Hello,

I'm looking for some information about interpreting second level analysis, and to perform group comparisons. 

I'm investigating whether a difference in connectivity can be seen in patients compared to controls in ROI-to ROI analysis (n=20). 

Settings in 1st level analysis is: functional connectivity, ROI-to-ROI analysis, correlation (bivariate) with no weighing. Two seeds/sources are chosen. 

Settings in 2nd level analysis are; Subject effect (I have marked condition patients and controls already prepared in Setup conditions). Between-subjects contrast [1 0; 0 1] (Any effect among controls or patiens), between-conditions contrast =1 and between-sources contrast=1.

Results explorer I see F(2) (18) = 51.80 p ung and p FWE =0.000. In a results explorer from another date I got a T-value of 4.85 instead. Why has it changed the statistics and what do I do with this data?

How do I interpret this? What is the connectivity in patients compared to controls? Is the difference significant?

My other questions concerns the beta-values for each individual subject. What is the beta value and how do I convert it into a connectivity value? I find the beta values in the first level analysis folder in the matrix need "Z". But which of all these values should look at?

I plan to add more Seeds/sources in time. Do I need to change anything in the settings if I do so??

Attached file is the first level analysis results for one subject.

Thank you very much for your time,

BR