[Eeglablist] simple question: logic of using ICLABEL to reject components

[Michael Wenger]

Scott -- thanks for your note, and this is very helpful. We'll re-examine
our data and our pre-processing per your suggestion. It is the case that
the components identified as brain account for much more of the data than
do the components labeled as other. Thanks again,

-Michael

-----

M. J. Wenger, Ph.D.
Department of Psychology
Graduate Program in Cellular and Behavioral Neurobiology
Stephenson Cancer Center, Cancer Prevention and Control
The University of Oklahoma
Norman OK 73019

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On Thu, Feb 23, 2023 at 2:02 PM Scott Makeig <smakeig at gmail.com> wrote:

> ICLABEL compares component properties in your data (e.g., component scalp
> projection maps, power spectra) with datasets in its large training data
> (mainly datasets from our 20-yr history of applying ICA decomposition to
> EEG data at SCCN). ICA decomposition can be negatively affected by several
> factors:  too little data, abundant non-brain noise in the data, etc. - and
> by the conditions under which it was recorded (e.g., Were participants
> moving? Were the electrodes securely placed? etc.).
>
> So the first thing I would suggest you look at is whether your data
> preprocessing and data rejection process was adequate for the data.
> Next, I would suggest you see how much of the data is accounted for by the
> labeled Brain components plus the non-brain components of known origin
> (e.g., Eye Movement components).
> Many times components rated as 'Other' by ICLabel account for quite little
> of the data (e.g., single-channel ICs) - the *de facto* decomposition
> noise subspace.
> If you perform PCA decomposition on your dataset and look at the values of
> the resulting eigenvalue spectrum, you will typically find that a large
> proportion of EEG data 'lives' in relatively few dimensions - ICA
> decompositions finds a basis for this subspace such that each basis element
> (Independent Component) is as temporally distinct from the others as
> possible -- and is thereby typically *functionally* distinct from others,
> And *spatially* distinct from others.
>
> Scott
>
> On Thu, Feb 23, 2023 at 12:56 PM Michael Wenger <Michael.J.Wenger at ou.edu>
> wrote:
>
>> All -- we've recently begun adding the use of ICLABEL to our
>> pre-processing
>> pipeline. What we've found is that it labels only a minority of components
>> as brain activity, with the majority being labeled as "other." If we
>> reject
>> the components labeled as non-brain activity, we end up rejecting the
>> majority of the components, and this seems wrong. Can anyone who has been
>> using ICLABEL comment on how to select components for removal? Thanks in
>> advance,
>>
>> -Michael
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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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