[Eeglablist] How can I extract P300 from a continuous EEG dataset using EEGLAB?

[Makoto Miyakoshi]

Dear Anastasios,

If you haven't done so, I recommend you follow EEGLAB online tutorial and
workshop. There is a lot of learning materials online.
However, EEGLAB does not necessarily provide the most convenient functions
to meet the needs of conventional ERP studies. You might want to check
ERPLAB too, which is more dedicated for that needs (that's what I heard,
sorry I have no experience there!)

However, if you want to do it at the group level using EEGLAB STUDY, you
can use my plugin ERPstudio.
https://sccn.ucsd.edu/wiki/Std_erpStudio
You enter window beginning and ending for computing mean/defining peak to
perform statistics.

So what you need is

   1. Define event types and time
   2. Preprocess scalp-recorded continuous signals up to dipole fitting
   (see https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline for
   preprocessing data)
   3. Epoch to compute ERP
   4. Integrate the group-level results by creating EEGLAB STUDY
   5. Use std_erpStudio to perform statistics on user-defined time window

Too complicated? Indeed, I think knowing all of these steps in good detail
deserves one PhD. In addition, using ICA results to perform the final
group-level statistics requires a lot of courage because of complexities of
post-ICA processes (the group-level statistics can be done only
probabilistically due to inconsistency across subjects) and open
parameters. However, many of us challenged it and got successful results. I
hope you challenge it also!

Makoto

On Sun, Jul 15, 2018 at 9:05 PM Anastasios Giannopoulos <
angianno_8 at hotmail.com> wrote:

> Hello,
>
> I have loaded my continuous EEG data into EGGLAB and I want to find the
> P300 values. I also know the times of the beginning of each stimulus. I
> have not yet defined events and epochs. How should I work to finally export
> the P300 values?
>
> Thank you in advance!
>
>
>
>
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows 10
>
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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