[Eeglablist] Comments regarding talk

Mon Aug 12 15:57:57 PDT 2019

Dear Makoto,

Keeping up the conversation:

The whole hypothesis perhaps points out to something like a limitation

principle. What I try to mean is that, perhaps the amount of information is
limited by definition - not only from a practical approach but from a
theoretical framework. Did you try to address in any way this?

Yes exactly..

  *   Do you foresee any kind of issue that might limit the applicability of such framework?

As ICA algorithms suppose working principles, the 10-20 brain ICs you

referred would not be guaranteed to be the same in every subject. This
might also be a component to add into the "pessimism".

I like you say 'working principles'. Yes, even after critical thinking, I
still like to use ICA as a working principle.

In scalp EEG study, there are some factors that are neuroscientifically
non-interesting but still determine what can be measured at the scalp
level, such as individual differences in head geometry, cortical
gyrification patterns, total skull conductivity, etc. For example, if a
cortical region of interest in one subject happened to be centrally located
in a sulcus rather than a gyrus, this alone makes scalp-level measurement
harder. Personally I have never seen a ratio of gyral area vs. sulcal area,
but such a statistics would help us to estimate how much of our cortical
activity is obscured just because of this unfortunate fact.

I do trust ICA's capability to remove mutual information to recover
temporal independence (given the stationarity assumption holds--which is
never be true in reality), but if our 'raw signal' is compromised as I
discussed, we can't expect that ICA 'recovers' information, but it is
rather projecting blurred scalp projection back into the brain; it seems to
work as a deblurr filter, but it may not 'recover' the lost information. It
is a pessimistic situation, but not independent one but it is already
included by EEG's hard problem I proposed.

  *   Besides what you mention, I was also referring to the assumptions that ICA must hold in order to be consistent. My concern specifically focus on the election of ICA algorithm, as there are many available (each with its own particularities), results after application of ICA can be different when applying, for example, an algorithm that relies on Mutual Information in relation to when we apply an algorithm based on Tensor Diagonalization. This uncertainty is what also encouraged me to think of it as part of the pessimism. However, perhaps I'm exceeding a bit and this can be addressed successfully by other steps.

Actually, I would like to know if you have developed some short studies

that allowed to observe some kind of pattern of the ICs that are linked to
the effective degrees of freedom - maybe even the most important EEG
channels.

No, I have never thought of it. If we agree to use single-model ICA as a
working principle, there could be some approach. It seems possible to draw
an empirical conclusion that some group of scalp channels receives central
projection by ICs more frequently than other channels... but we have to
consider the dipole orientation in doing this, which could be another
neuroscientifically non-interesting factor.

  *   I agree entirely. But, I think it might be useful to know such group of scalp channels. This way, even computational models can focus more on data that comes from specific channels and perhaps increase the amount of useful information that is used in EEG based technologies - like BCIs.

ECoG relies on having very specific local arrays of microelectrodes. In

my opinion, this might not be very suitable to represent the entire brain
complexity.

The ideal ECoG recording is to record from ALL of the cortical surface. If
it is difficult (and it is difficult), I think we should try to minimize
the inter-electrode gap. In ECoG, volume conduction gets attenuated very
rapidly. But if the electrode is touching most of the cortical surface, we
can record multiple small source activity as a linear mixture.

On the other hand, a combination of EEG with ECoG could represent an

increase of the amount of EDoF, do you know of any work that addressed such
idea?

There are some scalpEEG-ECoG simultaneous recording papers and data
available. Neurotycho is one such database available http://neurotycho.org/ The
problem of scalpEEG-ECoG data is that the data is rare because when ECoG is
available recording scalpEEG seems almost unnecessary

By the way, when I returned from SFI I saw this news. I welcome these
ambitious approaches. https://www.biorxiv.org/content/10.1101/703801v2
Repeating
one-bit information generation by repeating experiments is a traditional
scientific model of clarifying something, and scalp-recorded EEG may be ok
for that purpose. But these silicon-valley guys seems to have more direct
and ambitious ideas in mind, and they have budget to test the ideas too.

  *   Thanks for sharing. I will check those works.

Again, thank you very much for your interest.

Thanks for answering.

Guillermo

Makoto

On Tue, Jul 30, 2019 at 6:04 PM GUILLERMO SAHONERO ALVAREZ <
guillermo.sahonero at ucb.edu.bo<mailto:guillermo.sahonero at ucb.edu.bo>> wrote:

Dear Makoto,

I would like to share some comments about your one hour talk at Santa Fe
Institute:

  *   The whole hypothesis perhaps points out to something like a
limitation principle. What I try to mean is that, perhaps the amount of
information is limited by definition - not only from a practical approach
but from a theoretical framework. Did you try to address in any way this?
  *   As ICA algorithms suppose working principles, the 10-20 brain ICs
you referred would not be guaranteed to be the same in every subject. This
might also be a component to add into the "pessimism". Actually, I would
like to know if you have developed some short studies that allowed to
observe some kind of pattern of the ICs that are linked to the effective
degrees of freedom - maybe even the most important EEG channels.
  *   ECoG relies on having very specific local arrays of microelectrodes.
In my opinion, this might not be very suitable to represent the entire
brain complexity. On the other hand, a combination of EEG with ECoG could
represent an increase of the amount of EDoF, do you know of any work that
addressed such idea?

I hope we could exchange some ideas. Thank you for your attention.

Guillermo

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