ArticlePLoS computational biology2017
A single-cell spiking model for the origin of grid-cell patterns.
Article in PLoS computational biology, 2017. 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.
- Distinct cortical spatial representations learned along disparate visual pathways.Science advances · 2026Article
- The role of oscillations in grid cells' toroidal topology.PLoS computational biology · 2025Article
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- A spatial transformation-based CAN model for information integration within grid cell modules.Cognitive neurodynamics · 2024Article
- Modeling the grid cell activity based on cognitive space transformation.Cognitive neurodynamics · 2024Article
- Self-organization of modular activity in immature cortical networks.Nature communications · 2024Article
- A consistent map in the medial entorhinal cortex supports spatial memory.Nature communications · 2024Article
- A consistent map in the medial entorhinal cortex supports spatial memory.bioRxiv : the preprint server for biology · 2023Article
- Microcircuits for spatial coding in the medial entorhinal cortex.Physiological reviews · 2022Review
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- Article
- A Plane-Dependent Model of 3D Grid Cells for Representing Both 2D and 3D Spaces Under Various Navigation Modes.Frontiers in computational neuroscience · 2021Article
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- A Brain-Inspired Adaptive Space Representation Model Based on Grid Cells and Place Cells.Computational intelligence and neuroscience · 2020Article
- A Generalized Linear Model of a Navigation Network.Frontiers in neural circuits · 2020Article
- Article
- Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity.eLife · 2018Article
- Article
- Learning an Efficient Hippocampal Place Map from Entorhinal Inputs Using Non-Negative Sparse Coding.eNeuroArticle
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.
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