[Eeglablist] What should be said about subjects that do not contribute to a given independent component cluster?

[Scott Burwell]

Greetings,

I am working with a large resting-state EEG dataset and using Measure
Projection Analysis to combine and cluster independent components' spectra
across multiple subjects. While MPA takes some of the guesswork out of more
traditional methods of clustering independent components (e.g., k-means),
it still leaves the possibility that some subjects do not contribute to a
given cluster (or in MPA-speak, "domain"). For example, if a "medial
frontal theta" cluster is found in MPA but a given subject does not have an
independent component dipole within close proximity of that cluster, the
subjects' contribution to the cluster is undefined or NaN.

For these subjects that do not contribute to certain clusters / domains, I
am curious how others might interpret the results? I know Scott Makeig and
others have written about EEG independent components as reflecting "EEG
effective sources," suggesting that only certain sources are sufficiently
"effective" (e.g., generating large signals, acceptable orientation /
distance from sensors) to contribute to the scalp EEG and ICA
decomposition.

If a subject does not contribute to a given cluster, are we to interpret
that the subject simply does not possess certain sources (~they're missing
a brain part!?). Or, perhaps with more channels and better coverage, we
might be able to better resolve the source of interest (~we don't presently
have enough measurements to faithfully capture the source of interest)?
Other explanations? Any suggested readings that discuss these issues in the
context of EEG/ICA would be greatly appreciated.

Thank you in advance.

Best,
Scott

-- 
Scott J. Burwell, PhD
He/Him/His
NIDA T32 Postdoctoral Research Fellow
Department of Psychiatry & Behavioral Sciences
University of Minnesota, Minneapolis, MN
View my profile on: LinkedIn
<https://urldefense.com/v3/__https://www.linkedin.com/in/scottjburwell/__;!!Mih3wA!R4dgkVnIcGO6T84r_m0RvI7mxl1b9LFXDtYlLb-clkuXCeGQaQ-zVO7LXlA7A1XTCJR4Bg$ > | Google
Scholar <https://urldefense.com/v3/__https://scholar.google.com/citations?user=S-DUpywAAAAJ&hl=en__;!!Mih3wA!R4dgkVnIcGO6T84r_m0RvI7mxl1b9LFXDtYlLb-clkuXCeGQaQ-zVO7LXlA7A1XZjHLVLA$ > |
GitHub <https://urldefense.com/v3/__https://github.com/sjburwell__;!!Mih3wA!R4dgkVnIcGO6T84r_m0RvI7mxl1b9LFXDtYlLb-clkuXCeGQaQ-zVO7LXlA7A1X_KgsTJA$ > | ResearchGate
<https://urldefense.com/v3/__https://www.researchgate.net/profile/Scott_Burwell__;!!Mih3wA!R4dgkVnIcGO6T84r_m0RvI7mxl1b9LFXDtYlLb-clkuXCeGQaQ-zVO7LXlA7A1WF_OCm8Q$ >