Implementation of Memristive Hodgkin-Huxley Neuron Model in Verilog HDL

Realizing neuronal networks at the circuit level requires understanding how the brain processes information and modeling neural circuits. This necessitates the realization of the Hodgkin-Huxley (HH) model to replicate the subtle and nonlinear dynamics of realistic biological neurons. This paper aims to implement and compare the dynamics of a traditional HH neuron model modelled using nonlinear differential equations with a highly nonlinear Memristive HH (MHH) model. Verilog HDL was employed to implement both models, and functional verification was conducted using Modelsim. The experimental results suggest that MHH exhibited high sensitivity to external disturbances, as evidenced by the increased rate of action notential discharge.