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Hello I'm not 100% sure about whether I understand the question - as I see it, you may be asking one of two things: 1. Instead of plugging the region A time series into the model as the independent variable and then seeing if region B is one of the areas that emerges as significantly covarying with activity in A, you extract a time series from region A and from region B and see if they correlate. If this is what you're asking, then you may well be able to establish the presence of functional connectivity between A and B (functional connectivity being precisely as you've defined it) but there are both pros and cons to your approach (relative to the "standard" approach in which you select only one region). Notably, your approach is more model-based and dependent upon your predictions. If you select the wrong bit of region B from which to extract your signal, you may not observe a correlation. However, the fact that it is clearly hypothesis-led removes the multiple comparisons problems since the other approach looks across the whole brain for functionally connected regions 2. Or perhaps you're asking whether it is a good idea to produce an average signal for region A for each subject and an average signal for region B and then put them into a multi-subject model and see if the A-B correlation occurs across subjects. This is a very different question since it is asking: do the subjects who show stronger activation in region A also show stronger activation in region B? (This is in contrast to the "standard" approach in which you're asking: For a given subject, when A goes up, does B go up too?). This approach does not, I think, produce very interesting or convincing evidence of functional connectivity. It could just be that all subjects are activating A AND B, but some subjects are big activators and some subjects are little activators thus producing a correlation across subjects. Of course this could be interesting but it doesn't really get at functional connectivity as it interests most of us. Very best Paul On Mar 1 2007, Ray Norbury wrote: >Hi, > > I believe that functional connectivty refers to the correlation between > the activation time series for two distinct brain regions A & B. If this > is true, how does this compare to estimating percent signal change in > region A and region B for each subject and entering these values into a > correlation analyses? Is the latter option less valid or totally invalid? > >Cheers, > >Ray >