[Eeglablist] ICA analysis + interpolation + rank of EEG data
jumana.ahmad at kcl.ac.uk
Mon Apr 3 01:50:47 PDT 2017
You just have to remember to extract less components with ICA. Either delete the original reference after average reference, and for interpolated channels reduce your rank for ICA with PCA reduction by the number of channels interpolated.
I used to interpolate after ICA, but EEGlab often complains. So I redid my pre-processing with the rank reduction method.
From: eeglablist-bounces at sccn.ucsd.edu [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Tarik S Bel-Bahar
Sent: 03 April 2017 01:05
To: Dr. Sonia Baloni <sbaloni at cbcs.ac.in>
Cc: eeglablist <eeglablist at sccn.ucsd.edu>
Subject: Re: [Eeglablist] ICA analysis + interpolation + rank of EEG data
Hello Sonia, some notes below, best wishes.
Generally speaking one ICA should be enough if you clean your data appropriately before running ICA. Not sure which tutorial you are referring to. If it is the general eeglab tutorial or Makoto's pipeline (check it out if you have not) remember those are recommendations not golden rules. Many investigators make their own unique choices.
Channels should not be interpolated before any ICA.
I might be wrong, but cleanline as far as I know is meant to denoise data, not drop channels, so you may want to double check that you are running cleanline and not PREP toolbox or clean_rawdata.
Regarding rank see Makoto's pipeline and past discussions and responses on eeglablist.
Last, if you have not had a chance to fully process eeglab tutorial data it is highly recommended.
On Thu, Mar 30, 2017 at 6:42 AM, Dr. Sonia Baloni <sbaloni at cbcs.ac.in<mailto:sbaloni at cbcs.ac.in>> wrote:
I am new to EEGlab and trying to work with ICA analysis. I have been reading the eeglab list mails on ICA topic. I have gather few footnotes and few question which I would like to ask:
1. Cleanline algorithm removes bad channels from the data. Posts in EEGlablist suggests that interpolation should be done after ICA.The tutorial suggests that two ICAs should be performed on the same data-set. So if we are performing two ICAs, we should interpolate these channels after second ICA?
2. I assume rank of the data (used in ICA analysis) would be equivalent to the number of channels in data after running clean line function. If there are for example 128 channels with which data was collected and 10 channels were removed with clean line function then the rank of the data would be 118. If we now want to run ICA on this data do we need to add “ ‘pca’,117 “ in command line option - next to ‘extended’, 1 ? as suggested in the tutotrial : https://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA<https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsccn.ucsd.edu%2Fwiki%2FChapter_09%3A_Decomposing_Data_Using_ICA&data=01%7C01%7Cjumana.ahmad%40kcl.ac.uk%7Cb966bd588c9745aad0d608d47a4d80fb%7C8370cf1416f34c16b83c724071654356%7C0&sdata=4iBmdZ3UByj4g77z5gdcF%2Fxh9nUPB7Ub9O5tdQeVXv4%3D&reserved=0>.
Thanks a lot.
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