Our research is theoretically driven by ideas of Predictive Coding, a computational framework that posits the brain is a predictive, efficient and adaptive machine. The main goal of the group is to understand how the brain’s circuitry implements these mechanisms, which enable us to make predictions about future events as well as learn about, and adapt to, the contingencies of a novel environment. Along with our work on typical cognition in healthy human individuals, our mission is to contribute to the understanding of mental illness, in particular to those conditions where predictive processes and brain circuitry are disrupted such as in schizophrenia and anxiety. To pursue this endeavour we use a combination of computational modelling, machine learning and brain imaging techniques such as magnetoencephalography (MEG), electroencephalography (EEG), and magnetic resonance imaging (MRI).