A novel BCI based on ERP components sensitive to configural processing of human faces

Yu Zhang, Qibin Zhao, Jing Jin, Xingyu Wang, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

127 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number026018
JournalJournal of Neural Engineering
Volume9
Issue number2
DOIs
Publication statusPublished - Apr 2012
Externally publishedYes

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