Psychotic symptoms, including hallucinations, delusions, and disorganized thought, occur across psychiatric and neurological disorders, yet their underlying mechanisms remain poorly integrated across scales. Here, we propose a transdiagnostic framework in which disturbances in dopamine, glutamate, GABA, serotonin, and acetylcholine alter neuronal gain and synaptic efficacy, disrupting the precision weighting of sensory evidence, prediction errors, and internally generated representations. These local disturbances propagate through cortico-striato-thalamo-cortical circuits and large-scale functional networks, producing abnormal integration-segregation dynamics and unstable attractor states. This multilevel model links molecular and cellular perturbations to circuit dysfunction, network instability, and symptom expression while allowing distinct biological pathways to converge on shared computational vulnerabilities. Emerging neuroimaging, dynamical systems, and artificial intelligence approaches may enable individualized tests of these mechanisms and support more precise, circuit-informed interventions for psychotic symptoms.
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Braun et al. (2026) studied this question.
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