Collaborative Brain-Computer Interfaces to Enhance Group Decisions in an Outpost Surveillance Task

We present a two-layered collaborative Brain-Computer Interface (cBCI) to aid groups making decisions under time constraints in a realistic video surveillance setting - the very first cBCI application of this type. The cBCI first uses response times (RTs) to estimate the decision confidence the user would report after each decision. Such an estimate is then used with neural features extracted from EEG to refine the decision confidence so that it better correlates with the correctness of the decision. The refined confidence is then used to weigh individual responses and obtain group decisions. Results obtained with 10 participants indicate that cBCI-assisted groups are significantly more accurate than groups using standard majority or weighing decisions using reported confidence values. This two-layer architecture allows the cBCI to not only further enhance group performance but also speed up the decision process, as the cBCI does not have to wait for all users to report their confidence after each decision.