[Eeglablist] isolating a CNV with ICA

[Marco Congedo]

Hello,
 may I also suggest a recent review paper on SOS methods for EEG:

Congedo M., Gouy-Pailler C., Jutten C. (2008). On the blind source
separation of human electroencephalogram by approximate joint
diagonalization of second order statistics. *Clinical neurophysiology*, 119,
2677-2686. {pdf} <http://hal.archives-ouvertes.fr/hal-00343628/fr/>

<http://hal.archives-ouvertes.fr/hal-00343628/fr/>The pdf is available at:
http://www.lis.inpg.fr/pages_perso/congedo/MC_Publications.html

Regards,

Marco Congedo,
Senior Scientist, cnrs
GIPSA-lab, Grenoble
FRANCE


On Fri, Sep 11, 2009 at 9:56 AM, Ronald Phlypo <ronald.phlypo at ugent.be>wrote:

>  Dear Keith,
>
>
> If it concerns slowly evolving potentials, or potentials with a slowly
> decreasing autocorrelation function, second-order (statistics) methods based
> on non-proportional autocorrelation functions might be more appropriate than
> the non-gaussian (higher order statistics) versions of ICA.
>
> Some references:
>
>
>    - *SOBI:* Adel Belouchrani and Karim Abed-meraim and J.F. Cardoso and
>    E. Moulines, 'A Blind Source Separation Technique Using Second Order
>    Statistics', IEEE Trans on Signal Processing, pp434--444 (45), 1997
>    - *TDSEP: *A. Ziehe & K-R Müller, 'TDSEP - an efficient algorithm for
>    blind separation using time structure', Proc. of the 8th Int'l Conf on
>    Artificial Neural Networks, pp675-680, 1998
>    - *AMUSE: *Lang Tong and Ruey-Wen Liu and Soon, Victor C. and Yih-Fang
>    Huang, 'Indeterminacy and Identifiability of Blind Identification', IEEE
>    Trans. on Circuits and Systems, pp499-509 (38) 1991
>    - *but also* L. Molgedey and Schuster, H.G., 'Separation of a Mixture
>    of Independent Signals using Time Delayed Correlations', Physical Review
>    Letters, pp3634-3637, (72), 1994
>
>
> SOBI is included in the EEGLab package in an implementation of Belouchrani
> and Cichocki [sobi.m] and might be worth the try either for separating the
> signal of interest, either for a non-parametric slow varying potential wave
> subtraction as a preprocessing step.
>
>
> Good luck!
>
>
> Ronald
>
>
> Joseph Dien a écrit :
>
> You might try doing a PCA in the temporal domain instead of an ICA in
> the spatial domain, if the time course is sufficiently consistent.
>
> Cheers!
>
> Joe
>
> On Sep 8, 2009, at 1:01 PM, Keith Yoder 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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>  --------------------------------------------------------------------------------
>
> Joseph Dien,
> Senior Research Scientist
> Center for Advanced Study of Language
> University of Maryland
> 7005 52nd Avenue
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>
> E-mail: jdien07 at mac.com
> Phone: 301-226-8848
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-- 
Marco Congedo
http://www.lis.inpg.fr/pages_perso/congedo/MC_Home.html
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