A Bayesian perspective on delusions: Suggestions for modifying two reasoning tasks

摘要

Background and objectives: There are a range of mechanistic explanations on the formation and maintenance of delusions. Within the Bayesian brain hypothesis, particularly within the framework of predictive coding models, delusions are seen as an aberrant inference process characterized by either a failure in sensory attenuation or an aberrant weighting of prior experience. Testing of these Bayesian decision theories requires measuring of both the patients' confidence in their beliefs and the confidence they assign new, incoming information. In the Bayesian framework we apply here, the former is referred to as the prior while the latter is usually called the data or likelihood.