field
theory first. Otherwise, you would not be even able to answer basic
questions such as 'What is traveling there?'

Makoto

On Wed, Dec 20, 2023 at 4:10 PM Scott Makeig <smakeig at gmail.com> wrote:

> > At least in the case of classical ERPs, phases of major ERP components
> are more or less the same  across scalp electrodes or independent
> components.
>
> Makoto -  This is definitely not the case for "components" if by the term
> are meant 'scalp map ERP peaks', for example auditory N1, etc.  The
> classical "ERP" analyses did *not* look for or measure spatiotemporal
> dynamics at/around peaks in the net ERP waveform. ICA decomposition of EEG
> does nearly(?) always separate ERPs very largely into the sums of ~5-7 ICs
> each with static scalp projections (scalp maps) - parsimoniously accounting
> for the moving scalp peak patterns.
>
> That is not to say that in ECoG recordings one should expect to see static
> large (6+cm^2??) 'patches' of  locally synchronous activity at the implied
> cortical location of the imputed IC 'effective source' (as I like to call
> them). I am investigating this question directly now with Yahya Shirazi and
> Julie Onton. Modeling 'swirling' cortical potentials with fluid dynamic
> measure (gradient wavefront directions and patterns) is a modeling approach
> of recent interest in the literature (e.g., from at least two groups at
> UCSD, Salk).
>
> As for the question as to why single-dipole models of EEG ICs so often are
> near radial, the recent observation in this thread [that sulcal cortex is
> deeper and near-tangentially oriented w.r.t. the scalp,  and thus should
> project to the scalp much less strongly] seems promising. Other possible
> contributions to the observed (IC equivalent-dipole angle) distribution:
> Similar cortical surface-depth dipole activity on both sides of a sulcus
> (e.g., somatomotor, as documented in an abstract I once read) could produce
> cancellation of far-field (scalp) potentials;  failure of sulcal cortex to
> support wide-area synchrony in some or many cases; synchronous,
> near-bilateral source activities imperfectly modeled by a single
> central/radial dipole ...
>
> By the way, evidence uncovered by Zeynep Akalin-Acar before she retired
> implies that (in adults), such 'bilateral effective sources' are
> (typically?) temporally unstable, with synchronous activity in 'mirroring'
> cortex being intermittent (though very possibly not so in infants, as
> suggested by results of Caterina Piazza).
>
> Scott
>
>
> On Tue, Dec 19, 2023 at 9:08 AM Makoto Miyakoshi via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
>> Hi Ramesh,
>>
>> > I think Paul's intent was specifically to challenge the thalamocortical
>> account in humans.
>>
>> But he would not say the local and global theories are mutually exclusive,
>> right? I thought they co-exist with some interaction.
>>
>> > I don't think we need that at all. Suppose there is a phase difference
>> between two adjacent gyri.  There will be some cancellation of signal but
>> there will still be more signal than if only 1 gyrus was active except for
>> the 180 degree out of phase case.
>>
>> It seems easier for that scenario to happen for the smaller sources, such
>> as a source with only two gyri.
>> But for larger sources, you need more number of sulci to be synchronized.
>> In that case, you still need some mechanism to explain multi-gyral
>> synchronization, right?
>>
>> > In this scenario different scalp electrodes will show different phases
>> which can be observed in many papers.
>>
>> At least in the case of classical ERPs, phases of major ERP components are
>> more or less the same  across scalp electrodes or independent components.
>> In the case of resting-state, this is definitely not a general picture.
>> Maybe you are talking about the latter case?
>>
>> Makoto
>>
>>
>> On Wed, Dec 13, 2023 at 10:33 PM Ramesh Srinivasan <srinivar at uci.edu>
>> wrote:
>>
>> > Makoto
>> >
>> > I think Paul's intent was specifically to challenge the thalamocortical
>> > account in humans.
>> >
>> > I want to point out one other thing I noticed in the discussion going
>> back
>> > to Scott and your comments
>> >
>> > The idea that the lag zero synchrony is a requirement over the cortex is
>> > often used to justify the thalamocortical account.
