Speaker
Description
Neuron excitation and generation of action potential can be simplified by using the FitzHugh–Nagumo (FHN) model [1]. Such models are not only required for understanding complex neural activity but also to predict and replicate in software and hardware [2]. Hardware emulation is indispensable for building brain computing platforms inspired by brain, medical devices and analyzing real time performances [3]. In this work, the coupled differential equations for the membrane potential and recovery potential are solved using electronic components comprising of integrators, linear and nonlinear amplifiers, adders etc. To accurately replicate the model dynamics, the individual components are optimized and the efficiency found out in terms of correlation with the theoretical model. The suitability of the electronic model is also tested by varying the FHN parameters like the time scale of recovery variable, the external stimuli, etc. The results show that the optimized circuit faithfully reproduces the FHN dynamics and provides a method for neural signal simulation and hardware emulation in future.
