[Eeglablist] Mean frequency power expectra plotted in bars

[Makoto Miyakoshi]

Dear Alberto,

Sorry for slow response.

> First of all, thanks for creating this email list for support.

Oh this email list is for user communication, not for support!

> im new in Matlab and my question is, im trying to plot in bars the mean
frequency power spectra of all the electrodes for each band (alpha,
theta...), is there any way to do it?
For example, for a 30 minutes recording I need mean Alpha, Beta, etc, each
one in a different bar. Each bar represents mean power of the 30min
recording.
> Also, I want to do ANOVA between different conditions/subjects. So
basically I need to compare alpha between different recordings. Is there
any way to import the data to SPSS or any other recommended software to
analyze it?

I see. You need spectopo() to calculate spectra, and statcond() to
calculate inferential statistics, and bar() to plot bar graphs. You may
also want to use errorbar() to show error bars on top of bars, and std() to
compute standard deviation and divide it with sqrt(n) where n is the number
of subjects. I don't see any necessity to use SPSS to take care of this
simple statistics, just use statcond().

Good luck!

Makoto


On Wed, Sep 14, 2016 at 3:16 PM, Alberto Sainz <albertosainzc at gmail.com>
wrote:

>
> Hello,
>
> First of all, thanks for creating this email list for support.
>
> im new in Matlab and my question is, im trying to plot in bars the mean
> frequency power spectra of all the electrodes for each band (alpha,
> theta...), is there any way to do it?
> For example, for a 30 minutes recording I need mean Alpha, Beta, etc, each
> one in a different bar. Each bar represents mean power of the 30min
> recording.
>
> Also, I want to do ANOVA between different conditions/subjects. So
> basically I need to compare alpha between different recordings. Is there
> any way to import the data to SPSS or any other recommended software to
> analyze it?
>
> Thank you
>
>
>
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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