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International Conference on Artificial General Intelligence

AGI 2015: Artificial General Intelligence pp 283–292Cite as

A New View on Grid Cells Beyond the Cognitive Map Hypothesis

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9205))

Abstract

Grid cells in the entorhinal cortex are generally considered to be a central part of a path integration system supporting the construction of a cognitive map of the environment in the brain. Guided by this hypothesis existing computational models of grid cells provide a wide range of possible mechanisms to explain grid cell activity in this specific context. Here we present a complementary grid cell model that treats the observed grid cell behavior as an instance of a more abstract, general principle by which neurons in the higher-order parts of the cortex process information.

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References

  1. Azizi, A.H., Schieferstein, N., Cheng, S.: The transformation from grid cells to place cells is robust to noise in the grid pattern. Hippocampus 24(8), 912–919 (2014)

    Article  Google Scholar 

  2. Barry, C., Burgess, N.: Neural mechanisms of self-location. Current Biology 24(8), R330–R339 (2014)

    Article  Google Scholar 

  3. de Berg, M., Cheong, O., van Kreveld, M., Overmars, M.: Computational Geometry: Algorithms and Applications. Springer (2008)

    Google Scholar 

  4. Burak, Y.: Spatial coding and attractor dynamics of grid cells in the entorhinal cortex. Current Opinion in Neurobiology 25, 169–175 (2014), theoretical and computational neuroscience

    Google Scholar 

  5. Burgess, N.: Grid cells and theta as oscillatory interference: Theory and predictions. Hippocampus 18(12), 1157–1174 (2008)

    Article  Google Scholar 

  6. Chen, T.W., Wardill, T.J., Sun, Y., Pulver, S.R., Renninger, S.L., Baohan, A., Schreiter, E.R., Kerr, R.A., Orger, M.B., Jayaraman, V., Looger, L.L., Svoboda, K., Kim, D.S.: Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499(7458), 295–300 (2013)

    Article  Google Scholar 

  7. Delaunay, B.: Sur la sphère vide. Bull. Acad. Sci. URSS 1934(6), 793–800 (1934)

    Google Scholar 

  8. Franzius, M., Vollgraf, R., Wiskott, L.: From grids to places. Journal of Computational Neuroscience 22(3), 297–299 (2007)

    Article  MathSciNet  Google Scholar 

  9. Fritzke, B.: Unsupervised ontogenetic networks. In: Fiesler, E., Beale, R. (eds.) Handbook of Neural Computation. Institute of Physics Publishing and Oxford University Press (1996)

    Google Scholar 

  10. Fritzke, B.: A growing neural gas network learns topologies. In: Advances in Neural Information Processing Systems, vol. 7, pp. 625–632. MIT Press (1995)

    Google Scholar 

  11. Fyhn, M., Molden, S., Witter, M.P., Moser, E.I., Moser, M.B.: Spatial representation in the entorhinal cortex. Science 305(5688), 1258–1264 (2004)

    Article  Google Scholar 

  12. Giocomo, L., Moser, M.B., Moser, E.: Computational models of grid cells. Neuron 71(4), 589–603 (2011)

    Article  Google Scholar 

  13. 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)

    Article  Google Scholar 

  14. Jia, H., Rochefort, N.L., Chen, X., Konnerth, A.: Dendritic organization of sensory input to cortical neurons in vivo. Nature 464(7293), 1307–1312 (2010)

    Article  Google Scholar 

  15. Jung, M.W., McNaughton, B.L.: Spatial selectivity of unit activity in the hippocampal granular layer. Hippocampus 3(2), 165–182 (1993)

    Article  Google Scholar 

  16. Kerdels, J., Peters, G.: A computational model of grid cells based on dendritic self-organized learning. In: Proceedings of the International Conference on Neural Computation Theory and Applications (2013)

    Google Scholar 

  17. Killian, N.J., Jutras, M.J., Buffalo, E.A.: A map of visual space in the primate entorhinal cortex. Nature 491(7426), 761–764 (11 2012)

    Google Scholar 

  18. Kohonen, T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43(1), 59–69 (1982)

    Article  MathSciNet  Google Scholar 

  19. Kropff, E., Treves, A.: The emergence of grid cells: Intelligent design or just adaptation? Hippocampus 18(12), 1256–1269 (2008)

    Article  Google Scholar 

  20. Martinetz, T.M., Schulten, K.: Topology representing networks. Neural Networks 7, 507–522 (1994)

    Article  Google Scholar 

  21. McNaughton, B.L., Battaglia, F.P., Jensen, O., Moser, E.I., Moser, M.B.: Path integration and the neural basis of the ‘cognitive map’. Nat. Rev. Neurosci. 7(8), 663–678 (2006)

