[FieldTrip] Connectivity comparison across conditions

[Jose Rebola]

Hi!



I am trying to assess if there is a difference in connectivity across two
conditions in my data. Condition 1 has 240 trials and condition 2 has 252
trials.

I have chosen to use the *phase-locking-value* as a measure of connectivity.

*My first question is:*



Which formula should I use to evaluate the difference between conditions?

Would   plv1- plv2 be appropriate, or do I have to do some kind of
transformation or normalization? If I choose to use other connectivity
measures, will it be much different?

 I have seen for example in the paper of Jan-Mathijs Schoffelen in 2011
that he uses the formula in the following image for the assessment of
differences between the coherence values x1 and x2.

I should note that I would like to evaluate differences at the
intra-subject level.


[image: Inline image 1]



*My second question is:*



In order to do the non-parametric testing, my null hypothesis is that there
are no differences between plv1 and plv2 ( I guess). So I can randomize
trial labels, evaluate plv1 and plv2 again, do this 1000 times and count
the number of times that this difference is bigger than my original
difference, right?



*My third and fourth questions concern clustering:*

In order to do clustering, I should first establish a threshold value for
the metric under evaluation. This may be easy to set if I was using
t-values, but if I am evaluating differences in means, what should be an
appropriate value to use?



Regarding spatial clustering, I now have two levels of “neighbour”
electrodes, right? At the seed level, and at the destination level. How can
these be clustered? I mean, if I consider for example the electrode-pairing
T7-P3, both T9-P3 and T7-P5 will be neighbours…



*Lastly,*

Are these issues already implemented in Fieldtrip or do I have to build my
own MATLAB code for the randomization, thresholding and clustering?



Thank you so much,



 José Rebola
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