ArticleCognitive neurodynamics2024
Modeling the grid cell activity based on cognitive space transformation.
Article in Cognitive neurodynamics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.Frontiers in neuroscience · 2025Article
- A spatial transformation-based CAN model for information integration within grid cell modules.Cognitive neurodynamics · 2024Article
- A Review of Brain-Inspired Cognition and Navigation Technology for Mobile Robots.Cyborg and bionic systems (Washington, D.C.) · 2024Review
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4 authors.
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Abstract
The grid cells in the medial entorhinal cortex are widely recognized as a critical component of spatial cognition within the entorhinal-hippocampal neuronal circuits. To account for the hexagonal patterns, several computational models have been proposed. However, there is still considerable debate regarding the interaction between grid cells and place cells. In response, we have developed a novel grid-cell computational model based on cognitive space transformation, which established a theoretical framework of the interaction between place cells and grid cells for encoding and transforming positions between the local frame and global frame. Our model not only can generate the firing patterns of the grid cells but also reproduces the biological experiment results about the grid-cell global representation of connected environments and supports the conjecture about the underlying reason. Moreover, our model provides new insights into how grid cells and place cells integrate external and self-motion cues.
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