The combination of brain-computer interfaces and artificial intelligence: applications and challenges

Xiayin Zhang, Ziyue Ma, Huaijin Zheng, Tongkeng Li, Kexin Chen, Xun Wang, Chenting Liu, Linxi Xu, Xiaohang Wu, Duoru Lin, Haotian Lin


Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BCI applications with AI assistance have emerged. These “smart” BCIs including motor and sensory BCIs have shown notable clinical success, improved the quality of paralyzed patients’ lives, expanded the athletic ability of common people and accelerated the evolution of robots and neurophysiological discoveries. However, despite technological improvements, challenges remain with regard to the long training periods, real-time feedback, and monitoring of BCIs. In this article, the authors review the current state of AI as applied to BCIs and describe advances in BCI applications, their challenges and where they could be headed in the future.

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