[Eeglablist] Subtract individual subject mean spectrum...what does that mean?

[arno delorme]

Dear Krishnaj,


> I wanted to know, what exactly does the option "Subtract individual  
> subject mean spectrum" do?
>

This option computes the average spectrum for all data channels or  
components and subtract from the subject spectrum. This is useful if  
you want to minimize the effect of individual subjects so only the  
part of the spectrum that differs from the average spectrum in a  
subject is visible.

To compute significance, you simply need to select the type of  
significance you want to compute in the GUI (parametric or  
permutation). For further processing you may also retrieve the scalp  
map values from the command line. For instance, if you plotted the ERP  
scalp maps of the channel data

chanlocs = eeg_mergelocs(ALLEEG.chanlocs); % merge all channel  
location structures

chanlist = { chanlocs.labels }; % labels for all the channels

[STUDY erps erptimes pvalcond pvalgroup ] = std_erpplot(STUDY, ALLEEG,  
chanlist, 'topotime', [100]); % assumes that you have pre-computed  
ERPs and plot the grand-average scalp map at 100 ms

figure; topoplot(mean(erps{1,1},3), chanlocs); % replot the scalp map  
- the mean averages across subjects (first condition and first group)

[F df pvals] = statcond(erps); % recompute statistics if you have  
several groups and/or conditions

figure; topoplot(-log10(pvals{1}), chanlocs); clim([0 3]); cbar;% plot  
statistical significance across conditions (scale 0 to 3 in log10 -> 1  
to 0.001).

Note that of course, you can do all of this from the GUI. However, it  
is sometimes useful to go back to the command line for instance if you  
have 2 groups of subject and want to compute statistics of ERP/ERSP  
difference across conditions. You may then use the std_erpplot (or  
std_specplot, std_erspplot) to retrieve the scalp maps/curves/images  
you are interested in, compute the difference and then apply the  
statcond function or your own function to recompute significance and  
plot it.

Hope this helps.
Best,

Arno

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