mlsanityData to 7 Oct 2026

Recent Advances and New Frontiers in Spiking Neural Networks

arXiv 2204.07050 ↗First posted 12 Mar 2022cs.NE cs.AIcited by 10

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Abstract (arXiv)

In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding methods, and event-driven characteristics that naturally fit the neuromorphic hardware. With the development of SNNs, brain-inspired intelligence, an emerging research field inspired by brain science achievements and aiming at artificial general intelligence, is becoming hot. This paper reviews recent advances and discusses new frontiers in SNNs from five major research topics, including essential elements (i.e., spiking neuron models, encoding methods, and topology structures), neuromorphic datasets, optimization algorithms, software, and hardware frameworks. We hope our survey can help researchers understand SNNs better and inspire new works to advance this field.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 19 of its 78 references that are in the map. First posted on arXiv 12 Mar 2022.

Builds on

19 of 78 references.

References · 19

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networkscited by 829
  3. 2021Deep Residual Learning in Spiking Neural Networkscited by 326
  4. 2015Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccadescited by 308
  5. 2020Going Deeper With Directly-Trained Larger Spiking Neural Networkscited by 268
  6. 2018SLAYER: Spike Layer Error Reassignment in Timecited by 257
  7. 2018Going Deeper in Spiking Neural Networks: VGG and Residual Architecturescited by 236
  8. 2017SuperSpike: Supervised learning in multi-layer spiking neural networkscited by 178
  9. 2021Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networkscited by 134
  10. 2014How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagationcited by 77
  11. 2018BindsNET: A machine learning-oriented spiking neural networks library in Pythoncited by 42
  12. 2021Pruning of Deep Spiking Neural Networks through Gradient Rewiringcited by 41
7 more
  1. 2018A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rulecited by 36
  2. 2019SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per Neuroncited by 23
  3. 2021Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learningcited by 21
  4. 2020Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagationcited by 15
  5. 2018PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasingcited by 7
  6. 2022Motif-topology and Reward-learning improved Spiking Neural Network for Efficient Multi-sensory Integrationcited by 4
  7. 2021Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networkscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 4; 2024: 2; 2025: 0; 2026: 1.

10 papers.

  1. 2023Direct Learning-Based Deep Spiking Neural Networks: A Reviewcited by 31
  2. 2022Spiking Graph Convolutional Networkscited by 26
  3. 2024Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applicationscited by 7
  4. 2023Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunitiescited by 4
  5. 2022Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Networkcited by 3
  6. 2023Resource Constrained Model Compression via Minimax Optimization for Spiking Neural Networkscited by 3
  7. 2023Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transformscited by 2
  8. 2024Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networkscited by 2
  9. 2022Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neuronscited by 0
  10. 2026SDPAD: A Fully Spike-Driven Pipeline for End-to-End Autonomous Drivingcited by 0