Bayesian Inferences on Neural Activity in EEG-Based Brain-Computer Interface

Date: 
August 24, 2022
Time: 
3:00 - 4:00pm
Place: 
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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 

 

Register:  http://tiny.cc/EpiBioEmailList

Event Type: 
Biostatistics and Bioinformatics Seminar