[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]

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://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_pipeline#Two_presentations_at_a_seminar:_EEG_preprocessing_and_generative_mechanism_.28For_240.2C000_page_views.2C_09.2F21.2F2023_added.2C_10.2F18.2F2023_updated.29

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/large-scale_model_of_human_brain.htm__;!!Mih3wA!FLAtrGcNSxCRup1LcnfgWIJkdfC5HMOr_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/10.1002/hbm.26540__;!!Mih3wA!FPOThEiX2hsD7TJBq7WyhlV8v6HSkTe_swsBEoB2RM-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
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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
>