[Eeglablist] eeglablist Digest, Vol 101, Issue 30

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Fri Mar 22 10:00:57 PDT 2013


Dear Neelam,

If you have only 14 channels, do not use automatic channel rejection. That
function is for the channel-rich.

>After running ica i try to use Tool>interpolate electrode to add one
channel that was rejected.  but its not working..

Make sure you specify a dataset that has complete channel set. Could you
check it again?

Makoto

2013/3/19 neelam sharma <sharma21neelam at gmail.com>

> Dear all,
>
> I am working on eeg signal processing. I have 14 channel eeg recorded data
> from emotive epoc in edf format. i am applying ica to remove artifact from
> it. when i use Tools> automatic channel rejection, one of the 14 channels
> is removed. For example P7 is rejected out of Af3.....Af4. After running
> ica i try to use Tool>interpolate electrode to add one channel that was
> rejected.  but its not working..
> Now my question is how to interpolate or add one electrode which was
> removed...?
>
>
>
> On Wed, Mar 20, 2013 at 12:30 AM, <eeglablist-request at sccn.ucsd.edu>wrote:
>
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>> Today's Topics:
>>
>>    1. Re: MEG_data_in_EEGLAB (Makoto Miyakoshi)
>>    2. Re: What to do with more than one IC per subject in a     cluster
>>       (Arnaud Delorme)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Tue, 19 Mar 2013 10:43:29 -0700
>> From: Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>> Subject: Re: [Eeglablist] MEG_data_in_EEGLAB
>> To: Vadim A <astakhov at ncmir.ucsd.edu>, John Iversen
>>         <jiversen at ucsd.edu>
>> Cc: eeglablist at sccn.ucsd.edu
>> Message-ID:
>>         <CAEqC+SVJJoxiF1wTBtTpXxk213-adENb=
>> N8218Zfs1rnfkexFQ at mail.gmail.com>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> Dear John,
>>
>> Would you mind helping him?
>>
>> Makoto
>>
>> 2013/3/18 Vadim A <astakhov at ncmir.ucsd.edu>
>>
>> > Hi All,
>> >
>> > I need to analyse  some magnetoencephalography data , can I use EEGLAb
>> for
>> > that?
>> >
>> > On the web page it is says that EEGLab can be used for MEG but I did not
>> > found any tutorial how to deal with such data.
>> >
>> > Can somebody advice?
>> >
>> > Thanks a lot in advance.
>> >
>> > Vadim.
>> >
>> >
>> > > _______________________________________________
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>>
>>
>>
>> --
>> Makoto Miyakoshi
>> JSPS Postdoctral Fellow for Research Abroad
>> Swartz Center for Computational Neuroscience
>> Institute for Neural Computation, University of California San Diego
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>> Message: 2
>> Date: Tue, 19 Mar 2013 18:55:55 +0100
>> From: Arnaud Delorme <arno at ucsd.edu>
>> Subject: Re: [Eeglablist] What to do with more than one IC per subject
>>         in a    cluster
>> To: <tarikbelbahar at gmail.com>
>> Cc: "eeglablist at sccn.ucsd.edu" <eeglablist at sccn.ucsd.edu>,
>>  Aleksandra
>>         Vuckovic <Aleksandra.Vuckovic at glasgow.ac.uk>
>> Message-ID: <EA05868A-23B5-4CB2-BF89-3105FC5F2A25 at ucsd.edu>
>> Content-Type: text/plain; charset="us-ascii"
>>
>> Yes, this sounds like a good solution.
>> When using STUDY, if you want to plot ERP for a given cluster, you may
>> simply add the ERP of all components from the same subjects. The code below
>> will do that and merge components if there are several per subject.
>>
>> clust   = 10;
>> STUDY = std_erpplot(STUDY,ALLEEG,'clusters',clust);
>>
>> erpData  = STUDY.cluster(clust).erpdata;
>> erpTimes = STUDY.cluster(clust).erptimes;
>> setInds  = STUDY.cluster(clust).setinds;
>>
>> % scan design
>> for iCell = 1:length(setInds(:))
>>     % scan subjects
>>     uniqueSubj = unique(setInds{iCell});
>>     for iSubj = 1:length(uniqueSubj)
>>         subjInd    = setInds{iCell} == uniqueSubj(iSubj);
>>         erpData2{iCell}(:,iSubj) = sum( erpData{iCell}(:,subjInd), 2);
>>     end;
>> end;
>>
>> std_plotcurve(erpTimes, erpData2);
>>
>> Best,
>>
>> Arno
>>
>> On 15 Mar 2013, at 01:24, Tarik S Bel-Bahar wrote:
>>
>> > Hello,
>> > Here below is an example of some code that used to work when I had to
>> > merge ICs in the past,
>> > So I am not sure if it still works.
>> > A standardized solution would be useful.
>> > If possible, any followup thoughts from Makoto or Arno would be nice.
>> > For the time being, I hope it's a step in the right direction.
>> >
>> >
>> > IC1=1;IC2=3;
>> > % normalize scalp maps (columns of W^-1) to have same sign
>> >    sgn = sign(corr(EEG.icawinv(:,IC1),EEG.icawinv(:,IC2)));
>> >
>> > % average the scalp maps
>> >
>> > EEG.icawinv(:,IC1) = (EEG.icawinv(:,IC1) + sgn*EEG.icawinv(:,IC2))/2;
>> > EEG.icawinv(:,IC2) = [];
>> >
>> > % recompute weights and sphering matrix % note that we assume
>> > icaweights= W*Q where Q is the "true" sphering % matrix (who's
>> > information is already contained in icawinv = W^-1=A)
>> >
>> > EEG.icaweights = pinv(EEG.icawinv); EEG.icasphere = eye(EEG.nbchan);
>> >
>> > % recompute ICA activations (S = W*X)
>> >
>> > EEG.icaact = EEG.icaweights*EEG.data(:,:); EEG.icaact =
>> > reshape(EEG.icaact,size(EEG.icaact,1),EEG.pnts,EEG.trials);
>> > [ALLEEG, EEG, CURRENTSET] = eeg_store( ALLEEG, EEG, 2 ); eeglab redraw
>> > _______________________________________________
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>
>
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-- 
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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