Despite advances in the computational study of perception, there has been remarkably little progress in understanding perceptual abnormalities like hallucinations. In recent work, we identified abnormalities in information processing that underlie hallucinations using cutting-edge computational modeling of perception. We adopted a hierarchical Bayesian framework, which views perception as a constructive process wherein prior knowledge of the environment is combined with incoming sensory information to build an internal representation of one?s surroundings. The weight each of these sources exerts during perception is dependent upon its precision (or reliability). Thus, within this framework, hallucinations?percepts in the absence of corresponding incoming sensory evidence?may arise from an over-weighting of prior knowledge in comparison to incoming sensory evidence. To demonstrate this, we used classical conditioning to safely and reversibly induce hallucinations of simple tones in those both with and without auditory verbal hallucinations (AVH). Those with AVH were roughly five times more susceptible to this Conditioned Hallucinations effect because of a tendency to weigh prior knowledge more than incoming sensory information during perception. This relative weighting of priors versus sensory evidence during perception depends critically on cholinergic signaling: acetylcholine biases perceptual inference toward sensory data and away from priors. Thus, in voice- hearers with abnormally high prior weighting, enhancing cholinergic signaling could result in fewer hallucinations. We propose to characterize the effects of cholinergic signaling on the perceptual, computational, physiological, and clinical signatures of hallucinations. Principally, we hypothesize that: 1) Decreasing cholinergic tone with scopolamine (an M1 cholinergic receptor antagonist) in healthy participants will result in exhibit higher prior weighting, more conditioned hallucinations, and more prior-related brain activity compared to placebo; 2) Increasing cholinergic tone with IV physostigmine (a reversible, centrally-acting cholinesterase inhibitor) in patients with daily hallucinations will result in decreases in prior weighting, conditioned hallucinations, and clinical hallucinations compared to placebo; and 3) These effects will depend on the existence of high prior weighting at baseline assessment. Our goal is use the knowledge generated to take the first steps toward a computationally-informed, personalized treatment approach to hallucinations.
Auditory hallucinations are among the most distressing aspects of psychotic illness, and between 10 and 30% of people with hallucinations do not respond to antipsychotic medications. We have used computational modeling of behavior to link brain activity to development of auditory hallucinations in the hope of guiding new treatment development. The proposed studies take the first step toward individualized treatment approaches to hallucinations by attempting causal, pharmacological manipulation of relevant model parameters underlying these phenomena.