文献类型：期刊文献

英文题名：A novel BCI based on ERP components sensitive to configural processing of human faces

作者：Zhang, Yu[1,2];Zhao, Qibin[2];Jin, Jing[1];Wang, Xingyu[1];Cichocki, Andrzej[2,3]

机构：[1]E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]RIKEN, Lab Adv Brain Signal Proc, Brain Sci Inst, Wako, Saitama 3250198, Japan;[3]Polish Acad Sci PAN, Syst Res Inst, PL-00901 Warsaw, Poland

年份：2012

卷号：9

期号：2

外文期刊名：JOURNAL OF NEURAL ENGINEERING

收录：;EI(收录号：20121414921101);WOS:【SCI-EXPANDED(收录号:WOS:000302144100018)】；

基金：This study was supported in part by the National Natural Science Foundation of China 61074113, Shanghai Leading Academic Discipline Project B504 and Fundamental Research Funds for the Central Universities WH0914028 and WH1114038. The authors would like to thank Dr Zhou and Mr Onishi for experimental work.

语种：英文

外文关键词：Feature extraction - Interfaces (computer) - Discriminant analysis

摘要：This study introduces a novel brain-computer interface (BCI) based on an oddball paradigm using stimuli of facial images with loss of configural face information (e.g., inversion of face). To the best of our knowledge, till now the configural processing of human faces has not been applied to BCI but widely studied in cognitive neuroscience research. Our experiments confirm that the face-sensitive event-related potential (ERP) components N170 and vertex positive potential (VPP) have reflected early structural encoding of faces and can be modulated by the configural processing of faces. With the proposed novel paradigm, we investigate the effects of ERP components N170, VPP and P300 on target detection for BCI. An eight-class BCI platform is developed to analyze ERPs and evaluate the target detection performance using linear discriminant analysis without complicated feature extraction processing. The online classification accuracy of 88.7% and information transfer rate of 38.7 bits min(-1) using stimuli of inverted faces with only single trial suggest that the proposed paradigm based on the configural processing of faces is very promising for visual stimuli-driven BCI applications.