Probabilistic reasoning in schizophrenia is volatile but not biased

Abstract

We update our beliefs based on evidence. Aberrant belief updating has been linked to schizophrenia and autism. It is not clear whether the faulty updating is due to reducedgeneral cognitive abilities, overweighting of recent information, or lower thresholds for switching from one belief to another. A common task to assess belief updating isthe beads task. Patients with schizophrenia show hasty decision-making.We here present a model describing the deviations from an ideal Bayesian observer and apply the model to three independent datasets, totalling n=176 healthy controlsand n=128 patients with schizophrenia. The parameters describe a) the number of beads considered (memory), b) systematic deviation and c) unsystematic deviations (volatility) from probability estimates.We find that, on average, patients use fewer beads and or more volatile responding. However, patients have, on average, probability estimates that are closer to the true probabilities. Closer investigations yielded relevant differences among the datasets and sequences used. Morechallenging sequences improve the performance of patients.Our model captures well the cognitive mechanisms proposed to contribute to the performance differences in the beads task.