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Hallucinations and a computationally-informed psychiatric nosology


Auditory verbal hallucinations (AVH) are among the most distressing symptoms in psychosis, and up to 30% of patients exhibit little to no response to current treatments. This is especially concerning given that the presence of hallucinations alone increases risk of suicide in patients with psychosis. Recent advances in computational psychiatry have identified latent cognitive and perceptual states that predispose to hallucinations. Behavioral data fit to Bayesian models have demonstrated an over-reliance on priors (i.e., prior over-weighting) during perception in select samples of individuals with hallucinations. Ongoing work demonstrates that this over-reliance reflects recent symptom severity, is sensitive to the sensory modalities affected, and may be impacted by environmental exposures known to increase risk for psychosis. Taken together, this work demonstrates the potential utility of formal mathematical frameworks for understanding the generation of symptoms in psychiatric illness.


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