The general idea of a Bayesian brain is fairly well-accepted. Not everyone agrees that oh, this must be the way the brain works, but there are definitely experiments demonstrating set-ups in which you can get a good approximation of a Bayesian posterior distribution out of subjects.

The question is how the brain might do Bayesian inference in a very broad class of generative models (not just affine-Gaussian!), and what else it might be doing inference in service to.