[Eeglablist] Fw: question on SICA approach

[David Contreras Ros]

Hi Edward.

For ICA it is irrelevant whether the data is continuous or not. ICA 
(infomax ICA) does not take into account the temporal order of the time 
samples, so you could perfectly well shuffle all the samples and the 
result would be the same. The important thing is that you try to keep 
the data as clean as possible and that the data you inject into ICA span 
those time periods in which the cognitive processes you are interested 
in were more likely to be active. So I wouldn't be worried because the 
data is discontinuous.

Other algorithms, as SOBI ICA, do take into account the temporal 
sequence of the time samples. However, you can always segment the data 
into 90s epochs before calling runica so that eeglab knows where the 
discontinuities are, and apply then whatever ICA algorithm you prefer.

David.

Edward Justin Modestino, M.Phil. wrote:
> Hello,
> I have data that I wished to import into EEGLAB to run ICA in an attempt
> to remove eye movements and artifacts.  All of my subjects are recorded in
> 90 second blocks with 82 EEG channels recorded at 256 hz.  The majority
> have 48 blocks, i.e. 48 X 90 second, thus approximately 72 minutes total
> of recording.  However, as stated earlier, they are in separate 90 second
> blocks.
>
> As the subjects had brief breaks between these 90 second recordings to
> move and/or rest their eyes, the recorder was shut off. Thus the
> recordings are NOT continuous for the whole experiment, but only for each
> separate 90 second block.
>
> Is it possible to run ICA on this data with the 90 second blocks?  Or is
> it not possible as the data is not continuous?
>
> Could I concatenate the data, all 48 90 second blocks, into one large
> matrix, and import it into EEGLAB to run ICA?  Or would this not work as
> it really was not continuous data in the first place?
>
> There are 10 different conditions and only two require responses.  This is
> all done with markers for the reaction times, conditions, false alarms,
> etc.  Is there any protocol to deal with markers in EEGLAB?
>
> Thanks,
> Ed
>
>   
>> Frederica -
>>   You've misinterpreted -- ICA learns a (channels,channels) unmixing
>> matrix,
>> so the number of data frames (time points) needed to separate as many
>> components increases as the square of the number of channels. The faq is a
>> bit out of date -- in our work with 72-256 channel data in the lab, we
>> have
>> found that as the channel density becomes high, good ICA solutions
>> typically
>> require a considerable multiple of the channel number squared (up to 30 or
>> more for 256-channel data).
>>
>> For 148-channel data I would like to collect 30*128^2 ~ 650k (~40 min of
>> data at 256 Hz) ... though it could well be that smaller data sets could
>> also give useful solutions. I will update the faq to better reflect this,
>> and will try to do a numerical study to get a more detailed heuristic
>> understanding.
>>
>> Scott Makeig
>>
>> On Feb 16, 2008 2:36 AM, Federica Di Grazia <federicadigrazia at hotmail.com>
>> wrote:
>>
>>     
>>> ----- Original Message ----- *From:* Federica Di
>>> Grazia<federicadigrazia at hotmail.com>
>>> *To:* eeglablist at sccn.ucsd.edu
>>> *Sent:* Tuesday, January 29, 2008 10:13 PM
>>> *Subject:* question on SICA approach
>>>
>>> I saw the faq on Independent Component Analysis but I couldn't
>>> understand
>>> how many samples(in time) I need to analyze 148 channels with SICA
>>> approach?
>>>
>>> I saw that it's necessary a number of samples(in time) equal to the
>>> square
>>> of the channels, but for SICA  the sample are represented by the 148
>>> channels, so I need the square root of 148 as samples(in time)?
>>>
>>>
>>>
>>> Best Regards,
>>>
>>> ____________________________________________________________________
>>>
>>> Federica Di Grazia
>>> Ph. D. Student in Electronics, Automation and Complex Systems
>>> Engineering
>>> Dipartimento di Ingegneria Elettrica Elettronica e dei Sistemi
>>> Università degli Studi di Catania
>>> v.le A.Doria 6 - 95125 Catania, Italy
>>> Tel. +39-095-7382342
>>> Fax +39-095-330793
>>> e-mail: fdigra at diees.ing.unict.it
>>>            federicadigrazia at hotmail.com
>>> ____________________________________________________________________
>>>
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>>>       
>>
>> --
>> Scott Makeig, Research Scientist and Director, Swartz Center for
>> Computational Neuroscience, Institute for Neural Computation, University
>> of
>> California San Diego, La Jolla CA 92093-0961, http://sccn.ucsd.edu/~scott
>> _______________________________________________
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>
>
> ---------------------------------------------------
> Edward Justin Modestino, M.Phil.
> Ph.D. Candidate in Complex Systems and Brain Sciences
> Cognitive Neurodynamics Laboratory
> Center for Complex Systems and Brain Sciences
> Florida Atlantic University
> (561) 297-2238
> Fax: (561) 297-3634
> modestino at ccs.fau.edu
> http://www.ccs.fau.edu/~modestino/
> Lab: http://www.ccs.fau.edu/~bressler/CNL_CCSBS/CNL_CCSBS_FAU.html
> ---------------------------------------------------
>
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>   
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