>> >
>> > I don't think we need that at all. Suppose there is a phase difference
>> > between two adjacent gyri.  There will be some cancellation of signal
>> but
>> > there will still be more signal than if only 1 gyrus was active except
>> for
>> > the 180 degree out of phase case.
>> >
>> > In this scenario different scalp electrodes will show different phases
>> > which can be observed in many papers.
>> >
>> > Ramesh Srinivasan
>> > Professor
>> > Cognitive Sciences
>> > Biomedical Engineering
>> >
>> > On Wed, Dec 13, 2023, 5:16 PM Makoto Miyakoshi via eeglablist <
>> > eeglablist at sccn.ucsd.edu> wrote:
>> >
>> >> Thanks Pål for your comments.
>> >> I don't think many people believe the thalamus==pacemaker hypothesis
>> any
>> >> more.
>> >> Lopes da Silva found high coherence between dog's visual cortex and
>> >> pulvinar instead of LGN in his 1980 paper. Saalmann et al. (2012) was a
>> >> nice confirmation of that using monkeys. Basically, they identified the
>> >> pulvinar-V4/TEO (i.e. thalamo-cortical) network of the active visual
>> >> attention. Such a network is 'recruited' upon top-down demand, perhaps
>> as
>> >> a
>> >> part of a larger network.
>> >>
>> >> Although Nunez insisted on the presence of traveling and standing
>> waves, I
>> >> do not think his claim was to replace the conventional alpha models.
>> >> Instead, such a network can be present on top of something else. I
>> agree
>> >> with you that his claim was 'more or less shot down' except no one
>> dared
>> >> to
>> >> shoot it but it has been unattended. But you know, Alex Fornito's the
>> >> Nature paper in the early 2023 is nothing but fMRI version of Nunez's
>> >> global field theory with less explanation. They could not explain what
>> >> exactly is traveling in their model. In the case of Nunez's model, the
>> >> medium of the traveling wave is clear: the synaptic action fields
>> mediated
>> >> by white matters.
>> >>
>> >> > 3. The amplitudes of EEG will be linear to the number of synchronous
>> >> firing neurons. If they are firing stochasticly the amplitude will be
>> >> closer to the square root. E.g. 1000000 neurons will in synchrony give
>> an
>> >> unite amplitude of 1000000 as if they have a stochastic firing 1000.
>> >> Coherences gives amplitudes somewhere in between.
>> >>
>> >> I made a humble plot from this simulation. If you are curious, please
>> see
>> >> slide 49 linked below. Basically, after passing some critical point,
>> the
>> >> small-number synchronous firing effect start to outweigh the mass
>> random
>> >> firing effect. It's a replication of Hari et al. (1997).
>> >>
>> >>
>> https://urldefense.com/v3/__https://sccn.ucsd.edu/mediawiki/images/1/13/On_EEG*27s_generative_mechanism.pdf__;JQ!!CzAuKJ42GuquVTTmVmPViYEvSg!ICVjAWd2SZrqFNUJPogEQBLx6o5k3xGNW-hHxSnaf7aCYHU_zo4Jt_XjJOIJCHBOxtCMaVK2EfXI7J-oMMrUGQ00$
>> >>
>> >> In the actual 3-D implementation of the sheet of (a massive number of)
>> >> parallel pyramidal neurons, there is also a counter-intuitive
>> non-linear
>> >> spatial summation effect. I call it a transducer array effect. This
>> also
>> >> favors the wide EEG sources to be scalp-recorded. The explanation is
>> lined
>> >> below.
>> >>
>> >>
>> https://urldefense.com/v3/__https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline*Transducer_array_effect_.28For_140.2C000_page_views.2C_10.2F09.2F2020_added.29__;Iw!!CzAuKJ42GuquVTTmVmPViYEvSg!ICVjAWd2SZrqFNUJPogEQBLx6o5k3xGNW-hHxSnaf7aCYHU_zo4Jt_XjJOIJCHBOxtCMaVK2EfXI7J-oMDXc1K8M$
>> >>
>> >> > 2. The nature is not redundant in the way that many neurons are used
>> for
>> >> the same function. You will not expect close by neurons to be in
>> >> synchrony.
