Skip to main content

What the Escherichia Coli Tells Neurons about Learning

  • Chapter
Integral Biomathics

Abstract

The Escherichia coli is a bacterium that comfortingly lives in the human gut and one of the best known living organisms. The sensitivity of this cell to environmental changes is reflected in two kind of movements that can be observed in a swimming bacterium: “run” towards an attractant, for example food, and “tumbling”, in which a new direction is chosen randomly for the next “run”.

This simple bimodal behavior of the E. coli constitutes in itself a paradigm of adaptation in which roboticists and cognitive psychologists have found inspiration. We present a new approach to synaptic plasticity in the nervous system by scrutinizing Escherichia coli’s motility and the signaling pathways that mediate its adaptive behavior. The formidable knowledge achieved in the last decade on bacterial chemotaxis, serve as the basis for a theory of a simple form of learning called habituation, that is applicable to biological and other systems. In this paper we try to establish a new framework that helps to explain what signals mean to the organisms, how these signals are integrated in patterns of behavior, and how they are sustained by an internal model of the world. The concepts of adaptation, synaptic plasticity and learning will be revisited within a new perspective, providing a quantitative basis for the understanding of how brains cope with a changing environment.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alon, U., Surette, M.G., Barkai, N., Leibler, S.: Robustness in bacterial chemotaxis. Nature 397(6715), 168–171 (1999)

    Article  Google Scholar 

  2. Barkai, N., Leibler, S.: Robustness in simple biochemical networks. Nature 387(6636), 913–917 (1997)

    Article  Google Scholar 

  3. Berg, H.C.: E. coli in Motion. Springer, New York (2004)

    Google Scholar 

  4. Blair, D.F.: How bacteria sense and swim. Annual Review of Microbiology 49(1), 489–520 (1995)

    Article  Google Scholar 

  5. Bray, D.: Wetware: A Computer in Every Living Cell. Yale University Press (2009)

    Google Scholar 

  6. Bray, D., Levin, M.D., Morton-Firth, C.J.: Receptor clustering as a cellular mechanism to control sensitivity. Nature 393(6680), 85–88 (1998)

    Article  Google Scholar 

  7. Davis, G.W.: Homeostatic control of neural activity: from phenomenology to molecular design. Annual Review of Neuroscience 29, 307–323 (2006)

    Article  Google Scholar 

  8. Dudai, Y.: The Neurobiology of Memory: Concepts, Findings, Trends, 1st edn. Oxford University Press, USA (1989)

    Google Scholar 

  9. Fiorillo, C.D.: Towards a general theory of neural computation based on prediction by single neurons. PLoS ONE 3(10), e3298 (2008)

    Google Scholar 

  10. Fiorillo, C.D.: Towards a general theory of neural computation based on prediction by single neurons. In: Simeonov, P.L., Smith, L.S., Ehresmann, A.C. (eds.) Integral Biomathics: Tracing the Road to Reality. Springer, Heidelberg (2011)

    Google Scholar 

  11. Francis, B.A., Wonham, W.M.: The internal model principle of control theory. Automatica 12, 457–465 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  12. Friston, K.: The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 11, 127–138 (2010)

    Article  Google Scholar 

  13. Jacob, F.: Evolution and tinkering. Science 196(4295), 1161–1166 (1977)

    Article  Google Scholar 

  14. Kandel, E.R., Schwatz, J., Jessell, T.M.: Principles of Neural Science. McGraw-Hill, New York (2000)

    Google Scholar 

  15. Kawato, M.: Internal models for motor control and trajectory planning. Current Opinion in Neurobiology 9(6), 718–727 (1999)

    Article  Google Scholar 

  16. Knox, B., Devreotes, P., Goldbeter, A., Segel, L.: A molecular mechanism for sensory adaptation based on ligand-induced receptor modification. Proc. Natl. Acad. Sci. 83, 2345–2349 (1986)

    Article  Google Scholar 

  17. Marder, E., Goaillard, J.-M.: Variability, compensation and homeostasis in neuron and network function. Nat. Rev. Neurosci. 7(7), 563–574 (2006)

    Article  Google Scholar 

  18. Milhorn, H.T.: The Application of Control Theory to Physiological systems. W.B. Saunders Company, Philadelphia (1966)

    Google Scholar 

  19. Molnar, Z., Brown, R.E.: Insights into the life and work of sir charles sherrington. Nature Reviews. Neuroscience 11(6), 429–436 (2010)

    Article  Google Scholar 

  20. Morgenstern, O., von Neumann, J.: Theory of Games and Economic Behavior, 3rd edn. Princeton University Press (1980)

    Google Scholar 

  21. Neidhardt, F.C., et al.: Escherichia Coli and Salmonella Typhimurium: Vols 1-2: Cellular and Molecular Biology, 2 volume set edn. American Society for Microbiology (1987)

    Google Scholar 

  22. Sanz, R., López, I., Rodríguez, M., Hernández, C.: Principles for consciousness in integrated cognitive control. Neural Networks: The Official Journal of the International Neural Network Society 20(9), 938–946 (2007)

    Article  Google Scholar 

  23. Sourjik, V., Berg, H.C.: Receptor sensitivity in bacterial chemotaxis. Proceedings of the National Academy of Sciences of the United States of America 99(1), 123–127 (2002)

    Article  Google Scholar 

  24. Trimmer, J.D.: Response of physical systems. John Wiley & Sons Inc. (1956)

    Google Scholar 

  25. Turrigiano, G.G., Nelson, S.B.: Homeostatic plasticity in the developing nervous system. Nat. Rev. Neurosci. 5(2), 97–107 (2004)

    Article  Google Scholar 

  26. Vilar, J.M.G., Guet, C., Leibler, S.: Modeling network dynamics: the lac operon, a case study. The Journal of Cell Biology (3), 471–476 (2003)

    Google Scholar 

  27. Wadhams, G.H., Armitage, J.P.: Making sense of it all: bacterial chemotaxis. Nature Reviews. Molecular Cell Biology 5(12), 1024–1037 (2004)

    Article  Google Scholar 

  28. Yi, T.-M., Huang, Y., Simon, M.I., Doyle, J.: Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proceedings of the National Academy of Sciences 97(9), 4649–4653 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jaime Gomez-Ramirez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag GmbH Berlin Heidelberg

About this chapter

Cite this chapter

Gomez-Ramirez, J., Sanz, R. (2012). What the Escherichia Coli Tells Neurons about Learning. In: Simeonov, P., Smith, L., Ehresmann, A. (eds) Integral Biomathics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28111-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28111-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28110-5

  • Online ISBN: 978-3-642-28111-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics