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

[Scott Makeig]

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