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Theoretical background and experimental measurements of human brain noise intensity in perception of ambiguous images

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  • Runnova, Anastasiya E.
  • Hramov, Alexander E.
  • Grubov, Vadim V.
  • Koronovskii, Alexey A.
  • Kurovskaya, Maria K.
  • Pisarchik, Alexander N.

Abstract

We propose a theoretical approach associated with an experimental technique to quantitatively characterize cognitive brain activity in the perception of ambiguous images. Based on the developed theoretical background and the obtained experimental data, we introduce the concept of effective noise intensity characterizing cognitive brain activity and propose the experimental technique for its measurement. The developed theory, using the methods of statistical physics, provides a solid experimentally approved basis for further understanding of brain functionality. The rather simple way to measure the proposed quantitative characteristic of the brain activity related to the interpretation of ambiguous images will hopefully become a powerful tool for physicists, physiologists and medics. Our theoretical and experimental findings are in excellent agreement with each other.

Suggested Citation

  • Runnova, Anastasiya E. & Hramov, Alexander E. & Grubov, Vadim V. & Koronovskii, Alexey A. & Kurovskaya, Maria K. & Pisarchik, Alexander N., 2016. "Theoretical background and experimental measurements of human brain noise intensity in perception of ambiguous images," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 201-206.
    • Handle: RePEc:eee:chsofr:v:93:y:2016:i:c:p:201-206
    DOI: 10.1016/j.chaos.2016.11.001
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    References listed on IDEAS

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    1. Guido Gigante & Maurizio Mattia & Jochen Braun & Paolo Del Giudice, 2009. "Bistable Perception Modeled as Competing Stochastic Integrations at Two Levels," PLOS Computational Biology, Public Library of Science, vol. 5(7), pages 1-9, July.
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    Cited by:

    1. Andreev, Andrey V. & Makarov, Vladimir V. & Runnova, Anastasija E. & Pisarchik, Alexander N. & Hramov, Alexander E., 2018. "Coherence resonance in stimulated neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 80-85.
    2. Moskalenko, Olga I. & Koronovskii, Alexey A. & Zhuravlev, Maksim O. & Hramov, Alexander E., 2018. "Characteristics of noise-induced intermittency," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 269-275.
    3. Andreev, Andrey V. & Ivanchenko, Mikhail V. & Pisarchik, Alexander N. & Hramov, Alexander E., 2020. "Stimulus classification using chimera-like states in a spiking neural network," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).

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