Towards an Auditory Attention BCI

  • Peter Brunner
  • Karen Dijkstra
  • William G. Coon
  • Jürgen Mellinger
  • Anthony L. Ritaccio
  • Gerwin Schalk
Chapter

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.

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Copyright information

© The Author(s) 2015

Authors and Affiliations

  • Peter Brunner
    • 1
    • 2
  • Karen Dijkstra
    • 1
    • 4
  • William G. Coon
    • 1
  • Jürgen Mellinger
    • 3
  • Anthony L. Ritaccio
    • 2
  • Gerwin Schalk
    • 1
    • 2
  1. 1.New York State Department of HealthCenter for Adaptive Neurotechnology, Wadsworth CenterAlbanyUSA
  2. 2.Department of NeurologyAlbany Medical CollegeAlbanyUSA
  3. 3.Institute of Medical Psychology and Behavioral Neurobiology, University of TübingenTübingenGermany
  4. 4.Department of Artificial IntelligenceDonders Institute for Brain, Cognition and BehaviourNijmegenThe Netherlands

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