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A high-performance brain–computer interface

Nature volume 442, pages 195–198 (2006)Cite this article

Abstract

Recent studies have demonstrated that monkeys1,2,3,4 and humans5,6,7,8,9 can use signals from the brain to guide computer cursors. Brain–computer interfaces (BCIs) may one day assist patients suffering from neurological injury or disease, but relatively low system performance remains a major obstacle. In fact, the speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on eye movements. This is true whether BCIs use recordings from populations of individual neurons using invasive electrode techniques1,2,3,4,5,7,8 or electroencephalogram recordings using less-6 or non-invasive9 techniques. Here we present the design and demonstration, using electrode arrays implanted in monkey dorsal premotor cortex, of a manyfold higher performance BCI than previously reported9,10. These results indicate that a fast and accurate key selection system, capable of operating with a range of keyboard sizes, is possible (up to 6.5 bits per second, or ∼15 words per minute, with 96 electrodes). The highest information throughput is achieved with unprecedentedly brief neural recordings, even as recording quality degrades over time. These performance results and their implications for system design should substantially increase the clinical viability of BCIs in humans.

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Figure 1: Instructed-delay (real reach) and BCI (prosthetic cursor) tasks, with accompanying neural data.
Figure 2: Single-trial accuracy and ITRC with monkey H.
Figure 3: ITRC as a function of number of neural units and Tint.

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Acknowledgements

We thank S. Eisensee for administrative assistance, M. Howard for surgical assistance and veterinary care, and N. Hatsopoulos for surgical assistance (monkey G implant). We also thank M. Churchland and M. Sahani for scientific discussions; E. Knudsen and T. Moore for comments on the manuscript; and A. Batista for collecting the blink-memory data. This study was supported by NDSEG Fellowships (G.S. and B.M.Y.), NSF Graduate Research Fellowships (G.S. and B.M.Y.), the Christopher Reeve Foundation (S.I.R. and K.V.S.), Bio-X Fellowship (A.A.), the NIH Medical Scientist Training Program (A.A.), and the following awards to K.V.S.: a Burroughs Wellcome Fund Career Award in the Biomedical Sciences, the Stanford Center for Integrated Systems, the NSF Center for Neuromorphic Systems Engineering at Caltech, ONR Adaptive Neural Systems, the Sloan Foundation, and the Whitaker Foundation. Author Contributions G.S. and S.I.R. contributed equally to this work. S.I.R. was responsible for the initial experimental concept and surgical implantation; G.S. and S.I.R. were responsible for experimental design, animal training, data collection and preliminary analysis; G.S. was responsible for infrastructure development, in-depth analysis and writing of the paper. B.M.Y. and A.A. participated in animal training, data collection and analysis. K.V.S. was involved in all aspects of the study.

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Author notes

  1. Gopal Santhanam and Stephen I. Ryu: *These authors contributed equally to this work

Authors and Affiliations

  1. Department of Electrical Engineering, Stanford University, Stanford, 330 Serra Mall, 319 Paul G. Allen Center for Integrated Systems Annex, California, 94305-4075, USA

    Gopal Santhanam, Stephen I. Ryu, Byron M. Yu, Afsheen Afshar & Krishna V. Shenoy

  2. Department of Neurosurgery, Stanford University School of Medicine, Stanford, 300 Pasteur Drive, Edwards Building, R-297, California, 94305-5327, USA

    Stephen I. Ryu

  3. Medical Scientist Training Program, Stanford University School of Medicine, 251 Campus Drive, MSOB 309, California, 94305-5404, Stanford, USA

    Afsheen Afshar

  4. Neurosciences Program, Stanford University School of Medicine, Stanford, California, 94305, USA

    Krishna V. Shenoy

Authors
  1. Gopal Santhanam
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  2. Stephen I. Ryu
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  3. Byron M. Yu
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  5. Krishna V. Shenoy
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Corresponding author

Correspondence to Krishna V. Shenoy.

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Supplementary information

Supplementary Notes

This file contains Supplementary Video Legends, Supplementary Discussion, Supplementary Methods, Supplementary Figures 1–7 and Supplementary Table 1. The Supplementary Discussion covers the following topics: motor-related activity in the absence of the visual stimulus, selection of Tskip, ITRC for multi-target task, ITRC comparisons with monkey G, effects of losing neural units on single-trial accuracy, and EMG measurements. (PDF 433 kb)

Supplementary Video 1

Instructed-delay task. This video shows the monkey's performance in the instructed-delay task. Trials were started by touching the center square and fixating the cross. The reach target appeared in the periphery and the monkey was required to wait until the 'go' cue before making the reach. (MPG 4777 kb)

Supplementary Video 2

Moderately-paced BCI experiments. This video shows the monkey's performance during a moderately-paced BCI experiment. Video annotations are used to denote real reaches and prosthetic cursor trials (not seen by monkey). (MPG 4512 kb)

Supplementary Video 3

Fast-paced BCI experiments. This video shows the monkey's performance during a fast-paced BCI experiment. The video contains three separate sequences, each of five cursor trials followed by a real reach. The three sequences were performed at different times in the experiment. (MPG 2866 kb)

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Santhanam, G., Ryu, S., Yu, B. et al. A high-performance brain–computer interface. Nature 442, 195–198 (2006). https://doi.org/10.1038/nature04968

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