Complexity · 2018 · 49 citations · 53 references
Life SciencesElectrical EngineeringNeuroscienceComputational NeuroscienceNeural CircuitryNeural EngineeringNeural Circuit DynamicsNeural Circuit ModelingNeural CircuitsNeural OscillationsNeuronal DynamicsSynaptic TransmissionChemical SynapsesElectrical SynapsesHopf BifurcationNeuron CouplingNeuron DynamicsNeuron SimulationsNeuronal OscillationsNumerical Simulation
The induced current produced by electromagnetic induction can adjust the membrane potential of neuron through the feedback of a magnetic flux‐controlled memristor. We adopt the numerical simulation method with the aim of investigating the synchronous behavior in the neuronal system that is coupled by chemical and electrical synapses under electromagnetic induction. Within the improved model, the effects of electromagnetic induction on neurons are described with additive memristive current on the membrane variable, and the memristive current is dependent on the variation of magnetic flow. The simulation results show that the two coupling modes play an important role in the synchronization of the system. By increasing the chemical synaptic feedback gain, we observe a transition from mixed oscillatory to periodic state at a critical value. In addition, two Hopf bifurcation points are found with the change of the external stimuli, and the state of neuron discharge is influenced by initial values. Furthermore, there is a domain of coupling strength and feedback gain values, in which the two coupled neuron system is synchronized and longer time lag is not conducive to the system synchronization.
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Memristor-The missing circuit element
Leon O. Chua · IEEE Transactions on Circuit Theory · 1971 · 10K citations
Memristive devices and systems
Leon O. Chua, Sung Mo Kang · Proceedings of the IEEE · 1976 · 2.6K citations
Voltage oscillations in the barnacle giant muscle fiber
Catherine E. Morris, Harold Lecar · Biophysical Journal · 1981 · 2.3K citations · Full text