ReviewNeuroscience and biobehavioral reviews2021
Adaptive learning is structure learning in time.
Review in Neuroscience and biobehavioral reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- Methamphetamine-induced adaptation of learning rate dynamics depend on baseline performance.eLife · 2025Trial
- Belief updating in uncertain environments is differentially sensitive to reward and punishment learning: Evidence from ERP.iScience · 2026Article
- Computational learning phenotypes are not related to individual differences in resting-state fMRI connectivity.Frontiers in neuroscience · 2026Article
- Replay in the human visual cortex during brief task pauses is linked to implicit learning of successor representations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Separable neural signals for reward and emotion prediction errors.Nature communications · 2025Article
- Article
- Early maladaptive schemas from child maltreatment in depression and psychotherapeutic remediation: a predictive coding framework.Frontiers in psychiatry · 2025Review
- The Ubiquity of Time in Latent-cause Inference.Journal of cognitive neuroscience · 2024Article
- Toward a computational role for locus coeruleus/norepinephrine arousal systems.Current opinion in behavioral sciences · 2024Article
- Thalamocortical architectures for flexible cognition and efficient learning.Trends in cognitive sciences · 2024Review
- Surprise-minimization as a solution to the structural credit assignment problem.PLoS computational biology · 2024Article
- Predictions transform memories: How expected versus unexpected events are integrated or separated in memory.Neuroscience and biobehavioral reviews · 2023Review
- Trait anxiety is associated with hidden state inference during aversive reversal learning.Nature communications · 2023Article
- Transfer of Learned Cognitive Flexibility to Novel Stimuli and Task Sets.Psychological science · 2023Article
- Article
- Thalamic regulation of frontal interactions in human cognitive flexibility.PLoS computational biology · 2022Article
- Adaptive Learning through Temporal Dynamics of State Representation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
People use information flexibly. They often combine multiple sources of relevant information over time in order to inform decisions with little or no interference from intervening irrelevant sources. They adjust the degree to which they use new information over time rationally in accordance with environmental statistics and their own uncertainty. They can even use information gained in one situation to solve a problem in a very different one. Learning flexibly rests on the ability to infer the context at a given time, and therefore knowing which pieces of information to combine and which to separate. We review the psychological and neural mechanisms behind adaptive learning and structure learning to outline how people pool together relevant information, demarcate contexts, prevent interference between information collected in different contexts, and transfer information from one context to another. By examining all of these processes through the lens of optimal inference we bridge concepts from multiple fields to provide a unified multi-system view of how the brain exploits structure in time to optimize learning.
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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.