[FieldTrip] WPLI statistic, permutation like test??

Matteo Demuru suforraxi at gmail.com
Fri Jul 1 11:49:36 CEST 2011


Thanks a lot



On Wed, Jun 29, 2011 at 5:35 PM, Michael Wibral <michael.wibral at web.de>wrote:

> Hi matteo,
>
> sorry for my sloppy description,
>
> of course you would only shuffle trials on one channel, not both.
>
> Michael
>
>
>
> ------------------------------
> *Von:* "Matteo Demuru" <suforraxi at gmail.com>
> *Gesendet:* Jun 29, 2011 10:01:15 AM
> *An:* "Email discussion list for the FieldTrip project" <
> fieldtrip at donders.ru.nl>
> *Betreff:* Re: [FieldTrip] WPLI statistic, permutation like test??
>
>
> Hi Micheal,
>
> It seems to me that if you shuffle the trials and then compute the WPLI,
> the result is the same as if you do not shuffle.
>
> For example I have tried compute the WPLI on my trials and then switch
> trial{1} with trial{2} and the obtained WPLI is the same.
>
> Matteo
>
> On Tue, Jun 28, 2011 at 8:34 PM, Michael Wibral <michael.wibral at web.de>wrote:
>
>> Hi Matteo,
>>
>> I am not an expert on the WPLI measures, but to me it seems that in doing
>>
>>
>> "2) Randomly permute the ch2 time series"
>>
>> you're destroying a lot of ch2's properties (ie.g. it's spectrum will get
>> a lot of high ferquencies this way) and this will typically lead to false
>> positives. This is why permutation tests for connectivity measures typically
>> shuffle trials (i.e. permute data in a very controlled way, keeping the
>> intrinsic structure of the data).
>>
>> Michael
>>
>>
>> ------------------------------
>> *Von:* "Matteo Demuru" <suforraxi at gmail.com>
>> *Gesendet:* Jun 28, 2011 2:46:28 PM
>> *An:* fieldtrip at donders.ru.nl
>> *Betreff:* [FieldTrip] WPLI statistic, permutation like test??
>>
>>
>>
>> Hi,
>>
>> I have a couple of questions about using the WPLI index to assess the
>> phase on my MEG data.
>>
>> The experiment consists of recordings during a mental calculation task: I
>> have 30 sec in which each subject performed continuously an arithmetic
>> operation.
>>
>> It seems to me that WPLI index required more than one trial in order to be
>> computed. Am I right? (Is this necessary in order to reduce volume
>> conduction problems?)
>> I could divide my 30 sec in 5 sec-trials to create my trials, but I was
>> wandering if this could be a misuse of the WPLI, i.e. WPLI is not
>> appropriate for my experiment.
>>
>> I am also interested in assessing the significance of WPLI index, I would
>> like to gauge the significance per se of my WPLI values.
>> The idea is to calculate the WPLI distribution under the null hypothesis
>> (not phase coupling) for each pair of channels in this way:
>>
>> Example to assess the significance of WPLI value for ch1 vs ch2
>>
>> 1) Calculate the WPLI for ch1 and ch2, this would be the observed WPLI
>>  (WPLI_observed)
>>
>> 2) Randomly permute the ch2 time series
>>
>> 3) Calculate the WPLI for ch1 and ch2 (WPLI_i)
>>
>> 4) Repeat step 2 and 3 (for instance 100 times) in order to create the
>> WPLI_i distribution
>>
>> 5) Calculate the proportion ( # (WPLI_i  > WPLI_observed)  /  # (WPLI_i  ) )
>>  of WPLI_i which are greater than the WPLI_observed, if this  proportion
>> is < 0.05 I could say that the WPLI_observed represents a significant
>> degree of phase, otherwise not.
>>
>> Does it make sense or is it not the right approach?
>>
>> Let suppose this is a correct approach, I have two other questions:
>>
>> First, usually when I compute the WPLI value between two channels I obtain
>> a number of WPLI values  according to the cross-spectrum times (one WPLI for
>> each sliding window), in the steps above I am assuming to compute the
>> average WPLI_observed and the average WPLI_i for each step. Does this
>> raise any problems?
>>
>> Second, is it a problem using the same random permutations employed to
>> obtain ch1-ch2 (WPLI_i distribution) to calculate also the ch1-ch3 (WPLI
>> _i distribution). This is just an implementatiion question. I would like
>> to know if I could shuffle the time series of other channels in one step
>> (i.e. for ch1 something like data.trial{other_than_ch1,perm}), and finally
>> extract just the column relative to ch1 from WPLI matrix.
>>
>> thanks
>>
>> Matteo
>>
>>
>>
>>
>>
>>
>>
>>
>>
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