Large-Scale Cortical Network Analysis and Classification of MI-BCI Tasks Based on Bayesian Nonnegative Matrix Factorization-Reference-Cited by-同舟云学术

Large-Scale Cortical Network Analysis and Classification of MI-BCI Tasks Based on Bayesian Nonnegative Matrix Factorization

Published:2024 Issue: Volume:32 Page:2187-2197
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Yu Shiqi¹^ORCID,Mao Bin¹,Zhou Yuanhang¹,Liu Yunhong¹,Yi Chanlin²^ORCID,Li Fali²^ORCID,Yao Dezhong²^ORCID,Xu Peng²^ORCID,San Liang X.³,Zhang Tao¹^ORCID

Affiliation:

1. Mental Health Education Center and the School of Science, Xihua University, Chengdu, China

2. Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China

3. Artificial Intelligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

Funder

National Natural Science Foundation of China

Project of Southern Marine Science and Engineering Guangdong Laboratory

Sichuan Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7333/10398877/10550019.pdf?arnumber=10550019

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3. A Model Combining Multi Branch Spectral-Temporal CNN, Efficient Channel Attention, and LightGBM for MI-BCI Classification

4. Identification and analysis of autism spectrum disorder via large‐scale dynamic functional network connectivity

5. Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities