Radiophysics and Quantum Electronics

, Volume 37, Issue 8, pp 607–614 | Cite as

Modeling “preattention” and “attention” information processing by synchronization of neural activity

  • G. N. Borisyuk
  • R. M. Borisyuk
  • Ya. B. Kazanovich


Oscillatory neural-network preattention and attention models are examined. A two-layer network of Wilson-Cowan oscillators is used to show that two-frequency oscillations can appear in response to a compound stimulus. It is shown that these oscillations can be synchronized at the low frequency, which can be interpreted as feature binding. Partial synchronization is studied in a model of a network of phased oscillators with a central element. Formulas are given for approximation of the average frequency of the central oscillator for small and large networks. The results describe the effect of a distracting stimulus on attention focus.


Information Processing Neural Activity Large Network Average Frequency Central Element 
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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Literature Cited

  1. 1.
    U. Neisser, Cognitive Psychology, Prentice-Hall, New York (1967).Google Scholar
  2. 2.
    R. Groner and M. Groner, Eur. Arch. Psychiatr. Neurol Sci.,239, 9 (1989).Google Scholar
  3. 3.
    C. von der Malsburg, The Correlation Theory of Brain Function, Internal Report 81-2, Department of Neurobiology, Max Planck Institute for Biophysical Chemistry (1981).Google Scholar
  4. 4.
    G. N. Borisyuk, R. M. Borisyuk, Ya. B. Kazanovich, T. B. Luzyanina, T. S. Turova, and G. S. Tsymbalyuk, Mat. Modelir.,4, No. 1, 3 (1992).Google Scholar
  5. 5.
    V. I. Kryukov, R. M. Borisyuk, G. N. Borisyuk, A. B. Kirillov, and E. I. Kovalenko, in: Stochastic Cellular Systems: Ergodicity, Memory, Morphogenesis, R. D. Dobrushin, V. Kryukov, and A. Toom (eds.), Vol. 3, Manchester University Press (1990), p. 225.Google Scholar
  6. 6.
    G. N. Borisyuk, R. M. Borisyuk, and A. I. Khibnik, in: Neural Networks Dynamics, Proc. of Workshop on Complex Dynamics (Springer Series: Perspectives in Neural Computing), Springer-Verlag (1992), p. 208.Google Scholar
  7. 7.
    V. I. Kryukov, in: Neurocomputers and Attention I, Neurobiology, Synchronization and Chaos, A. V. Holden and V. I. Kryukov (eds.), Manchester University Press (1991), p. 319.Google Scholar
  8. 8.
    A. Damasio, Neural Computation,1, 123 (1989).Google Scholar
  9. 9.
    C. M. Gray, P. Konig, A. K. Engel, and W. Singer, Nature,338, 334 (1989).Google Scholar
  10. 10.
    R. M. Borisyuk and A. B. Kirillov, Biol. Cybern.,66, 319 (1992).Google Scholar
  11. 11.
    A. I. Khibnik, R. M. Borisyuk, and D. Roose, In: International Series of Numerical Mathematics, Vol. 104, Birkhauser Verlag, Basel (1992), p. 215.Google Scholar
  12. 12.
    R. M. Borisyuk and L. M. Urzhumtseva, In: Neural Networks: Theory and Architecture, A. Holden and V. Kryukov (eds.), Manchester University Press (1990), p. 9.Google Scholar
  13. 13.
    Y. Kuramoto, Physika D,50, 15 (1991).Google Scholar
  14. 14.
    Ya. B. Kazanovich and R. M. Borisyuk, Mat. Modelir.,6, No. 8, 45 (1994).Google Scholar

Copyright information

© Plenum Publishing Corporation 1995

Authors and Affiliations

  • G. N. Borisyuk
  • R. M. Borisyuk
  • Ya. B. Kazanovich

There are no affiliations available

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