Identify of Spatial Similarity of Electroencephalography (EEG) during Working-Memory Maintenance

被引：0

作者：

Song, Yufan ^{[1
]}

Zhang, ZhiHong ^{[1
]}

Hu, Te ^{[1
]}

Gong, Xiaoliang ^{[1
]}

Nandi, Asoke K. ^{[1
,2
]}

机构：

[1] Tongji Univ, Coll Elect & Informat Engn, Shanghai, Peoples R China

[2] Brunel Univ London, Dept Elect & Comp Engn, Uxbridge, Middx, England

来源：

2019 27TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2019年

基金：

美国国家科学基金会;

关键词：

Consensus clustering; data-driven; spatial similarity; working memory maintenance; EEG;

D O I：

10.23919/eusipco.2019.8902595

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Working memory maintenance is one of the important procedures during working memory storage into long-term memory. This paper utilizes consensus clustering to analyze the spatial similarity amongst whole brain regions during working-memory maintenance processing with 128 channels of scalp Electroencephalography (EEG) records. This paper sets the methodology research to extract the similarity of spatial information processing on the larger brain system during working memory maintenance based on a data-driven method. Based on group analysis of 20 subjects, the EEG channels with similarities are extracted to illustrate the functional brain connectivity of material-specific memory maintenance. The power of alpha frequency band (8-12Hz) appears to provide the discriminative information of the material-specific memory maintenance.

引用

页数：5

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