>> >> Why should they? But there will be coherent elements.
>> >>
>> >> Right. I think the point is sparsity and efficiency.
>> >> For example, we might think 1% of synchrony is trivial. But most of the
>> >> esoteric cognitive neuroscience studies rely on BOLD signal measurement
>> >> that shows changes often less than 1%.
>> >> I think when samples are ample, a small fraction of changes still
>> counts.
>> >>
>> >> Speaking of the global field theory, when I asked Paul Nunez what
>> >> he thought of the view by Buszaki that frequencies of the brain rhythm
>> are
>> >> stable across species, he immediately disagreed. I would love to
>> >> see someone replicate Buszaki's claim there.
>> >>
>> >> Makoto
>> >>
>> >> On Wed, Dec 13, 2023 at 12:10 PM Pål Gunnar Larsson <pall at ous-hf.no>
>> >> wrote:
>> >>
>> >> > Hi Makoto
>> >> >
>> >> > I hope I did not open Pandoras box. First a small history.
>> >> > Andersen and Andersson publish in 1968 that alpha activity came from
>> >> > pacemaker cells in Thalamus. This was a cat study. In 1971 Sturm van
>> >> Leuwen
>> >> > and Lopez da Silva showed in dog that there were no good coherence
>> >> between
>> >> > the thalamus activity and the alpha. Even the frequencies didn’t
>> match.
>> >> > Then Nunez suggested alpha was generated by standing waves in cortex
>> >> with
>> >> > some human data. However, also his hypothesis was more or less shot
>> >> down.
>> >> > Now, it seems like a leading hypothesis is that alpha is generated by
>> >> > cortical spreading activity that to some extend is influenced by
>> >> standing
>> >> > waves. My point here is that model and methods to a large extend
>> >> influences
>> >> > your results.
>> >> >
>> >> > Let me make some points
>> >> > 1. Propagating takes time, hence you get a phase shifted as a
>> function
>> >> of
>> >> > distance in cortex. This will give cancellations in the EEG due to
>> the
>> >> > spatial averaging. Therefore our electrodes "sees" patchy activity.
>> >> > 2. The cortico-cortical fibers propagate AP with up to 9 m/s and
>> >> > intracortical propagation is 0.2m/s- 0.5 m/s.
>> >> > 2. The nature is not redundant in the way that many neurons are used
>> for
>> >> > the same function. You will not expect close by neurons to be in
>> >> synchrony.
>> >> > Why should they? But there will be coherent elements.
>> >> > 3. The amplitudes of EEG will be linear to the number of synchronous
>> >> > firing neurons. If they are firing stochasticly the amplitude will be
>> >> > closer to the square root. E.g. 1000000 neurons will in synchrony
>> give
>> >> an
>> >> > unite amplitude of 1000000 as if they have a stochastic firing 1000.
>> >> > Coherences gives amplitudes somewhere in between.
>> >> > 4. The EEG we record are to a large extend from not highly correlated
>> >> > neurons with coherences waxing and waning depending on the activity.
>> >> E.g.
>> >> > Evoked potentials gives higher coherences and hence, higher
>> amplitudes.
>> >> > 5. Thalamus is an important relay station in the brain, but I am not
>> >> > convinced that it has an important pacemaker function, at least not
>> in
>> >> > humans.
>> >> > 6. I think I have to go back to the PL Nunez book to find his
>> references
>> >> > on the human vs rodent brain wiring.
>> >> >
>> >> > To me the EEG is mostly modulated by changing activities in the brain
>> >> and
>> >> > not by some pacemakers.
>> >> >
>> >> > Best
>> >> > Pål
>> >> >
>> >> > E-mail: pall at ous-hf.no
>> >> >
>> >> > Ikke sensitiv
>> >> >
>> >> > -----Opprinnelig melding-----
>> >> > Fra: eeglablist <eeglablist-bounces at sccn.ucsd.edu> På vegne av
>> Makoto
>> >> > Miyakoshi via eeglablist
>> >> > Sendt: 12. desember 2023 19:35
>> >> > Til: eeglablist <eeglablist at sccn.ucsd.edu>
>> >> > Emne: Re: [Eeglablist] Why most of good 'brain' ICs are 'dipolar'
>> with
>> >> > show 'red'-centerd scalp topos, although 2/3 of the cortex is in
>> sulci?
