ArticlePLoS computational biology2018
Model-based spatial navigation in the hippocampus-ventral striatum circuit: A computational analysis.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Inferential planning in the frontal cortex.Cell reports · 2026Article
- Choice-induced preference change under a sequential sampling model framework.Scientific reports · 2026Article
- Goal-directed behavior and hippocampal activity predict real-life impact of drinking intentions in alcohol use disorder.Translational psychiatry · 2025Article
- Deep Hybrid Models: Infer and Plan in a Dynamic World.Entropy (Basel, Switzerland) · 2025Article
- A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit.Nature communications · 2024Article
- Dopamine-mediated formation of a memory module in the nucleus accumbens for goal-directed navigation.Nature neuroscience · 2024Article
- An Improved Dyna-Q Algorithm Inspired by the Forward Prediction Mechanism in the Rat Brain for Mobile Robot Path Planning.Biomimetics (Basel, Switzerland) · 2024Article
- Grid cells: the missing link in understanding Parkinson's disease?Frontiers in neuroscience · 2024Article
- The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Habit formation viewed as structural change in the behavioral network.Communications biology · 2023Article
- A quadruple dissociation of reward-related behaviour in mice across excitatory inputs to the nucleus accumbens shell.Communications biology · 2023Article
- Flexible intentions: An Active Inference theory.Frontiers in computational neuroscience · 2023Article
- Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges.Wiley interdisciplinary reviews. Cognitive science · 2022Review
- Context coding in the mouse nucleus accumbens modulates motivationally relevant information.PLoS biology · 2022Article
- Absolute Winding Number Differentiates Mouse Spatial Navigation Strategies With Genetic Risk for Alzheimer's Disease.Frontiers in neuroscience · 2022Article
- Learning, memory and consolidation mechanisms for behavioral control in hierarchically organized cortico-basal ganglia systems.Hippocampus · 2020Review
- The Neuroscience of Spatial Navigation and the Relationship to Artificial Intelligence.Frontiers in computational neuroscience · 2020Review
- Caching mechanisms for habit formation in Active Inference.Neurocomputing · 2019Article
- Making the Environment an Informative Place: A Conceptual Analysis of Epistemic Policies and Sensorimotor Coordination.Entropy (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While the neurobiology of simple and habitual choices is relatively well known, our current understanding of goal-directed choices and planning in the brain is still limited. Theoretical work suggests that goal-directed computations can be productively associated to model-based (reinforcement learning) computations, yet a detailed mapping between computational processes and neuronal circuits remains to be fully established. Here we report a computational analysis that aligns Bayesian nonparametrics and model-based reinforcement learning (MB-RL) to the functioning of the hippocampus (HC) and the ventral striatum (vStr)-a neuronal circuit that increasingly recognized to be an appropriate model system to understand goal-directed (spatial) decisions and planning mechanisms in the brain. We test the MB-RL agent in a contextual conditioning task that depends on intact hippocampus and ventral striatal (shell) function and show that it solves the task while showing key behavioral and neuronal signatures of the HC-vStr circuit. Our simulations also explore the benefits of biological forms of look-ahead prediction (forward sweeps) during both learning and control. This article thus contributes to fill the gap between our current understanding of computational algorithms and biological realizations of (model-based) reinforcement 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.