Anomalies in effective connectivity explain different hallucination subtypes in Parkinson’s disease psychosis

Psychosis and visual hallucinations (VH) in Parkinson’s disease (PD) significantly impact patient outcomes, yet underlying neural mechanisms remain unclear, limiting effective treatments. Here, we used dynamic causal modelling (DCM) to leverage the fast temporal dynamics captured with EEG data during a visual mismatch negativity task in PD patients with (N = 20) and without (N = 18) VH to examine effective connectivity. We found reduced top-down and enhanced bottom-up connectivity in ventral visual and prefrontal regions during task performance in PD-VH, suggesting deficits in sensory prediction updating and an over-reliance on visual input. Connectivity patterns differed with hallucination complexity: minor VH related to left hemisphere deficits, complex VH to altered top-down and bottom-up right-hemisphere connectivity, and multimodal hallucinations to widespread bilateral disruption. Increased task activity as computed with source reconstruction correlated positively with cortical 5-HT2A receptor distribution. These findings highlight specific neural targets for early therapeutic interventions, supporting a transdiagnostic computational architecture of hallucinations.