ArticleeLife2019
Velocity coupling of grid cell modules enables stable embedding of a low dimensional variable in a high dimensional neural attractor.
Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 29 citations in OpenAlex.
- REMI: Reconstructing Episodic Memory During Internally Driven Path Planning.bioRxiv : the preprint server for biology · 2025Article
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- Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps.Advances in neural information processing systems · 2024Article
- Grid cells: the missing link in understanding Parkinson's disease?Frontiers in neuroscience · 2024Article
- Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model.Scientific reports · 2022Article
- Multiple bumps can enhance robustness to noise in continuous attractor networks.PLoS computational biology · 2022Article
- Grid-cell modules remain coordinated when neural activity is dissociated from external sensory cues.Neuron · 2022Article
- Spiking Neural Networks and Hippocampal Function: A Web-Accessible Survey of Simulations, Modeling Methods, and Underlying Theories.Cognitive systems research · 2021Article
- Dynamical self-organization and efficient representation of space by grid cells.Current opinion in neurobiology · 2021Review
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- Targeted photostimulation uncovers circuit motifs supporting short-term memory.Nature neuroscience · 2021Article
- Article
- Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Grid cells in the medial entorhinal cortex (MEC) encode position using a distributed representation across multiple neural populations (modules), each possessing a distinct spatial scale. The modular structure of the representation confers the grid cell neural code with large capacity. Yet, the modularity poses significant challenges for the neural circuitry that maintains the representation, and updates it based on self motion. Small incompatible drifts in different modules, driven by noise, can rapidly lead to large, abrupt shifts in the represented position, resulting in catastrophic readout errors. Here, we propose a theoretical model of coupled modules. The coupling suppresses incompatible drifts, allowing for a stable embedding of a two-dimensional variable (position) in a higher dimensional neural attractor, while preserving the large capacity. We propose that coupling of this type may be implemented by recurrent synaptic connectivity within the MEC with a relatively simple and biologically plausible structure.
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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.