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Decoding Motor Plans Using a Closed-Loop Ultrasonic Brain-Machine Interface

Griggs, Whitney S. and Norman, Sumner L. and Deffieux, Thomas and Segura, Florian and Osmanski, Bruno-Félix and Chau, Geeling and Christopoulos, Vasileios and Liu, Charles and Tanter, Mickaël and Shapiro, Mikhail G. and Andersen, Richard A. (2022) Decoding Motor Plans Using a Closed-Loop Ultrasonic Brain-Machine Interface. . (Unpublished)

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Brain-machine interfaces (BMIs) can be transformative for people living with chronic paralysis. BMIs translate brain signals into computer commands, bypassing neurological impairments and enabling people with neurological injury or disease to control computers, robots, and more with nothing but thought. State-of-the-art BMIs have already made this future a reality in limited clinical trials. However, high performance BMIs currently require highly invasive electrodes in the brain. Device degradation limits longevity to about 5 years. Their field of view is small, restricting the number, and type, of applications possible. The next generation of BMI technology should include being longer lasting, less invasive, and scalable to sense activity from large regions of the brain. Functional ultrasound neuroimaging is a recently developed technique that meets these criteria. In this present study, we demonstrate the first online, closed-loop ultrasonic brain-machine interface. We used 2 Hz real-time functional ultrasound to measure the neurovascular activity of the posterior parietal cortex in two nonhuman primates (NHPs) as they performed memory-guided movements. We streamed neural signals into a classifier to predict the intended movement direction. These predictions controlled a behavioral task in real-time while the NHP did not produce overt movements. Both NHPs quickly succeeded in controlling up to eight independent directions using the BMI. Furthermore, we present a simple method to “pretrain” the BMI using data from previous sessions. This enables the BMI to work immediately from the start of a session without acquiring extensive additional training data. This work establishes, for the first time, the feasibility of an ultrasonic BMI and prepares for future work on a next generation of minimally invasive BMIs that can restore function to patients with neurological, physical, or even psychiatric impairments.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Griggs, Whitney S.0000-0003-2941-6803
Norman, Sumner L.0000-0001-9945-697X
Deffieux, Thomas0000-0001-9114-2028
Osmanski, Bruno-Félix0000-0003-1198-5303
Chau, Geeling0000-0002-7634-8586
Christopoulos, Vasileios0000-0002-0541-8700
Liu, Charles0000-0001-6423-8577
Tanter, Mickaël0000-0001-7739-8051
Shapiro, Mikhail G.0000-0002-0291-4215
Andersen, Richard A.0000-0002-7947-0472
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. We thank Kelsie Pejsa for assistance with animal care, surgeries, and training. We thank Claire Rabut and Lydia Lin for helpful discussions. We thank Krissta Passanante for her illustrations. W.S.G was supported by an NEI F30 (NEI F30 EY032799), the Josephine de Karman Fellowship, and the UCLA-Caltech MSTP (NIGMS T32 GM008042). S.L.N was supported by the Della Martin Foundation. This research was supported by the National Institute of Health BRAIN Initiative (grant 1R01NS123663-01 to R.A.A., M.G.S., and M.T.), the T&C Chen Brain-Machine Interface Center, and the Boswell Foundation (R.A.A.). Author Contributions. W.S.G., S.L.N., V.C., M.T., M.G.S., and R.A.A. conceived the study; S.L.N. established the fUS neuroimaging sequences and T.D., B.-F.O., F.S., and M.T. wrote the acquisition software for 2 Hz real-time fUS neuroimaging; W.S.G. and S.L.N. wrote the code for the fUS-BMI; W.S.G. trained the NHPs and acquired the data; W.S.G., S.L.N., and G.C performed the data processing and analysis; W.S.G. and S.L.N. drafted the manuscript with substantial contributions from M.G.S and R.A.A., and all authors edited and approved the final version of the manuscript. V.C., C.L., M.T., M.G.S., and R.A.A. supervised the research. Competing Interest Statement. B.-F.O. is an employee of Iconeus. T.D., B.-F.O., and M.T. are co-founders and shareholders of Iconeus, which commercializes ultrasonic neuroimaging scanners.
Group:Tianqiao and Chrissy Chen Institute for Neuroscience, Heritage Medical Research Institute
Funding AgencyGrant Number
NIH Postdoctoral FellowshipF30 EY032799
Howard Hughes Medical Institute (HHMI)UNSPECIFIED
Josephine De Karman Fellowship TrustUNSPECIFIED
NIH Predoctoral FellowshipT32 GM008042
Della Martin FoundationUNSPECIFIED
Tianqiao and Chrissy Chen Brain-Machine Interface CenterUNSPECIFIED
James G. Boswell FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20230316-182888000.72
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:120178
Deposited By: George Porter
Deposited On:17 Mar 2023 23:23
Last Modified:17 Mar 2023 23:23

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