avgoverfreq is good or bad?

[Manish Saggar]

Dear all,

I have spatio-spectral EEG data (no temporal information) from two
groups. Group A was tested three times (t1,t2,t3) during a treatment
and group B (control group) was also tested at the same three time
points. Now I simply want to know which <channel, frequency> pairs
differ for each group separately. Thus, I ran depsamplesF test
(cluster with montecarlo) for each group for a large frequency range,
say 0.5 - 100Hz, cfg.avgoverfreq = 'no'.  I then used Bonferroni
correction (for two tests) and plotted the clusters using multiplotTFR
with 'mask' as zstat parameter. The clusters of <ch, freq> I get are
mostly in 15-40Hz range and usually there is only one big cluster.

Now my question is - by running over a huge range of frequency (using
no averaging over freq), did I lower the power for low freq bands
(like delta, theta, and alpha)? Should I rather run these tests
separately for low freq bands (like delta, theta, and alpha) with
avgoverfreq='yes'. And may be another test for high frequencies like
14-100 Hz with no averaging over frequencies.

The reason I was running one test for all frequencies was to avoid
multiple tests and hence avoiding more stringent Bonferroni
correction.

Thanks,
m-



Manish Saggar,
Doctoral Candidate,
Department of Computer Science,
The University of Texas at Austin,
Web: http://www.cs.utexas.edu/~mishu/
Email: mishu at cs.utexas.edu

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