An adaptive representational account of predictive processing in human cognition

As a new research direction in contemporary cognitive science, predictive processing surpasses traditional computational representation and embodied cognition and has emerged as a new paradigm in cognitive science research. The predictive processing theory advocates that the brain is a hierarchical predictive model based on Bayesian inference, and its purpose is to minimize the difference between the predicted world and the actual world, so as to minimize the prediction error. Predictive processing is therefore essentially a context-dependent model representation, an adaptive representational system designed to achieve its cognitive goals through the minimization of prediction error.