Visual hallucinations are characterized by impaired sensory evidence accumulation : insights from hierarchical drift diffusion modelling in Parkinson’s disease

Claire O'Callaghan, Julie M. Hall, Alessandro Tomassini, Alana J. Muller, Ishan C. Walpola, Ahmed A. Moustafa, James M. Shine, Simon J. G. Lewis

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)

Abstract

Background: Models of hallucinations emphasise an imbalance between sensory input and top-down influences over perception, as false perceptual inference can arise when top-down predictions are afforded too much precision (certainty) relative to sensory evidence. Visual hallucinations in Parkinson’s disease (PD) are associated with lower-level visual and attentional impairments, accompanied by over activity in higher-order association brain networks. PD therefore provides an attractive framework to explore the contributions of bottom-up versus top-down disturbances in hallucinations. Methods: We characterised sensory processing during perceptual decision-making in PD patients with (n=20) and without (n=25) visual hallucinations, and controls (n=12), by fitting a hierarchical drift diffusion model (hDDM) to an attentional task. The hDDM uses Bayesian estimates to decompose task performance into parameters reflecting drift rates of evidence accumulation, decision thresholds and non-decision time. Results: We observed slower drift rates in patients with hallucinations, which were less sensitive to changes in task demand. In contrast, wider decision boundaries and shorter non decision times relative to controls were found in PD regardless of hallucinator status. Inefficient and less flexible sensory evidence accumulation emerge as unique features of PD hallucinators. Conclusions: We integrate these results with evidence accumulation and predictive coding models of hallucinations, suggesting that in PD sensory evidence is less informative, and may therefore be down-weighted resulting in over reliance on top-down influences. Considering impaired drift rates as an approximation of reduced sensory precision, our findings provide a novel computational framework to specify the impairments in sensory processing that contribute to the development of visual hallucinations.
Original languageEnglish
Pages (from-to)680-688
Number of pages9
JournalBiological Psychiatry: Cognitive Neuroscience and Neuroimaging
Volume2
Issue number8
DOIs
Publication statusPublished - 2017

Keywords

  • Bayesian statistical decision theory
  • Parkinson's disease
  • hallucinations and illusions
  • perception

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