    Article  Google Scholar 

  22. Mhatre, H., Gorchetchnikov, A., Grossberg, S.: Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex (published online 2010). Hippocampus 22(2), 320–334 (2010)

    Article  Google Scholar 

  23. Moser, E.I., Moser, M.B.: A metric for space. Hippocampus 18(12), 1142–1156 (2008)

    Article  Google Scholar 

  24. Moser, E.I., Moser, M.B., Roudi, Y.: Network mechanisms of grid cells. Philosophical Transactions of the Royal Society B: Biological Sciences 369(1635) (2014)

    Google Scholar 

  25. O’Keefe, J., Dostrovsky, J.: The hippocampus as a spatial map. preliminary evidence from unit activity in the freely-moving rat. Brain Research 34(1), 171–175 (1971)

    Article  Google Scholar 

  26. O’Keefe, J., Nadel, L.: The Hippocampus as a Cognitive Map. Oxford University Press, Oxford (1978)

    Google Scholar 

  27. O’Keefe, J.: Place units in the hippocampus of the freely moving rat. Experimental Neurology 51(1), 78–109 (1976)

    Article  Google Scholar 

  28. Pilly, P.K., Grossberg, S.: How do spatial learning and memory occur in the brain? coordinated learning of entorhinal grid cells and hippocampal place cells. J. Cognitive Neuroscience, 1031–1054 (2012)

    Google Scholar 

  29. Rolls, E.T., Stringer, S.M., Elliot, T.: Entorhinal cortex grid cells can map to hippocampal place cells by competitive learning. Network: Computation in Neural Systems 17(4), 447–465 (2006)

    Article  Google Scholar 

  30. Rosenblatt, F.: The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65(6), 386–408 (1958)

    Article  MathSciNet  Google Scholar 

  31. Sargolini, F., Fyhn, M., Hafting, T., McNaughton, B.L., Witter, M.P., Moser, M.B., Moser, E.I.: Conjunctive representation of position, direction, and velocity in entorhinal cortex. Science 312(5774), 758–762 (2006)

    Article  Google Scholar 

  32. Solstad, T., Boccara, C.N., Kropff, E., Moser, M.B., Moser, E.I.: Representation of geometric borders in the entorhinal cortex. Science 322(5909), 1865–1868 (2008)

    Article  Google Scholar 

  33. Solstad, T., Moser, E.I., Einevoll, G.T.: From grid cells to place cells: A mathematical model. Hippocampus 16(12), 1026–1031 (2006)

    Article  Google Scholar 

  34. Stensola, H., Stensola, T., Solstad, T., Froland, K., Moser, M.B., Moser, E.I.: The entorhinal grid map is discretized. Nature 492(7427), 72–78 (2012)

    Article  Google Scholar 

  35. Taube, J., Muller, R., Ranck, J.: Head-direction cells recorded from the postsubiculum in freely moving rats. i. description and quantitative analysis. The Journal of Neuroscience 10(2), 420–435 (1990)

    Google Scholar 

  36. Tolman, E.C.: Cognitive maps in rats and men. Psychological Review 55, 189–208 (1948)

    Article  Google Scholar 

  37. Tóth, L.: Lagerungen in der Ebene: auf der Kugel und im Raum. Die Grundlehren der Mathematischen Wissenschaften in Einzeldarstellungen mit besonderer Berücksichtigung der Anwendungsgebiete. Springer (1972)

    Google Scholar 

  38. Welinder, P.E., Burak, Y., Fiete, I.R.: Grid cells: The position code, neural network models of activity, and the problem of learning. Hippocampus 18(12), 1283–1300 (2008)

    Article  Google Scholar 

  39. Zhang, K.: Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory. The Journal of Neuroscience 16(6), 2112–2126 (1996)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of Hagen - Chair of Human-Computer Interaction, Universitätsstrasse 1, 58097, Hagen, Germany

    Jochen Kerdels & Gabriele Peters

Authors
  1. Jochen Kerdels
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  2. Gabriele Peters
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Correspondence to Jochen Kerdels .

Editor information

Editors and Affiliations

  1. Reykjavik University, Reykjavik, Iceland

    Jordi Bieger

  2. Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR

    Ben Goertzel

  3. Mechanics and Optics, Saint Petersburg State University of Information Technologies, St. Petersburg, Russia

    Alexey Potapov

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Kerdels, J., Peters, G. (2015). A New View on Grid Cells Beyond the Cognitive Map Hypothesis. In: Bieger, J., Goertzel, B., Potapov, A. (eds) Artificial General Intelligence. AGI 2015. Lecture Notes in Computer Science(), vol 9205. Springer, Cham. https://doi.org/10.1007/978-3-319-21365-1_29

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  • DOI: https://doi.org/10.1007/978-3-319-21365-1_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21364-4

  • Online ISBN: 978-3-319-21365-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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