ReviewNature reviews. Neuroscience2019
Adaptive learning under expected and unexpected uncertainty.
Review in Nature reviews. Neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 155 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
155 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Brain and Cognitive Development in Adolescents with Anorexia Nervosa: A Systematic Review of fMRI Studies.Nutrients · 2019Pooled it
- Prior Expectations of Volatility Following Psychotherapy for Delusions: A Randomized Clinical Trial.JAMA network open · 2025Trial
- Evolution of behavioral flexibility and the forming and breaking of habits.Evolution letters · 2026Article
- Article
- Posterior parietal cortex mediates rarity-induced decision bias.National science review · 2026Article
- Reward-induced endogenous pain inhibition scales with action-outcome certainty in humans.Pain · 2026Article
- Modality-general sensitivity of pupil responses to regularity violations.Cognitive, affective & behavioral neuroscience · 2026Article
- An effort recalibration framework for digital media use and cognition.Nature human behaviour · 2026Review
- Orbitofrontal noradrenaline supports adaptive learning-rate adjustment in probabilistic reversal learning.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Dissociating volatility and stochasticity reveals transdiagnostic computational signatures of psychopathology.bioRxiv : the preprint server for biology · 2026Article
- Article
- Adaptive reorganization of history encoding in the retrosplenial cortex supports flexible decision-making strategies.Neuron · 2026Article
- Regime shift detection and neurocomputational substrates for under and overreactions to change.eLife · 2026Article
- Environmental uncertainty shapes human effort learning.PLoS biology · 2026Article
- Acetylcholine demixes heterogeneous dopamine signals for learning and moving.Nature neuroscience · 2026Article
- Anterior cingulate neurons combine outcome monitoring of past decisions with ongoing movement signals.Nature communications · 2026Article
- Persistent representation of a prior schema in the orbitofrontal cortex facilitates learning of a conflicting schema.Nature communications · 2026Article
- Uncertainty and reward histories have distinct effects on decisions after wins and losses.Scientific reports · 2026Article
- Discovery, Interruption, and Updating of Auditory Regularities in Memory: Evidence from Low-Frequency Brain Dynamics in Human MEG.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Transforming uncertainty into exploration: effects of text-to-image AI on EFL learners' writing anxiety, motivation, and performance.Frontiers in psychology · 2026Article
95 more citing papers are in PubMed but not listed here.
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
The outcome of a decision is often uncertain, and outcomes can vary over repeated decisions. Whether decision outcomes should substantially affect behaviour and learning depends on whether they are representative of a typically experienced range of outcomes or signal a change in the reward environment. Successful learning and decision-making therefore require the ability to estimate expected uncertainty (related to the variability of outcomes) and unexpected uncertainty (related to the variability of the environment). Understanding the bases and effects of these two types of uncertainty and the interactions between them - at the computational and the neural level - is crucial for understanding adaptive learning. Here, we examine computational models and experimental findings to distil computational principles and neural mechanisms for adaptive learning under uncertainty.
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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.