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Brain-Computer Interfacing
An Introduction


  • Date Published: June 2019
  • availability: Available
  • format: Paperback
  • isbn: 9781108708012
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About the Authors
  • The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoration and augmentation of human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and neurally controlled prosthetic limbs for the paralyzed are becoming almost commonplace. Brain-computer interfaces (BCIs) are also increasingly being used in security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used for self-study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features include questions and exercises in each chapter and a supporting website.

    • The first single-author introductory textbook on brain-computer interfacing
    • No background is assumed in neuroscience, computing or engineering
    • Provides exhaustive coverage, including review questions, an extensive bibliography and an index
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    Reviews & endorsements

    'Rajesh P. N. Rao has written the perfect introduction to the exciting world of brain-computer interfaces. The book is remarkably comprehensive – not only including full descriptions of classic and current experiments but also covering essential background concepts, from the brain to Bayes and back. Brain-Computer Interfacing will be welcomed by a wide range of intelligent readers interested in understanding the first steps toward the symbiotic merger of brains and computers.' Eberhard E. Fetz, University of Washington

    'Brain-computer interfacing is one of the fastest growing areas of neuroengineering and Rajesh P. N. Rao has written the go-to book for anyone who wants an introduction and a clear overview of the field. The book includes questions and exercises at the end of each chapter to help students master the material and a mathematical appendix to make the technical aspects more accessible to all.' Terrence Sejnowski, Howard Hughes Medical Institute Investigator and Francis Crick Professor at the Salk Institute for Biological Studies, California

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    Customer reviews

    28th Apr 2018 by ZXXXS402

    I think it is a perfect book,I can benefit a lot from it

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    Product details

    • Date Published: June 2019
    • format: Paperback
    • isbn: 9781108708012
    • dimensions: 254 x 178 x 18 mm
    • weight: 0.452kg
    • contains: 130 b/w illus. 16 colour illus. 3 tables 179 exercises
    • availability: Available
  • Table of Contents

    1. Introduction
    Part I. Background:
    2. Basic neuroscience
    3. Recording and stimulating the brain
    4. Signal processing
    5. Machine learning
    Part II. Putting it All Together:
    6. Building a BCI
    Part III. Major Types of BCIs:
    7. Invasive BCIs
    8. Semi-invasive BCIs
    9. Non-invasive BCIs
    10. BCIs that stimulate
    11. Bidirectional and recurrent BCIs
    Part IV. Applications and Ethics:
    12. Applications of BCIs
    13. Ethics of brain-computer interfacing
    14. Conclusion

  • Author

    Rajesh P. N. Rao, University of Washington
    Rajesh P. N. Rao is an Associate Professor in the Computer Science and Engineering Department at the University of Washington, Seattle. He has been awarded an NSF CAREER award, an ONR Young Investigator Award, a Sloan Faculty Fellowship and a David and Lucile Packard Fellowship for Science and Engineering. Rao has published more than 150 papers in conferences and leading scientific journals, including Science, Nature, and PNAS, and is the co-editor of Probabilistic Models of the Brain (with Bruno A. Olshausen and Michael S. Lewicki, 2002) and Bayesian Brain (with Kenji Doya, Shin Ishii and Alexandre Pouget, 2007). His research targets problems at the intersection of computational neuroscience, artificial intelligence and brain-computer interfacing.

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