Autor: |
Zhanjun Zhang, Wen-Xu Wang, Nikolai Axmacher, Ying-Cheng Lai, Liang Wang, Dong Chen, Kai-Jia Sun |
Rok vydání: |
2018 |
Předmět: |
|
Popis: |
Grid cells constitute a crucial component of the “GPS” in the mammalian brain. Recent experiments revealed that grid cell activity is anchored to environmental boundaries. More specifically, these results revealed a slight yet consistent offset of 8 degrees relative to boundaries of a square environment. The causes and possible functional roles of this orientation are still unclear. Here we propose that this phenomenon maximizes the spatial information conveyed by grid cells. Computer simulations of the grid cell network reveal that the universal grid orientation at 8 degrees optimizes spatial coding specifically in the presence of noise. Our model also predicts the minimum number of grid cells in each module. In addition, analytical results and a dynamical reinforcement learning model reveal the mechanism underlying the noise-induced orientation preference at 8 degrees. Together, these results suggest that the experimentally observed common orientation of grid cells serves to maximize spatial information in the presence of noise. Author summary Spatial navigation depends on several specialized cell types including place and grid cells. Grid cells have multiple firing fields that are arranged in a regular hexagonal pattern. The axes of this pattern are anchored to environmental boundaries at a universal angle of 8°. Here, we combine computer simulations of the grid cell network with analytical derivations and a reinforcement learning model to explain the functional relevance of this universal grid cell orientation. We show that spatial information provided by grid cells is maximized at the experimentally observed grid orientation within a broad parameter range. This relationship occurs only in the presence of noise. The model allows for several experimentally testable predictions including the number of grid cells. |
Databáze: |
OpenAIRE |
Externí odkaz: |
|