Thank you for your quick reply! 

I did correct for multiple comparisons but I did it differently from what you mentioned. I used linear regression to assess case-control differences and did permutation testing 1000 times to determine the empirical p-values. For the 3 global-level network metrics, significance was determined through the empirical p-values with Bonferroni correction of 0.05/3. For each of the 2 node-level network metrics, significance was determined for case-control effects using FDR correction for 85 nodes, with threshold pFDR <� 0.05/2. Does this sound feasible to you? A lot of measures were significant after permutation testing but not FDR correction.

Also, sorry but I still do not really understand why it is possible to see differences in nodal metrics but not connectivity. Isn't it differences at the connection level that will lead to differences at the nodal level? Especially for node-level metrics like nodal efficiency and clustering coefficient?

Thank you again and happy to continue this conversation over email too if it is not too relevant here! 

Best Regards
GT