An Ultralow-Power CMOS Integrated and Fire Neuron for Neuromorphic Computing

Abstract

Very large-scale integration (VLSI) implementations of spiking neurons are vital for a range of applications, from high-speed modeling of large neural systems to real-time behavioral systems and bidirectional brain-machine interfaces. The circuit solution utilized to implement the silicon neuron is determined by the application’s needs. This paper describes an ultralow-power analog circuit for realizing a leaky integrate and fire neuron model. The suggested circuit comprises parts for executing spike-frequency adaptation and modifying the neuron’s threshold voltage, in addition to being designed for low-power consumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.