Brain-computer interface paradigms and neural coding

Pengrui Tai; Pengrui Tai; Peng Ding; Peng Ding; Fan Wang; Fan Wang; Anmin Gong; Tianwen Li; Tianwen Li; Lei Zhao; Lei Zhao; Lei Su; Lei Su; Yunfa Fu; Yunfa Fu

doi:10.3389/fnins.2023.1345961

Frontiers in Neuroscience (Jan 2024)

Brain-computer interface paradigms and neural coding

Pengrui Tai,
Pengrui Tai,
Peng Ding,
Peng Ding,
Fan Wang,
Fan Wang,
Anmin Gong,
Tianwen Li,
Tianwen Li,
Lei Zhao,
Lei Zhao,
Lei Su,
Lei Su,
Yunfa Fu,
Yunfa Fu

Affiliations

Pengrui Tai: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Pengrui Tai: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Peng Ding: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Peng Ding: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Fan Wang: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Fan Wang: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Anmin Gong: School of Information Engineering, Chinese People’s Armed Police Force Engineering University, Xi’an, China
Tianwen Li: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Tianwen Li: Faculty of Science, Kunming University of Science and Technology, Kunming, China
Lei Zhao: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Lei Zhao: Faculty of Science, Kunming University of Science and Technology, Kunming, China
Lei Su: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Lei Su: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
Yunfa Fu: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Yunfa Fu: Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China

DOI: https://doi.org/10.3389/fnins.2023.1345961
Journal volume & issue: Vol. 17

Abstract

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Brain signal patterns generated in the central nervous system of brain-computer interface (BCI) users are closely related to BCI paradigms and neural coding. In BCI systems, BCI paradigms and neural coding are critical elements for BCI research. However, so far there have been few references that clearly and systematically elaborated on the definition and design principles of the BCI paradigm as well as the definition and modeling principles of BCI neural coding. Therefore, these contents are expounded and the existing main BCI paradigms and neural coding are introduced in the review. Finally, the challenges and future research directions of BCI paradigm and neural coding were discussed, including user-centered design and evaluation for BCI paradigms and neural coding, revolutionizing the traditional BCI paradigms, breaking through the existing techniques for collecting brain signals and combining BCI technology with advanced AI technology to improve brain signal decoding performance. It is expected that the review will inspire innovative research and development of the BCI paradigm and neural coding.

Published in Frontiers in Neuroscience

ISSN: 1662-4548 (Print); 1662-453X (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: http://www.frontiersin.org/neuroscience

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