CLC number: TP391; TP24
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2016-04-11
Cited: 0
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Yang Zhou, De-wei Wu. Biologically inspired model of path integration based on head direction cells and grid cells[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(5): 435-448.
@article{title="Biologically inspired model of path integration based on head direction cells and grid cells",
author="Yang Zhou, De-wei Wu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="5",
pages="435-448",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500364"
}
%0 Journal Article
%T Biologically inspired model of path integration based on head direction cells and grid cells
%A Yang Zhou
%A De-wei Wu
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 5
%P 435-448
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500364
TY - JOUR
T1 - Biologically inspired model of path integration based on head direction cells and grid cells
A1 - Yang Zhou
A1 - De-wei Wu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 5
SP - 435
EP - 448
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500364
Abstract: Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells (HDCs) and grid cells (GCs) is related to the moving direction and distance, respectively. Thus, it is considered that these cells play an important role in the rodents’ path integration. To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired model of path integration based on the firing characteristics of HDCs and GCs. The detailed implementation process of this model is discussed. Besides, the proposed model is realized by simulation, and the path integration performance is analyzed under different conditions. Simulations validate that the proposed model is effective and stable.
This paper develops a novel path integration model based on neurobiological concepts. Overall, the model was well explained.
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