[Eeglablist] Reduction of Data Dimensionality before ICA

[Krebber, Martin]

Dear EEGLab users,

I have obtained a script for EEG data analysis and stumbled upon a part 
that I don't quite understand.

It calls ICA with the following line

[wts, sph] = runica( input_data, 'extended', 1, 'stop', 1e-7, 
'maxsteps', 600, 'pca', pc);

where pc is 96 minus the number of excluded and interpolated channels 
(this is mentioned earlier in the script, but without an explanation). 
As far as I understand, the 'pca' argument in that line initiates a 
reduction of the dimensionality of the data using a PCA.

However, the script is intended for the analysis of 128 channel data, 
like we use in our Lab. Why does the script reduce the dimensionality of 
the data to 96 or below. Is it justified to do that and is there a rule 
for data reduction before performing an ICA. The number seems kind of 
arbitrary to me.

Thanks to anybody who can help!

Regards,
Martin