A comparison of face speller approaches for P300 BCIs

Brain-Computer Interfaces (BCIs) can provide users with communication, control, and other capabilities based on specific types of brain activity. In the "P300 BCI" approach, a user views a matrix containing letters or other characters and silently counts each time a target item flashes. Classically, characters flashed by briefly reversing color or other basic changes. Recent work has shown that the new "face speller" approach can improve P300 BCI performance. In this approach, each character changes to a human face during each "flash" instead of simply reversing color or other simple changes. The neural activity required to process the attended face, as well as other stimulus changes, may elicit more distinct evoked potentials that can improve classification. While the "face speller" has shown that face presentation may improve BCI performance, it raises the broader possibility that other stimulus changes could provide further performance improvements. The present study explored P300 BCI performance across four conditions. A control condition used "upturned" black and white stimuli that simply reversed color during each flash. Three other conditions explored different face conditions, varying color and the number of different faces presented during each flash. Accuracy was higher in all three face speller conditions than in the conventional "upturned" condition. Colored faces may yield higher accuracy than black and white faces.