类脑导航中基于差分Hebbian学习的网格细胞构建模型

doi:10.3969/j.issn.1001-506X.2020.03.023

Abstract

Abstract:

The grid cell is a kind of important neuron cell related to spatial cognition and navigation in animal brain. It has hexagonal firing field extending to the whole two-dimensional space. The place cell is one of the main information sources of grid cells. The place cells can generate the grid cell through Hebbian learning, but the existing learning methods have assumed the Mexican hat model in advance for the adaptive function or learning window function of Hebbian learning. A place-to-grid cell model based on difference Hebbian learning is proposed. The input correlation with the Mexican hat model is generated spontaneously by using the difference of cells firing rates, and then the grid cell with the hexagonal firing field is generated through competitive nonlinear constraint of synaptic weights from place cells to the grid cell. The simulation results show that the difference Hebbian learning model can provide reference for the construction of the brain-inspired navigation system of unmanned platform.

Key words: brain-inspired navigation, grid cell, place cell, difference Hebbian learning, competitive nonlinear constraint

CLC Number:

TN96
Q811

Kun HAN, Dewei WU, Lei LAI. Model of generating grid cell based on difference Hebbian learning in brain-inspired navigation[J]. Systems Engineering and Electronics, 2020, 42(3): 674-679.

Figures/Tables 5

References 28

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参数	变量	数值
正方形区域	L×L	80 m×80 m
位置细胞个数	N×N	80×80
位置细胞放电率系数	a	10
b	1/8
突触权重更新率	η	5×10^-6
位置细胞放电率缩放系数	p	3
q	3
突触权重边界	Th_down	0
突触权重边界	Th_up	0.1

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[2]	Chenhao ZHAO, Deiwei WU, Kun HAN, Haonan ZHU, Chuanjin DAI. Path integration model based on multi-scale grid cell [J]. Systems Engineering and Electronics, 2021, 43(10): 2961-2967.

Model of generating grid cell based on difference Hebbian learning in brain-inspired navigation

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