Artificial Neurons

Shriram Ramanathan; Abhronil Sengupta

doi:10.1017/9781009564335.005

4 - Artificial Neurons

Published online by Cambridge University Press: 01 January 2026

Shriram Ramanathan and

Abhronil Sengupta

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Shriram Ramanathan: Affiliation:
Rutgers University, New Jersey
Abhronil Sengupta: Affiliation:
Pennsylvania State University

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Summary

The chapter begins with physics and mathematical description of the nonlinear dynamics seen in biological neurons and their adaptation into neuromorphic hardware. Various abstractions of the Hodgkin–Huxley model of squid neuron have been studied in neuromorphic computing. Filamentary threshold switches that can act as neurons are discussed. The combination of ionic and electronic relaxation pathways offers unique abilities to design low-power artificial neurons. Ferroelectric, insulator–metal transition, 2D materials, and organic semiconductor-based neurons are discussed wherein modulation of long-range transport and/or bound charge displacement are utilized for neuron function. Besides electron transport, light and spin state can also be effectively utilized to create photonic and spintronic neurons respectively. The chapter should provide the reader a comprehensive insight into design of artificial neurons that can generate action potentials, spanning various classes of inorganic and organic semiconductors, and different stimuli for input and readout of signals such as voltage, light, spin current, and ionic currents.

Keywords

artificial neurons leaky-integrate-fire neuron action potential photonic neuron spintronic neuron IMT neuron phase-change neuron phase transition silicon neuron CMOS neuron 2D neuron layered semiconductor photonic neuron spintronic neuron ferroelectric neuron tunnel junction phase change

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Type: Chapter
Information: Introduction to Neuromorphic Computing , pp. 77 - 112

DOI: https://doi.org/10.1017/9781009564335.005 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2026

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