>> >> >
>> >> > Hi Pal and Ramesh,
>> >> >
>> >> > Thank you for your comments.
>> >> > Let me quote an explanation from Jones (2002) "Thalamic circuitry and
>> >> > thalamocortical synchrony" p.1669. He explains how the two types of
>> >> > thalamocortical projections, core and matrix, interact to create
>> >> cortical
>> >> > activities, which is probably the direct source of EEG/MEG signals.
>> >> >
>> >> > %%%%%%%%%%%%%%%%%
>> >> > The relay cells of the thalamic core, with their focused projections
>> to
>> >> an
>> >> > individual cortical area, clearly form the basis for the relay of
>> place-
>> >> > and modality-specific information to the cortex whereas those of the
>> >> > thalamic matrix form a more obvious basis for the dispersion of
>> >> activity in
>> >> > the thalamocortical network across larger areas of cortex. Within a
>> >> zone of
>> >> > cortex, the terminations of matrix cell axons on distal dendrites in
>> >> > superficial layers and of matrix cell axons on more proximal
>> dendrites
>> >> in
>> >> > middle layers should serve as a coincidence detection circuit,
>> providing
>> >> > for a high degree of temporal integration between inputs coming from
>> the
>> >> > two classes of thalamic cells (Llinas&Pare 1997; figure 11).
>> >> Coincidence of
>> >> > this kind should promote synchronous activity in the cells of
>> individual
>> >> > cortical columns and in any group of columns activated by the same
>> >> > stimulus. Activity in these columns would then be returned via layer
>> VI
>> >> > corticothalamic cells to the thalamic nucleus from which they receive
>> >> > input, serving  to reinforce thalamocortical synchrony. This activity
>> >> would
>> >> > be spread to other cortical columns in the same cortical area and in
>> >> > adjacent cortical areas via the diffuse projections of matrix cells
>> in
>> >> the
>> >> > thalamic nucleus through which externally or internally generated
>> >> activity
>> >> > was first passed to the cortex.
>> >> > %%%%%%%%%%%%%%%%%
>> >> >
>> >> > I guess fMRI-based 'functional mapping' is rather close to the
>> mapping
>> >> of
>> >> > the projections by 'core thalamic nuclei'.
>> >> >
>> >> > When I analyzed the USCD mismatch negativity (MMN) database, I found
>> MMN
>> >> > is a whole-brain phenomenon and not limited to Fz. One of the
>> coauthors
>> >> > (probably Juan) asked me why the 'visual cortex' showed ERP as well.
>> I
>> >> > could not answer to his question. Now I have a better
>> explanation--From
>> >> the
>> >> > core/matrix point of view, it is not surprising that auditory
>> stimulus
>> >> > activates cortices of other sensory modalities.
>> >> >
>> >> > Giandomenico Ianetti from U Rome showed me 4 or 5 ERPs evoked by
>> stimuli
>> >> > of different modalities including visual, auditory, tactile, and
>> >> > laser-evoked pain. His point was clear: These ERPs are the same. It
>> was
>> >> > eyes opening.
>> >> >
>> >> > So, this is my proposal: Let us unlearn the fMRI-based functional
>> brain
>> >> > mapping when we do EEG. Instead, let us pay more attention to
>> thalamus.
>> >> >
>> >> > I do not know about the cortico-cortical connection via u fiber very
>> >> much.
>> >> > If you know a paper detailing that point, please let me know. My
>> initial
>> >> > respose is, is the u-fiber connection fast enough to form a
>> >> > near-simultaneous activity across the cortex? Isn't a region-wide
>> >> > projection from the thalamus more feasible to explain it?
>> >> >
>> >> > Makoto
>> >> >
>> >> >
>> >> > On Tue, Dec 12, 2023 at 12:25 PM Ramesh Srinivasan via eeglablist <
>> >> > eeglablist at sccn.ucsd.edu> wrote:
>> >> >
>> >> > > I've been enjoying this discussion because it taps into one of
>> those
>> >> > > EEG truths/inconsistencies we never talk about.
