Brain–computer interfaces and neurofeedback for enhancing human performance: human performance optimization

Ranganatha Sitaram, Andrea Sánchez Corzo, Mariana Zurita, Constanza Levican, Daniela Huepe-Artigas, Juan Andrés Mucarquer, Matías Ramírez

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Brain–computer interfaces (BCIs), also known as brain–machine interfaces (BMIs), are a group of experimental procedures in which an external sensor is used to provide information about a specific brain process in order to change the measured quantity. A BCI acquires signals from the brain of a human or an animal using any one or more of these sensors, then selects or extracts specific features of interest from the signal and converts and then translates these into artificial output that can act on the body or the outside world. A BCI may influence human performance by replacing, restoring, supplementing, or enhancing brain function. In this chapter, we discuss the extant research in terms of experimental work and neuroscience understanding of the application of BCIs and neurofeedback systems in influencing human performance in different brain functions, namely, action, perception, cognition, and emotion, in healthy individuals, expert performers, and patients.
Original languageEnglish
Title of host publicationHuman performance optimization
Subtitle of host publicationthe science and ethics of enhancing human capabilities
EditorsMichael D. Matthews, David M. Schnyer
Place of PublicationNew York
PublisherOxford University Press
Chapter6
Pages125-141
Number of pages17
ISBN (Electronic)9780190455149, 9780190455156
ISBN (Print)9780190455132
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • brain–computer interface
  • brain–machine interface
  • neurofeedback
  • biofeedback
  • neuroimaging
  • neurorehabilitation

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