A Bayesian account of the mirror system. (360G-Wellcome-081048_Z_06_Z)

Social interaction depends upon our ability to infer beliefs and intentions inother minds. Impairments of this ability can lead to major developmental and psychiatric disorders such as autism and schizophrenia. Little is known about the neural basis of our ability to read' the intentions of others, but a very likely candidate is the mirror neuron system.These neurons discharge, not only when an animal model acts, but also when the animal observes someone else performing the same action. However, it is not known how someone else's intentions can be inferred by the mirror system. The proposed research addresses this issue. More specifically I propose that the mirror system is best considered within a predictive coding framework that appeals to empirical Bayes. Within this scheme the most likely cause of an observed action can be inferred by minimising the prediction error at all levels of a cortical hierarchy that is engaged during action observation. This account specifies a precise role for the mirror system in our ability to infer intentions and formalises the underlying computations. Furthermore, it makes specific predictions about the behaviour and organisation of the mirror systemthat can be tested empirically. The proposed research will test these predictions.