[Eeglablist] value of PCA pre-processing before running ICA on EEG data?

[arno]

> There is no accepted rule. If you 'n' sample points, you should use no 
> more than sqrt(n) "channels" (so if you have more than sqrt(n) channel 
> in your data, you use PCA to reduce the dimensionality). This is because 
> there is  number_channel^2 values in the weight matrix so you need at 
> least one value in the data (on time frame) per value in the matrix. In 
> our experience, it is good to have number_channel^2<sqrt(n/20).
>   
Above, the correct statement if "nc" is the number of channels and "ns" 
the number of sample point is

nc < sqrt(ns)

and in general it is good to have

ns > 20*nc^2 (or nc < sqrt(ns/20))

Thanks to Jeff Eriksen for pointing that out to me,

Arno