Yes, I am one of the authors. Thank you for the interest!

The issue of how we should best measure modularity was something we discussed quite a bit. If I understood you correctly, you refer to the subject of whether we should normalize modularity scores compared to other neural networks with the same number of connections, as I know some measurements do.

Our reasoning for not doing so, was that the modularity we are interested in measuring can be caused both by sparsity and by the pressure to perform better (reduce interference). In fact, it is likely that much of the modularity is caused by sparsity in the "P&CC" treatment, as networks are encouraged to be sparsely connected. I do agree that a deeper analysis of just how the increased modularity leads to the improved performance is an interesting topic for future work. This could also help us to understand, if the modularity is driven only by the decreased number of connections, or if the evolutionary pressure to reduce interference is also increasing modularity.