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作者:

Yu, Naigong (Yu, Naigong.) (学者:于乃功) | Liao, Yishen (Liao, Yishen.) | Zheng, Xiangguo (Zheng, Xiangguo.) | Feng, Hui (Feng, Hui.)

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摘要:

Biological studies have shown that place cells have a single firing fields, which is the main basis for rats to know the current spatial location. The grid fields is hexagonal in the form of the whole space area. Grid cells are the main source of information input for place cells, so it is necessary to build a mapping model from grid cells to place cells. In order to solve this problem, an iteration model from grid cells to place cells is proposed. The model iterates the activation rate matrix of grid fields with different grid parameters in a given region, and realizes the mapping of grid cells to place cells. On this basis, a single place fields detection algorithm is added to improve the accuracy and efficiency of the model. The experimental results show that the model can not only map multiple grid fields to a single place fields, but also accurately locate the rat’s position in a given region. © Springer Nature Singapore Pte Ltd. 2020.

关键词:

Cells Cytology Iterative methods Mapping

作者机构:

  • [ 1 ] [Yu, Naigong]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Yu, Naigong]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Liao, Yishen]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Liao, Yishen]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zheng, Xiangguo]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Zheng, Xiangguo]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Feng, Hui]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Feng, Hui]Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

  • 于乃功

    [yu, naigong]beijing key laboratory of computational intelligence and intelligent system, beijing university of technology, beijing; 100124, china;;[yu, naigong]faculty of information technology, beijing university of technology, beijing; 100124, china

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ISSN: 1876-1100

年份: 2020

卷: 586

页码: 68-78

语种: 英文

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