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Published December 2025 | Version Supplemental material
Journal Article Open

A wireless subdural-contained brain–computer interface with 65,536 electrodes and 1,024 channels

Creators

  • 1. ROR icon Columbia University
  • 2. Kampto Neurotech LLC, Troy, NY, USA
  • 3. ROR icon Stanford University
  • 4. ROR icon University of Göttingen
  • 5. ROR icon New York University
  • 6. ROR icon University of Pennsylvania
  • 7. ROR icon Baylor College of Medicine
  • 8. ROR icon University of California, Santa Barbara
  • 9. ROR icon California Institute of Technology
  • 10. ROR icon MIT Lincoln Laboratory
  • 11. ROR icon University of Chicago
  • 12. Shirley Ryan Ability Labs, Chicago, IL, USA
  • 13. ROR icon Northwestern University

Abstract

Electrocorticography uses non-penetrating electrodes embedded in flexible substrates to record electrical activity from the surface of the brain. To use the technology to develop minimally invasive, high-bandwidth brain–computer interfaces, it will be necessary to improve the number of recording channels and the scalability of devices, which could be achieved by merging electrodes and electronics onto a single substrate. Here we report a 50-μm-thick, mechanically flexible micro-electrocorticography brain–computer interface that integrates a 256 × 256 array of electrodes, signal processing, data telemetry and wireless powering on a single complementary metal–oxide–semiconductor substrate. The device contains 65,536 recording electrodes, from which we can simultaneously record a selectable subset of up to 1,024 channels at a given time. Our chip is wirelessly powered, and when implanted below the dura, it can communicate bidirectionally with an external relay station outside the body. We show that the device can provide chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from the somatosensory, motor and visual cortices, decoding brain signals at high spatiotemporal resolution.

Copyright and License

© The Author(s), under exclusive licence to Springer Nature Limited 2025.

Acknowledgement

This work was partly supported by the Defense Advanced Research Project Agency (DARPA) under contract number N66001-17-C-4001, the Department of the Defense Congressionally Directed Medical Research Program under contract number HT9425-23-1-0758, the National Science Foundation under grant number 1546296 and the National Institutes of Health under grant number R01DC019498. We acknowledge the use of facilities and instrumentation at the Columbia Nano Initiative, the CUNY ASRC and the UPenn Quattrone Nanofabrication Facility. We also thank Y. Borisenkov, A. Banees and K. Kim at Columbia University for help with chip processing and many helpful discussions.

Funding

This work was partly supported by the Defense Advanced Research Project Agency (DARPA) under contract number N66001-17-C-4001, the Department of the Defense Congressionally Directed Medical Research Program under contract number HT9425-23-1-0758, the National Science Foundation under grant number 1546296 and the National Institutes of Health under grant number R01DC019498.

Contributions

These authors contributed equally: Taesung Jung, Nanyu Zeng.

K.L.S., N.Z., T.J. and R.J.C. conceived the project. N.Z., T.J., G.E., M.S., K.T., G.R., Y.H., K.L.S. and R.J.C. designed the implant circuitry. J.D.F., J.K. and H.Y. post-processed the implant. N.Z. and T.J. implemented the relay station hardware. G.E., N.Z., P.M., R.J.C., S.P., T.J., A.M. and L.P.C. implemented the relay station software. T.J., N.Z., J.D.F. and S.P. performed the bench-top characterizations. B.Y., E.S., T.J., N.Z., K.L.S., R.H., I.G. and G.E. performed the in vivo experiments on the porcine subject. T.J., B.Y. and P.C. conducted the porcine data analysis and histology. B.P., A. Dubey, K.E.W., N.Z. and T.J. performed the in vivo experiments on the motor cortex of the NHP. T.J., B.P. and K.E.W. performed the motor cortex data analysis. A.T., S.P., K.L.S., R.J.C., T.J., N.Z., G.E., T.S., G.J.R. and C.N. performed the in vivo experiments on the visual cortex of the NHP. Z.L., K.W., A.T., S.P., D.O., R.J.C., E.Z., A. Das and J.J. performed the visual cortex data analysis. K.L.S., A.T., B.P., M.R., J.J. and D.Y. acquired the funding. K.L.S., A.T., B.Y., B.P., R.J.C., L.P.C. and J.J. provided supervision. T.J., N.Z., J.D.F., G.E., K.L.S., Z.L., K.W., A.T., A. Das, E.Z., J.J. and S.P. wrote the paper with review and editing contributed by all authors.

Conflict of Interest

N.Z. is a principal with Kampto Neurotech, LLC, which is commercializing the BISC technology. The BISC technology is patented under US patent 11617890, issued on 4 April 2023, and exclusively licensed to Kampto from Columbia University. The other authors declare no competing interests.

Data Availability

All electrophysiological data relevant to the figures presented in this paper are available via GitHub at https://github.com/klshepard/bisc with a version archived in Zenodo (https://doi.org/10.5281/zenodo.17074065)70. All other relevant data are available from the corresponding authors upon reasonable request.

Code Availability

All scripts used for the data analysis are available via GitHub at https://github.com/klshepard/bisc. All other relevant codes are available from the corresponding authors upon reasonable request.

Supplemental Material

Supplementary Information

Supplementary Discussions 1–10, Figs. 1–26, Tables 1 and 2, and captions for Videos 1–9.

Supplementary Video 1

Normalized somatosensory evoked potential (SSEP) recording from a porcine model, trial averaged (n = 100 per location).

Supplementary Video 2

Motor cortex recording from a NHP model performing asynchronous reach-and-grab task.

Supplementary Video 3

Dot-triggered-average responses of all channels without filtering.

Supplementary Video 4

Dot-triggered-average responses of all channels after wavelet transformation (central frequency 8 Hz).

Supplementary Video 5

Dot-triggered-average responses of all channels after wavelet transformation (central frequency 16 Hz).

Supplementary Video 6

Dot-triggered-average responses of all channels after wavelet transformation (central frequency 32 Hz).

Supplementary Video 7

Dot-triggered-average responses of all channels after wavelet transformation (central frequency 64 Hz).

Supplementary Video 8

Dot-triggered-average responses of all channels after wavelet transformation (central frequency 128 Hz).

Supplementary Video 9

Dot-triggered travelling waves used for decoding stimuli location. The travelling waves are computed from the γ-band (30–90 Hz) signals recorded from 32 × 32 spatially dense channels at a pitch of 26.5 μm × 29 μm. The spatiotemporal sequence of these travelling waves, measured within each dot presentation, is used to predict the current location of the dot stimuli presented to the subject.

Additional Information

Extended data:

Extended Data Fig. 1 Bench-top in vitro characterization of the BISC implant

Extended Data Fig. 2 BISC recordings over visual cortex with natural images

 

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Additional details

Additional titles

Alternative title
Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device

Related works

Describes
Journal Article: https://rdcu.be/eWN9s (ReadCube)
Is new version of
Discussion Paper: 10.1101/2024.05.17.594333 (DOI)
Is supplemented by
Dataset: https://github.com/klshepard/bisc (URL)
Dataset: 10.5281/zenodo.17074065 (DOI)
Software: https://github.com/klshepard/bisc (URL)

Funding

Defense Advanced Research Projects Agency
N66001-17-C-4001
Congressionally Directed Medical Research Programs
HT9425-23-1-0758
National Science Foundation
1546296
National Institutes of Health
R01DC019498

Dates

Submitted
2025-03-21
Accepted
2025-10-22
Available
2025-12-08
Version of record

Caltech Custom Metadata

Caltech groups
Kavli Nanoscience Institute, Division of Biology and Biological Engineering (BBE), Division of Engineering and Applied Science (EAS), Division of Physics, Mathematics and Astronomy (PMA)
Publication Status
Published