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Comparison of Some Fractal Analysis Methods for Studying the Spontaneous Activity in Medullar Auditory Units

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Advances in Neural Computation, Machine Learning, and Cognitive Research (NEUROINFORMATICS 2017)

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Abstract

We recorded the spontaneous background impulse activity in the medullar and midbrain single auditory neurons of the paralyzed grass frog. This activity was considered by us as a chaotic point process. For the analyses of temporal changes of this process we used the approach based upon the recording of the Hurst index. This approach was juxtaposed with the methods based on the study of the dependence of Fano and Allan factors on the duration of the analyzed interval. A comparative analysis of the Fano, Allan and Hurst indices by Kendall’s rank correlation method have been made. We observed a close correlation of the values of the Fano and Allan indices for the spontaneous activity of the same neuron. Correlation of the Fano and Hurst indices was not so pronounced and did not quite correspond to the properties of typical fractal point processes. It is possible to formulate assumptions about the possibility and efficiency of using Hurst index to analyze the sequence of pulsed discharges of a neuron. In most cells, chaotic changes in impulse density were observed, which is indicative of the trend behavior of neuron’s firing. Anti-trend behavior was not observed.

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References

  1. Bibikov, N.G.: Investigation of spontaneous activity of neurons in the acoustic center of the frog’s midbrain. Statistical Electrophysiology. Vilnius: Science, pp. 70–80 (1968). (in Russian)

    Google Scholar 

  2. Mandelbrot, B.: Fractal Geometry of Nature/Translation from English by A.R. Logunov, 656 pp. Institute for Computer Research, Moscow (2002). (in Russian)

    Google Scholar 

  3. Fano, U.: Ionization yield of radiations. II. Fluctuations Number Ions. Phys. Rev. 72(1), 26–29 (1947)

    Google Scholar 

  4. Hurst, H.E.: Long term storage capacity of reservoirs. Trans. Am. Soc. Civ. Eng. 116(1), 770–799 (1951)

    Google Scholar 

  5. Barnes, J.A., Allan, D.W.: A statistical model of Flicker noise. Proc. IEEE 54(2), 176–178 (1966)

    Article  Google Scholar 

  6. Bibikov, N.G., Dymov, A.B.: Fano and Allan factors of the process of spontaneous impulse activity of acoustic neurons of the medulla oblongata. Sensor. Syst. 23(3), 246–259 (2009). (in Russian)

    Google Scholar 

  7. Dymov, A.B.: Use of Fano and Allan factors to analyze the properties of the spike sequence of neurons in the auditory system. In: Proceedings of the XI All-Russian Scientific and Technical Conference “Neuroinformatics-2009”, pp. 257–263. MIFI Press, Moscow (2009) (in Russian)

    Google Scholar 

  8. Bibikov, N.G.: Correlation of the responses of the neurons in the cochlear nucleus of the frog with low-frequency noise amplitude modulation of the tone signal. Acoust. Phys. 60(5), 597–607 (2014)

    Article  Google Scholar 

  9. Naiman, E.L.: Calculation of the Hurst index for the purpose of revealing the trend (persistence) of financial markets and macroeconomic indicators. http://wealth-lab.net/Data/Sites/1/SharedFiles/doc/forindicators/articles/04_erik_naiman_herst.pdf

  10. Aksyonov, V.Y., Dmitriev, V.N.: Algorithms of fractal analysis of time series in monitoring systems of sensor networks. Bull. Astrakhan State Tech. Univ. Ser. Manag. Comput. Sci. Inform. 1, 91–96 (2012). (in Russian)

    Google Scholar 

  11. Kendall, M., Stewart, A.: Statistical Conclusions and Connections, pp. 687–718. Nauka, Moscow (1973)

    Google Scholar 

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Bibikov, N.G., Makushevich, I.V. (2018). Comparison of Some Fractal Analysis Methods for Studying the Spontaneous Activity in Medullar Auditory Units. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research. NEUROINFORMATICS 2017. Studies in Computational Intelligence, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-66604-4_26

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  • DOI: https://doi.org/10.1007/978-3-319-66604-4_26

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