[Eeglablist] pop_comperp

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Thu Feb 20 10:30:15 PST 2014


Dear Andres,

Ok if that's the case my recommendations are the same.

I forgot to mention another approach though, which should be the standard
solution for EEGLAB. You select epochs according to event types, and in
your case you need to create three smaller sets each of which contains
single condition. Then use plot ERP function and specify the dataset
numbers in the top box and you can visualize the 3 line plots overlaid for
each channel.

Makoto


2014-02-20 10:24 GMT-08:00 Andres Munguia Barcenas <
andres.munguiabs at udlap.mx>:

>  Thank you, Makoto
>
>
>  Anyway, I think I wasn't specific enough. I want to see graphically the
> Grand Average of the 3 conditions togheter
>  ------------------------------
> *De:* Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> *Enviado:* martes, 18 de febrero de 2014 09:24 p. m.
> *Para:* Andres Munguia Barcenas
> *Cc:* eeglablist at sccn.ucsd.edu
> *Asunto:* Re: [Eeglablist] pop_comperp
>
>  Dear Andres,
>
>  I haven't use it myself but people say ERPLAB is a good solution for
> that.
>
>  My other suggestion is that you create STUDY with a single subject. You
> can visualize single IC ERPs across conditions with statistics. You can do
> this with and without ICA-decomposition (though I haven't used channel
> version of STUDY myself).
>
>  Makoto
>
>
> 2014-02-18 11:08 GMT-08:00 Andres Munguia Barcenas <
> andres.munguiabs at udlap.mx>:
>
>>  Hi,
>>
>>
>>  I am heading an experiment where I 'am working with ERP's. During a
>> task, my subjects are under 3 conditions.
>>
>>
>>  I want to know if it is possible to see graphically the 3 conditions
>> togheter using the function pop_comperp.
>>
>>
>>  If not, which function may I use to see this?
>>
>>
>>
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>
>
>
>  --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>



-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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