ArticleBehavioural brain research2016
Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data.
Article in Behavioural brain research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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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.
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Who cites it
30 citing papers in PubMed.
- The relationship between duration of access to intravenous oxycodone self-administration, economic demand for oxycodone, and cognition in rats.Psychopharmacology · 2026Article
- The relationship between duration of access to intravenous oxycodone self-administration, economic demand for oxycodone, and cognition in rats.Research square · 2026Article
- The relationship between regular substance use and cost comparisons in stable and volatile learning contexts.Translational psychiatry · 2026Article
- The role of the prefrontal cortex in cocaine-induced noradrenaline release in the nucleus accumbens: a computational study.Biological cybernetics · 2025Article
- Dissociating social reward learning and behavior in alcohol use disorder.Translational psychiatry · 2025Article
- Neural Correlates of Metacognition Impairment in Opioid Addiction.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2024Article
- The Neural Correlates of Individual Differences in Reinforcement Learning during Pain Avoidance and Reward Seeking.eNeuro · 2024Article
- Negative valuation of ambiguous feedback may predict near-term risk for suicide attempt in Veterans at high risk for suicide.Frontiers in psychiatry · 2024Article
- Active learning impairments in substance use disorders when resolving the explore-exploit dilemma: A replication and extension of previous computational modeling results.Drug and alcohol dependence · 2023Article
- Active learning impairments in substance use disorders when resolving the explore-exploit dilemma: A replication and extension of previous computational modeling results.medRxiv : the preprint server for health sciences · 2023Article
- Computational models of exploration and exploitation characterise onset and efficacy of treatment in methamphetamine use disorder.Addiction biology · 2022Article
- Computational analysis of probabilistic reversal learning deficits in male subjects with alcohol use disorder.Frontiers in psychiatry · 2022Article
- Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders.Frontiers in psychiatry · 2022Review
- Behavioral Analysis of EEG Signals in Loss-Gain Decision-Making Experiments.Behavioural neurology · 2022Article
- Computational theory-driven studies of reinforcement learning and decision-making in addiction: What have we learned?Current opinion in behavioral sciences · 2021Article
- The Role of User Behaviour in Improving Cyber Security Management.Frontiers in psychology · 2021Review
- Imprecise action selection in substance use disorder: Evidence for active learning impairments when solving the explore-exploit dilemma.Drug and alcohol dependence · 2020Article
- A reinforcement-learning model of active avoidance behavior: Differences between Sprague Dawley and Wistar-Kyoto rats.Behavioural brain research · 2020Article
- Males are more sensitive to reward and less sensitive to loss than females among people with internet gaming disorder: fMRI evidence from a card-guessing task.BMC psychiatry · 2020Article
- Computational Markers of Risky Decision-making for Identification of Temporal Windows of Vulnerability to Opioid Use in a Real-world Clinical Setting.JAMA psychiatry · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals' performance on the task. Although behavioral results showed that opioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to "chase reward" when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction.
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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.