[Mne_analysis] PLV in label in source space

Ghuman, Avniel ghumana at upmc.edu
Fri Sep 19 11:58:33 EDT 2014
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Dear Alex and Laetitia,

One thing to mention is that my experience is that the statistical
significance does not change much either way. This has to do with the fact
that averaging first boosts the SNR of the signal going into the PLV
calculation, increasing the PLV values. If one calculates the PLV for each
source, the individual PLV values are lower (lower SNR for each estimate),
but because you have averaged many together, your confidence in the
resulting PLV is increased. You can do this comparison using monte carlo
or permutation testing, the p-values should not change much as long as you
perform all of the same procedures on the permuted data as you did for the
original data.

Best wishes,
Avniel

On 9/19/14 11:50 AM, "Alexandre Gramfort"
<alexandre.gramfort at telecom-paristech.fr> wrote:

>hi,
>
>thanks for sharing these insights. Any suggestion to make this
>straightforward
>and update/deprecate source_induced_power is welcome.
>
>Laetitia if you can/want to share a gist it would be great.
>
>Alex
>
>
>On Fri, Sep 19, 2014 at 4:54 PM, Ghuman, Avniel <ghumana at upmc.edu> wrote:
>> Dear Laetitia,
>>
>> Generally I find that spatially averaging across the label, then
>>calculating the PLV works better.
>>
>> Best wishes,
>> Avniel
>>
>> From: Laetitia Grabot
>><laetitia.grabot at gmail.com<mailto:laetitia.grabot at gmail.com>>
>> Reply-To: Discussion and support forum for the users of MNE Software
>><mne_analysis at nmr.mgh.harvard.edu<mailto:mne_analysis at nmr.mgh.harvard.edu
>>>>
>> Date: Friday, September 19, 2014 10:27 AM
>> To: 
>>"mne_analysis at nmr.mgh.harvard.edu<mailto:mne_analysis at nmr.mgh.harvard.edu
>>>" 
>>><mne_analysis at nmr.mgh.harvard.edu<mailto:mne_analysis at nmr.mgh.harvard.ed
>>>u>>
>> Subject: [Mne_analysis] PLV in label in source space
>>
>> Dear all,
>>
>> When calculating the phase-locking value (PLV) from n trials in a label
>>in source space, I'm wondering if it is more relevant to:
>> - spatially averaging the trials across the label, then calculated the
>>PLV.
>> - calculating the PLV on each source then averaging the PLVs across the
>>label.
>>
>> I compared the two methods, and things change a lot (the PLV is larger
>>when the average is done at the level of the trials than when it's done
>>at the level of the PLVs). I would have the feeling that averaging the
>>trials first is more relevant, especially if using svd, so that the
>>averaged signal is more robust. Could someone confirm/contradict my
>>feeling?
>>
>> Thanks in advance,
>> Laetitia G.
>>
>>
>>
>>
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