[Eeglablist] Reduction of Data Dimensionality before ICA

[Krebber, Martin]

Hello Tarik,

thank you very much for your comments on PCA and ICA. It was all very helpful!

I would agree that the ICA results are easier to interpret and more vaild without a previous reduction of the dimensionality of the data with PCA. For now, I decided to go ahead without the PCA.

When I get the chance I might compare both methods and see for myself. I think the advantage of doing a PCA first is that there are fewer ICs to look at. In my experience most components beyond 30 (when sorted with respect to variance explained) don't look like physiologically plausible brain activity, so it's always a pain to look through all of them. But apart from that, I don't think there is a good reason to apply PCA in our case.

Regards,
Martin


On 12.01.2013 01:24, Tarik S Bel-Bahar wrote:

Greetings Martin,

just a one small clarification point:
I meant that not doing PCA should allow you to retain the true
dimensionality of your dense EEG data,
and doing ICA to this non-reduced data should lead to an ICA
decomposition that more accurately
reflects the true dynamics within your eeg data. Cheers!

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