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

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This study introduces functional ultrasound (fUS) for brain-machine interfaces (BMIs), enabling thought-controlled devices. Ultrasonic BMIs offer a less-invasive, long-lasting solution for restoring function in paralysis.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Medical Technology

Background:

  • Existing brain-machine interfaces (BMIs) present trade-offs in invasiveness, performance, and resolution.
  • Functional ultrasound (fUS) neuroimaging is an emerging technology with potential to balance these attributes.

Purpose of the Study:

  • To demonstrate a successful implementation of a closed-loop ultrasonic brain-machine interface (BMI).
  • To evaluate the performance and long-term usability of fUS-based BMIs.

Main Methods:

  • Streaming fUS data from the posterior parietal cortex of two rhesus macaque monkeys during eye and hand movements.
  • Developing a pretraining method for the BMI using data from previous sessions to enable rapid recalibration.

Main Results:

  • Monkeys successfully controlled up to eight movement directions using the fUS-based BMI after training.
  • The pretraining method allowed for immediate BMI control on subsequent days, even months apart, without extensive recalibration.

Conclusions:

  • Ultrasonic BMIs are feasible, offering a new class of less-invasive (epidural) interfaces.
  • These interfaces demonstrate generalization across extended time periods, promising to restore function for individuals with neurological impairments.