ArticleCognitive neurodynamics2016
Locating and navigation mechanism based on place-cell and grid-cell models.
Article in Cognitive neurodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- 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
- Place cells dynamically refine grid cell activities to reduce error accumulation during path integration in a continuous attractor model.Scientific reports · 2022Article
- Entorhinal-hippocampal interactions lead to globally coherent representations of space.Current research in neurobiology · 2022Review
- A gaze bias with coarse spatial indexing during a gambling task.Cognitive neurodynamics · 2018Article
- Influence of multiple action-outcome associations on the transition dynamics toward an optimal choice in rats.Cognitive neurodynamics · 2018Article
- An Energy Model of Place Cell Network in Three Dimensional Space.Frontiers in neuroscience · 2018Article
- The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.Frontiers in neuroscience · 2018Article
- Drugs Interfering with Muscarinic Acetylcholine Receptors and Their Effects on Place Navigation.Frontiers in psychiatry · 2017Review
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Authors and funding
4 authors.
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Abstract
Extensive experiments on rats have shown that environmental cues play an important role in goal locating and navigation. Major studies about locating and navigation are carried out based only on place cells. Nevertheless, it is known that navigation may also rely on grid cells. Therefore, we model locating and navigation based on both, thus developing a novel grid-cell model, from which firing fields of grid cells can be obtained. We found a continuous-time dynamic system to describe learning and direction selection. In our simulation experiment, according to the results from physiology experiments, we successfully rebuild place fields of place cells and firing fields of grid cells. We analyzed the factors affecting the locating accuracy. Results show that the learning rate, firing threshold and cell number can influence the outcomes from various tasks. We used our system model to perform a goal navigation task and showed that paths that are changed for every run in one experiment converged to a stable one after several runs.
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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.