BENEFITS OF MULTI-DOMAIN FEATURE OF MISMATCH NEGATIVITY EXTRACTED BY NON-NEGATIVE TENSOR FACTORIZATION FROM EEG COLLECTED BY LOW-DENSITY ARRAY

被引：54

作者：

Cong, Fengyu ^{[1
]}

Anh Huy Phan ^{[2
]}

Zhao, Qibin ^{[2
]}

Huttunen-Scott, Tiina ^{[3
]}

Kaartinen, Jukka ^{[3
]}

Ristaniemi, Tapani ^{[1
]}

Lyytinen, Heikki ^{[3
]}

Cichocki, Andrzej ^{[2
]}

机构：

[1] Univ Jyvaskyla, Dept Math Informat Technol, SF-40351 Jyvaskyla, Finland

[2] RIKEN Brain Sci Inst, Lab Adv Brain Signal Proc, Wako, Saitama, Japan

[3] Univ Jyvaskyla, Dept Psychol, SF-40351 Jyvaskyla, Finland

来源：

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2012年 / 22卷 / 06期

关键词：

EEG; event-related potential; mismatch negativity; multi-domain feature; non-negative tensor factorization; INDEPENDENT COMPONENT ANALYSIS; MATRIX FACTORIZATION; MULTIWAY ANALYSIS; DECOMPOSITION; MMN; BRAIN; CLASSIFICATION; PERCEPTION; RESPONSES; DYNAMICS;

D O I：

10.1142/S0129065712500256

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Through exploiting temporal, spectral, time-frequency representations, and spatial properties of mismatch negativity (MMN) simultaneously, this study extracts a multi-domain feature of MMN mainly using non-negative tensor factorization. In our experiment, the peak amplitude of MMN between children with reading disability and children with attention deficit was not significantly different, whereas the new feature of MMN significantly discriminated the two groups of children. This is because the feature was derived from multi-domain information with significant reduction of the heterogeneous effect of datasets.

引用

页数：19

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