Abstract

This talk considers formal or computational approaches to phenomenology. I will use psychopathology to offer a case study of aberrant perception. This motivates the choice of a formal or computational framework within which to understand psychopathology; particularly, in terms of false beliefs or inference. This framework is the Bayesian brain. We will focus on the (neuromodulatory) encoding of uncertainty or precision within predictive coding implementations of active inference – to demonstrate computational approaches to perception and phenomenology. The endpoint of this analysis is the key role of neuromodulation in selecting those aspects of the sensorium that underwrite our belief updating – and making sense of our sensations. This speaks to (i) the key role of modulatory neurotransmitters (and psychopharmacological drugs) in shaping our inferences about the lived world, and (ii) the accompanying attentional sets that might characterize meditation, dissociative states, flow states, and other states of mind.