Collective Dynamics in Models of Communicating Populations

  • A. S. Mikhailov
Part of the Springer Series in Synergetics book series (SSSYN, volume 62)


Three characteristic examples of the populations employing different modes of communication, such as exchange of addressed messages, mass communication and remote sensing, are investigated. We find that the populations are able to collectively perform some functions of the information processing that are typical for neural networks.


Receptive Field Associative Memory Axonic Terminal Dictyostelium Discoideum Mass Communication 
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.


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  1. 1.
    F. Alcantara, M. Monk “Signal propagation during aggregation in the slime mold Dictyostelium discoideum” J. Gen. Microbiol. 85, 321–334 (1974)Google Scholar
  2. 2.
    G. Gerisch, D. Hulser, D. Malchow, U. Wick “Cell communication by periodic cyclic AMP pulses” Phil. Trans. R. Soc. Lond. B 272, 181–192 (1975)ADSGoogle Scholar
  3. 3.
    E. O. Budrene, H. C. Berg “Complex patterns formed by motile cells of Escherichia coli” Nature, 349, 630–633 (1991)ADSCrossRefGoogle Scholar
  4. 4.
    J. D. Murray Mathematical Biology (Springer, Berlin 1989)MATHGoogle Scholar
  5. 5.
    G. M. Shepherd Neurobiology (Oxford Univ. Press 1983)Google Scholar
  6. 6.
    A. W. Robards, W. J. Lucas “Plasmodesmata” Annu. Rev. Plant Physiol. Plant Mol. Biol. 41, 369–419 (1990)CrossRefGoogle Scholar
  7. 7.
    J. M. Pateels, J. L. Deneudourg (eds.) “From Individual to Collective Behaviour in Social Insects” (Birkhauser, Basel 1987)Google Scholar
  8. 8.
    J. M. Tyson, K. Alexander, V. Manoranjan, J. Murray “Spiral waves of cyclic AMP in a model of slime mold aggregation” Physica D 34, 193–207 (1989)MathSciNetADSMATHCrossRefGoogle Scholar
  9. 9.
    P. B. Monk, H. G. Othmer “Wave propagation in aggregation fields of the cellular slime mould Dictyostelium discoideum” Proc. R. Soc. Lond. B 240, 555–589 (1990)ADSCrossRefGoogle Scholar
  10. 10.
    A. S. Mikhailov Foundations of Synergetics I. Distributed Active Systems (Sprmger, Berlin 1990)MATHCrossRefGoogle Scholar
  11. 11.
    Parallel Distributed Processing. Vol.1, eds. D. E. Rumelhart et al. (MIT Press, Cambridge, MA 1986)Google Scholar
  12. 12.
    H. Haken Synergetic Computers and Cognition (Springer, Berlin 1990)CrossRefGoogle Scholar
  13. 13.
    A. S. Mikhailov, I. V. Mit’kov, N. A. Sveshnikov “Molecular Associative Memory” Bio Systems 23, 291–295 (1990)CrossRefGoogle Scholar
  14. 14.
    A. S. Mikhailov “Information processing by systems with chemical communication”, in Rhythms in Physiological Systems. eds. H. Haken, H. P. Koepchen (Springer, Berlin 1991) pp.339–350.CrossRefGoogle Scholar
  15. 15.
    W. C. McCulloch, W. Pitts “A logical calculus of the ideas immanent in nervous activity” Bull. Math. Biophys. 5, 115–137 (1943)MathSciNetMATHCrossRefGoogle Scholar
  16. 16.
    N. K. Jerne “Towards a network theory of the immune system” Ann. Immunol. (Inst. Pasteur) 125C, 373–389 (1974)Google Scholar
  17. 17.
    B. Derrida, E. Gardner, A. Zippelius “An exactly solvable asymmetric neural network model” Europhys. Lett. 4, 167–171 (1987)ADSCrossRefGoogle Scholar
  18. 18.
    D. O. Hebb The Organization of Behaviour (Wiley, New York 1949)Google Scholar
  19. 19.
    J. J. Hopfield “Neural networks and physical systems with emergent collective computational abilities” Proc. Natl. Acad. Sci. USA 79, 2554–2558 (1982)MathSciNetADSCrossRefGoogle Scholar
  20. 20.
    A. S. Mikhailov, I. V. Mit’kov, N. A. Sveshnikov “Dual description and dynamics of the Hopfield model”, preprint 89–50/127, Institute of Nuclear Physics, University of Moscow, 1989Google Scholar
  21. 21.
    E. M. Izhikevich, A. S. Mikhailov, N. A. Sveshnikov “Memory, learning and neuromediators” Bio Systems 25, 219–229 (1991)CrossRefGoogle Scholar
  22. 22.
    K. Koketsu “Modulation of receptor sensitivity and action potentials by transmitters in vertebrate neurones” Jap. J. Physiol. 34, 945–960 (1984)CrossRefGoogle Scholar
  23. 23.
    M. Berry “Cellular differentiation: development of dendritic arborisation under normal and experimentally altered conditions” Neurosci. Res. Prog. Bull. 20, 451–463 (1982)Google Scholar
  24. 24.
    F. Hucho Neurochemistry (VCH Verlagsgesellschaft 1986)Google Scholar
  25. 25.
    A. S. Mikhailov “Artificial life: an engineering perspective”, in Evolution of Dynamical Structures in Complex Systems. eds. R. Friedrich, A. Wunderlin (Springer, Berlin 1992) pp. 301–312CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • A. S. Mikhailov
    • 1
  1. 1.Abteilung Physikalische ChemieFritz-Haber-Institut der Max-Planck-GesellschaftBerlin 33Fed. Rep. of Germany

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