avgoverfreq is good or bad?

Manish Saggar manish.saggar at GMAIL.COM
Mon Nov 29 06:46:51 CET 2010


Dear Eric,

Thanks for explaining in detail and apologies for late reply, I was on vacation.

Regards,
m-


On Sat, Nov 20, 2010 at 6:41 AM, Eric Maris <e.maris at donders.ru.nl> wrote:
> 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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>> and to discuss  new ideas for MEG and EEG analysis.
>> See also http://listserv.surfnet.nl/archives/fieldtrip.html
>> and http://www.ru.nl/neuroimaging/fieldtrip.
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>
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> You are receiving this message because you are subscribed to
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> between  users of the FieldTrip  toolbox, to share experiences
> and to discuss  new ideas for MEG and EEG analysis.
> See also http://listserv.surfnet.nl/archives/fieldtrip.html
> and http://www.ru.nl/neuroimaging/fieldtrip.
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and http://www.ru.nl/neuroimaging/fieldtrip.
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