Beliefs and the brain: understanding hallucinations and delusions through predictive coding
Assistant Professor in Psychiatry, Yale School of Medicine
The problem of whether and how information is integrated across hierarchical brain networks embodies a fundamental tension in contemporary cognitive neuroscience, and by extension, cognitive neuropsychiatry. Indeed, the penetrability of perceptual processes in a ‘top-down’ manner by higher-level cognition—a natural extension of hierarchical models of perception—may contradict a strictly modular view of mental organization. Furthermore, some in the cognitive science community have challenged cognitive penetration as an unlikely, if not impossible, process. I will present behavioral and functional imaging evidence that perception is penetrated by top-down expectation and that hallucinations, the percepts without stimulus that characterize serious mental illnesses like schizophrenia are associated with excessively strong top-down expectation. This is the case in patients with a psychotic disorder as well as healthy voice hearers. However, patients without voices and matched controls do not show the effect. Indeed, people with delusions may be protected from the effect. I will discuss these findings in the context of predictive coding accounts of symptoms, and data linking delusions to weak conceptual priors. I will conclude that our data defy a simple explanation in terms of weaker priors in schizophrenia. Rather, the hierarchical level of a deficit may be crucial and the relationships between lower level sensory prediction errors and top down priors (mediated by their precision) may well govern whether a particular network disruption manifests as a hallucination or delusion and will contribute to the contents of the symptom.