ArticleComputational psychiatry (Cambridge, Mass.)2022
Slower Learning Rates from Negative Outcomes in Substance Use Disorder over a 1-Year Period and Their Potential Predictive Utility.
Article in Computational psychiatry (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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Who cites it
16 citing papers in PubMed.
- Computational mechanisms of learning and forgetting differentiate affective and substance use disorders.Molecular psychiatry · 2026Article
- The relationship between regular substance use and cost comparisons in stable and volatile learning contexts.Translational psychiatry · 2026Article
- Attenuated learning rates for negative outcomes in substance use disorders: A replication and extension of prior longitudinal computational modeling results.Drug and alcohol dependence · 2026Article
- A computational mechanism linking momentary craving and decision-making in alcohol drinkers and cannabis users.Nature. Mental health · 2026Article
- Individuals with methamphetamine use disorder show reduced directed exploration and learning rates independent of an aversive interoceptive state induction.Communications psychology · 2025Article
- Deep computational neurophenomenology: a methodological framework for investigating the how of experience.Neuroscience of consciousness · 2025Article
- Transdiagnostic failure to adapt interoceptive precision estimates across affective, substance use, and eating disorders: A replication and extension of previous results.Biological psychology · 2024Article
- Test-retest reliability of behavioral and computational measures of advice taking under volatility.PloS one · 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
- Barriers and solutions to the adoption of translational tools for computational psychiatry.Molecular psychiatry · 2023Review
- Reward Maximization Through Discrete Active Inference.Neural computation · 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
- Active inference and the two-step task.Scientific reports · 2022Article
- From Generative Models to Generative Passages: A Computational Approach to (Neuro) Phenomenology.Review of philosophy and psychology · 2022Article
- Test-retest reliability of computational parameters versus manifest behavior for decisional flexibility in psychosis.Psychological assessmentArticle
- Elevated decision uncertainty and reduced avoidance drives in depression, anxiety and substance use disorders during approach-avoidance conflict: a replication study.Journal of psychiatry & neuroscience : JPNArticle
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Computational modelling is a promising approach to parse dysfunctional cognitive processes in substance use disorders (SUDs), but it is unclear how much these processes change during the recovery period. We assessed 1-year follow-up data on a sample of treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, hallucinogens, and/or opioids;
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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.