The effects of base rate neglect on sequential belief updating and real-world beliefs

The parieto-occipital cortex is a candidate neural substrate for the human ability to approximate Bayesian inference

Adaptive decision-making often requires one to infer unobservable states based on incomplete information. Bayesian logic prescribes that individuals should do so by estimating the posterior probability by integrating the prior probability with new information, but the neural basis of this integration is incompletely understood. We record fMRI during a task in which participants infer the posterior probability of a hidden state while we independently modulate the prior probability and likelihood of evidence regarding the state; the task incentivizes participants to make accurate inferences and dissociates expected value from posterior probability. Here we show that activation in a region of left parieto-occipital cortex independently tracks the subjective posterior probability, combining its subcomponents of prior probability and evidence likelihood, and reflecting the individual participants' systematic deviations from objective probabilities. The parieto-occipital cortex is thus a candidate neural substrate for humans' ability to approximate Bayesian inference by integrating prior beliefs with new information.

Action prediction in psychosis

Aberrant motor-sensory predictive functions have been linked to symptoms of psychosis, particularly reduced attenuation of self-generated sensations and misattribution of self-generated actions. Building on the parallels between prediction of self- and other-generated actions, this study aims to investigate whether individuals with psychosis also demonstrate abnormal perceptions and predictions of others' actions. Patients with psychosis and matched controls completed a two-alternative object size discrimination task. In each trial, they observed reaching actions towards a small and a large object, with varying levels of temporal occlusion ranging from 10% to 80% of movement duration. Their task was to predict the size of the object that would be grasped. We employed a novel analytic approach to examine how object size information was encoded and read out across progressive levels of occlusion with single-trial resolution. Patients with psychosis exhibited an overall pattern of reduced and discontinuous evidence integration relative to controls, characterized by a period of null integration up to 20% of movement duration, during which they did not read any size information. Surprisingly, this drop in accuracy in the initial integration period was not accompanied by a reduction in confidence. Difficulties in action prediction were correlated with the severity of negative symptoms and impaired functioning in social relationships.

Hallucination-Proneness is Associated With a Decrease in Robust Averaging of Perceptual Evidence

BACKGROUND AND HYPOTHESIS

Hallucinations are characterized by disturbances in perceptual decision-making about environmental stimuli. When integrating across multiple stimuli to form a perceptual decision, typical observers engage in "robust averaging" by down-weighting extreme perceptual evidence, akin to a statistician excluding outlying data. Furthermore, observers adapt to contexts with more unreliable evidence by increasing this down-weighting strategy. Here, we test the hypothesis that hallucination-prone individuals (n = 38 high vs n = 91 low) would show a decrease in this robust averaging and diminished sensitivity to changes in evidence variance.

STUDY DESIGN

We used a multielement perceptual averaging task to elicit dichotomous judgments about the "average color" (red/blue) of an array of stimuli in trials with varied strength (mean) and reliability (variance) of decision-relevant perceptual evidence. We fitted computational models to task behavior, with a focus on a log-posterior-ratio (LPR) model which integrates evidence as a function of the log odds of each perceptual option and produces a robust averaging effect.

STUDY RESULTS

Hallucination-prone individuals demonstrated less robust averaging, seeming to weigh inlying and outlying extreme or untrustworthy evidence more equally. Furthermore, the model that integrated evidence as a function of the LPR of the two perceptual options and produced robust averaging showed poorer fit for the group prone to hallucinations. Finally, the weighting strategy in hallucination-prone individuals remained insensitive to evidence variance.

CONCLUSIONS

Our findings provide empirical support for theoretical proposals regarding evidence integration aberrations in psychosis and alterations in the perceptual systems that track statistical regularities in environmental stimuli.

A Distinct Neural Code Supports Prospection of Future Probabilities During Instrumental Information-Seeking

To make adaptive decisions, we must actively demand information, but relatively little is known about the mechanisms of active information gathering. An open question is how the brain estimates expected information gains (EIG) when comparing the current decision uncertainty with the uncertainty that is expected after gathering information. We examined this question using fMRI in a task in which people placed bids to obtain information in conditions that varied independently by prior decision uncertainty, information diagnosticity, and the penalty for an erroneous choice. Consistent with value of information theory, bids were sensitive to EIG and its components of prior certainty and expected posterior certainty. Expected posterior certainty was decoded above chance from multivoxel activation patterns in the posterior parietal and extrastriate cortices. This representation was independent of instrumental rewards and overlapped with distinct representations of EIG and prior certainty. Thus, posterior parietal and extrastriate cortices are candidates for mediating the prospection of posterior probabilities as a key step to estimate EIG during active information gathering.