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For multimodal Human-Computer Interaction (HCI), it is very useful to identify the modalities on which the user is currently processing information. This would enable a system to select complementary output modalities to reduce the user's workload. In this paper, we develop a hybrid Brain-Computer Interface (BCI) which uses Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS) to discriminate and detect visual and auditory stimulus processing. We describe thedoi:10.3389/fnins.2014.00373 pmid:25477777 pmcid:PMC4235375 fatcat:iey6uss7njaaheeb3bkv4xiqne