首页 | 本学科首页   官方微博 | 高级检索  
   检索      

基于鼠脑海马位置细胞与Q学习面向目标导航
引用本文:方略,何洪军.基于鼠脑海马位置细胞与Q学习面向目标导航[J].生物信息学,2019,17(1):31-38.
作者姓名:方略  何洪军
作者单位:中国电子科技集团公司第二十一研究所
基金项目:中国电子科技集团公司第二十一研究所资助项目(No.CB066) .
摘    要:生理学实验表明在鼠脑海马结构中存在的一种具有特异性放电特征的细胞,它在大鼠空间导航和环境认知中起着关键性作用,该特异性神经元被称之为位置细胞。本文将基于位置细胞、运动神经元来构建一种前馈神经网络模型,采用Q学习算法实现大鼠面向目标导航任务。实验结果表明该前馈神经网络模型能快速实现大鼠面向目标导航任务。

关 键 词:位置细胞  Q学习算法  前馈神经网络模型  目标导航
收稿时间:2018/9/6 0:00:00
修稿时间:2018/11/16 0:00:00

Goal oriented navigation based on place cells of rat's brain hippocampus and Q-learning
FANG Lue and HE Hongjun.Goal oriented navigation based on place cells of rat''s brain hippocampus and Q-learning[J].China Journal of Bioinformation,2019,17(1):31-38.
Authors:FANG Lue and HE Hongjun
Institution:The Twenty-First Research Institute of China Electronics Technology Group Corporation, Shanghai 200030, China and The Twenty-First Research Institute of China Electronics Technology Group Corporation, Shanghai 200030, China
Abstract:Physiological experiments show that a cell with specific discharge characteristics in the hippocampus of rats brain plays a key role in rats spatial navigation and environmental cognition, and the specific neurons are called place cells. In this paper, a feed-forward neural network model based on place cells and motor neurons is constructed, and Q-learning algorithm is used to realize the goal-oriented navigation task of the rat. The experimental results show that the feed-forward neural network model can quickly achieve the goal-oriented navigation task of the rat.
Keywords:Place cells  Q-learning algorithm  Feed-forward neural network model  Goal-oriented navigation
本文献已被 CNKI 等数据库收录!
点击此处可从《生物信息学》浏览原始摘要信息
点击此处可从《生物信息学》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号