What is simulated in the action observation network when we observe actions?

In the last decade there has been a great amount of research investigating the role of simulation in our ability to infer the underlying intentions of any observed action. The majority of studies have focussed on the role of mirror neurons and the network of cortical areas active during action observation (AON) in inferring the goal of an observed action. However, it remains unclear what precisely is simulated when we observe an action and how such simulations can enable the observer to infer the underlying intention of that action. In particular it is not known how simulation in the AON enables the inference of the same goal when the kinematics observed to achieve that goal differ, such as when reaching to grasp an object with the left or right hands. Here we performed a behavioural study with healthy human subjects to address this question. We show that the subjects were able to detect very subtle changes in the kinematics of an observed action. In addition, we fitted the behavioural responses with a model based on the predictive coding account of mirror neurons. This is a Bayesian account of action observation that can be explained by the free-energy principle. Here we show that we can model all the effects observed when the action observation system is considered within a predictive coding framework.