>> >> > >
>> >> > > 1. We artifact edit EEG data mostly based on the idea it should be
>> >> > > smooth low spatial frequency information.  We don't trust very
>> >> > > (channel, frequency, time)  localized EEG signals.
>> >> > >
>> >> > > 2. Then after we clean the EEG data we want a story for our paper
>> that
>> >> > > is time, frequency, source localized as compact as possible
>> because it
>> >> > > makes a nice narrative.
>> >> > >
>> >> > > Regarding synchrony in adjacent gyri, u-fibers are helpful and
>> yes, I
>> >> > > think most of it is corticocortical rather than thalamocortical
>> but I
>> >> > > think the 2% is just a guess. It's clearly not as thalamocortical
>> as
>> >> > > animal models
>> >> > >
>> >> > > Ramesh Srinivasan
>> >> > > Professor
>> >> > > Cognitive Sciences
>> >> > > Biomedical Engineering
>> >> > >
>> >> > > On Tue, Dec 12, 2023, 6:40 AM Pål Gunnar Larsson via eeglablist <
>> >> > > eeglablist at sccn.ucsd.edu> wrote:
>> >> > >
>> >> > > > Just want to add. In rats about 50% of all fiber going in and
>> out of
>> >> > > > the cortex are connected to the thalamus. In humans connections
>> are
>> >> > > > about 2%, according to Nunez. Hence, we should be very careful
>> when
>> >> > > > you try to extrapolate from animal research to humans.
>> >> > > >
>> >> > > > Pål G. Larsson
>> >> > > >
>> >> > > > Ikke sensitiv
>> >> > > >
>> >> > > >
>> >> > > > -----Opprinnelig melding-----
>> >> > > > Fra: eeglablist <eeglablist-bounces at sccn.ucsd.edu> På vegne av
>> >> > > > Makoto Miyakoshi via eeglablist
>> >> > > > Sendt: 11. desember 2023 19:06
>> >> > > > Til: EEGLAB List <eeglablist at sccn.ucsd.edu>
>> >> > > > Emne: Re: [Eeglablist] Why most of good 'brain' ICs are 'dipolar'
>> >> > > > with show 'red'-centerd scalp topos, although 2/3 of the cortex
>> is
>> >> in
>> >> > sulci?
>> >> > > >
>> >> > > > Hi Scott,
>> >> > > >
>> >> > > > > "How are LFP signals across each of these gyrii synchronized
>> >> > > > > across the
>> >> > > > dataset?"
>> >> > > >
>> >> > > > The answer is not so special. The synchrony is achieved via
>> >> > > > thalamo-cortical loops.
>> >> > > > In the following Wiki article, I linked to my presentation at an
>> NIH
>> >> > > > summer seminar in which I showed multiple evidence that cortical
>> >> > > synchrony
>> >> > > > and coupling is controlled by thalamus.
>> >> > > >
>> >> > > >
>> >> > >
>> >> https://urldefense.com/v3/__https://sccn.ucsd.edu/wiki/Makoto*27s_prep
>> >> > >
>> rocessing_pipeline*Two_presentations_at_a_seminar:_EEG_preprocessing_a
>> >> > >
>> nd_generative_mechanism_.28For_240.2C000_page_views.2C_09.2F21.2F2023_
>> >> > >
>> added.2C_10.2F18.2F2023_updated.29__;JSM!!CzAuKJ42GuquVTTmVmPViYEvSg!I
>> >> > >
>> xfdnbB611_BrP_68EFD1xVZHKoKQu6E2vLO7VJL104Il5HhWcGfwu-K0btGTDMoDcUuo0-
>> >> > > 5NDYMK30iA7NCfDue$
>> >> > > >
>> >> > > > So, when thalamus makes different cortical regions to fire
>> together,
>> >> > > > then you see the synchronous activity. That's it. The distant
>> >> > > > cortical regions do not have to be directly connected via each
>> >> > > > neuron's lateral branches (which does exist, but the conduction
>> >> > > > speed is very slow compared with
>> >> > > that
>> >> > > > of white matter) Note this is not a one-way 'imposing' the rhythm
>> >> > > > from
>> >> > > the
>> >> > > > thalamus to the cortex, like the historical 'pace-maker'
>> hypothesis
>> >> > > > by Andersen and Andersen (1967) but it is a bi-directional
>> >> interaction.
