ArticleFrontiers in neural circuits2020
A Generalized Linear Model of a Navigation Network.
Article in Frontiers in neural circuits, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Coordinating Cognition: The Entorhinal Cortex in Mnemonic, Temporal and Spatial Representation.Cells · 2026Review
- Schizophrenia pathology reverse-translated into mouse shows hippocampal hyperactivity, psychosis behaviors and hyper-synchronous events.Molecular psychiatry · 2025Article
- Article
- Widespread coding of navigational variables in prefrontal cortex.Current biology : CB · 2023Article
- Efficient spline regression for neural spiking data.PloS one · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Navigation by mammals is believed to rely on a network of neurons in the hippocampal formation, which includes the hippocampus, the medial entorhinal cortex (MEC), and additional nearby regions. Neurons in these regions represent spatial information by tuning to the position, orientation, and speed of the animal in the form of head direction cells, speed cells, grid cells, border cells, and unclassified spatially modulated cells. While the properties of single cells are well studied, little is known about the functional structure of the network in the MEC. Here, we use a generalized linear model to study the network of spatially modulated cells in the MEC. We found connectivity patterns between all spatially encoding cells and not only grid cells. In addition, the neurons' past activity contributed to the overall activity patterns. Finally, position-modulated cells and head direction cells differed in the dependence of the activity on the history. Our results indicate that MEC neurons form a local interacting network to support spatial information representations and suggest an explanation for their complex temporal properties.
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