I am a computational cognitive neuroscientist, an have worked at many levels. I find each kind of data and model useful to some extent, but I have to admit that the least useful, are, to my mind, those at the detailed neural network level, like the ones discussing in this paper. Somewhat more useful are higher level dynamic architecture models, and, at the highest level, cognitive models, which constrain the behavioral target we are trying to explain. I personally (as one can tell from my other posts here) find the dynamics brain development models to be the most compelling as overall models, but they are not particularly explanatory at the detailed level. Brain science is trying to do the hardest thing you can imagine, that is, explain the most complex machine in the known universe. We persist, but no one entering this field should have very high expectations of near term grand successes.