On the minimal theory of consciousness implicit in active inference

• Starting with active inference, a first principles mathematical framework for modelling adaptive behaviour, we build up to a minimal theory of consciousness which emerges from the shared features of computational models derived under active inference. • We review a body of work applying active inference models to the study of consciousness and argue that there is implicit in all these models a small set of theoretical commitments that point to a minimal (and testable) theory of consciousness. • All active inference models minimise the same objective functions — which can be decomposed into a small set of interpretable terms —allowing us to expose commonalities and differences across diverse phenomena within consciousness science. • Emphasis is placed on the relationship between the (minimal) theory and data. The multifaceted nature of subjective experience poses a challenge to the study of consciousness. Traditional neuroscientific approaches often concentrate on isolated facets, such as perceptual awareness or the global state of consciousness and construct a theory around the relevant empirical paradigms and findings. Theories of consciousness are, therefore, often difficult to compare; indeed, there might be little overlap in the phenomena such theories aim to explain. Here, we take a different approach: starting with active inference, a first principles framework for modelling behaviour as (approximate) Bayesian inference, and building up to a minimal theory of consciousness, which emerges from the shared features of computational models derived under active inference. We review a body of work applying active inference models to the study of consciousness and argue that there is implicit in all these models a small set of theoretical commitments that point to a minimal (and testable) theory of consciousness.