ArticleJournal of psychopathology and clinical science2025
Computational modeling of reversal learning impairments in schizophrenia and bipolar disorder reveals shared failure to exploit rewards.
Article in Journal of psychopathology and clinical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Beyond reward learning deficits: Exploration-exploitation instability reveals computational heterogeneity in value-based decision making in early psychosis.medRxiv : the preprint server for health sciences · 2025Article
- Transdiagnostic Predictors of Everyday Functioning: Examining the Relationships of Depression and Reinforcement Learning.Schizophrenia bulletin · 2023Article
- Test-retest reliability of computational parameters versus manifest behavior for decisional flexibility in psychosis.Psychological assessmentArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
The distinction between the concepts of schizophrenia and bipolar disorder is fundamental to the Kraepelinian tradition in psychiatry. One mechanism undergirding this distinction, a difference in reward sensitivity, has been championed by a number of scholars. As part of the Cognitive Neuroscience Test Reliability and Clinical applications for Serious mental illnesses consortium, 225 participants including people with schizophrenia (
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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.