A feasible neuron for estimating the magnetic field effect
- PDF / 4,123,036 Bytes
- 19 Pages / 547.087 x 737.008 pts Page_size
- 37 Downloads / 201 Views
(0123456789().,-volV) ( 01234567 89().,-volV)
ORIGINAL PAPER
A feasible neuron for estimating the magnetic field effect Yin Zhang . Ying Xu . Zhao Yao . Jun Ma
Received: 10 June 2020 / Accepted: 28 September 2020 Ó Springer Nature B.V. 2020
Abstract 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 fluxcontrolled 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.
Y. Zhang Y. Xu Z. Yao J. Ma (&) Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China e-mail: [email protected]; [email protected] Y. Xu School of Mathematics and Statistics, Shandong Normal University, Ji’nan 250014, China J. Ma School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China
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. Keywords Bifurcation Magnetic field Memristor Josephson junction Coherence resonance
1 Introduction The nervous system is made of a variety of functional neurons, which are developed to percept different stimuli, and thus appropriate firing patterns are generated during the activation of synapse function. Inspired by the pioneering works [1–4] finished by Hodgkin–Huxley in 1952, the main dynamical
123
Y. Zhang et al.
properties in neural activities of neurons have been discussed in many extended neuron models [5–10]. Based on these theoretical models, standard bifurcation analysis is often carried out and potential mode
Data Loading...
