Yes and no. On the one hand, yes, theoretical neuroscience does use some ideas originating in machine learning and computational statistics. So does computati

Yes and no. On the one hand, yes, theoretical neuroscience does use some ideas originating in machine learning and computational statistics. So does computational cognitive science. On the other hand, in these fields we set ourselves a different explanatory task: point to the real brain, the real body, and real behavior, and explain them in their full complexity. When asked, "how does this explain the real world", machine learning feels no more compunction than an aeronautical engineer asked to explain wings. This would be great, if only machine learning actually built its engineering artifacts from solid normative principles! Instead, it mostly just hacks things together, as a result of which, its lack of compunction comes across as a reluctance to stand up to the challenge of explaining any aspect of the real world at all, which becomes embarrassing which the machine learning world begins opining on the nature of intelligence and such. Meanwhile, if you ask cognitive scientists and neuroscientists to opine on the nature of intelligence, we have many fewer cool demos, but many more principles and better scientific evidence.