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Book Chapter

BCIs That Use Brain Metabolic Signals

MPS-Authors
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Sitaram,  R
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84496

Lee,  S
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780195388855.001.0001/acprof-9780195388855-chapter-018
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Citation

Sitaram, R., Lee, S., & Birbaumer, N. (2012). BCIs That Use Brain Metabolic Signals. In J. Wolpaw, & E. Winter Wolpaw (Eds.), Brain–Computer Interfaces: Principles and Practice (pp. 301-314). Oxford, UK: Oxford University Press.


Cite as: https://hdl.handle.net/21.11116/0000-0001-979F-2
Abstract
Most brain-computer interfaces (BCIs) currently under development use the brain's electrical signals. Nevertheless, nonelectrical metabolic signals also have potential for use in BCI development. Two methods currently available for measuring brain metabolic activity that are of greatest immediate interest for BCI development are: functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI). fNIRS has the advantages of being noninvasive and inexpensive. fMRI has the advantages of being noninvasive and providing very high spatial resolution. This chapter focuses on BCIs based on fNIRS and fMRI methods. It reviews the fundamental principles underlying their use, the factors important in their use for BCIs, the kinds of BCI applications that are most promising, and possible future directions and challenges.