>> >> > > >
>> >> > > > One fact that might help you see the situation is that only 1% of
>> >> > > > neurons need to be synchronized to form 95% of the amplitude of
>> the
>> >> > > > observed
>> >> > > signal
>> >> > > > according to Hari (1997).
>> >> > > >
>> >> > > > Also, it might also help to remember that there is no general
>> >> > > > guarantee that an EEG source is stationary and localizable. See
>> >> > > > Izhikevich's classical simulation.
>> >> > > >
>> >> > > >
>> >> > >
>> >> https://urldefense.com/v3/__https://www.izhikevich.org/publications/la
>> >> > >
>> rge-scale_model_of_human_brain.htm__;!!Mih3wA!FLAtrGcNSxCRup1LcnfgWIJk
>> >> > >
>> dfC5HMOr_rPujEIjdmGug69GeOA7PxjXg5NqsRrbtx3VtKZRJhKrQ9HIAFxdjg0n5Fg$
>> >> > > > There is an established principle of functional brain mapping
>> but it
>> >> > > > is a product of statistical processing such as (heavy) averaging.
>> >> > > > ICA model is the same, hence it is stationary across time. The
>> small
>> >> > > > and localizable
>> >> > > EEG
>> >> > > > source is heavily a statistical concept. The actual ongoing EEG
>> is
>> >> > > > stochastic, dynamic, and diffuse. When we see ICA results,
>> >> > > > therefore, we should distinguish properties of the filter from
>> >> > properties of data.
>> >> > > >
>> >> > > > Makoto
>> >> > > >
>> >> > > >
>> >> > > > On Mon, Dec 11, 2023 at 11:42 AM Scott Makeig <smakeig at gmail.com
>> >
>> >> > wrote:
>> >> > > >
>> >> > > > > Makoto -
>> >> > > > >
>> >> > > > > When you repeat the claim that EEG sources 'found' by ICA
>> >> > > > > decomposition must be at least several adjacent gyrii in size,
>> you
>> >> > > > > fail to ask, "How are LFP signals across each of these gyrii
>> >> > > > synchronized across the dataset?"
>> >> > > > > Doesn't this require some physiological basis, and if so, what
>> is
>> >> > it??
>> >> > > > >
>> >> > > > > Scott Makeig
>> >> > > > >
>> >> > > > > On Mon, Dec 11, 2023 at 11:17 AM Makoto Miyakoshi via
>> eeglablist <
>> >> > > > > eeglablist at sccn.ucsd.edu> wrote:
>> >> > > > >
>> >> > > > >> Hello EEGLAB list,
>> >> > > > >>
>> >> > > > >> For those who have wondered so, here are my answers.
>> >> > > > >> I asked two questions:
>> >> > > > >>
>> >> > > > >> (1) Why do good 'brain' ICs show dipolar scalp topos although
>> 2/3
>> >> > > > >> of the cortex is in sulci?
>> >> > > > >> (2) Why do these dipolar IC scalp topos show red (positive)
>> >> centers?
>> >> > > > >>
>> >> > > > >> The answer was published a few days ago.
>> >> > > > >>
>> >> > > > >>
>> >> > > > >>
>> >> https://urldefense.com/v3/__https://onlinelibrary.wiley.com/doi/1
>> >> > > > >> 0.10
>> >> > > > >>
>> 02/hbm.26540__;!!Mih3wA!FPOThEiX2hsD7TJBq7WyhlV8v6HSkTe_swsBEoB2R
>> >> > > > >> M-Bh -BGerduzZBnmEtDBamyosThbqv9Xrc1gGPSmdm52LpO7jM$
>> >> > > > >>
>> >> > > > >> The answer to (1): It is because scalp-recorded EEG is
>> >> > > > >> insensitive to sulcal sources compared with gyral sources.
