avgoverfreq is good or bad?

Eric Maris e.maris at DONDERS.RU.NL
Sat Nov 20 13:41:20 CET 2010


Dear Manish,


As a rule, whenever you incorporate valid prior information in your
statistical analysis, you will increase sensitivity. For instance, assume
that there physiological reasons why effects should always occur in a number
of discrete frequency bands; [0.5,1.5] (delta), [4,6] (theta), [8,12]
(alpha), [13,30] (beta), and [31,80] (gamma). Then, you will increase power
by (1) estimating the average power in these frequency bands (using
multitaper estimation with the appropriate spectral smoothing), and (2)
performing a cluster-based permutation test on the resulting
(channel,frequency bin)-data. Without frequency smoothing in the a priori
defined frequency intervals sensitivity will be lower, assumed the intervals
are valid of course. You can further increase sensitivity if you know a
priori that effects will only occur in one of the frequency bands, but that
does not seem to be the case for you.

Good luck,

Eric Maris


dr. Eric Maris
Donders Institute for Brain, Cognition and Behavior
Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging
Radboud University
P.O. Box 9104
6500 HE Nijmegen
The Netherlands
T:+31 24 3612651
Mobile: 06 39584581
F:+31 24 3616066
E: e.maris at donders.ru.nl







> -----Original Message-----
> From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On
> Behalf Of Manish Saggar
> Sent: zaterdag 20 november 2010 8:21
> To: FIELDTRIP at NIC.SURFNET.NL
> Subject: [FIELDTRIP] avgoverfreq is good or bad?
>
> 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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