[Eeglablist] Problems in calculating baseline power estimates of tfdata

[Makoto Miyakoshi]

Dear Cindy,

I'm interested in knowing how they are different. Do they differ only by DC
shift? Do they differ completely with nothing in common? Why don't you send
us some screencaptures of your data visualization (using imagesc...)?

Makoto

2013/3/20 Cindy Eckart <cindy.eckart at web.de>

> Dear EEGLablist-experts,
>
> I am working on a time-frequency analysis for EEG-Data of a working memory
> task and thus have to correct a retention phase (the time period where some
> images have to be memorized) to an 'external' baseline (fixation cross
> before the first image is presented). However, I am uncertain if I procede
> correctly.
>
> To get the standard deviation of baseline trials I saved the single trials
> (tfdata) for each subject. As tfdata consists of complex data I tried to
> transform it to power information with ERSP{n}.tfdataPOW{r} =*10*(log10(abs(tfdata).^2))
> * and saved it in a frequency x timepoint x trials - matrix tfdataPOW,
> where n is the condition (baseline) and r the channel.
>
> Well, if I understood (and did) everything correctly the mean over all
> trials (i.e. mean(ERSP{1,1}.tfdataPOW{1,1},3)) should now correspond to the
> power estimates of newtimef (i.e. ERSP{1,1}.chan{1,1}(1,:)); however, this
> is not the case.... Do I transform the data in a wrong way??
>
> Thank you very much for your help!
>
> Kind regards,
>
> Cindy
>
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-- 
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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