ArticleBiological psychiatry. Cognitive neuroscience and neuroimaging2018
Impaired Expected Value Computations Coupled With Overreliance on Stimulus-Response Learning in Schizophrenia.
Article in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Arousal shapes motivation: an integrative framework for understanding motivational deficits.Translational psychiatry · 2026Review
- How working memory and reinforcement learning interact when avoiding punishment and pursuing reward concurrently.Journal of experimental psychology. General · 2025Article
- The joint estimation of uncertainty and its relationship with psychotic-like traits and psychometric schizotypy.Npj mental health research · 2025Article
- A generalized reward processing deficit pathway to negative symptoms across diagnostic boundaries.Psychological medicine · 2025Article
- Partially Observable Predictor Models for Identifying Cognitive Markers.Computational brain & behavior · 2025Article
- The challenge of learning adaptive mental behavior.Journal of psychopathology and clinical science · 2024Article
- From Computation to Clinic.Biological psychiatry global open science · 2023Review
- Using Computational Modeling to Capture Schizophrenia-Specific Reinforcement Learning Differences and Their Implications on Patient Classification.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022Article
- Reduced learning bias towards the reward context in medication-naive first-episode schizophrenia patients.BMC psychiatry · 2022Article
- Reinforcement-learning in fronto-striatal circuits.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Review
- Hot and cold cognitive disturbances in antidepressant-free patients with major depressive disorder: a NeuroPharm study.Psychological medicine · 2021Article
- Computational approaches and machine learning for individual-level treatment predictions.Psychopharmacology · 2021Review
- Retention of Value Representations Across Time in People With Schizophrenia and Healthy Control Subjects.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2021Article
- High-frequency neuromodulation improves obsessive-compulsive behavior.Nature medicine · 2021Article
- Mechanisms Underlying Motivational Dysfunction in Schizophrenia.Frontiers in behavioral neuroscience · 2021Review
- Impaired Expected Value Computations in Schizophrenia Are Associated With a Reduced Ability to Integrate Reward Probability and Magnitude of Recent Outcomes.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2019Article
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Authors and funding
4 authors.
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Abstract
backgroundWhile many have emphasized impaired reward prediction error signaling in schizophrenia, multiple studies suggest that some decision-making deficits may arise from overreliance on stimulus-response systems together with a compromised ability to represent expected value. Guided by computational frameworks, we formulated and tested two scenarios in which maladaptive representations of expected value should be most evident, thereby delineating conditions that may evoke decision-making impairments in schizophrenia.
methodsIn a modified reinforcement learning paradigm, 42 medicated people with schizophrenia and 36 healthy volunteers learned to select the most frequently rewarded option in a 75-25 pair: once when presented with a more deterministic (90-10) pair and once when presented with a more probabilistic (60-40) pair. Novel and old combinations of choice options were presented in a subsequent transfer phase. Computational modeling was employed to elucidate contributions from stimulus-response systems (actor-critic) and expected value (Q-learning).
resultsPeople with schizophrenia showed robust performance impairments with increasing value difference between two competing options, which strongly correlated with decreased contributions from expected value-based learning (Q-learning). Moreover, a subtle yet consistent contextual choice bias for the probabilistic 75 option was present in people with schizophrenia, which could be accounted for by a context-dependent reward prediction error in the actor-critic.
conclusionsWe provide evidence that decision-making impairments in schizophrenia increase monotonically with demands placed on expected value computations. A contextual choice bias is consistent with overreliance on stimulus-response learning, which may signify a deficit secondary to the maladaptive representation of expected value. These results shed new light on conditions under which decision-making impairments may arise.
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