[Mne_analysis] phase locking analysis with MNE

Ghuman, Avniel (NIH/NIMH) [F] ghumana at mail.nih.gov
Thu Sep 16 15:20:46 EDT 2010
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Hi All,

PLV does in fact depend on the number of trials because it follows the Raleigh distribution.  Think of this like a chi-square distribution.  The mean/peak of the distribution will get closer to 0 as there are more trials, so your result is exactly what you would expect.  It does not have anything to do with the SNR however.

For an example of this, calculate the PLV for random data with different numbers of trials.  You will see the PLV change.

Avniel


On 9/16/10 3:15 PM, "Matti Hamalainen" <msh at nmr.mgh.harvard.edu> wrote:



On Sep 16, 2010, at 2:53 PM, Elisabeth Fonteneau wrote:

> Hi All,
>
> I am running a phase-locking analysis on MEG/EEG combined source
> data on the single trial level.
>
> And I have a quick question for this mailing list
>
> I was wondering whether the number of trials used for computing the
> Phase Lock Value (PLV) will affect the synchrony results?
>
> I meant if I am comparing 2 conditions with different numbers of
> trials in each (let's say N=50 vs N=100) do you think that the
> synchrony will change because of different signal to noise ratio?
>
> I am asking this because I have done such comparison, and strangely
> this is the condition with the less number of items that is showing
> increasing synchrony compared to the condition with the larger
> number (in the gamma band).
>
> It will be very helpful if somebody already came across this issue,
> and/or if you can point me toward a relevant paper discussing this
> problem.
>
> Thx to all for reading!

To my understanding, the PLV should not depend on the number of
trials. However, here are two tests you could do:

1. Pick N = 50 trials from the N = 100 condition a few times and check
whether the PLV is the same as when using all the trials.

2. Using bootstrapping, you could calculate the variability
(confidence intervals) of PLV in each condition to see whether this
difference is true or just due to the variability in the data.

- Matti




---------

Matti Hamalainen, Ph.D.
Athinoula A. Martinos Center for Biomedical Imaging
Massachusetts General Hospital

msh at nmr.mgh.harvard.edu






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