I'm not an expert but I think the FAQ might help you...

http://www.alfnie.com/software/conn

"Analyses: What are the different connectivity measures in the first-level analysis step? Should I use correlation or regression measures?
There are four connectivity measures that can be computed by the toolbox: bivariate correlation, semipartial correlation, bivariate regression, and multiple regression measures. Most people seem to be using the simpler bivariate correlations (as a measure of 'total' functional connectivity between two areas). Semi-partial correlations are used when you want to obtain instead the 'unique' contribution of a given source on a target area (controlling for the contributions of other additional source areas), this is useful for example when studying in more detail potential paths underlying the functional connectivity between two areas. Bivariate and multiple regression measures are equivalent to bivariate and semi-partial correlation measures, but their units instead represent 'effective change' (percent signal change in target area associated with each percent signal change in source area; something closer to 'effective' connectivity). These measures are useful for example when one is concerned about potential differences in BOLD signal variance driving the connectivity/correlation results (regression measures are not biased by differences in variance between conditions/populations, while correlation measures can be (e.g. Friston, 2011).

Analyses: I ran bivariate correlations, what are my 2nd level beta values?
They represent Fisher-transformed correlation coefficient values, i.e. atanh(r), where r is the correlation coefficient between the source area and target area (voxels or regions)"