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

[Arnaud Delorme]

Dear Christian,

Makoto solution would work but there is a (much) easier way.
Declare your conditions as paired in your design and the common baseline to all conditions will be subtracted by default. No command line needed. A message will be shown on the command line.
Best,

Arno

On Aug 10, 2012, at 1:14 PM, Makoto Miyakoshi wrote:

> 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
> 
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