ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval

doi:10.1088/1741-2552/ac5eb7

	ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval
	Wei, Wei1 ; Qiu, Shuang1 ; Zhang, Yukun1,2 ; Mao, Jiayu1,2 ; He, Huiguang1,3
发表期刊	JOURNAL OF NEURAL ENGINEERING
ISSN	1741-2560
	2022-04-01
卷号	19 期号:2 页码:17
通讯作者	He, Huiguang(huiguang.he@ia.ac.cn)
摘要	Objective. A rapid serial visual presentation (RSVP)-based brain-computer interface (BCI) is an efficient information detection technology through detecting event-related potentials (ERPs) evoked by target visual stimuli. The BCI system requires a time-consuming calibration process to build a reliable decoding model for a new user. Therefore, zero-calibration has become an important topic in BCI research. Approach. In this paper, we construct an RSVP dataset that includes 31 subjects, and propose a zero-calibration method based on a metric-based meta-learning: ERP prototypical matching net (EPMN). EPMN learns a metric space where the distance between electroencephalography (EEG) features and ERP prototypes belonging to the same category is smaller than that of different categories. Here, we employ prototype learning to learn a common representation from ERP templates of different subjects as ERP prototypes. Additionally, a metric-learning loss function is proposed for maximizing the distance between different classes of EEG and ERP prototypes and minimizing the distance between the same classes of EEG and ERP prototypes in the metric space. Main results. The experimental results showed that EPMN achieved a balanced-accuracy of 86.34% and outperformed the comparable methods. Significance. Our EPMN can realize zero-calibration for an RSVP-based BCI system.
关键词	EEG RSVP-based BCI zero-calibration meta-learning prototypical matching
DOI	10.1088/1741-2552/ac5eb7
关键词[WOS]	SERIAL VISUAL PRESENTATION ; MOTOR IMAGERY ; COMPUTER ; BCI ; POTENTIALS ; MODEL
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62020106015] ; National Natural Science Foundation of China[61976209] ; National Natural Science Foundation of China[U21A20388] ; CAS International Collaboration Key Project[173211KYSB20190024] ; Strategic Priority Research Program of CAS[XDB32040000] ; Beijing Natural Science Foundation[J210010]
项目资助者	National Natural Science Foundation of China ; CAS International Collaboration Key Project ; Strategic Priority Research Program of CAS ; Beijing Natural Science Foundation
WOS研究方向	Engineering ; Neurosciences & Neurology
WOS类目	Engineering, Biomedical ; Neurosciences
WOS记录号	WOS:000777811400001
出版者	IOP Publishing Ltd
七大方向——子方向分类	脑机接口
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48241
专题	脑图谱与类脑智能实验室_神经计算与脑机交互
通讯作者	He, Huiguang
作者单位	1.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Wei, Wei,Qiu, Shuang,Zhang, Yukun,et al. ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval[J]. JOURNAL OF NEURAL ENGINEERING,2022,19(2):17.
APA	Wei, Wei,Qiu, Shuang,Zhang, Yukun,Mao, Jiayu,&He, Huiguang.(2022).ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval.JOURNAL OF NEURAL ENGINEERING,19(2),17.
MLA	Wei, Wei,et al."ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval".JOURNAL OF NEURAL ENGINEERING 19.2(2022):17.