Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization

Wei，Chen1; Lou，Kexin1; Wang，Zhengyang2; Zhao，Mingqi3; Mantini，Dante3; Liu，Quanying1

10.1109/IJCNN52387.2021.9533968

2021-07-18

International Joint Conference on Neural Networks (IJCNN)

2161-4393

978-1-6654-4597-9

Proceedings of the International Joint Conference on Neural Networks

2021-July

1-8

JUL 18-22, 2021

null,null,ELECTR NETWORK

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

EEG source localization is an important technical issue in EEG analysis. Despite many numerical methods existed for EEG source localization, they all rely on strong priors and the deep sources are intractable. Here we propose a deep learning framework using spatial basis function decomposition for EEG source localization. This framework combines the edge sparsity prior and Gaussian source basis, called Edge Sparse Basis Network (ESBN). The performance of ESBN is validated by both synthetic data and real EEG data during motor tasks. The results suggest that the supervised ESBN outperforms the traditional numerical methods in synthetic data and the unsupervised fine-tuning provides more focal and accurate localizations in real data. Our proposed deep learning framework can be extended to account for other source priors, and the real-time property of ESBN can facilitate the applications of EEG in brain-computer interfaces and clinics.

deep learning edge sparsity EEG Inverse problem source localization

第一 ; 通讯

英语

CPCI-S ; EI

National Natural Science Foundation of China[62001205] ; Guangdong Natural Science Foundation Joint Fund[2019A1515111038] ; Shenzhen Key Laboratory of Smart Healthcare Engineering[ZDSYS20200811144003009]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Engineering, Electrical & Electronic

WOS:000722581705048

20214110995677

Brain computer interface ; Deep learning ; Inverse problems

Ergonomics and Human Factors Engineering:461.4 ; Computer Peripheral Equipment:722.2 ; Numerical Methods:921.6

2-s2.0-85116418201

Scopus

1.Southern University of Science and Technology,Shenzhen Key Laboratory of Smart Healthcare Engineering,Department of Biomedical Engineering,Shenzhen,China
2.Wake Forest School of Medicine,Department of Neurology and Anatomy,Winston-Salem,United States
3.Movement Control and Neuroplasticity Research Group,Ku Leuven,Leuven,Belgium

Wei，Chen,Lou，Kexin,Wang，Zhengyang,et al. Edge Sparse Basis Network: A Deep Learning Framework for EEG Source Localization[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:1-8.