[Eeglablist] isolating a CNV with ICA

[Scott Makeig]

Keith -

We typically highpass filter the data before applying ICA decomposition to
better focus on the oscillatory regime and above. The data filtered out
(e.g. < 1 Hz) could also be decomposed by ICA -- and the results might well
be different. I fear that the lowpass data could contain slow sweeping
potentials for which ICA is not ideal (though perhaps still useful). ICA
must decompose a spatially-moving phenomenon into a series of components
activated in overlapping succession, like overlapping 'movie frames.'  How
is the CNV in fact accounted by ICA? e.g. What does an envtopo()  (Plot >
Component ERPs > With Component Maps) look like?

It would be of interest to hear more about what your results might be in
these directions.

Scott Makeig

On Tue, Sep 8, 2009 at 10:01 AM, Keith Yoder <kjyoder at gmail.com> wrote:

> Hi all,
> Our group has EEG time-series data collected with a BioSemi ActiveTwo
> 128-electrode cap.  Our paradigm includes a Go-NoGo, with an alerting
> stimulus (S1) preceding the presentation of the Go-NoGo stimulus (S2).  S1
> and S2 are separated by 3 seconds.  When we examine ERPs from single
> electrodes, we observe a typical contingent negative variation (CNV).
>  However, when we run ICA (runica), none of the components isolate the CNV.
>  We've tried highpass filtering at 0.5hz (obviously to high), 0.01hz and
> without any highpass filtering, all without success.  Has anyone else run
> into a similar problem?  Does anyone have any additional advice for
> isolating a CNV with ICA?
> Thanks,
> Keith Yoder
> --
> Research Assistant
> Belmonte Autism Lab
> Cornell University
>
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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 92093-0961, http://sccn.ucsd.edu/~scott
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