Many neuropsychiatric illnesses are associated with psychosis, i.e., hallucinations (perceptions in the absence of causative stimuli) and delusions (irrational, often bizarre beliefs). Current models of brain function view perception as a combination of two distinct sources of information: bottom-up sensory input and top-down influences from prior knowledge. This framework may explain hallucinations and delusions. Here, we characterized the balance between visual bottom-up and top-down processing in people with early psychosis (study 1) and in psychosis-prone, healthy individuals (study 2) to elucidate the mechanisms that might contribute to the emergence of psychotic experiences. Through a specialized mental-health service, we identified unmedicated individuals who experience early psychotic symptoms but fall below the threshold for a categorical diagnosis. We observed that, in early psychosis, there was a shift in information processing favoring prior knowledge over incoming sensory evidence. In the complementary study, we capitalized on subtle variations in perception and belief in the general population that exhibit graded similarity with psychotic experiences (schizotypy). We observed that the degree of psychosis proneness in healthy individuals, and, specifically, the presence of subtle perceptual alterations, is also associated with stronger reliance on prior knowledge. Although, in the current experimental studies, this shift conferred a performance benefit, under most natural viewing situations, it may provoke anomalous perceptual experiences. Overall, we show that early psychosis and psychosis proneness both entail a basic shift in visual information processing, favoring prior knowledge over incoming sensory evidence. The studies provide complementary insights to a mechanism by which psychotic symptoms may emerge.visual perception | psychosis | top-down processing | predictive coding | schizophrenia

isrctn.org Identifier: ISRCTN78923965.

AbstractThe study of the brain’s processing of sensory inputs from within the body (‘interoception’) has been gaining rapid popularity in neuroscience, where interoceptive disturbances have been postulated to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity (accuracy), decision bias, metacognitive bias, and metacognitive performance. We describe a task that is tailored to methods for assessing respiratory interoceptive accuracy and metacognition, and pair this with an established hierarchical statistical model of metacognition (HMeta-d) to overcome significant challenges associated with the low trial numbers often present in interoceptive experiments. Two major new developments have been incorporated into this task analysis by pairing: (i) an adaptive algorithm to maintain task performance at 70-75% accuracy, and (ii) an extended metacognitive model developed to hierarchically estimate multiple regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of both developments, using both simulated and empirical data from three separate studies. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with the practical constraints in clinical settings.

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