Ferroelectric FET-Based Implementation of FitzHugh-Nagumo Neuron Model

• Published in: IEEE transactions on computer-aided design of integrated circuits and systems 2022-07, Vol.41 (7), p.2107-2114
• Main Authors: Rajasekharan, Dinesh, Gaidhane, Amol, Trivedi, Amit Ranjan, Chauhan, Yogesh Singh
• Format: Article
• Language: English
• Subjects: Aspect ratio; Biological properties; Biological system modeling; Circuits; Computational modeling; Energy consumption; Excitation; FDSOI; FeFETs; ferroelectric; Ferroelectric materials; Ferroelectricity; Field effect transistors; FitzHugh-Nagumo neuron; Integrated circuit modeling; Mathematical model; MOSFET; neuromorphic computing; neuron; Neurons; Semiconductor devices; Transistors; winner-take-all (WTA)
• ISSN: 0278-0070; 1937-4151
• DOI: 10.1109/TCAD.2021.3101407

Ferroelectric field-effect transistor (FeFET)-based circuit implementation mimicking FitzHugh-Nagumo neuron is proposed in this work. The proposed circuit is shown to mimic biological neuron properties, such as excitation block and anodal break excitation which are not mimicked by an integrate and fire neuron model. We also show a winner-take-all circuit that can be used with this proposed neuron implementation. The neuron implementation requires just one FeFET, three baseline field-effect transistors, and one capacitor, making it area and energy-efficient. The neuron circuit, with minimum sized transistors, consumes approximately 10 pJ per spike. The neuron's energy consumption per spike can be reduced to as low as 100 fJ by designing some of the transistors with aspect ratio less than one.