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Development of a neural interface for high-definition, long-term recording in rodents and nonhuman primates.

Authors :
Chiang, Chia-Han
Won, Sang Min
Orsborn, Amy L.
Yu, Ki Jun
Trumpis, Michael
Bent, Brinnae
Wang, Charles
Xue, Yeguang
Min, Seunghwan
Woods, Virginia
Yu, Chunxiu
Kim, Bong Hoon
Kim, Sung Bong
Huq, Rizwan
Li, Jinghua
Seo, Kyung Jin
Vitale, Flavia
Richardson, Andrew
Fang, Hui
Huang, Yonggang
Source :
Science Translational Medicine; 4/8/2020, Vol. 12 Issue 538, p1-12, 12p
Publication Year :
2020

Abstract

Recording in high resolution: Recording large number of neural signals in real time with high definition for long periods of time is necessary for understanding brain physiology and disease pathophysiology. Unfortunately, current brain interface devices only allow recordings of small brain areas with limited number of electrodes. Here, Chiang et al. developed a neural interface device, called Neural Matrix, that allowed stable in vivo neural recordings with high throughput in rodents and nonhuman primates. The system provided stable recordings projected to last for 6 years after implantation. The Neural Matrix will be useful for the study of brain physiology in preclinical setting and might be scalable to humans for clinical purposes. Long-lasting, high-resolution neural interfaces that are ultrathin and flexible are essential for precise brain mapping and high-performance neuroprosthetic systems. Scaling to sample thousands of sites across large brain regions requires integrating powered electronics to multiplex many electrodes to a few external wires. However, existing multiplexed electrode arrays rely on encapsulation strategies that have limited implant lifetimes. Here, we developed a flexible, multiplexed electrode array, called "Neural Matrix," that provides stable in vivo neural recordings in rodents and nonhuman primates. Neural Matrix lasts over a year and samples a centimeter-scale brain region using over a thousand channels. The long-lasting encapsulation (projected to last at least 6 years), scalable device design, and iterative in vivo optimization described here are essential components to overcoming current hurdles facing next-generation neural technologies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19466234
Volume :
12
Issue :
538
Database :
Complementary Index
Journal :
Science Translational Medicine
Publication Type :
Academic Journal
Accession number :
142600723
Full Text :
https://doi.org/10.1126/scitranslmed.aay4682