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Review
. 2021 Aug;15(4):569-584.
doi: 10.1007/s11571-021-09676-z. Epub 2021 Apr 10.

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

Lichao Xu  1 , Minpeng Xu  1   2 , Tzyy-Ping Jung  1   2   3 , Dong Ming  1   2
Affiliations
Review

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

Lichao Xu et al. Cogn Neurodyn. 2021 Aug.

Erratum in

Abstract

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.

Keywords: BCI; Decoding algorithms; EEG; Encoding paradigms; Review.

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Conflict of interest statement

Conflict of interestThe authors declare that they have no conflict of interest.

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