tl;dr: I feel like multiple comparison can be easily manipulated to have significant results.
As far as I understand, the concept of multiple comparison problem is very simple. As we are conducting every tests with alpha level 0.05, the false positive rates will increase dramatically as the number of tests conducted increases.
Here comes my confusion, while I was reading researchers correcting for multiple comparison (say for instance you are doing correlations between 5 behavioral measures and 10 brain signals from different location, therefore 50 correlations in total), no matter you choose FDR, bonferroni or others, you could possibly find none of the results is significant due to that large amount of tests. But one can always "claim" he/she only did correlation tests, for example, just on 1 behavioral measure, and those insignificant results then become significant.
I have been discussing with my colleagues but we dont have a good explanation on this confusion, it made me hard to believe "significant" results from papers. Of course correction is generally recommended, but who know if these researchers were not telling lies? Claim that they were doing 5 tests but actaully they have done 100 tests?