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Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges.

Jianshi TangFang YuanXinke ShenZhongrui WangMingyi RaoYuanyuan HeYuhao SunXinyi LiWenbin ZhangYijun LiBin GaoHe QianGuoqiang BiSen SongJ Joshua YangHuaqiang Wu
Published in: Advanced materials (Deerfield Beach, Fla.) (2019)
As the research on artificial intelligence booms, there is broad interest in brain-inspired computing using novel neuromorphic devices. The potential of various emerging materials and devices for neuromorphic computing has attracted extensive research efforts, leading to a large number of publications. Going forward, in order to better emulate the brain's functions, its relevant fundamentals, working mechanisms, and resultant behaviors need to be re-visited, better understood, and connected to electronics. A systematic overview of biological and artificial neural systems is given, along with their related critical mechanisms. Recent progress in neuromorphic devices is reviewed and, more importantly, the existing challenges are highlighted to hopefully shed light on future research directions.
Keyphrases
  • artificial intelligence
  • neural network
  • machine learning
  • big data
  • resting state
  • white matter
  • deep learning
  • functional connectivity
  • current status
  • risk assessment
  • climate change