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International Conference of Artificial Intelligence, Medical Engineering, Education

AIMEE 2019: Advances in Artificial Systems for Medicine and Education III pp 241–252Cite as

Synchronization of Neural Ensembles in the Formation of Attention in the Brain

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1126))

Abstract

The method of studying the synchronization of relaxation self-oscillations, based on a modified axiomatic method and using the properties of uniform almost-periodic functions is used. A computational algorithm is used to study the synchronization of relaxation self-oscillations, using axiomatic algebraic models and properties of the theory of uniform almost periodic functions. It is shown that synchronization is a flexible and efficient process for shaping the attention of other cognitive processes to certain external informational influences. The five synchronization modes of neural ensembles of 100 peripheral neurons were investigated: asynchronous mode, full synchronization, partial synchronization, “incorrect” synchronization mode, transient phase-dynamic process. The complex synchronization regimes of relaxation self-oscillations are considered: “incorrect” synchronization, the presence of specific and “phase-dynamic” transient processes caused by the properties of uniform almost-periodic functions. Discussed the adequacy of the used mathematical computer model for the formation of attention.

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Authors and Affiliations

  1. Russian Economic University G.V. Plekhanova, Moscow, Russia

    M. Mazurov

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  1. M. Mazurov
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Correspondence to M. Mazurov .

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Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Davie, FL, USA

    Matthew He

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Mazurov, M. (2020). Synchronization of Neural Ensembles in the Formation of Attention in the Brain. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Medicine and Education III. AIMEE 2019. Advances in Intelligent Systems and Computing, vol 1126. Springer, Cham. https://doi.org/10.1007/978-3-030-39162-1_22

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