Decoding motor plans using a closed-loop ultrasonic brain-machine interface.

Autor: Griggs WS; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA. wsgriggs@gmail.com.; David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. wsgriggs@gmail.com., Norman SL; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA. sumner.norman@gmail.com., Deffieux T; Physics for Medicine Paris, INSERM, CNRS, ESPCI Paris, PSL Research University, Paris, France.; INSERM Technology Research Accelerator in Biomedical Ultrasound, Paris, France., Segura F; Physics for Medicine Paris, INSERM, CNRS, ESPCI Paris, PSL Research University, Paris, France.; INSERM Technology Research Accelerator in Biomedical Ultrasound, Paris, France., Osmanski BF; Iconeus, Paris, France., Chau G; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA., Christopoulos V; T&C Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, CA, USA.; Department of Bioengineering, University of California, Riverside, Riverside, CA, USA., Liu C; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.; Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, USA.; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, USA.; Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA., Tanter M; Physics for Medicine Paris, INSERM, CNRS, ESPCI Paris, PSL Research University, Paris, France.; INSERM Technology Research Accelerator in Biomedical Ultrasound, Paris, France., Shapiro MG; Division of Chemistry & Chemical Engineering, California Institute of Technology, Pasadena, CA, USA.; Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA.; Howard Hughes Medical Institute, Pasadena, CA, USA., Andersen RA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.; T&C Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, CA, USA.
Jazyk: angličtina
Zdroj: Nature neuroscience [Nat Neurosci] 2024 Jan; Vol. 27 (1), pp. 196-207. Date of Electronic Publication: 2023 Nov 30.
DOI: 10.1038/s41593-023-01500-7
Abstrakt: Brain-machine interfaces (BMIs) enable people living with chronic paralysis to control computers, robots and more with nothing but thought. Existing BMIs have trade-offs across invasiveness, performance, spatial coverage and spatiotemporal resolution. Functional ultrasound (fUS) neuroimaging is an emerging technology that balances these attributes and may complement existing BMI recording technologies. In this study, we use fUS to demonstrate a successful implementation of a closed-loop ultrasonic BMI. We streamed fUS data from the posterior parietal cortex of two rhesus macaque monkeys while they performed eye and hand movements. After training, the monkeys controlled up to eight movement directions using the BMI. We also developed a method for pretraining the BMI using data from previous sessions. This enabled immediate control on subsequent days, even those that occurred months apart, without requiring extensive recalibration. These findings establish the feasibility of ultrasonic BMIs, paving the way for a new class of less-invasive (epidural) interfaces that generalize across extended time periods and promise to restore function to people with neurological impairments.
(© 2023. The Author(s).)
Databáze: MEDLINE
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