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How do we use neural signals to improve human interactions with computers, autonomous agents, their environment, and even other humans?
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The ultimate goal of this science area is to perform the critical hypothesis-driven research needed for initial proof-of-concept demonstration systems that will truly guide the way towards the development of robust and useful BCI technologies for healthy populations. However, there are numerous challenges that must be overcome to achieve this goal. The projects in this area are therefore focused on addressing these challenges through clearly planned, hypothesis-driven research that is evaluated within functioning real-time systems.
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Barriers to understanding Brain Computer Interaction (BCI):
The restriction of experimental designs to highly controlled and impoverished stimulus-response paradigms and environments.
Lack of principles and approaches to utilize real-time measures of physiological signals to influence operator cognitive state or inform adaptive technologies to improve human-system performance over time and across individuals.
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Topic Area 1
BCI generalization through the investigation of user-to-user transfer:
• Across individuals
• Within an individual over time
Topic Area 2
BCI generalization through the investigation of transfer across tasks or scenarios:
• Perceptual (e.g. target detection)
• Cognitive (e.g. working memory)
• Motor (e.g. driving)
Topic Area 3
BCI generalization through the investigation of performance across states:
• Arousal
• Stress
• Fatigue