[Eeglablist] Data Processing Steps for ICA?

[Paul Yu-Chun Chang]

Dear Makoto,

Wow many thanks and I appreciate that!

Best regards,

Paul

2014-10-30 0:09 GMT+01:00 Makoto Miyakoshi <mmiyakoshi at ucsd.edu>:

> Dear Paul,
>
> I made this page for you.
> http://sccn.ucsd.edu/wiki/Preprocess_pipeline
>
> > 1. When to perform base-line correction:
> It seems most people suggest not to do it before ICA training based on
> Groppe's 'split-half' paper:
> http://sccn.ucsd.edu/pipermail/eeglablist/2010/003080.html
> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
> But there are some counterarguments:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/005513.html
> So I guess it's still better to do it after ICA?
>
> Yes, do it after ICA.
>
> > 2. When and how to perform re-referencing:
> It seems I should re-reference to average before ICA, but there seems to
> be some counterarguments, too:
> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html
> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
> http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html
>
> Just re-reference to the average reference. Don't forget to reject one
> channel after this.
>
> > I'm not pretty sure whether to include EOG channels either, as there
> seems to be pros and cons:
> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
> http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html
>
> Do include EOG channels for ICA. I made a wrong answer last time.
>
> Makoto
>
> On Sat, Oct 25, 2014 at 2:54 AM, Paul Yu-Chun Chang <Y.Chang at lipp.lmu.de>
> wrote:
>
>> Dear All,
>>
>> I have 32-channel Neuroscan recordings (ca. 1 hr per subject) and am
>> recently trying to use ICA to remove blinks and eye movements from the data
>> (EEGLAB version 12.0.2.4b). After checking out some relevant
>> discussions/wiki pages/tutorials I find myself however still a bit confused
>> (particularly regarding re-referencing, baseline correction, and channels
>> to be included when running ICA) and am having some further questions. I'd
>> really appreciate your help.
>>
>> Some essential steps as I understand now involve (pls correct me if I'm
>> wrong):
>>
>> 1. Reject bad epochs/channels to prune the data.
>> (source: http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA
>> ;
>> http://sccn.ucsd.edu/eeglab/workshop06/handout/Practicum_3_ICA_Process.pdf
>> )
>> 2. Train ICA firstly on 1 Hz high-pass filtered pruned dataset.
>> 3. Apply ICA weights to the same subject's 0.1 Hz high-pass filtered data
>> and evaluate components.
>> (source: http://sccn.ucsd.edu/pipermail/eeglablist/2011/004424.html)
>> 4. Interpolate bad channels.
>>
>> I'm however not so clear about:
>>
>> 1. When to perform base-line correction:
>> It seems most people suggest not to do it before ICA training based on
>> Groppe's 'split-half' paper:
>> http://sccn.ucsd.edu/pipermail/eeglablist/2010/003080.html
>> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
>> But there are some counterarguments:
>> http://sccn.ucsd.edu/pipermail/eeglablist/2012/005513.html
>> So I guess it's still better to do it after ICA?
>>
>> 2. When and how to perform re-referencing:
>> It seems I should re-reference to average before ICA, but there seems to
>> be some counterarguments, too:
>> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008309.html
>> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
>> http://sccn.ucsd.edu/pipermail/eeglablist/2003/000090.html
>>
>> I'm not pretty sure whether to include EOG channels either, as there
>> seems to be pros and cons:
>> http://sccn.ucsd.edu/pipermail/eeglablist/2014/008854.html
>> http://sccn.ucsd.edu/pipermail/eeglablist/2007/001801.html
>>
>> Also is it all right to use average of M1/M2 (mastoid sites) for
>> re-referencing instead? Should M1/M2 be included for ICA training?
>>
>> Many thanks!
>>
>> Paul
>>
>>
>>
>>
>>
>>
>>
>>
>> --
>>
>> Paul Yu-Chun Chang
>> Graduate School Language & Literature Munich - Class of Language
>> Ludwig-Maximilians-Universität München
>> Schellingstraße 10
>> 80799 München, Deutschland
>> Email: Y.Chang at lipp.lmu.de
>>
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>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>



-- 

Paul Yu-Chun Chang
Graduate School Language & Literature Munich - Class of Language
Ludwig-Maximilians-Universität München
Schellingstraße 10
80799 München, Deutschland
Email: Y.Chang at lipp.lmu.de
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