Behavioral Control Of Electrical Activity Of A Class Of Functional Neurons

The main dynamic characteristics of the electrical activity pro cess of biological neurons can be realized through the modeling of neuron models and the simulation of corresponding nonlinear circuits.However,the research of functional neuron models and the design of artificial synapses connect ed neuron circuits are facing huge challenges.T his paper used Josephson junctions,memristors,capacitors,inductance coils,and electronic component resistances to design functional neuron models and hybrid synapses that sense changes in magnetic fields.By exploring the underl ying physical mechanism,it has important theoretical guiding significance for understanding the dynamic characteristics of biological neurons and complex biological systems.Specific research content and results include:(1)Construct a functional neuron model with external magnetic field response and study its dynamic characteristics.Based on the Fitz Hugh-Nagumo(FHN)neuron circuit model connected to a Josephson junction,the dynamic equations are established through standard scale transformation and th e dynamic characteristics of the external magnetic field response are studied by statistical analysis methods.The research results show that the additional phase error in the Josephson junction can change the current at both ends of the junction under the action of a magnetic field,thereby affecting the dynamic characteristics of neurons.In addition,it is found that under different external magnetic field conditions,a constant external magnetic field has a significant impact on the system mode conversi on and selection.T his conclusion may provide ideas for sensors that detect magnetic fields.(2)Using the inherent physical properties of Josephson junctions and memristors,a neuron model that is sensitive to electromagnetic induction and external magnet ic fields is constructed.A simple neural circuit is composed of capacitors,inductance coils,Josephson junctions,memristors,linear resistors and continuous voltage sources.Numerical simulation and statistical methods are used to study the dynamic characteristics of the neural circuit.It was found that different discharge modes in the neural circuit can be detected by changing the normalized parameters.By calculating Hamiltonian energy,the relationship between mode selection and energy release is explained from the energy point of view.Under the condition of external magnetic field,the neural circuit appears nonlinear resonance phenomenon.T his kind of neural circuit is helpful to further study the dynamic characteristics of neural network.(3)T he influence of the mixed synapse formed by Josephson structure on the synchronization stability of coupled neurons was studied.A hybrid synapse is constructed using Josephson junctions and resistors in parallel.The hybrid synapse is used to connect two FHN neuron circuits driven by two periodic signals.Numerical simulation and statistical analysis are used to explore the stability of the coupling and synchronization between the two neuron circuits.Studies have shown that: adjusting the selection parameter s of the Josephson junction in the coupling channel can achieve the synchronization of the two neuron circuits.Related researches provide useful guidance for the further design of artificial synapses and their use in neural circuit signal processing.Based on the above discussion,the functional neuron model and artificial synapse built using the Josephson structure not only provide research ideas for the dynamic characteristics of biological neurons and neural network research,but also design functional neuron circuits and artificial intelligence networks in neuroscience.The field has studied new ideas,which will help to further understand the brain and higher animal organs.