Prediction error, ketamine and psychosis: an updated model
Corlett, Philip R
Honey, Garry D
Predictive processing, ketamine and psychosis
Journal of Psychopharmacology
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Corlett, P. R., Honey, G. D., & Fletcher, P. (2016). Prediction error, ketamine and psychosis: an updated model. Journal of Psychopharmacology https://www.repository.cam.ac.uk/handle/1810/255854
In 2007, we proposed an explanation of delusion formation as aberrant prediction error-driven associative learning. Further, we argued that the NMDA receptor antagonist ketamine provided a good model for this process. Subsequently, we validated the model in patients with psychosis, relating aberrant prediction error signals to delusion severity. During the ensuing period, we have developed these ideas, drawing on the simple principle that brains build a model of the world and refine it by minimizing prediction errors as well as using it to guide perceptual inferences. While previously we focused on the prediction error signal per se, an updated view takes into account its precision as well as the precision of prior expectations. With this expanded perspective, we see several possible routes to psychotic symptoms – which may explain the heterogeneity of psychotic illness as well as the fact that other drugs, with different pharmacological actions, can produce psychotomimetic effects. In this paper, we review the basic principles of this model and highlight specific ways in which prediction errors can be perturbed, in particular considering the reliability and uncertainty of predictions. The expanded model explains hallucinations as perturbations of the uncertainty mediated balance between expectation and prediction error. Here, expectations dominate and create perceptions by suppressing or ignoring actual inputs. Negative symptoms may arise due to poor reliability of predictions in service of action. By mapping from biology to belief and perception, the account proffers new explanations of psychosis. However challenges remain. We attempt to address some of these concerns and suggest future directions, incorporating other symptoms into the model, building towards better understanding of psychosis.
This work was supported by the Connecticut Mental Health Center (CMHC) and Connecticut State Department of Mental Health and Addiction Services (DMHAS). PRC was funded by an IMHRO / Janssen Rising Star Translational Research Award and CTSA Grant Number UL1 TR000142 from the National Center for Research Resources (NCRR) and the National Center for Advancing Translational Science (NCATS), components of the National Institutes of Health (NIH), and NIH roadmap for Medical Research. PCF is supported by the Wellcome Trust and the Bernard Wolfe Health Neuroscience Fund.
Wellcome Trust (093875/Z/10/Z)
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