The Predictive Coding Account of Psychosis

Abstract

Fueled by developments in computational neuroscience, there has been increasing interest in the underlying neuro-computational mechanisms of psychosis. One successful approach involves predictive coding and Bayesian inference. Here, inferences regarding the current state of the world are made by combining prior beliefs with incoming sensory signals. Mismatches between prior beliefs and incoming signals constitute prediction errors that drive new learning. Psychosis has been suggested to result from a decreased precision in the encoding of prior beliefs relative to the sensory data, thereby garnering maladaptive inferences. Here, we review the current evidence for aberrant predictive coding and discuss challenges for this canonical predictive coding account of psychosis. For example, hallucinations and delusions may relate to distinct alterations in predictive coding, despite their common co-occurrence. More broadly, some studies implicate weakened prior beliefs in psychosis, and others find stronger priors. These challenges might be answered with a more nuanced view of predictive coding. Different priors may be specified for different sensory modalities and their integration, and deficits in each modality need not be uniform. Furthermore, hierarchical organization may be critical. Altered processes at lower levels of a hierarchy need not be linearly related to processes at higher levels (and vice versa). Finally, canonical theories do not highlight active inference – the process through which the effects of our actions on our sensations are anticipated and minimized. It is possible that conflicting findings might be reconciled by considering these complexities, portending a framework for psychosis more equipped to deal with its many manifestations.

Ketamine Affects Prediction Errors about Statistical Regularities: A Computational Single-Trial Analysis of the Mismatch Negativity

“…The robust impairment of MMN in schizophrenia, and the fact that a similar MMN reduction can be achieved with NMDAR antagonists like ketamine, are in line with the long-standing notion that the pathophysiology of schizophrenia involves NMDAR dysfunction, leading to both cognitive and perceptual abnormalities and positive symptoms (16)(17)(18)(19)(20)(21)(22). This has been interpreted as an impairment of perceptual inference under a predictive coding view.…”

“…Current theories of schizophrenia conceptualize psychotic symptoms as disturbed hierarchical Bayesian inference, characterized by an imbalance in the relative weight (precision) assigned to prior beliefs (or predictions) and new sensory information that elicits PEs (18,19,22).…”

Evaluating the neurophysiological evidence for predictive processing as a model of perception

“…Although this represents a considerable challenge using conventional paradigms and neurophysiological techniques, methodological advances in highresolution fMRI, optogenetics, calcium imaging, and serial single-unit recordings at multiple levels of the processing hierarchy are providing powerful new opportunities to trace neural markers of hierarchical PP dynamics. 41,128,158,196,209,210 Pairing these increasingly sophisticated neural assays with anatomical models, computational modeling, and simulations 137,211 will enable researchers to derive fine-grained a priori hypotheses and compare model evidence for variant architectures and also for near-variant ones that share much with the core PP picture but differ in their conceptions of the encoding, flow, or use of prediction errors (e.g., Refs. 2, 10 and 11; see Ref.…”

Auditory predictions and prediction errors in response to self-initiated vowels

“…To explain self-produced action, such as speech, current accounts treat motor commands as predictions of proprioceptive and somatosensory consequences of an intended act, while the efference copy or corollary discharge corresponds to the predictions in the exteroceptive (e.g. auditory or visual) domain (Sterzer et al, 2018). Crucially, to act, it is necessary to attenuate the gain or precision of ascending prediction errors.…”