A brain-like navigation method inspired by the spatial cells' cognitive mechanism. (October 2022)

• Record Type: Journal Article
• Authors: Liao, Yishen; Yu, Hejie; Yu, Naigong
• Is Part Of: Computers & electrical engineering. Volume 103(2022)
• Publication Date: 2022-10
• Subjects: Entorhinal-Hippocampal -- Path integration -- Visual pathway -- Goal-oriented navigation; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.108305
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: How to give the cognitive abilities of higher mammals to robots is a common concern. Entorhinal-hippocampal neural computing model is used for path integration. The visual pathway computing model corrects the cumulative error of path integration. Self-organizing model of hippocampal CA1 place cells optimizes the navigation path. Abstract: How rats achieve goal-oriented navigation is a hot research topic in neuroscience. Inspired by neurophysiological research, this paper proposes a brain-like navigation method inspired by the spatial cells' cognitive mechanism. Firstly, a neural computational model of the entorhinal-hippocampal structure is constructed for path integration. Subsequently, a visual pathway computational model is constructed to correct the accumulated errors. Finally, a self-organizing computational model of hippocampal CA1 place cells is constructed to optimize the navigation path. In order to verify the model, this paper designs the 2-D simulation experiment, and the proposed model is also compared with other models. The experimental results show that the proposed model cannot only make the navigation process more robust by using visual information. Moreover, it can gradually optimize the navigation path through the self-organized activity of hippocampal CA1 place cells, thus improving the efficiency of navigation. Graphical abstract: Image, graphical abstract