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Principles of signal coding by the discharge pattern of a neuron population

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Abstract

The principles of information coding by “rings” of stochastic dependence, formed by neuron populations, are described. Such a population was shown to be capable of existing only in strictly definite stochastic states, determined by a certain number of “rings” of stochastic dependence, A system consisting of a fixed number of neurons was shown to be able to code and transmit a number of different messages equal to the square of the number of stochastic states permitted for that system. The number of messages differing from each other either in the number of letters or their order in the word was equal to the number of permitted stochastic states, whereas the number of messages containing the same number of letters in the word was equal to the difference between the number of permitted stochastic states and the number of neurons in the system. The alphabet consists of two letters: A for assembling of the ring of stochastic dependence, and B for breaking of this ring, together with punctuation signs indicating neither assembling nor breaking (compared with the initial state) of stochastic dependence rings.

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Literature cited

  1. N. P. Bekhtereva, P. V. Bundzen, V. D. Kaidel, and é. é. David, “Principles of organization of the structure of the spatiotemporal code of short-term verbal memory,” Fiziol. Zh. SSSR,59, No. 11, 1785 (1973).

    Google Scholar 

  2. S. I. Kovbasa, “Assessment of interdependence of spike trains in neuronal systems,” Biofizika,25, No. 6, 1086 (1980).

    Google Scholar 

  3. S. I. Kovbasa, “Coding of information sources by ratio of stochastic dependence of spike discharges of groups of neurons,” in: Engineering Problems in Medicine [in Russian], Tomsk (1983), pp. 81–82.

  4. S. I. Kovbasa, S. V. Yagodin, and A. D. Nozdrachev, “Quantitative evaluation of matching of the spike trains of a functional group of neurons,” Fiziol. Zh. SSSR,69, No. 12, 1644 (1983).

    Google Scholar 

  5. A. B. Kogan, “Neuronal groups as elements in the construction of a neural center,” in: Mechanisms of Combination of Neurons in a Neural Center [in Russian], Kiev (1972), pp. 21–26.

  6. G. Edelman and V. B. Mountcastle, The Mindful Brain, MIT Press, Cambridge, Massachusetts (1978).

    Google Scholar 

  7. A. D. Nozdrachev, S. I. Kovbasa, and S. V. Yagodin, “Quantitative evaluation of interference between action potentials in combined electroneurograms,” Fiziol. Zh. SSSR,68, No. 10, 1454 (1982).

    Google Scholar 

  8. A. N. Radchenko, Models of the Principal Mechanisms of the Brain [in Russian], Nauka, Leningrad (1968).

    Google Scholar 

  9. E. N. Sokolov, Neuronal Mechanisms of Memory and Learning [in Russian], Nauka, Moscow (1981).

    Google Scholar 

  10. G. Somjen, Sensory Coding in the Mammalian Nervous System, Plenum Press (1975).

  11. R. L. Stratonovich, Information Theory [in Russian], Sov. Radio, Moscow (1975).

    Google Scholar 

  12. M. I. Shtokman, “On a correlation-optical method of studying interaction between neurons in nerve networks,” Preprint No. 96, Novosibirsk (1979).

  13. H. T. Chang. “The repetitive discharges of corticothalamic reverberating circuits,” J. Neurophysiol.,13, No. 3, 235 (1950).

    Google Scholar 

  14. W. Freeman, “Linear analysis of the dynamics of neural masses,” Ann. Rev. Biophys. Bioeng.,1, 225 (1972).

    Google Scholar 

  15. A. Grinvald, L. B. Cohen, S. Lesher, and M. B. Boyle, “Simultaneous optical monitoring of activity of many neurons in invertebrate ganglia using a 124-element photodiode array,” J. Neurophysiol.,45, 829 (1981).

    Google Scholar 

  16. R. J. MacGregor and C. A. Radeliffe, “A random walk model for reverberatory pathways in reticularlike networks,” Brain Res.,63, 374 (1973).

    Google Scholar 

  17. D. H. Perkel, G. L. Gerstein, M. S. Smith, and W. G. Tatton, “Nerve-impulse patterns: a quantitative display technique for three neurons,” Brain Res.,100, 271 (1975).

    Google Scholar 

  18. R. B. Stein, K. V. Leung, M. N. Oguztöreli, and D. W. Williams, “Properties of small neural networks,” Kybernetik,14, 223 (1974).

    Google Scholar 

  19. H. R. Wilson and J. D. Cowan, “A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue,” Kybernetik,13, 55 (1973).

    Google Scholar 

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Authors and Affiliations

  1. Department of Higher Mathematics, N. A. Voznesenskii Leningrad Financial and Economic Institute, USSR

    S. I. Kovbasa, A. D. Nozdrachev & S. V. Yagodin

  2. Department of Human and Animal Physiology, A. A. Zhdanov State University, Leningrad

    S. I. Kovbasa, A. D. Nozdrachev & S. V. Yagodin

Authors
  1. S. I. Kovbasa
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  2. A. D. Nozdrachev
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  3. S. V. Yagodin
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Translated from Fiziologicheskii Zhurnal SSSR imeni I. M. Sechenova, Vol. 70, No. 4, pp. 492–500, April, 1984.

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Kovbasa, S.I., Nozdrachev, A.D. & Yagodin, S.V. Principles of signal coding by the discharge pattern of a neuron population. Neurosci Behav Physiol 16, 314–321 (1986). https://doi.org/10.1007/BF01148175

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  • DOI: https://doi.org/10.1007/BF01148175

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