[Eeglablist] What to do with more than one IC per subject in a cluster

[Makoto Miyakoshi]

Dear James,

If it were inappropriate then most of our publications would be bad :-)

ICA is data driven and generates subspaces where ICs are intradependent. It
also reflects individual differences. This is like cost for this nice
method. However, what actually matter is convention, isn't it?

> If so, what is a good method for selecting which components to use?

Selecting ICs can bias data. Try Measure Projection developped by Nima
Bigdely-Shamlo. That could be a smart solution for this issue.

Makoto

2013/2/27 James Schaeffer <schaefj3 at gmail.com>

> Dear Eeglablist,
>
> After clustering components using k-means, some of my clusters contain
> more than one component from a single subject.  I want to compare ERSPs
> using permutation analysis.  Is it inappropriate to include more than one
> component from the same subject in the analysis? If so, what is a good
> method for selecting which components to use?
>
> Thanks for your help,
> James
>
>
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-- 
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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