ArticleeLife2018
Offline replay supports planning in human reinforcement learning.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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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
62 citing papers in PubMed.
- The hippocampus rapidly integrates sequence representations during novel multistep predictions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Article
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning.Scientific data · 2026Article
- Planning in the Brain: It's Not What You Think It Is.Annual review of neuroscience · 2026Review
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- Article
- Post-learning replay of hippocampal-striatal activity is biased by reward-prediction signals.Nature communications · 2025Article
- The distinct functions of working memory and intelligence in model-based and model-free reinforcement learning.NPJ science of learning · 2025Article
- A brain-inspired agentic architecture to improve planning with LLMs.Nature communications · 2025Article
- The Hippocampus Rapidly Integrates Sequence Representations During Novel Multistep Predictions.bioRxiv : the preprint server for biology · 2025Article
- Model-based algorithms shape automatic evaluative processing.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Using computational models of learning to advance cognitive behavioral therapy.Communications psychology · 2025Review
- Diminished State Space Theory of Human Aging.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025Article
- Proactive and reactive construction of memory-based preferences.Nature communications · 2025Article
- Proactive and reactive construction of memory-based preferences.bioRxiv : the preprint server for biology · 2024Article
- Learning probability distributions of sensory inputs with Monte Carlo predictive coding.PLoS computational biology · 2024Article
- Humans adaptively deploy forward and backward prediction.Nature human behaviour · 2024Article
- State-dependent connectivity in auditory-reward networks predicts peak pleasure experiences to music.PLoS biology · 2024Article
- Heuristics in risky decision-making relate to preferential representation of information.Nature communications · 2024Article
- Paradoxical replay can protect contextual task representations from destructive interference when experience is unbalanced.bioRxiv : the preprint server for biology · 2024Article
- A multi-stage anticipated surprise model with dynamic expectation for economic decision-making.Scientific reports · 2024Article
2 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
4 authors.
Funding
Abstract
Making decisions in sequentially structured tasks requires integrating distally acquired information. The extensive computational cost of such integration challenges planning methods that integrate online, at decision time. Furthermore, it remains unclear whether 'offline' integration during replay supports planning, and if so which memories should be replayed. Inspired by machine learning, we propose that (a) offline replay of trajectories facilitates integrating representations that guide decisions, and (b) unsigned prediction errors (uncertainty) trigger such integrative replay. We designed a 2-step revaluation task for fMRI, whereby participants needed to integrate changes in rewards with past knowledge to optimally replan decisions. As predicted, we found that (a) multi-voxel pattern evidence for off-task replay predicts subsequent replanning; (b) neural sensitivity to uncertainty predicts subsequent replay and replanning; (c) off-task hippocampus and anterior cingulate activity increase when revaluation is required. These findings elucidate how the brain leverages offline mechanisms in planning and goal-directed behavior 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.