Altered probabilistic learning and response biases in schizophrenia: Behavioral evidence and neurocomputational modeling.
Open accessAbstract
OBJECTIVE: Patients with schizophrenia (SZ) show reinforcement learning impairments related to both the gradual/procedural acquisition of reward contingencies, and the ability to use trial-to-trial feedback to make rapid behavioral adjustments. METHOD: We used neurocomputational modeling to develop plausible mechanistic hypotheses explaining reinforcement learning impairments in individuals with SZ. We tested the model with a novel Go/NoGo learning task in which subjects had to learn to respond or withhold responses when presented with different stimuli associated with different probabilities of gains or losses in points. We analyzed data from 34 patients and 23 matched controls, characterizing positive- and negative-feedback-driven learning in both a training phase and a test phase. RESULTS: Consistent with simulations from a computational model of aberrant dopamine input to the basal ganglia patients, patients with SZ showed an overall increased rate of responding in the training phase, together with reduced response-time acceleration to frequently rewarded stimuli across training blocks, and a reduced relative preference for frequently rewarded training stimuli in the test phase. Patients did not differ from controls on measures of procedural negative-feedback-driven learning, although patients with SZ exhibited deficits in trial-to-trial adjustments to negative feedback, with these measures correlating with negative symptom severity. CONCLUSIONS: These findings support the hypothesis that patients with SZ have a deficit in procedural "Go" learning, linked to abnormalities in DA transmission at D1-type receptors, despite a "Go bias" (increased response rate), potentially related to excessive tonic dopamine. Deficits in trial-to-trial reinforcement learning were limited to a subset of patients with SZ with severe negative symptoms, putatively stemming from prefrontal cortical dysfunction.
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Some studies found that individuals with schizophrenia are impaired during reward motivation and outcome, while others did not find a selective impairment in reward motivation.
“Although some studies have found that individuals with schizophrenia are impaired during reward motivation and outcome [403-407], others have not found a selective impairment in reward motivation [386,408].”
From Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings (2012) · cites this paper as [406]
Reward-processing deficits in schizophrenia are consistent with impaired functioning of DA.
“Waltz et al. [406] used computer simulations to show that the reward-processing deficits in schizophrenia are consistent with impaired functioning of DA.”
From Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings (2012) · cites this paper as [406]
Behavioral studies report that sensitivity to reward is intact in schizophrenia, but deficits are evident in rapid reward learning on trial-to-trial feedback, such as reversal learning, and in reward-related decision-making.
“Behavioral studies of reward learning have reported that sensitivity to reward is intact in schizophrenia, but deficits are evident in rapid reward learning on the basis of trial-to-trial feedback, such as reversal learning, and in reward-related decision-making [406,409-413].”
From Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings (2012) · cites this paper as [406]
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References 71 · Cited by 132
- Authors
- Waltz, J. A., Frank, M. J., Wiecki, T. V., & Gold, J. M.
- Affiliations
- University of Maryland, Baltimore (US)
- Brown University (US)
- Venue
- Neuropsychology
- Published
- 2011
- Volume
- 25
- Issue
- 1
- Pages
- 86-97
- ISSN
- 0894-4105 (ISSN-L)
- 1931-1559
- PMC
- PMC3050485
- OpenAlex
- W2096070994
- Cited by
- 132
- References
- 71
- Citations by year
- 2026: 6 · 2025: 4 · 2023: 6 · 2022: 10 · 2021: 9 · 2020: 9 · 2019: 4 · 2018: 12 · 2017: 9 · 2016: 14 · 2015: 17 · 2014: 10 · 2013: 12 · 2012: 6
- FWCI
- 4.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neuropsychology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01mh080066-10)
- National Institute of Mental Health (R01-MH080066, R24MH072647)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- schizophrenia, reinforcement learning, probabilistic learning, response bias, dopamine, basal ganglia, dopamine D1 receptor, tonic dopamine, negative symptoms, feedback-driven learning, prefrontal cortex, neurocomputational model
- MeSH terms
- Adult, Analysis of Variance, Choice Behavior, Computer Simulation, Female, Humans, Male, Middle Aged, Models, Neurological, Neuropsychological Tests, Probability Learning, Psychiatric Status Rating Scales, Reaction Time, Reinforcement, Psychology, Schizophrenia, Schizophrenic Psychology, Statistics as Topic, Bias
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