Neural Decoding for Intracortical Brain-Computer Interfaces

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Neural Decoding for Intracortical Brain-Computer Interfaces. / Dong, Yuanrui; Wang, Shirong; Huang, Qiang; Berg, Rune W.; Li, Guanghui; He, Jiping.

In: Cyborg and Bionic Systems, Vol. 4, 0044, 2023.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Dong, Y, Wang, S, Huang, Q, Berg, RW, Li, G & He, J 2023, 'Neural Decoding for Intracortical Brain-Computer Interfaces', Cyborg and Bionic Systems, vol. 4, 0044. https://doi.org/10.34133/cbsystems.0044

APA

Dong, Y., Wang, S., Huang, Q., Berg, R. W., Li, G., & He, J. (2023). Neural Decoding for Intracortical Brain-Computer Interfaces. Cyborg and Bionic Systems, 4, [0044]. https://doi.org/10.34133/cbsystems.0044

Vancouver

Dong Y, Wang S, Huang Q, Berg RW, Li G, He J. Neural Decoding for Intracortical Brain-Computer Interfaces. Cyborg and Bionic Systems. 2023;4. 0044. https://doi.org/10.34133/cbsystems.0044

Author

Dong, Yuanrui ; Wang, Shirong ; Huang, Qiang ; Berg, Rune W. ; Li, Guanghui ; He, Jiping. / Neural Decoding for Intracortical Brain-Computer Interfaces. In: Cyborg and Bionic Systems. 2023 ; Vol. 4.

Bibtex

@article{8824b774080145069a73af8a3eda9bbe,
title = "Neural Decoding for Intracortical Brain-Computer Interfaces",
abstract = "Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.",
author = "Yuanrui Dong and Shirong Wang and Qiang Huang and Berg, {Rune W.} and Guanghui Li and Jiping He",
note = "Publisher Copyright: Copyright {\textcopyright} 2023 Yuanrui Dong et al. Exclusive licensee Beijing Institute of Technology Press. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0).",
year = "2023",
doi = "10.34133/cbsystems.0044",
language = "English",
volume = "4",
journal = "Cyborg and Bionic Systems",
issn = "2097-1087",
publisher = "American Association for the Advancement of Science",

}

RIS

TY - JOUR

T1 - Neural Decoding for Intracortical Brain-Computer Interfaces

AU - Dong, Yuanrui

AU - Wang, Shirong

AU - Huang, Qiang

AU - Berg, Rune W.

AU - Li, Guanghui

AU - He, Jiping

N1 - Publisher Copyright: Copyright © 2023 Yuanrui Dong et al. Exclusive licensee Beijing Institute of Technology Press. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY 4.0).

PY - 2023

Y1 - 2023

N2 - Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.

AB - Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.

U2 - 10.34133/cbsystems.0044

DO - 10.34133/cbsystems.0044

M3 - Journal article

C2 - 37519930

AN - SCOPUS:85169605774

VL - 4

JO - Cyborg and Bionic Systems

JF - Cyborg and Bionic Systems

SN - 2097-1087

M1 - 0044

ER -

ID: 366988448