[Eeglablist] running ICA a second time

[Veerle ROSS]

Dear Tarik

Thank you for your quick response.

I will look into the ADJUST plugin and the other points you mention.

Best Veerle

 

From: Tarik S Bel-Bahar [mailto:tarikbelbahar at gmail.com] 
Sent: woensdag 20 februari 2013 2:01
To: Veerle ROSS
Cc: eeglablist at sccn.ucsd.edu
Subject: Re: [Eeglablist] running ICA a second time


 

Greetings Ross:


 


Some brief responses to your questions below, I hope they are helpful. I've numbered the responses according to your questions.


 


0. if you have note please search eeglab list archives where you will definitely find some past discussions.


PLease read through the articles about cleaning with eeglab, which you can easily find on Google Scholar.


Check out the eeglab tutorial and wiki, particular guidelines. 


 


1a. You can use PCA (see post within last 2 months on this subject based on a "should I PCA and if so what is best method")


Reducing by PCA may decrease the "validity" or "truthfullness" of your ICs. 


Check Joseph Dien's PCA toolkit for some principled methods to do PCA. 


 


1c. You should find similar ICs after 2 ICAs, as the second ICA decomposition. The ones in the second ICA should be cleaner and more accurate.


Some people just publish their first ICA results, as it is not always the case that you gain much from a second ICA.


 


2a. I assume you have properly cleaned your data before the first ICA. 


My recommendation is, if you want to do a second ICA, first consider doing what eeglab documentation recommend: 


after your first ICA, then do artifactual epoch rejection using ICA-based rejection, then do a second ICA.


 


2b. it's not clear what your question is, perhaps there is a word missing in your question.


You could remove noisy or blink or other artifactual components if you want to, go ahead


and do a second ICA, and compare the results to doing it via the method suggested in the response to 2a above.


 


also:


Check out the the ADJUST plugin (amongst others for a variety of cleaning techniques). 


&


Note there are least three camps:


a. those who use ICA just to deblink or otherwise clean their data, and then they reconstruct the EEG and do their analyses outside of ICA space. [ergo, ICA is a cleaning tool]


b. those who use ICA to get ICs that reflect brain dynamics and (often) established ERP components, they do their analyses on ICs [ergo, ICA gives real brain dynamics]


c. those who use PCA (with or without ICA) to decompose ERPs into spatial (and/or) temporal components, they do their analyses on PCs


 


 


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://sccn.ucsd.edu/pipermail/eeglablist/attachments/20130220/b12b9be6/attachment.html>