Mode selection in a neuron driven by Josephson junction current in presence of magnetic field |
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| Institution: | 1. School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China;2. Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China;3. School of Materials and Physics, China University of Mining and Technology, Xuzhou 221116, China;1. School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China;2. School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471000, China;1. Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China;2. School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China;1. School of Mathematics and Statistics, Northwestern Polytechnical University, Xi’an 710129, People’s Republic of China;2. College of Mathematics and Information Science, Shaan’xi Normal University, Xi’an 710062, People’s Republic of China;1. School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China;2. Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China |
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| Abstract: | Josephson junction is an active electric component and its channel current can be adjusted by external magnetic field, which can trigger additive phase error along the junction. From physical viewpoint, the Josephson junction can capture and release field energy when it is exposed to a magnetic field, and this time-varying current can be used to excite neural circuit for generating target firing patterns. In this paper, a Josephson junction is connected to a simple neural circuit, which is made of a capacitor, induction coil, a nonlinear resistor, two linear resistors and one constant voltage source in the branch, and the improved neural circuit is adjusted to percept external magnetic field and estimate the potential application of Josephson junction in nonlinear circuits. Bifurcation analysis is applied to explore the mode selection and dynamics dependence on parameters setting in the biophysical neural circuits. Furthermore, the neural circuit is exposed to external magnetic field and its physical effect is estimated by applying scale transformation on the variables and parameters in the neural circuit. It is confirmed that the neural circuit can be controlled and the neural activity shows distinct mode transition by taming the intensity (or angular frequency in periodic field) of external magnetic field. This kind of neural circuit can be further used as smart sensor for detecting weak magnetic field. |
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