Biologically Inspired Tonic and Bursting LIF Neuron Model for Spiking Neural Network: A CMOS Implementation

Abstract

The core part of the neuromorphic processors enti-tled as spiking neural network (SNN), which is more biologicallyplausible than ANN, where the signal is propagated in the form ofa spike. This perception seeks to create hardware systems thatresemble the brain in both shape and function; these systemsare comprised of artificial bio-neurons and synapses and can bescaled to the size of the brain. Many researchers have developedvarious bio-plausible neuron models to attain precise neuronvalues. This paper proposes a sub-threshold implementation ofthe Leaky Integrate and Fire (LIF) neuron model, which emulatesthe spiking behavior which is generally observed in biology.The models comprise analog and mixed (Analog and Digital)circuits that mimic biological spiking behaviors and exhibit bio-electric potential differences. The neuron models are simulatedin Cadence Virtuoso GPDK 45nm Technology and the multi-sim simulator powered by National Instruments to understandthe different spiking behaviors. The spike pulses with differentshapes and magnitudes, which are the functions of membranepotential and also applicable to realize the spiking behavior ofSNNs. The proposed neuron model operates at 1V power and 1msstep pulse, where it consumes less power (4.377μW ) and minimalenergy (761.146f J) per spike. The measured spike pulse widthstands at 15.823μs, while the refractory time period of the pulseis determined to be 57.795μs. The proposed model also comparedwith popular models like Hodgkin-Huxley and Izhikevich modelsin terms of the spike pattern.