ArticleComputational psychiatry (Cambridge, Mass.)2019
Cost Evaluation During Decision-Making in Patients at Early Stages of Psychosis.
Article in Computational psychiatry (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 28 citations in OpenAlex.
- Active information sampling in health and disease.Neuroscience and biobehavioral reviews · 2025Review
- Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- The Effect of Situational Experiment Conditions on Hasty Decision Making in the 'Beads Task'.Brain sciences · 2023Article
- Neural Circuitry of Salience and Reward Processing in Psychosis.Biological psychiatry global open science · 2023Review
- A Computational Analysis of Abnormal Belief Updating Processes and Their Association With Psychotic Experiences and Childhood Trauma in a UK Birth Cohort.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022Article
- Rethinking delusions: A selective review of delusion research through a computational lens.Schizophrenia research · 2022Review
- Jumping to conclusions, general intelligence, and psychosis liability: findings from the multi-centre EU-GEI case-control study.Psychological medicine · 2021Article
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- Cost Evaluation During Decision-Making in Patients at Early Stages of Psychosis.Computational psychiatry (Cambridge, Mass.) · 2019Article
- Action selection in early stages of psychosis: an active inference approach.Journal of psychiatry & neuroscience : JPNArticle
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 5 countries.
Funding
Abstract
Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modeling has provided evidence that patients with chronic schizophrenia jump to conclusions because of noisy decision-making. We developed a novel version of the classical beads task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of "draws to decision" when information sampling had no, a fixed, or an escalating cost. Computational modeling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall, patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block, participants sampled more information than an ideal Bayesian agent. Computational modeling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls did, Mann-Whitney
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.