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Power-saving design opportunities for wireless intracortical brain–computer interfaces

Nature Biomedical Engineering volume 4, pages 984–996 (2020)Cite this article

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Abstract

The efficacy of wireless intracortical brain–computer interfaces (iBCIs) is limited in part by the number of recording channels, which is constrained by the power budget of the implantable system. Designing wireless iBCIs that provide the high-quality recordings of today’s wired neural interfaces may lead to inadvertent over-design at the expense of power consumption and scalability. Here, we report analyses of neural signals collected from experimental iBCI measurements in rhesus macaques and from a clinical-trial participant with implanted 96-channel Utah multielectrode arrays to understand the trade-offs between signal quality and decoder performance. Moreover, we propose an efficient hardware design for clinically viable iBCIs, and suggest that the circuit design parameters of current recording iBCIs can be relaxed considerably without loss of performance. The proposed design may allow for an order-of-magnitude power savings and lead to clinically viable iBCIs with a higher channel count.

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Fig. 1: iBCI schematic signal flow.
Fig. 2: iBCI robustness to spike error.
Fig. 3: Study of iBCI performance as a function of the neural interface parameters (monkey J).
Fig. 4: Power consumption trends in neural amplifiers and ADCs.
Fig. 5: Power consumption estimates per channel (log scale) for systems described in Table 120,22,23,41,42,43,44,45,73.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw human neural data are available on request to K.V.S. or J.M.H., yet owing to the potential sensitivity of the data and to respect the participant’s expectation of privacy, an agreement between the researcher’s institution and the BrainGate consortium is required to facilitate the sharing of these datasets. Processed data are available at https://shenoy.people.stanford.edu/data.

Code availability

The custom code used to produce the figures is available at https://shenoy.people.stanford.edu/data.

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Acknowledgements

We thank S. I. Ryu for electrode array implantation surgical assistance, M. Risch, M. Wechsler and A. Craig for expert surgical assistance and veterinary care. We thank B. Davis, G. Bell and N. Lam for administrative assistance. We thank W. L. Gore Inc. for donating Preclude artificial dura, used as part of the chronic non-human-primate electrode array implantation procedure. This work was supported by a Stanford Bio-X Institute fellowship (to N.E.-C.), Wu Tsai Neurosciences Institute fellowships (to D.G.M. and S.D.S.), an ALS Association Milton Safenowitz Postdoctoral Fellowship (to S.D.S.), an A. P. Giannini Foundation Postdoctoral Research Fellowship in California (to S.D.S.), a Career Award at the Scientific Interface from the Burroughs Wellcome Fund (to S.D.S.), the Rehabilitation R&D Service, the Department of Veterans Affairs (grants N2864C, A2295R, N9288C and B6453R to L.R.H.), grant NINDS-UH2NS095548 (to L.R.H., J.M.H. and K.V.S.), grant NIDCD-R01DC009899 (to L.R.H., J.M.H. and K.V.S.), grant NIDCD RO1DC014034 (to J.M.H., K.V.S. and L.R.H.), grant NINDS-U01NS098968 (to L.R.H., J.M.H. and K.V.S.), the DARPA ‘NESD’ (to B.M. and K.V.S.), the DARPA ‘NeuroFast’ (grant W911NF-14-2-0013 to K.V.S.), NIH Director’s Pioneer Award 8DP1HD075623 (to K.V.S.), a Simons Foundation grant ‘Simons Collaboration on the Global Brain (SCGB)’ 543045 (to K.V.S.), the Office of Naval Research grant W911NF-14-2-0013 (to K.V.S.), and the Howard Hughes Medical Institute (to K.V.S.).

Author information

Author notes

  1. These authors contributed equally: Nir Even-Chen, Dante G. Muratore.

  2. These authors jointly supervised this work: Boris Murmann and Krishna V. Shenoy.

Authors and Affiliations

  1. Department of Electrical Engineering, Stanford University, Stanford, CA, USA

    Nir Even-Chen, Dante G. Muratore, Sergey D. Stavisky, Boris Murmann & Krishna V. Shenoy

  2. Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA

    Dante G. Muratore, Sergey D. Stavisky, Jaimie M. Henderson, Boris Murmann & Krishna V. Shenoy

  3. Department of Neurosurgery, Stanford University, Stanford, CA, USA

    Sergey D. Stavisky & Jaimie M. Henderson

  4. Department of Veterans Affairs Medical Center, Center for Neurorestoration and Neurotechnology, Providence, RI, USA

    Leigh R. Hochberg

  5. School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA

    Leigh R. Hochberg

  6. Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Leigh R. Hochberg

  7. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Krishna V. Shenoy

  8. Department of Neurobiology, Stanford University, Stanford, CA, USA

    Krishna V. Shenoy

  9. Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA

    Krishna V. Shenoy

  10. The Bio-X Institute, Stanford University, Stanford, CA, USA

    Krishna V. Shenoy

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Contributions

N.E.-C. and D.G.M. designed the study and analysis, and wrote the manuscript with input from all other authors. N.E.-C. and S.D.S. were responsible for data collection. J.M.H. planned and performed T5’s array placement surgery. L.R.H. is the sponsor investigator of the multi-site pilot clinical trial. J.M.H., B.M. and K.V.S. were involved in all aspects of the study.

Corresponding author

Correspondence to Nir Even-Chen.

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Competing interests

The MGH Translational Research Center has clinical research support agreements with Neuralink Inc., Paradromics Inc. and Synchron Medical, for which L.R.H. provides consultative input. K.V.S. and J.M.H. are consultants to Neuralink Inc. K.V.S. is on the Scientific Advisory Boards of CTRL-Labs Inc., Mind-X Inc., Inscopix Inc. and Heal Inc. These entities did not support this work.

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Even-Chen, N., Muratore, D.G., Stavisky, S.D. et al. Power-saving design opportunities for wireless intracortical brain–computer interfaces. Nat Biomed Eng 4, 984–996 (2020). https://doi.org/10.1038/s41551-020-0595-9

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