Psychotic Experiences in Schizophrenia and Sensitivity to Sensory Evidence

Abstract

Perceptual inference depends on an optimal integration of current sensory evidence with prior beliefs about the environment. Alterations of this process have been related to the emergence of positive symptoms in schizophrenia. However, it has remained unclear whether delusions and hallucinations arise from an increased or decreased weighting of prior beliefs relative to sensory evidence. To investigate the relation of this prior-to-likelihood ratio to positive symptoms in schizophrenia, we devised a novel experimental paradigm which gradually manipulates perceptually ambiguous visual stimuli by disambiguating stimulus information. As a proxy for likelihood precision, we assessed the sensitivity of individual participants to sensory evidence. As a surrogate for the precision of prior beliefs in perceptual stability, we measured phase duration in ambiguity. Relative to healthy controls, patients with schizophrenia showed a stronger increment in congruent perceptual states for increasing levels of disambiguating stimulus evidence. Sensitivity to sensory evidence correlated positively with the individual patients' severity of perceptual anomalies and hallucinations. Moreover, the severity of such experiences correlated negatively with phase duration. Our results indicate that perceptual anomalies and hallucinations are associated with a shift of perceptual inference toward sensory evidence and away from prior beliefs. This reduced prior-to-likelihood ratio in sensory processing may contribute to the phenomenon of aberrant salience, which has been suggested to give rise to the false inferences underlying psychotic experiences.

Keywords: Bayesian perceptual inference; bistable perception; predictive coding; psychosis.

Fig. 1.

The prior-to-likelihood ratio in Bayesian perceptual inference. Perceptual inference depends on the ratio of prior and likelihood precision. (A) Here, we depict a reference scenario with optimal precision estimates (Gaussian distributions, variance in white, mean of the posterior in black). (B) Changes in these estimates of precision may lead to alterations in perception. In case of an overestimation of prior precision and/or underestimation of likelihood precision, the posterior is shifted toward the prior. (C) By analogy, an overestimation of likelihood precision and/or underestimation of prior precision is associated with a shift of the posterior toward the likelihood.

Fig. 2.

Behavioral experiment. (A) In the main experiment, we measured the individual participants’ sensitivity to disambiguating stimulus evidence as a proxy for the prior-to-likelihood ratio. To visualize relevant variables, the lower panel displays typical perceptual responses in an ambiguous block and the corresponding partially disambiguated block. (B) To probe potential differences in stereovision, we determined individual stereo-disparity thresholds in an independent stereoacuity test.

Fig. 3.

Sensitivity to disambiguating stimulus evidence. We depict the fraction of congruency between perceptual states and sensory evidence across the levels of disambiguating stimulus evidence (D1–D7, left panel). Error bars represent the respective standard error of the mean. The nlme model yielded a main effect of disambiguating stimulus evidence [F(6) = 15.16, P = 6.44 × 10⁻¹⁵], and a significant interaction between the diagnostic group and the disambiguating stimulus evidence [F(6) = 2.52, P = .02]. The left panel shows the implicit interaction between levels of disambiguating stimulus evidence and diagnostic group: At low levels of disambiguation (D1–D3), controls exhibit a marginally higher proportion of congruent perceptual states. This is reversed for higher levels of disambiguating stimulus evidence (D4–D7), where patients show a greater proportion of congruency. We used the growth rate of individual exponential fits to the fraction of congruent perceptual states to express the individual sensitivities to disambiguating stimulus evidence during graded ambiguity (right panel; horizontal lines point to sample means; vertical line spans over the 95% CI). Bootstrapping revealed a borderline-significant between-group difference (estimated 95% CI = 0.004 to −0.08).

Fig. 4.

Individual symptom severity. Here, we depict the individual patients’ symptom severity with regard to perceptual anomalies (CAPS, top) and hallucination (P3, bottom) against the sensitivity to stimulus evidence (left) and phase duration (right) alongside regression lines (black) and 95% CI (light gray).