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Impact of Astrocytic Coverage of Synapses on the Short-Term Memory of a Computational Neuron-Astrocyte Network

Author

Listed:
  • Zonglun Li

    (Department of Mathematics, University College London, London WC1E 6BT, UK
    Institute for Women’s Health, University College London, London WC1E 6BT, UK)

  • Yuliya Tsybina

    (Department of Neurotechnology, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
    World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov University, 119991 Moscow, Russia)

  • Susanna Gordleeva

    (Department of Neurotechnology, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
    Neuroscience Research Institute, Samara State Medical University, 443099 Samara, Russia)

  • Alexey Zaikin

    (Department of Mathematics, University College London, London WC1E 6BT, UK
    Institute for Women’s Health, University College London, London WC1E 6BT, UK
    Department of Neurotechnology, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
    World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov University, 119991 Moscow, Russia)

Abstract

Working memory refers to the capability of the nervous system to selectively retain short-term memories in an active state. The long-standing viewpoint is that neurons play an indispensable role and working memory is encoded by synaptic plasticity. Furthermore, some recent studies have shown that calcium signaling assists the memory processes and the working memory might be affected by the astrocyte density. Over the last few decades, growing evidence has also revealed that astrocytes exhibit diverse coverage of synapses which are considered to participate in neuronal activities. However, very little effort has yet been made to attempt to shed light on the potential correlations between these observations. Hence, in this article, we leverage a computational neuron–astrocyte model to study the short-term memory performance subject to various astrocytic coverage and we demonstrate that the short-term memory is susceptible to this factor. Our model may also provide plausible hypotheses for the various sizes of calcium events as they are reckoned to be correlated with the astrocytic coverage.

Suggested Citation

  • Zonglun Li & Yuliya Tsybina & Susanna Gordleeva & Alexey Zaikin, 2022. "Impact of Astrocytic Coverage of Synapses on the Short-Term Memory of a Computational Neuron-Astrocyte Network," Mathematics, MDPI, vol. 10(18), pages 1-20, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3275-:d:910891
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    References listed on IDEAS

    as
    1. Victor Kazantsev & Susan Gordleeva & Sergey Stasenko & Alexander Dityatev, 2012. "A Homeostatic Model of Neuronal Firing Governed by Feedback Signals from the Extracellular Matrix," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-12, July.
    2. Makovkin, S Yu & Shkerin, I V & Gordleeva, S Yu & Ivanchenko, M V, 2020. "Astrocyte-induced intermittent synchronization of neurons in a minimal network," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    3. Zhang, Hai & Cheng, Jingshun & Zhang, Hongmei & Zhang, Weiwei & Cao, Jinde, 2021. "Quasi-uniform synchronization of Caputo type fractional neural networks with leakage and discrete delays★," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. Zhang, Hai & Cheng, Yuhong & Zhang, Hongmei & Zhang, Weiwei & Cao, Jinde, 2022. "Hybrid control design for Mittag-Leffler projective synchronization on FOQVNNs with multiple mixed delays and impulsive effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 341-357.
    5. Zhang, Hai & Ye, Miaolin & Ye, Renyu & Cao, Jinde, 2018. "Synchronization stability of Riemann–Liouville fractional delay-coupled complex neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 155-165.
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