Modeling synaptic plasticity of the FitzHugh-Nagumo neuron using memristive coupling elements.
Fediukov Danila E. student 1
Vadivasova Tatiana E., professor 1
1 Saratov State University, Russia, Institute of Physics, Chair of Radiophysics and Nonlinear Dynamics
Abstract
The FitzHugh-Nagumo oscillator (FHN) is the simplest oscillatory model of a neuron and its use in spiking neural networks seems promising. However, in the case of using FHN oscillators, problems arise in modeling the plasticity property associated with the shape of the spikes generated by the FHN oscillator. The solution to these problems may be the use of memristors. A memristor is a two-terminal network whose conductivity depends on a certain control variable inertially related to the input signal. Accordingly, the intensity of the memristive connection changes depending on the input signals.The work considers the possibility of using memristors to model the properties of synaptic plasticity. The spike activity of a postsynaptic neuron, which is affected by input neurons through a memristive connection with different characteristics, is studied.
Speaker
Fediukov Danila E.
Saratov State University, Institute of Physics, Chair of Radiophysics and Nonlinear Dynamics, student
Russia
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