[Eeglablist] Calculating ERSP in STUDY design using one whole condition as baseline

[Makoto Miyakoshi]

Dear Christian,

Off the top of my head I could think of something like this. This
operation is not fully GUI based.

1. Calculate ERSP with no baseline subtraction.
2. Create clusters.
3. Plot ERSPs for all clusters. Close the main edit/plot GUI.
4. Reopen edit/plot GUI.
5. Access ERSP data stored under (something like) STUDY.cluster(1,x).ersp...
6. Calculate global mean of one condition, and subtract it from the other.

Sorry this might not be as simple as using GUI.
If you have further questions please let us know.

Makoto

2012/8/9 Christian Scharinger <c.scharinger at gmx.net>:
> Dear eeglab users,
>
> one further question, maybe someone has any suggestions:
> I have run an experiment with 4 different conditions. I would now like
> to define one of these conditions as baseline against which the
> remaining three conditions are compared, i.e. their ERSPs are calculated.
>
> In other words: when calculating ERSPs in a STUDY design I would like to
> define a whole condition as baseline for other conditions.
>
> Is there any "easy" way to do this?
>
> In the std_ersp function I found the argument:
> 'powbase'    - [ncomps,nfreqs] optional input matrix giving baseline
> power spectra (not dB power, see >> help timef). For use in repeated
> calls to timef() using the same baseine {default|[] -> none; data
> windows centered before 0 latency}
>
> I guess this might be the argument where I could define my "common
> baseline"? But I didn't figure out what kind of matrix the 'powbase'
> argument does expect and how to calculate this matrix in an "easy" way.
>
> I would be very glad about any suggestions!
>
> Best,
> Christian
>
>
> --
> Christian Scharinger, M.A.
>
> Knowledge Media Research Center (KMRC)
> Schleichstraße 6 | 72076 Tuebingen
>
> Phone: +49 (0)7071 979-360
> Internet: http://www.iwm-kmrc.de/c.scharinger
> E-Mail: c.scharinger at iwm-kmrc.de
>
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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