ArticleProceedings of the National Academy of Sciences of the United States of America2018
Emergent elasticity in the neural code for space.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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40 citing papers in PubMed, 86 citations in OpenAlex.
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- Object-translocation induces event coding in the rat hippocampus.Communications biology · 2025Article
- Soft Modes as a Predictive Framework for Low-Dimensional Biological Systems Across Scales.Annual review of biophysics · 2025Review
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- Learning to use landmarks for navigation amplifies their representation in retrosplenial cortex.bioRxiv : the preprint server for biology · 2024Article
- Mental navigation in the primate entorhinal cortex.Nature · 2024Article
- A consistent map in the medial entorhinal cortex supports spatial memory.Nature communications · 2024Article
- Modeling Grid Cell Distortions with a Grid Cell Calibration Mechanism.Cyborg and bionic systems (Washington, D.C.) · 2024Article
- A consistent map in the medial entorhinal cortex supports spatial memory.bioRxiv : the preprint server for biology · 2023Article
- Ring Attractors as the Basis of a Biomimetic Navigation System.Biomimetics (Basel, Switzerland) · 2023Article
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- Bayesian inference in ring attractor networks.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model.Scientific reports · 2022Article
- Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues.Neuron · 2022Article
- Microcircuits for spatial coding in the medial entorhinal cortex.Physiological reviews · 2022Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Upon encountering a novel environment, an animal must construct a consistent environmental map, as well as an internal estimate of its position within that map, by combining information from two distinct sources: self-motion cues and sensory landmark cues. How do known aspects of neural circuit dynamics and synaptic plasticity conspire to accomplish this feat? Here we show analytically how a neural attractor model that combines path integration of self-motion cues with Hebbian plasticity in synaptic weights from landmark cells can self-organize a consistent map of space as the animal explores an environment. Intriguingly, the emergence of this map can be understood as an elastic relaxation process between landmark cells mediated by the attractor network. Moreover, our model makes several experimentally testable predictions, including (
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