Spiking neural networks: history, current status and the future

Article

Huyck, C. 2026. Spiking neural networks: history, current status and the future. Dynamics. 6 (1). https://doi.org/10.3390/dynamics6010010

ISSN
Type	Article
Title	Spiking neural networks: history, current status and the future
Authors	Huyck, C.
Abstract	Simulated spiking neural networks have been explored for over a hundred years. Many of these networks are driven by biological considerations and an attempt to simulate brains, but others are used with little biological consideration. This paper gives some history of the development of spiking neural models, and their use for modelling biological and cognitive phenomena, and for machine learning. It introduces the current state of the art in computational biological neuron and synapse modelling, and plasticity. It introduces and reviews balanced spiking networks, and their engineering applications. Spiking networks are also used for machine learning, with the hope that their implementation on neuromorphic hardware will bring an energy and time savings. Similarly, neuromorphic hardware can enable massive parallelism, supporting larger spiking networks. The use of spiking nets for machine learning, both with biologically plausible models and without, is discussed showing that effective models already exist. The paper concludes with some notes about implementing spiking nets and a discussion including open questions and future work.
Keywords	Spiking Neurons; Balanced Networks; Biological Models
Sustainable Development Goals	9 Industry, innovation and infrastructure
Middlesex University Theme	Sustainability
Research Group	Artificial Intelligence group
Publisher	MDPI
Journal	Dynamics
Electronic	2673-8716
Publication dates
Online	17 Mar 2026
Print	Mar 2026
Publication process dates
Submitted	06 Feb 2026
Accepted	13 Mar 2026
Deposited	13 Mar 2026
Output status	Published
Publisher's version	dynamics-06-00010.pdf License CC BY 4.0 File Access Level Open
Copyright Statement	Copyright © 2026 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Digital Object Identifier (DOI)	https://doi.org/10.3390/dynamics6010010
Language	English

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