A feasible neuron for estimating the magnetic field effect
Autor: | Zhao Yao, Ying Xu, Yin Zhang, Jun Ma |
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Rok vydání: | 2020 |
Předmět: |
Physics
Josephson effect Quantitative Biology::Neurons and Cognition Applied Mathematics Mechanical Engineering Aerospace Engineering Ocean Engineering Biological neuron model Memristor 01 natural sciences law.invention Magnetic field Control and Systems Engineering law visual_art Nonlinear resonance 0103 physical sciences Electronic component visual_art.visual_art_medium Biological neural network Electrical and Electronic Engineering Biological system 010301 acoustics Energy (signal processing) |
Zdroj: | Nonlinear Dynamics. 102:1849-1867 |
ISSN: | 1573-269X 0924-090X |
Popis: | Biological neurons are capable of encoding a variety of stimuli, and the synaptic plasticity can be enhanced for activating appropriate firing modes in the neural activities. Artificial neural circuits are effective to reproduce the main biophysical properties of neurons when the nonlinear circuits composed of reliable electronic components with distinct physical properties are tamed to generate similar firing patterns as biological neurons. In this paper, a simple neural circuit is proposed to estimate the effect of magnetic field on the neural activities by incorporating two physical electronic components. A magnetic flux-controlled memristor and an ideal Josephson junction in parallel connection are used to percept the induction currents induced by the magnetic field. The circuit equations are obtained according to the Kirchhoff’s theorem and an equivalent neuron model is acquired by applying scale transformation on the physical variables and parameters in the neural circuit. Standard bifurcation analysis is calculated to predict possible mode transition and evolution of firing patterns. The Hamilton energy is also obtained to find its dependence on the mode selection in electronic activities. Furthermore, External magnetic field is applied to estimate the mode transition of neural activities because the phase error and the junction current across the Josephson junction can be adjusted to change the dynamics of the neural circuit. It is found that the biophysical functional neuron can present rapid and sensitive response to external magnetic field. Nonlinear resonance is obtained when stochastic phase error is induced by external time-varying magnetic field. The neural circuit can be suitable for further calculating the collective behaviors of neurons exposed to magnetic field. |
Databáze: | OpenAIRE |
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