The Self-Face Paradigm Improves the Performance of the P300-Speller System

• Published in: Frontiers in computational neuroscience 2020-01, Vol.13, p.93-93
• Main Authors: Lu, Zhaohua, Li, Qi, Gao, Ning, Yang, Jingjing
• Format: Article
• Language: English
• Subjects: brain-computer interface (BCI); event-related potential; Event-related potentials; Experiments; Face; famous face; Interfaces; Neuroscience; P300-speller; Paradigms; self-face; Spelling; Studies
• ISSN: 1662-5188; 1662-5188
• DOI: 10.3389/fncom.2019.00093

Previous studies have shown that the performance of the famous face P300-speller was better than that of the classical row/column flashing P300-speller. Furthermore, in some studies, the brain was more active when responding to one's own face than to a famous face, and a self-face stimulus elicited larger amplitude event-related potentials (ERPs) than did a famous face. Thus, we aimed to study the role of the self-face paradigm on further improving the performance of the P300-speller system with the famous face P300-speller paradigm as the control paradigm. We designed two facial P300-speller paradigms based on the self-face and a famous face (Ming Yao, a sports star; the famous face spelling paradigm) with a neutral expression. ERP amplitudes were significantly greater in the self-face than in the famous face spelling paradigm at the parietal area from 340 to 480 ms (P300), from 480 to 600 ms (P600f), and at the fronto-central area from 700 to 800 ms. Offline and online classification results showed that the self-face spelling paradigm accuracies were significantly higher than those of the famous face spelling paradigm at superposing first two times ( < 0.05). Similar results were found for information transfer rates ( < 0.05). The self-face spelling paradigm significantly improved the performance of the P300-speller system. This has significant practical applications for brain-computer interfaces (BCIs) and could avoid infringement issues caused by using images of other people's faces.