  In this paper we consider the modern theory of the Bayesian brain from
cognitive neurosciences in the light of recommender systems and expose
potentials for our community. In particular, we elaborate on noisy user
feedback and the thus resulting multicomponent user models, which have indeed a
biological origin. In real user experiments we observe the impact of both
factors directly in a repeated rating task along with recommendation. As a
consequence, this contribution supports the plausibility of contemporary
theories of mind in the context of recommender systems and can be understood as
a solicitation to integrate ideas of cognitive neurosciences into our systems
in order to further improve the prediction of human behaviour.
