Evolution, Culture and Computation in Psychiatry

Abstract

This thesis develops an approach to integrate evolutionary, cultural, and computational approaches to psychiatry in 4 chapters. The claim at the core of this thesis is that a principled holistic explanation of mental disorders would benefit from the integration of explanations in computational, cultural, and evolutionary psychiatry. The argument is presented through two models. The first model is presented in chapter 3, and functions as an ontology of mental disorders that integrates principles of evolutionary, cultural, and computational psychiatry. The second model is presented in chapter 4 and implements this integrative view with a computational model of major depressive disorder. The models that I propose are based on two important philosophical assumptions about active inference, the formal theory that underwrites them. First, the two models assume that active inference — and implicitly the free-energy principle — can be applied to the behaviour of non-living systems. Second, the models assume that the cognition and behaviour (e.g., action, perception, and learning) of living systems — such as modelled under active inference — have a formal equivalent in non-living systems. This allows us to apply the free-energy principle to the dynamics of systems that involve nonliving components such as enculturated humans embedded in a material environment. The first portion of this thesis contained in chapters 1 and 2 defends these two assumptions. The second portion of this thesis contained in chapter 3 and 4 presents the two models.