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Biased Feedback in Brain-Computer Interfaces

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83795

Barbero Jimenez,  A
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83948

Grosse-Wentrup,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Barbero Jimenez, A., & Grosse-Wentrup, M. (2010). Biased Feedback in Brain-Computer Interfaces. Journal of NeuroEngineering and Rehabilitation, 7(34), 1-4. doi:doi:10.1186/1743-0003-7-34.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-BF1A-3
Abstract
Even though feedback is considered to play an important role in learning how to operate a brain-computer interface (BCI), to date no significant influence of feedback design on BCI-performance has been reported in literature. In this work, we adapt a standard motor-imagery BCI-paradigm to study how BCI-performance is affected by biasing the belief subjects have on their level of control over the BCI system. Our findings indicate that subjects already capable of operating a BCI are impeded by inaccurate feedback, while subjects normally performing on or close to chance level may actually benefit from an incorrect belief on their performance level. Our results imply that optimal feedback design in BCIs should take into account a subjectlsquo;s current skill level.