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Control the collective behaviors in a functional neural network

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  • Yao, Zhao
  • Wang, Chunni

Abstract

Specific biophysical neurons are presented to detect different stimuli, and these external exciting signals are encoded to trigger appropriate firing modes and action potentials for signal propagation between neurons in the network. A thermosensitive neuron can estimate the effect of temperature changes on the excitability and firing modes in nervous system, a photocurrent-dependent neuron can be sensitive to the changes of external illumination or light, and an auditory neuron can perceive acoustic wave when the vibration energy is absorbed and converted into field energy in the loop of neural circuits. From biophysical viewpoint, some specific electric components such as thermistor, phototube, and piezoelectric ceramics can be incorporated into neural circuits for activating specific functions, and thus the external stimuli such as heat, light and vibration can be detected because these energy injections can be converted to intrinsic field energy in the neural circuits. In this paper, three kinds of different neural circuits are coupled in a close loop, energy pumping and the stability of phase synchronization are investigated by regulating the properties of coupling channels, furthermore, the noise effect is also estimated. When induction coil is used to couple the neural circuits, phase stability is controlled under magnetic field coupling, and the activation of noise can change the stability of phase synchronization. The intrinsic field energy in the light-dependent neuron is increased with the increase of coupling intensity when voltage coupling via resistor and magnetic field coupling via induction coil are switched on. In case of electric field coupling via capacitor, the energy in the light-dependent neural circuit keeps oscillatory with small amplitude. These results indicate that magnetic field can be the most suitable way for realizing synchronous information encoding between different functional neurons than the electric synapse coupling because continuous pumping of ions can induce magnetic field in the cell, and all the neurons are controlled completely by effective pumping in field energy.

Suggested Citation

  • Yao, Zhao & Wang, Chunni, 2021. "Control the collective behaviors in a functional neural network," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007153
    DOI: 10.1016/j.chaos.2021.111361
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    References listed on IDEAS

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    1. Mostaghimi, Soudeh & Nazarimehr, Fahimeh & Jafari, Sajad & Ma, Jun, 2019. "Chemical and electrical synapse-modulated dynamical properties of coupled neurons under magnetic flow," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 42-56.
    2. Chunni Wang & Shengli Guo & Ying Xu & Jun Ma & Jun Tang & Faris Alzahrani & Aatef Hobiny, 2017. "Formation of Autapse Connected to Neuron and Its Biological Function," Complexity, Hindawi, vol. 2017, pages 1-9, February.
    3. Zhou, Ping & Yao, Zhao & Ma, Jun & Zhu, Zhigang, 2021. "A piezoelectric sensing neuron and resonance synchronization between auditory neurons under stimulus," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    4. Olga Dyakova & Yu-Jen Lee & Kit D. Longden & Valerij G. Kiselev & Karin Nordström, 2015. "A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
    5. Yao, Zhao & Zhou, Ping & Alsaedi, Ahmed & Ma, Jun, 2020. "Energy flow-guided synchronization between chaotic circuits," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    6. Xu, Ying & Guo, Yeye & Ren, Guodong & Ma, Jun, 2020. "Dynamics and stochastic resonance in a thermosensitive neuron," Applied Mathematics and Computation, Elsevier, vol. 385(C).
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    Cited by:

    1. Wu, Fuqiang & Kang, Ting & Shao, Yan & Wang, Qingyun, 2023. "Stability of Hopfield neural network with resistive and magnetic coupling," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    2. Wu, Fuqiang & Guo, Yitong & Ma, Jun & Jin, Wuyin, 2023. "Synchronization of bursting memristive Josephson junctions via resistive and magnetic coupling," Applied Mathematics and Computation, Elsevier, vol. 455(C).
    3. Fossi, Jules Tagne & Njitacke, Zeric Tabekoueng & Tankeu, William Nguimeya & Mendimi, Joseph Marie & Awrejcewicz, Jan & Atangana, Jacques, 2023. "Phase synchronization and coexisting attractors in a model of three different neurons coupled via hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

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