Review of brain encoding and decoding mechanisms for EEG-based brain–computer interface

A brain–computer interface (BCI) can connect humans and machines directly and has achieved successful applications in the past few decades. Many new BCI paradigms and algorithms have been developed in recent years. Therefore, it is necessary to review new progress in BCIs. This paper summarizes prog...

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Bibliographic Details
Published in:Cognitive neurodynamics Vol. 15; no. 4; pp. 569 - 584
Main Authors: Xu, Lichao, Xu, Minpeng, Jung, Tzyy-Ping, Ming, Dong
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.08.2021
Springer Nature B.V
Subjects:
Accuracy
Algorithms
Artificial Intelligence
Biochemistry
Biomedical and Life Sciences
Biomedicine
Brain
Coding
Cognition
Cognitive Psychology
Computer applications
Computer Science
Deep learning
Design
EEG
Elbow
Electroencephalography
Human-computer interface
Implants
Machine learning
Neurosciences
Paradigms
Review Paper
Reviews
Transfer learning
BCI
Review
EEG
Decoding algorithms
Encoding paradigms
ISSN:1871-4080, 1871-4099
Online Access:Get full text
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Summary:A brain–computer interface (BCI) can connect humans and machines directly and has achieved successful applications in the past few decades. Many new BCI paradigms and algorithms have been developed in recent years. Therefore, it is necessary to review new progress in BCIs. This paper summarizes progress for EEG-based BCIs from the perspective of encoding paradigms and decoding algorithms, which are two key elements of BCI systems. Encoding paradigms are grouped by their underlying neural meachanisms, namely sensory- and motor-related, vision-related, cognition-related and hybrid paradigms. Decoding algorithms are reviewed in four categories, namely decomposition algorithms, Riemannian geometry, deep learning and transfer learning. This review will provide a comprehensive overview of both modern primary paradigms and algorithms, making it helpful for those who are developing BCI systems.
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ISSN:1871-4080
1871-4099
DOI:10.1007/s11571-021-09676-z