ReviewBehavioural brain research2018
Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.
Review in Behavioural brain research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Altered value-based decision-making in anorexia nervosa: A systematic review.Neuroscience and biobehavioral reviews · 2024Pooled it
- Neural signatures of risk-taking adaptions across health, bipolar disorder, and lithium treatment.Molecular psychiatry · 2025Trial
- Hippocampal-cingulate dynamics in the human brain link reinforcement-learning and memory.bioRxiv : the preprint server for biology · 2026Article
- Humans are more prosocial in poor foraging environments.Nature communications · 2026Article
- From symptom-based heterogeneity to mechanism-based profiling in youth ADHD: the promise of computational psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- Complex functions of human lateral frontopolar cortex.Brain : a journal of neurology · 2025Review
- Computational mechanisms underlying the impact of Pavlovian bias on instrumental learning in problematic social media users.Journal of behavioral addictions · 2025Article
- Emotions and individual differences shape human foraging under threat.Nature. Mental health · 2025Article
- The future of transcranial ultrasound as a precision brain interface.PLoS biology · 2024Article
- Naturalistic reinforcement learning.Trends in cognitive sciences · 2024Review
- Decomposing decision-making in preschoolers: Making decisions under ambiguity versus risk.PloS one · 2024Article
- State-transition-free reinforcement learning in chimpanzees (Pan troglodytes).Learning & behavior · 2023Article
- Interindividual Brain and Behavior Differences in Adaptation to Unexpected Uncertainty.Biology · 2023Article
- Modulation of ventromedial orbitofrontal cortical glutamatergic activity affects the explore-exploit balance and influences value-based decision-making.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- A neural and behavioral trade-off between value and uncertainty underlies exploratory decisions in normative anxiety.Molecular psychiatry · 2022Article
- The effect of apathy and compulsivity on planning and stopping in sequential decision-making.PLoS biology · 2022Article
- Computational Psychiatry Needs Time and Context.Annual review of psychology · 2022Review
- Computational modelling of social cognition and behaviour-a reinforcement learning primer.Social cognitive and affective neuroscience · 2021Article
- Article
- Recent updates of eye movement abnormalities in patients with schizophrenia: A scoping review.Psychiatry and clinical neurosciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders.
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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.