Bayesian hierarchical precision-weighted prediction and its penetrability consequences

Recent accounts of cognition suggest that the brain implements a Predictive Processing mechanism. This thesis investigates how this framework could be applied to controversial domains that have been historically associated with a rival paradigm, such as human perception, language and social cognition. Using both philosophical and experimental tools, I argue that the same fundamental mechanism based on predictions and uncertainty is better in many respects.