A spatial cognition model based on the selection mechanism of hippocampus place cells.
10.7507/1001-5515.201901044
- Author:
Naigong YU
1
;
Yishen LIAO
1
;
Xiangguo ZHENG
1
Author Information
1. Faculty of Information Technology, Beijing University of Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, P.R.China.
- Publication Type:Journal Article
- Keywords:
border cells;
grid cells;
location cognition;
place cells
- From:
Journal of Biomedical Engineering
2020;37(1):27-37
- CountryChina
- Language:Chinese
-
Abstract:
Biological studies show that place cells are the main basis for rats to know their current location in space. Since grid cells are the main input source of place cells, a mapping model from grid cells to place cells needs to be constructed. To solve this problem, a neural network mapping model of back propagation error from grid cells to place cells is proposed in this paper, which can accurately express the location in a given region. According to the physiological characteristics of border cells' specific discharge to the environment, the periodic resetting of the grid field phase by border cells is realized, and the position recognition in any space is completed by this model. In this paper, we designed a simulation experiment to compare the activity of the theoretical place cell plate, and then compared the time consumption of the competitive neural network model and the positioning error of RatSLAM pose cells plate. The experimental results showed that the proposed model could obtain a single place field, and the algorithm efficiency was improved by 85.94% compared with the competitive neural network model in the time-consuming experiment. In the localization experiment, the mean localization error was 41.35% lower than that of RatSLAM pose cells plate. Therefore, the location cognition model proposed in this paper can not only realize the efficient transfer of information between grid cells and place cells, but also realize the accurate location of its own location in any spatial area.
