ArticleCurrent opinion in behavioral sciences2016
Challenges and promises for translating computational tools into clinical practice.
Article in Current opinion in behavioral sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Better Than Maximum Likelihood Estimation of Model-based and Model-free Learning Styles.Basic and clinical neuroscience · 2025Article
- Computational analysis of antimicrobial peptides targeting key receptors in infection-related cardiovascular diseases: molecular docking and dynamics insights.Scientific reports · 2025Article
- Neuromodulation of risk and reward processing during decision making in individuals with general anxiety disorder (GAD).Scientific reports · 2025Article
- Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms.Cognitive, affective & behavioral neuroscience · 2023Article
- The Bayesian Mutation Sampler Explains Distributions of Causal Judgments.Open mind : discoveries in cognitive science · 2023Article
- Reliability of Decision-Making and Reinforcement Learning Computational Parameters.Computational psychiatry (Cambridge, Mass.) · 2023Article
- Deliberative and Affective Risky Decisions in Teenagers: Different Associations with Maladaptive Psychological Functioning and Difficulties in Emotion Regulation?Children (Basel, Switzerland) · 2022Article
- Article
- Longitudinal Study on Sustained Attention to Response Task (SART): Clustering Approach for Mobility and Cognitive Decline.Geriatrics (Basel, Switzerland) · 2022Article
- Shuffle the Decks: Children Are Sensitive to Incidental Nonrandom Structure in a Sequential-Choice Task.Psychological science · 2022Article
- What do Reinforcement Learning Models Measure? Interpreting Model Parameters in Cognition and Neuroscience.Current opinion in behavioral sciences · 2021Article
- SART and Individual Trial Mistake Thresholds: Predictive Model for Mobility Decline.Geriatrics (Basel, Switzerland) · 2021Article
- Rapid, precise, and reliable measurement of delay discounting using a Bayesian learning algorithm.Scientific reports · 2020Article
- A computational model of the Cambridge gambling task with applications to substance use disorders.Drug and alcohol dependence · 2020Article
- Challenges and recommendations to improve the installability and archival stability of omics computational tools.PLoS biology · 2019Article
- Impulsivities and addictions: a multidimensional integrative framework informing assessment and interventions for substance use disorders.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Review
- Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.PloS one · 2019Article
- The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task.Cognitive science · 2018Article
- Computational neuroscience across the lifespan: Promises and pitfalls.Developmental cognitive neuroscience · 2018Review
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Computational modeling and associated methods have greatly advanced our understanding of cognition and neurobiology underlying complex behaviors and psychiatric conditions. Yet, no computational methods have been successfully translated into clinical settings. This review discusses three major methodological and practical challenges (A. precise characterization of latent neurocognitive processes, B. developing optimal assays, C. developing large-scale longitudinal studies and generating predictions from multi-modal data) and potential promises and tools that have been developed in various fields including mathematical psychology, computational neuroscience, computer science, and statistics. We conclude by highlighting a strong need to communicate and collaborate across multiple disciplines.
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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.