Two coherence computation methods [before 2019 vs. 2019]


I would like to get some of your opinions about coherence computation.
While I was running coherence computations for multiple subjects' data, brainstorm version was updated.
After the program was updated, there are two different [imaginary coherence] computations (which we mainly use), [2019] and [before 2019].
updated Brainstorm Coherence result using [before 2019] was identical with older Brainstorm (Dec 2019) coherence result.

Now I need to make a decision whether to use data from different computations or using the same computation for all subjects, and also want to know which one is better.

So my specific questions are...

  1. Is newer one [2019] superior than old one [before 2019]?
  2. Should I discard old data [used before 2019] and recalculate using the newer one?
  3. If we need to do, is there a way that we can convert the extracted coherence results with [before 2019] to [2019] without recompute everything (like just a ration changes?)?

Thank you,


The two measures are very different, you can't convert one to the other.
You should use either one or the other method for all your subjects: either you keep your previous results and keep going with the old method, or you recompute everything with the new version.

I can't help you with the decision on the measure to use. They are described in the header of the function bst_cohn.m, maybe try to pick the one that corresponds to the literature you are referring to:

@hossein27en Any suggestion?