A brain-computer interface (BCI) is a system that translates brain activity into commands to operate technology and help people with disabilities use technology for communication. A common design for an electroencephalogram (EEG) BCI relies on the classification of the P300 event-related potential (ERP), which is a response elicited by the rare occurrence of target stimuli among common non-target stimuli. We perform a method to identify relevant spatial-temporal differences of the neural activity in response to external stimuli, which provides the first statistical evidence of P300 ERP responses and helps design user-specific profiles for efficient BCIs. Our inference results also convincingly demonstrate the importance of ERPs from visual cortex for P300 speller performance.
Speaker: Jian Kang, PhD, Professor of Biostatistics, School of Public Health, University of Michigan
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