ArticleCurrent opinion in behavioral sciences2020
Learning Structures: Predictive Representations, Replay, and Generalization.
Article in Current opinion in behavioral sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 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.
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Who cites it
66 citing papers in PubMed.
- Acetylcholine: a candidate substrate for hippocampal predictive learning?Nature reviews. Neuroscience · 2026Review
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- Boundary Vector Cells Encode a Future-Biased Spectrum of Positions in the Rat.bioRxiv : the preprint server for biology · 2026Article
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- Knowledge of information cascades through social networks facilitates strategic gossip.Nature human behaviour · 2025Article
- A brain-inspired agentic architecture to improve planning with LLMs.Nature communications · 2025Article
- 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
- Hippocampal mismatch signals are based on episodic memories and not schematic knowledge.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Model-based algorithms shape automatic evaluative processing.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Attachment as Prediction: Insights from Cognitive and Developmental Neuroscience.Current directions in psychological science · 2025Article
- Empowering safer socially sensitive autonomous vehicles using human-plausible cognitive encoding.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A unified neural representation model for spatial and conceptual computations.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A framework for uniting space and time in the mind and brain.Frontiers in cognition · 2025Article
- Replay shapes abstract cognitive maps for efficient social navigation.Nature human behaviour · 2024Article
- Causal and Chronological Relationships Predict Memory Organization for Nonlinear Narratives.Journal of cognitive neuroscience · 2024Article
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- Architectural styles of curiosity in global Wikipedia mobile app readership.Science advances · 2024Article
- The brain hierarchically represents the past and future during multistep anticipation.Nature communications · 2024Article
6 more citing papers are in PubMed but not listed here.
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Authors and funding
1 author.
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Abstract
Memory and planning rely on learning the structure of relationships among experiences. Compact representations of these structures guide flexible behavior in humans and animals. A century after 'latent learning' experiments summarized by Tolman, the larger puzzle of cognitive maps remains elusive: how does the brain learn and generalize relational structures? This review focuses on a reinforcement learning (RL) approach to learning compact representations of the structure of states. We review evidence showing that capturing structures as predictive representations updated via replay offers a neurally plausible account of human behavior and the neural representations of predictive cognitive maps. We highlight multi-scale successor representations, prioritized replay, and policy-dependence. These advances call for new directions in studying the entanglement of learning and memory with prediction and planning.
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