Shengjie Zheng1,2, Lang Qian3, Pingsheng Li4, Chenggang He2, Xiaoqi Qin5 and Xiaojian Li2, 1University of Chinese Academy of Sciences, China, 2Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen-Hong Kong & Chinese Academy of Sciences, China, 3Tsinghua University, China, 4McGill University, Canada, 5Beijing University of Posts and Telecommunications, China

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 summarizes the basic properties of artificial neural networks as well as spiking neural networks. Our focus is on the biological background and theoretical basis of spiking neurons, different neuronal models, and the connectivity of neural circuits. We also review the mainstream neural network learning mechanisms and network architectures. This review hopes to attract different researchers and advance the development of brain intelligence and artificial intelligence.

Spiking Neural Networks, Brain-Inspired Intelligence, Deep Neural Networks, Artificial Intelligence and Biological Intelligence.