[Eeglablist] Comparing different ICA procedures

Guillaume Lio guillaume.lio at isc.cnrs.fr
Fri Apr 25 01:44:16 PDT 2014


And :

Congedo M, Gouy-Pailler C, Jutten C. On the blind source separation of 
human electroencephalogram by approximate joint diagonalization of 
second order statistics. Clin Neurophysiol. 2008 Dec;119(12):2677-86.

Lio G, Boulinguez P (2013): Greater robustness of second order 
statistics than higher order statistics algorithms to distortions of the 
mixing matrix in blind source separation of human EEG: Implications for 
single-subject and group analyses. NeuroImage 67:137--152.

Hope these help,

Guillaume.


Le 25.04.2014 05:25, Makoto Miyakoshi a écrit :
> Dear Norbert,
>
> Check out Delorme et al. 2012 PLoS One.
>
> Makoto
>
>
> 2014-04-24 6:43 GMT-07:00 Norbert Franke <nfranke at uni-bonn.de 
> <mailto:nfranke at uni-bonn.de>>:
>
>     Hi everybody,
>
>     I am comparing different ICA procedures.
>
>     In my case the results after running different ICAs with the same
>     EEG dataset (always beginning at scratch) are very similiar but
>     not always the same. To decide which ICA procedure fits best I
>     need to know more about preconditions of these algorithms.
>     Otherwise its a danger to use the results which fits best to what
>     I want to find and thats not science.
>
>     Is there literature existing which compares ICAs?
>
>
>     Norbert Franke
>     Bonn
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>
>
> -- 
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
>
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