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CLC number: TP391; TP24

On-line Access: 2016-05-04

Received: 2015-10-21

Revision Accepted: 2016-03-16

Crosschecked: 2016-04-11

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Citations:  Bibtex RefMan EndNote GB/T7714


Yang Zhou


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Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.5 P.435-448


Biologically inspired model of path integration based on head direction cells and grid cells

Author(s):  Yang Zhou, De-wei Wu

Affiliation(s):  College of Information and Navigation, Air Force Engineering University, Xian 710077, China

Corresponding email(s):   yydayl@sina.cn, wudewei74609@126.com

Key Words:  Head direction cells (HDCs), Grid cells (GCs), Path integration, Bionic navigation

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.

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%T Biologically inspired model of path integration based on head direction cells and grid cells
%A Yang Zhou
%A De-wei Wu
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%DOI 10.1631/FITEE.1500364

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
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SP - 435
EP - 448
%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1500364

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.


目的:以脑神经科学为基础,结合头朝向细胞(head direction cells)和网格细胞(grid cells)的放电特性,为运行体智能自主导航提供一种生物启发式的路径整合模型。
方法:首先,采用头朝向细胞感知其表征方向上的速度,并对运行方向进行度量。其次,相对头朝向细胞引入对应的距离细胞(distance cells),用于处理各头朝向细胞感知的速度,并对相对方位进行度量。最后,距离细胞处理得到的位移输入到网格细胞中用于计算各网格细胞的放电率,并结合网格细胞的放电样式,对运行距离进行度量。以此,运行体通过各类细胞的放电情况感知运行方向、相对方位以及运行距离,最终实现路径整合。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Burak, Y., Fiete, I.R., 2009. Accurate path integration in continuous attractor network models of grid cells. PLoS Comput. Biol., 5(2):e1000291.

[2]Burgess, N., Barry, C., O’Keefe, J., 2007. An oscillatory interference model of grid cell firing. Hippocampus, 17(9):801-812.

[3]Collett, T.S., Graham, P., 2004. Animal navigation: path integration, visual landmarks and cognitive maps. Current Biol., 14(12):R475-R477.

[4]Erdem, U.M., Hasselmo, M.E., 2014. A biologically inspired hierarchical goal directed navigation model. J. Physiol.-Paris, 108(1):28-37.

[5]Fuhs, M.C., Touretzky, D.S., 2006. A spin glass model of path integration in rat medial entorhinal cortex. J. Neurosci., 26(16):4266-4276.

[6]Giocomo, L.M., Moser, M.B., Moser, E.I., 2011. Computational models of grid cells. Neuron, 71(4):589-603.

[7]Giocomo, L.M., Stensola, T., Bonnevie, T., et al., 2014. Topography of head direction cells in medial entorhinal cortex. Current Biol., 24(3):252-262.

[8]Hafting, T., Fyhn, M., Molden, S., et al., 2005. Microstructure of a spatial map in the entorhinal cortex. Nature, 436:801-806.

[9]Hirel, J., Gaussier, P., Quoy, M., et al., 2013. The hippocampo-cortical loop: spatio-temporal learning and goal-oriented planning in navigation. Neur. Netw., 43:8-21.

[10]Huhn, Z., Somogyvári, Z., Kiss, T., et al., 2009. Distance coding strategies based on the entorhinal grid cell system. Neur. Netw., 22(5-6):536-543.

[11]Islam, T., Fukuzaki, R., 2010. A model of path integration and navigation based on head direction cells in entorhinal cortex. Int. Conf. on Neural Information Processing, p.82-90.

[12]Islam, T., Yamaguchi, Y., 2009. Representation of an environmental space by grid fields: a study with a computational model of the grid cell based on a column structure. Proc. Int. Joint Conf. on Neural Networks, p.14-19.

[13]Kesner, R.P., Rolls, E.T., 2015. A computational theory of hippocampal function, and tests of the theory: new developments. Neurosci. Biobehav. Rev., 48:92-147.

[14]Kim, D., Lee, J., 2011. Path integration mechanism with coarse coding of neurons. Neur. Process. Lett., 34(3):277-291.

[15]Kraus, B.J., Robinson, R.J.II, White, J.A., et al., 2013. Hippocampal ‘‘time cells’’: time versus path integration. Neuron, 78(6):1090-1101.

[16]Kyriacou, T., 2011. An implementation of a biologically inspired model of head direction cells on a robot. 12th Conf. Towards Autonomous Robotic Systems, p.66-77.

[17]McNaughton, B.L., Battaglia, F.P., Jensen, O., et al., 2006. Path integration and the neural basis of the ‘cognitive map’. Nat. Rev. Neurosci., 7:663-678.

[18]Mhatre, H., Gorchetchnikov, A., Grossberg, S., 2012. Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex. Hippocampus, 22(2):320-334.

[19]Moser, E.I., Moser, M.B., 2013. Grid cells and neural coding in high-end cortices. Neuron, 80(3):765-774.

[20]Muir, G.M., Taube, J.S., 2004. Head direction cell activity and behavior in a navigation task requiring a cognitive mapping strategy. Behav. Brain Res., 153(1):249-253.

[21]O’Keefe, J., Dostrovsky, J., 1971. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res., 34(1):171-175.

[22]Oshiro, N., Kurata, K., Yamamoto, T., 2008. A self-organizing VQ model of head-direction cells and grid cells. Artif. Life Robot., 12:206-209.

[23]Siegrist, C., Etienne, A.S., Boulens, V., et al., 2003. Homing by path integration in a new environment. Animal Behav., 65(1):185-194.

[24]Taube, J.S., 1998. Head direction cells and the neurophysiological basis for a sense of direction. Prog. Neurobiol., 55(3):225-256.

[25]Walters, D.M., Stringer, S.M., 2010. Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants. Biol. Cybern., 103(1):21-41.

[26]Wiener, J.M., Berthoz, A., Wolbers, T., 2010. Dissociable cognitive mechanisms underlying human path integration. Exp. Brain Res., 208(1):61-71.

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