Chapter

Brain-Computer Interface Research

Part of the series SpringerBriefs in Electrical and Computer Engineering pp 29-42

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Towards an Auditory Attention BCI

  • Peter BrunnerAffiliated withNew York State Department of Health, Center for Adaptive Neurotechnology, Wadsworth CenterDepartment of Neurology, Albany Medical College
  • , Karen DijkstraAffiliated withNew York State Department of Health, Center for Adaptive Neurotechnology, Wadsworth CenterDepartment of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour
  • , William G. CoonAffiliated withNew York State Department of Health, Center for Adaptive Neurotechnology, Wadsworth Center
  • , Jürgen MellingerAffiliated withInstitute of Medical Psychology and Behavioral Neurobiology, University of Tübingen
  • , Anthony L. RitaccioAffiliated withDepartment of Neurology, Albany Medical College
  • , Gerwin SchalkAffiliated withNew York State Department of Health, Center for Adaptive Neurotechnology, Wadsworth CenterDepartment of Neurology, Albany Medical College Email author 

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Abstract

People affected by severe neuro-degenerative diseases (e.g., late-stage amyotrophic lateral sclerosis (ALS) or locked-in syndrome) eventually lose all muscular control and are no longer able to gesture or speak. For this population, an auditory BCI is one of only a few remaining means of communication. All currently used auditory BCIs require a relatively artificial mapping between a stimulus and a communication output. This mapping is cumbersome to learn and use. Recent studies suggest that electrocorticographic (ECoG) signals in the gamma band (i.e., 70–170 Hz) can be used to infer the identity of auditory speech stimuli, effectively removing the need to learn such an artificial mapping. However, BCI systems that use this physiological mechanism for communication purposes have not yet been described. In this study, we explore this possibility by implementing a BCI2000-based real-time system that uses ECoG signals to identify the attended speaker.