I am running a connectivity analysis looking at the relationship between a behavioral change value and connectivity change from a seed (pre vs. post). 

Subject effects: 

ALL SUBJECTS

BEHAVIORAL CHANGE

[0 1]

Conditions: 

Pre 

Post

[-1, 1]

The data that I get out when a) run second-level analysis and then import the data to get the Fisher's transformed values from this analysis is DIFFERENT to b) when I output mask of significant cluster, rerun a second level between seed and significant cluster (in this case a mask) ROI-to-ROI analysis and import data to get Fisher's transformed values  

1) How do I interpret these differences? 

2) Which one gives me the pre and post connectivity between the target and significant cluster so that I can then create a scatter graph of these relationships?  I assume it would be b above?  

I should note that when I subtract out the pre and post values from a and b - I get exactly the same output.  Why are the fisher's transformed values slightly different?