>> This
>> >> > > > >> finding justifies the use of lissencephalic (i.e. no sulci)
>> brain
>> >> > > > >> model proposed in Electric Fields of the Brain (Nunez and
>> >> > > > >> Srinivasan, 2006) together
>> >> > > with
>> >> > > > Spline Laplacian.
>> >> > > > >> This also supports the view that the major source of
>> >> > > > >> scalp-recordable EEG is pretty broad (minimum 6.45 cm^2) which
>> >> > > > >> requires a continuum of multiple gyral crowns.
>> >> > > > >>
>> >> > > > >> I did not write it in the paper, but the result basically
>> refutes
>> >> > > > >> the claim that ICA is a high-resolution EEG spatial filter
>> >> > > > >> because the result confirms that ICA is mostly blind to 2/3 of
>> >> > > > >> the cortex. In fact, it seems ICA results are always
>> dominated by
>> >> > > > >> high-power, low-frequency, and very broad sources. I will
>> publish
>> >> > > > >> this view in the near future.
>> >> > > > >>
>> >> > > > >> The answer to (2): It is because EEGLAB's ICA sets the initial
>> >> > > > >> topos of all ICs red centered (i.e. positive dominant). Thus,
>> >> > > > >> unless necessary, the algorithm does not flip the polarities.
>> >> > > > >>
>> >> > > > >> Now you wonder--when does the ICA algorithm flip the polarity
>> to
>> >> > > > >> produce 'blue' centered (i.e. negative dominant) ICs? I found
>> >> > > > >> that those blue-centered ICs tend to show poor physiological
>> >> > > > >> validity with large index numbers. A known clear exception for
>> >> > > > >> this rule is ICs localized for the motor cortex.
>> >> > > > >>
>> >> > > > >> People use ICA to clean EEG. I use EEG to glean ICA, which is
>> >> > > > >> more
>> >> > > fun.
>> >> > > > >>
>> >> > > > >> Makoto
>> >> > > > >> _______________________________________________
>> >> > > > >> Eeglablist page:
>> >> > > >
>> >> > >
>> >> https://urldefense.com/v3/__http://sccn.ucsd.edu/eeglab/eeglabmail.htm
>> >> > >
>> l__;!!CzAuKJ42GuquVTTmVmPViYEvSg!IxfdnbB611_BrP_68EFD1xVZHKoKQu6E2vLO7
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>> >> > > > >> to eeglablist-request at sccn.ucsd.edu
>> >> > > > >>
>> >> > > > >
>> >> > > > >
>> >> > > > > --
>> >> > > > > Scott Makeig, Research Scientist and Director, Swartz Center
>> for
>> >> > > > > Computational Neuroscience, Institute for Neural Computation,
>> >> > > > > University of California San Diego, La Jolla CA 92093-0559,
>> >> > > > >
>> >> > > >
>> >> > >
>> >> https://urldefense.com/v3/__http://sccn.ucsd.edu/*scott__;fg!!CzAuKJ42
>> >> > >
>> GuquVTTmVmPViYEvSg!IxfdnbB611_BrP_68EFD1xVZHKoKQu6E2vLO7VJL104Il5HhWcG
>> >> > > fwu-K0btGTDMoDcUuo0-5NDYMK30iA0yMHq0i$
>> >> > > > >
>> >> > > > _______________________________________________
>> >> > > > Eeglablist page:
>> >> > > >
>> >> > >
>> >> https://urldefense.com/v3/__http://sccn.ucsd.edu/eeglab/eeglabmail.htm
>> >> > >
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>> >> > > > _______________________________________________
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>> >> > >
>> l__;!!CzAuKJ42GuquVTTmVmPViYEvSg!IxfdnbB611_BrP_68EFD1xVZHKoKQu6E2vLO7
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>> >> _______________________________________________
>> >> Eeglablist page:
>> >>
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>> >
>> _______________________________________________
>> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
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>
>
>
> --
> Scott Makeig, Research Scientist and Director, Swartz Center for
> Computational Neuroscience, Institute for Neural Computation, University of
> California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott
>


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