Bio-mimetic Path Integration Using a Self Organizing Population of Grid Cells

  • Ankur Sinha
  • Jack Jianguo Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)


Grid cells in the dorsocaudal medial entorhinal cortex (dMEC) of the rat provide a metric representation of the animal’s local environment. The collective firing patterns in a network of grid cells forms a triangular mesh that accurately tracks the location of the animal. The activity of a grid cell network, similar to head direction cells, displays path integration characteristics. Classical robotics use path integrators in the form of inertial navigation systems to track spatial information of an agent as well. In this paper, we describe an implementation of a network of grid cells as a dead reckoning system for the PR2 robot.


Grid Cell Synaptic Weight Place Cell Inertial Navigation System Head Direction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Barshan, B., Durrant-Whyte, H.F.: Inertial navigation systems for mobile robots. IEEE Transactions on Robotics and Automation 11(3), 328–342 (1995)CrossRefGoogle Scholar
  2. 2.
    Derdikman, D., Moser, E.I.: A manifold of spatial maps in the brain. Trends in Cognitive Sciences 14(12), 561–569 (2010)CrossRefGoogle Scholar
  3. 3.
    Gerstner, W., Kistler, W.M.: Mathematical formulations of hebbian learning. Biological Cybernetics 87(5-6), 404–415 (2002)CrossRefMATHGoogle Scholar
  4. 4.
    Gerstner, W., Kistler, W.M.: Spiking neuron models: Single neurons, populations, plasticity. Cambridge University Press (2002)Google Scholar
  5. 5.
    Giocomo, L.M., Moser, M.B., Moser, E.I.: Computational models of grid cells. Neuron 71(4), 589–603 (2011)CrossRefGoogle Scholar
  6. 6.
    Hafting, T., Fyhn, M., Molden, S., Moser, M.B., Moser, E.I.: Microstructure of a spatial map in the entorhinal cortex. Nature 436(7052), 801–806 (2005)CrossRefGoogle Scholar
  7. 7.
    Kyriacou, T.: Using an evolutionary algorithm to determine the parameters of a biologically inspired model of head direction cells. Journal of Computational Neuroscience 32(2), 281–295 (2012)CrossRefGoogle Scholar
  8. 8.
    McNaughton, B.L., Battaglia, F.P., Jensen, O., Moser, E.I., Moser, M.B.: Path integration and the neural basis of the ‘cognitive map’. Nature Reviews Neuroscience 7(8), 663–678 (2006)CrossRefGoogle Scholar
  9. 9.
    Muller, R.U., Ranck, J.B., Taube, J.S.: Head direction cells: properties and functional significance. Current Opinion in Neurobiology 6(2), 196–206 (1996)CrossRefGoogle Scholar
  10. 10.
    Muller, R.U., Stead, M., Pach, J.: The hippocampus as a cognitive graph. The Journal of General Physiology 107(6), 663–694 (1996)CrossRefGoogle Scholar
  11. 11.
    Nadel, L., MacDonald, L.: Hippocampus: Cognitive map or working memory? Behavioral and Neural Biology 29(3), 405–409 (1980)CrossRefGoogle Scholar
  12. 12.
    O’Keefe, J.: Place units in the hippocampus of the freely moving rat. Experimental Neurology 51(1), 78–109 (1976)CrossRefGoogle Scholar
  13. 13.
    O’Keefe, J.: The hippocampal cognitive map and navigational strategies (1991)Google Scholar
  14. 14.
    Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: Ros: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3 (2009)Google Scholar
  15. 15.
    Ranck Jr., J.: Head direction cells in the deep cell layer of dorsal presubiculum in freely moving rats. In: Society for Neuroscience Abstracts, vol. 10 (1984)Google Scholar
  16. 16.
    Stringer, S., Rolls, E., Trappenberg, T., De Araujo, I.: Self-organizing continuous attractor networks and path integration: two-dimensional models of place cells. Network: Computation in Neural Systems 13(4), 429–446 (2002)CrossRefGoogle Scholar
  17. 17.
    Stringer, S., Trappenberg, T., Rolls, E., Araujo, I.E.T.: Self-organizing continuous attractor networks and path integration: one-dimensional models of head direction cells. Network: Computation in Neural Systems 13(2), 217–242 (2002)CrossRefMATHGoogle Scholar
  18. 18.
    Trullier, O., Meyer, J.A.: Animat navigation using a cognitive graph. Biological Cybernetics 83(3), 271–285 (2000)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ankur Sinha
    • 1
  • Jack Jianguo Wang
    • 1
  1. 1.Faculty of Engineering and Information TechnologyThe University of TechnologySydneyAustralia

Personalised recommendations