Delusional unreality and predictive processing

Abstract

In their recent correspondence Feyearts and colleagues highlighted some similarities and differences between their phenomenological approach to delusions and the predictive processing explanation. In the present work we home in on some key points in the exchange and present data that show predictive processing can indeed explain the pervasive sense of unreality that characterizes some delusions (but by no means all of them). Indeed, our data show that some people with delusions and schizophrenia do not report a sense of unreality, and, furthermore, that some people with extreme esoteric beliefs (but no psychotic illness) also report a pervasive sense of unreality. Notably, no healthy control endorsed a sense of unreality (despite endorsing other delusion-like beliefs). By leveraging computational psychiatry, applied to behavioral data gathered during causal learning, we show that unreality experiences in clinical delusions and non-clinical delusion-like beliefs are associated with different types of aberrant prediction errors, prediction error weightings, and learning rates. Taken together, these data suggest that claims of distinction between predictive processing and phenomenological accounts, and that predictive processing cannot explain the sense of unreality, may have been premature. Furthermore, sense of unreality is not pathognomonic of delusion. Finally, these data suggest again that different patterns of prediction error dysfunction are associated with delusions and delusion-like beliefs with different contents, extending recent work to a belief unexamined through predictive processing: delusional unreality