Skip to main content
SpringerLink
Log in

A Continuous-Attractor Model of Flip Cell Phenomena

  • Conference paper
  • First Online:
Biologically Inspired Cognitive Architectures (BICA) for Young Scientists (BICA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 636))

Abstract

This paper is devoted to the problem of understanding mechanisms underlying behavioral correlates of head direction (HD) cells in the mammalian retrosplenial cortex. HD cells become active when an animal, such as rat, is facing a particular direction in its environment. The robustness of this phenomenon is usually attributed to attractor dynamics of the HD cell system. According to the standard view, a ring attractor exists in some abstract space, with HD cells symbolically allocated on the ring, so that any natural state of the system corresponds to a bump of activity on the ring. In apparent contradiction with this standard model are recent discoveries of so-called “flip cells”, that constitute a minority of HD cells and can either rotate their directional tuning by 180° when an animal transitions between two environments, or interpolate between discordant cues, or demonstrate a bimodal tuning curve. Here a continuous attractor network model is described that is capable of a qualitative reproduction of these phenomena, while being consistent with the ring attractor hypothesis. The model assumes that there is more than one attractor ring in the HD system. Results of the concept-proof simulation suggest a correction to the standard view of how the internal sense of direction is formed in the rat brain.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Taube, J.S., Muller, R.U., Ranck, J.B.: Head direction cells recorded from the postsubiculum in freely moving rats. I. Description and quantitative analysis. J. Neurosci. 10, 420–435 (1990)

    Article  Google Scholar 

  2. Dumont, J.R., Taube, J.S.: The neural correlates of navigation beyond the hippocampus. Prog. Brain Res. 219, 83–102 (2015)

    Article  Google Scholar 

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

    Article  Google Scholar 

  4. Samsonovich, A., McNaughton, B.L.: Path integration and cognitive mapping in a continuous attractor neural network model. J. Neurosci. 17(15), 5900–5920 (1997)

    Article  Google Scholar 

  5. Strogatz, S.H.: Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, p. 324. Addison-Wesley, Reading, MA (1994)

    Google Scholar 

  6. Skaggs, W.E., Knierim, J.J., Kudrimoti, H.S., McNaughton, B.L.: A model of the neural basis of the rat’s sense of direction. In: Tesauro, G., Touretzky, D., Leen, T. (eds.) Advances in Neural Information Processing Systems, pp. 130–180. MIT, Cambridge (1995)

    Google Scholar 

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

    Article  Google Scholar 

  8. Samsonovich, A.V.: Continuous attractor network. In: Izhikevich, E.M. (ed.) Scholarpedia: The Free Peer-Reviewed Encyclopedia (2010). http://www.scholarpedia.org/article/Continuous_Attractor_Network

  9. Peyrache, A., Lacroix, M.M., Petersen, P.C., Buzsaki, G.: Internally organized mechanisms of the head direction sense. Nat. Neurosci. 18(4), 569–575 (2015). https://doi.org/10.1038/nn.3968

    Article  Google Scholar 

  10. Jacob, P.Y., Casali, G., Spieser, L., Page, H., Overington, D., Jeffery, K.: Nat. Neurosci. 20(2), 173–175 (2017). https://doi.org/10.1038/nn.4465

    Article  Google Scholar 

  11. Knight, R., Piette, C.E., Page, H., Walters, D., Marozzi, E., Nardini, M., Stringer, S., Jeffery, K.J.: Weighted cue integration in the rodent head direction system. Philos. Trans. R. Soc. Lond. B 369(1635), 20120512 (2013)

    Article  Google Scholar 

  12. Page, H.J.I., Walters, D.M., Knight, R., Piette, C.E., Jeffery, K.J., Stringer, S.M.: A theoretical account of cue averaging in the rodent head direction system. Philos. Trans. R. Soc. Lond. B 369(1635), 20130283 (2013)

    Article  Google Scholar 

  13. Samsonovich, A.V.: Bringing consciousness to cognitive neuroscience: a computational perspective. J. Integr. Des. Process Sci. 11(3), 19–30 (2007)

    Google Scholar 

  14. Finkelstein, A., Derdikman, D., Rubin, A., Foerster, J.N., Las, L., Ulanovsky, N.: Three-dimensional head-direction coding in the bat brain. Nature 517(7533), 159-U65 (2015). https://doi.org/10.1038/nature14031

    Article  Google Scholar 

Download references

Acknowledgments

The author is grateful to Drs. Kate J. Jeffery and Hector Page from the Institute of Behavioural Neuroscience, University College London, London, United Kingdom, for fruitful discussions of the ideas of this work and its outcome. This work was supported by the RSF Grant # 15-11-30014.

Author information

Authors and Affiliations

  1. Department of Cybernetics and BICA Lab, Institute for Cyber Intelligence Systems, National Research Nuclear University “Moscow Engineering Physics Institute”, Kashirskoe Shosse 31, Moscow, 115409, Russian Federation

    Alexei V. Samsonovich

  2. George Mason University, Fairfax, VA, 22030, USA

    Alexei V. Samsonovich

Authors
  1. Alexei V. Samsonovich
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexei V. Samsonovich .

Editor information

Editors and Affiliations

  1. Krasnow Institute, George Mason University, Fairfax, VA, USA

    Alexei V. Samsonovich

  2. National Research Nuclear University MEPhI, Moscow, Russia

    Valentin V. Klimov

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Samsonovich, A.V. (2018). A Continuous-Attractor Model of Flip Cell Phenomena. In: Samsonovich, A., Klimov, V. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. BICA 2017. Advances in Intelligent Systems and Computing, vol 636. Springer, Cham. https://doi.org/10.1007/978-3-319-63940-6_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-63940-6_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63939-0

  • Online ISBN: 978-3-319-63940-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation