A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces

ABSTRACT The large power requirement of current brain–machine interfaces is a major hindrance to their clinical translation. In basic behavioural tasks, the downsampled magnitude of the

300–1,000 Hz band of spiking activity can predict movement similarly to the threshold crossing rate (TCR) at 30 kilo-samples per second. However, the relationship between such a spiking-band

power (SBP) and neural activity remains unclear, as does the capability of using the SBP to decode complicated behaviour. By using simulations of recordings of neural activity, here we show

that the SBP is dominated by local single-unit spikes with spatial specificity comparable to or better than that of the TCR, and that the SBP correlates better with the firing rates of

lower signal-to-noise-ratio units than the TCR. With non-human primates, in an online task involving the one-dimensional decoding of the movement of finger groups and in an offline

two-dimensional cursor-control task, the SBP performed equally well or better than the TCR. The SBP may enhance the decoding performance of neural interfaces while enabling substantial cuts

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SIMILAR CONTENT BEING VIEWED BY OTHERS BRAIN-INSPIRED SPIKING NEURAL NETWORKS FOR DECODING AND UNDERSTANDING MUSCLE ACTIVITY AND KINEMATICS FROM ELECTROENCEPHALOGRAPHY SIGNALS DURING HAND

MOVEMENTS Article Open access 28 January 2021 INFERRING ENTIRE SPIKING ACTIVITY FROM LOCAL FIELD POTENTIALS Article Open access 24 September 2021 GRASP-SQUEEZE ADAPTATION TO CHANGES IN

OBJECT COMPLIANCE LEADS TO DYNAMIC BETA-BAND COMMUNICATION BETWEEN PRIMARY SOMATOSENSORY AND MOTOR CORTICES Article Open access 26 April 2022 DATA AVAILABILITY The main data supporting the

results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, yet they

are available for research purposes from the corresponding authors on reasonable request. CODE AVAILABILITY The code used in this study is available from the corresponding author upon

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Rehabilitation Eng._ 16, 3–14 (2008). Google Scholar  Download references ACKNOWLEDGEMENTS We thank E. Kennedy for animal and experimental support. We thank G. Rising, A. Yanovich, L.

Burlingame, P. Lester, V. Dunivant, L. Durham, T. Hetrick, H. Noack, D. Renner, M. Bradley, G. Chan, K. Cornelius, C. Hunter, L. Krueger, R. Nichols, B. Pallas, C. Si, A. Skorupski, J. Xu,

J. Yang, M. Risch, M. Wechsler and R. Reeder for expert surgical assistance and veterinary care. We thank B. Davis for administrative assistance. We thank W. L. Gore Inc. for donating

Preclude artificial dura, used as part of some of the chronic electrode array implantation procedures, and S. Ryu for performing array implantation surgeries. This work was supported by NSF

grant no. 1926576, Craig H. Neilsen Foundation project 315108, A. Alfred Taubman Medical Research Institute, NIH grant no. R01GM111293, MCubed project 1482 and NIH grant no. R21EY029452.

S.R.N. was supported by NIH grant no. F31HD098804. A.K.V. was supported by fellowship from the Robotics Graduate Program at University of Michigan. M.S.W. was supported by NIH grant no.

T32NS007222. E.J.W. was supported by NIH grant nos. U01NS094375 and UF1NS107659, and Office of the Director National Institutes of Health OT2OD024907. H.A., T.J., H.-S.K. and D.B. were

supported by MCubed project 1482 and NIH grant no. R21EY029452. P.P.V., A.J.B., C.S.N. and J.C.K. were supported by NSF-GRFP. K.V.S. was supported in part by the following awards: NIH

National Institute of Neurological Disorders and Stroke Transformative Research Award R01NS076460, NIH National Institute of Mental Health Transformative Research Award R01MH09964703, NIH

Director’s Pioneer Award 8DP1HD075623, Defense Advanced Research Projects Agency (DARPA) Biological Technology Office (BTO) ‘REPAIR’ Award N66001-10-C-2010, DARPA BTO ‘NeuroFAST’ Award

W911NF-14-2-0013, Simons Foundation Collaboration on the Global Brain award 543045, the Office of Naval Research W911NF-14-2-0013 and the Howard Hughes Medical Institute. P.G.P. was

supported by NSF grant no. 1926576, A. Alfred Taubman Medical Research Institute and NIH grant no. R01GM111293. C.A.C. was supported by NSF grant no. 1926576, Craig H. Neilsen Foundation

project 315108, NIH grant nos. R01GM111293 and R21EY029452, and MCubed project 1482. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Biomedical Engineering, University of

Michigan, Ann Arbor, MI, USA Samuel R. Nason, Matthew S. Willsey, Elissa J. Welle, Philip P. Vu, Autumn J. Bullard, Chrono S. Nu, Parag G. Patil & Cynthia A. Chestek * Robotics Graduate

Program, University of Michigan, Ann Arbor, MI, USA Alex K. Vaskov & Cynthia A. Chestek * Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI, USA Matthew S.

Willsey & Parag G. Patil * Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA Hyochan An, Taekwang Jang, Hun-Seok Kim, David Blaauw 

& Cynthia A. Chestek * Department of Electrical and Computer Engineering, University of California, Los Angeles, Los Angeles, CA, USA Jonathan C. Kao * Neurosciences Program, University

of California, Los Angeles, Los Angeles, CA, USA Jonathan C. Kao * Department of Electrical Engineering, Stanford University, Stanford, CA, USA Krishna V. Shenoy * Department of

Bioengineering, Stanford University, Stanford, CA, USA Krishna V. Shenoy * Department of Neurobiology, Stanford University, Stanford, CA, USA Krishna V. Shenoy * The Bio-X Program, Stanford

University, Stanford, CA, USA Krishna V. Shenoy * Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA Krishna V. Shenoy * Howard Hughes Medical Institute, Stanford

University, Stanford, CA, USA Krishna V. Shenoy * Department of Information Technology and Electrical Engineering, ETH Zürich, Zürich, Switzerland Taekwang Jang * Department of Neurology,

University of Michigan Medical School, Ann Arbor, MI, USA Parag G. Patil * Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA Parag G. Patil & Cynthia A. Chestek

Authors * Samuel R. Nason View author publications You can also search for this author inPubMed Google Scholar * Alex K. Vaskov View author publications You can also search for this author

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Shenoy View author publications You can also search for this author inPubMed Google Scholar * Taekwang Jang View author publications You can also search for this author inPubMed Google

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search for this author inPubMed Google Scholar CONTRIBUTIONS M.S.W., K.V.S., P.G.P. and C.A.C. supervised this work and conducted non-human primate surgeries. H.A., T.J., H.-S.K. and D.B.

designed and estimated power consumption of the integrated circuits and wrote the relevant text. J.C.K. and K.V.S. conducted and supplied two-dimensional arm reaching experiments and data.

A.K.V., P.P.V., A.J.B. and C.S.N. assisted with non-human primate experiments and simulation programming. E.J.W. conducted rat experiments. S.R.N. programmed and executed all simulations,

decoding experiments and data analysis, and wrote the manuscript. All authors reviewed and modified the manuscript. CORRESPONDING AUTHOR Correspondence to Cynthia A. Chestek. ETHICS

DECLARATIONS COMPETING INTERESTS K.V.S. is a consultant for Neuralink Corp. and is on the scientific advisory board for CTRL-Labs Inc., MIND-X Inc., Inscopix Inc. and Heal Inc. These

entities did not provide support for this work. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and

institutional affiliations. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary methods and figures. REPORTING SUMMARY SUPPLEMENTARY VIDEO 1 Index-finger control in monkey W.

SUPPLEMENTARY VIDEO 2 Control of the middle/ring/small finger in monkey N. RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Nason, S.R., Vaskov, A.K.,

Willsey, M.S. _et al._ A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces. _Nat Biomed Eng_ 4, 973–983 (2020).

https://doi.org/10.1038/s41551-020-0591-0 Download citation * Received: 31 October 2018 * Accepted: 24 June 2020 * Published: 27 July 2020 * Issue Date: October 2020 * DOI:

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