mlsanityData to 7 Oct 2026

An Introductory Review of Spiking Neural Network and Artificial Neural Network: From Biological Intelligence to Artificial Intelligence

arXiv 2204.07519 ↗First posted 9 Apr 2022cs.NE cs.AIcited by 1

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Abstract (arXiv)

Recently, stemming from the rapid development of artificial intelligence, which has gained expansive success in pattern recognition, robotics, and bioinformatics, neuroscience is also gaining tremendous progress. A kind of spiking neural network with biological interpretability is gradually receiving wide attention, and this kind of neural network is also regarded as one of the directions toward general artificial intelligence. This review introduces the following sections, the biological background of spiking neurons and the theoretical basis, different neuronal models, the connectivity of neural circuits, the mainstream neural network learning mechanisms and network architectures, etc. This review hopes to attract different researchers and advance the development of brain-inspired intelligence and artificial intelligence.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 44 references that are in the map. First posted on arXiv 9 Apr 2022.

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3 of 44 references.

References · 3

  1. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,303
  2. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 604
  3. 2017Metaheuristic Design of Feedforward Neural Networks: A Review of Two Decades of Researchcited by 16

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