Exp Neurobiol.  2018 Dec;27(6):453-471. 10.5607/en.2018.27.6.453.

Implantable Neural Probes for Brain-Machine Interfaces – Current Developments and Future Prospects

  • 1Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (DGMIF), Daegu 41061, Korea.
  • 2Department of Medical Science, College of Medicine, Catholic Kwandong University, Gangneung 25601, Korea. jsohn@ish.ac.kr
  • 3Biomedical Research Institute, Catholic Kwandong University International St. Mary's Hospital, Incheon 21711, Korea.
  • 4Laboratory Animal Center, Daegu-Gyeongbuk Medical Innovation Foundation (DGMIF), Daegu 41061, Korea.
  • 5Department of Human Factors Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Korea.


A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings. Specifically, we focus on three key topics: (1) novel implantable neural probes that decrease the level of invasiveness without sacrificing performance, (2) multi-modal neural probes that measure both electrical and optical signals, (3) and neural probes developed using advanced materials. Because safety and precision are critical for practical applications of BMI systems, future studies should aim to enhance these properties when developing next-generation neural probes.


Implantable neural probes; Brain-machine interface; Multi-channel electrodes; Neural probes with advanced materials

MeSH Terms

Brain-Computer Interfaces*
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