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Editorial: Advances and challenges to bridge computational intelligence and neuroscience for brain-computer interface.

作者信息

Singh Avinash Kumar, Bianchi Luigi, Valeriani Davide, Nakanishi Masaki

机构信息

School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia.

Department of Civil Engineering and Computer Science Engineering, University of Rome Tor Vergata, Rome, Italy.

出版信息

Front Neuroergon. 2024 Aug 6;5:1461494. doi: 10.3389/fnrgo.2024.1461494. eCollection 2024.

DOI:10.3389/fnrgo.2024.1461494
PMID:39165885
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11333880/
Abstract
摘要

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本文引用的文献

1
Towards Bridging the Gap Between Computational Intelligence and Neuroscience in Brain-Computer Interfaces With a Common Description of Systems and Data.通过系统和数据的通用描述弥合脑机接口中计算智能与神经科学之间的差距
Front Neuroinform. 2021 Aug 23;15:699840. doi: 10.3389/fninf.2021.699840. eCollection 2021.
2
A comprehensive review of EEG-based brain-computer interface paradigms.基于脑电图的脑机接口范式的综合评述。
J Neural Eng. 2019 Feb;16(1):011001. doi: 10.1088/1741-2552/aaf12e. Epub 2018 Nov 15.
3
MOABB: trustworthy algorithm benchmarking for BCIs.MOABB：用于脑机接口的可信算法基准测试。
J Neural Eng. 2018 Dec;15(6):066011. doi: 10.1088/1741-2552/aadea0. Epub 2018 Sep 4.