[Eeglablist] P300 signal detection (Research Assistant)

Daniel Góngora d.marcell.gongora at gmail.com
Wed Oct 10 15:28:10 PDT 2012


Dear Habib Paracha,
I would recommend you to follow the BCI2000 tutorial. You can find it here:
http://www.bci2000.org/wiki/index.php/User_Tutorial:P300_BCI_Tutorial

Despite the lack of electrodes over the commonly used locations to record a
P300 response (Fz, Cz and Pz), you can still measure it -according to my
experiments- mainly over P7, O1, O2 and P8.

Regards,

Daniel Góngora


On Wed, Oct 10, 2012 at 3:00 PM, <eeglablist-request at sccn.ucsd.edu> wrote:

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> Today's Topics:
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>    1. P300 signal detection (Research Assistant)
>    2. ICA problema Massimiliano Papera (Massimiliano Papera)
>
>
> ---------- Forwarded message ----------
> From: Research Assistant <ra_lums at hotmail.co.uk>
> To: <eeglablist at sccn.ucsd.edu>
> Cc:
> Date: Wed, 10 Oct 2012 11:44:17 +0500
> Subject: [Eeglablist] P300 signal detection
>  Hi all,
>
> I want to extract P300 signals. I currently have with me EMOTIV EPOC
> headset with its research SDK. I am new in this domain. I have been
> following tutorials of EEGLAB and trying to see the signals which I saved
> in the Testbench of my SDK.  I used the OpenViBE'a keyboard simulator
> program provided at this link:
> http://neurofeedback.visaduma.info/emotivresearch.htm
>
> But I am unable to find anything significant.
> Can someone help me please and guide me how to proceed.
>
> Regards,
>
> Habib Paracha
>
>
> ---------- Forwarded message ----------
> From: Massimiliano Papera <massimiliano.papera at googlemail.com>
> To: eeglablist at sccn.ucsd.edu
> Cc:
> Date: Wed, 10 Oct 2012 14:12:07 +0100
> Subject: [Eeglablist] ICA problema Massimiliano Papera
> Dear all,
>
> I am just about to run the ICA and I just incurred in this statement in
> the tutorial:
>
> 'Note: If you try to run ICA on this new dataset, the number of dimensions
> of the data will have been reduced by the number of components subtracted.
> We suggest again 'baseline-zeroing' the data (if it is epoched when some
> components have been removed, data epoch-baseline means may change). To run
> ICA on the reduced dataset, use the *pca* option under the Tools > Run ICApop-up window, type
> * 'pca', '10' * in the Commandline options box to reduce the data
> dimensions to the number of remaining components (here 10), before running
> ICA (see runica.m<http://sccn.ucsd.edu/eeglab/locatefile.php?file=runica.m>.
> If the amount of data has not changed, ICA will typically return the same
> (remaining) independent components -- which were, after all, already found
> to be maximally independent for these data.'
>
> this is from
> http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA
>
> Let's us suppose that I have just removed, say, 4 ICS comps. Then how do I
> check if the amount of data has changed?
>
> Thank you very much for your help.
>
>
> Cheers
> Massimiliano Papera
>
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-- 
Daniel Góngora
https://twitter.com/dm_gf
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