ArticleNature neuroscience2024
A recurrent network model of planning explains hippocampal replay and human behavior.
Article in Nature neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Inferential planning in the frontal cortex.Cell reports · 2026Article
- Human hippocampal ripples coordinate planning sequences and compositional representations in neocortex.Nature neuroscience · 2026Article
- Planning in the Brain: It's Not What You Think It Is.Annual review of neuroscience · 2026Review
- Article
- Meta-learning is expressed through altered prefrontal cortical dynamics.bioRxiv : the preprint server for biology · 2026Article
- Learning to select computations in recurrent neural circuits.bioRxiv : the preprint server for biology · 2026Article
- Contextual inference through flexible integration of environmental features and behavioural outcomes.PLoS computational biology · 2026Article
- Article
- On the need for abstract, deep reinforcement learning models in neuroscience.Frontiers in neuroinformatics · 2026Article
- Dynamic Synchronization and Resonance as the Origin of 1/f Fluctuations-Amplitude Modulation Across Music and Nature.Entropy (Basel, Switzerland) · 2025Article
- Octopamine instructs head direction plasticity.bioRxiv : the preprint server for biology · 2025Article
- Learning to Move and Plan like the Knight: Sequential Decision Making with a Novel Motor Mapping.Computational brain & behavior · 2025Article
- Reasoning with programs in replay.bioRxiv : the preprint server for biology · 2025Article
- Behavioral Timing of Interictal Spikes, But Not Rate, Correlates with Impaired Working Memory Performance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Article
- The Role of Inner Speech in Human Behavior: Reflective Inner Speech Cycle (RISC) Model.Integrative psychological & behavioral science · 2025Article
- Article
- Adaptive planning depth in human problem-solving.Royal Society open science · 2025Article
- Article
- Flexible inference for animal learning rules using neural networks.Advances in neural information processing systems · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
When faced with a novel situation, people often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here, we capture these features of behavior by developing a neural network model where planning itself is controlled by the prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences from its own policy, which we call 'rollouts'. In a spatial navigation task, the agent learns to plan when it is beneficial, which provides a normative explanation for empirical variability in human thinking times. Additionally, the patterns of policy rollouts used by the artificial agent closely resemble patterns of rodent hippocampal replays. Our work provides a theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by-and adaptively affect-prefrontal dynamics.
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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.