Incorporating (variational) free energy models into mechanisms: the case of predictive processing under the free energy principle

Abstract The issue of the relationship between predictive processing (PP) and free energy principle (FEP) remains a subject debate controversy within research community. Many researchers have expressed doubts regarding actual integration PP with FEP, questioning whether FEP can truly contribute significantly to mechanistic understanding or even undermine such altogether. In this paper, I present an alternative perspective. argue that, from viewpoint constraint-based mechanisms approach, imposes important constraint, namely variational energy, on architecture proposed by PP. According high-level cognitive are integral parts extensive heterarchical networks that govern physiology behavior agents. Consequently, explanations phenomena should incorporate constraints flows as relevant components, given implemented operate long is available. Within framework, contend provides constraint for explaining at least some biological described in terms Bayesian generative models minimize prediction errors.