We live in a largely predictable world. Capitalising on this statistical structure allows us to predict events and agents around us, which can result in potentially more efficient encoding, learning and recognition of input, and therefore appears a crucial skill.

In my talk, I will discuss recent work from my lab, investigating behaviour and brain activity, in which we are trying to elucidate the nature of predictive processing. I will argue that the brain represents a temporally discounted representation of future expected states. This representational format may lead to an efficient neural processing of expected input, and directs information sampling to situations of maximal uncertainty and surprise. I will illustrate this principle in the realm of visual perception, and natural language and music listening.