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Researchers developed a novel brain-machine interface (BMI) in mice, incorporating artificial somatosensory feedback. This closed-loop system allows mice to learn tasks using only the BMI, paving the way for advanced prosthetic control.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Robotics

Background:

  • Current brain-machine interfaces (BMIs) lack somatosensory feedback, limiting prosthetic control.
  • Relying solely on vision and audition is maladaptive for prosthesis control compared to natural somatosensation.

Purpose of the Study:

  • To develop and test a novel brain-machine interface (BMI) in mice with artificial somatosensory cortical feedback.
  • To investigate the potential of integrating sensory feedback into BMIs for improved control.

Main Methods:

  • Utilized online recordings of neuronal activity from the whisker primary motor cortex (vM1).
  • Implemented simultaneous, low-latency, high-refresh-rate photo-stimulation of the whisker primary somatosensory cortex (vS1) as artificial feedback.
  • Employed intrinsic imaging to map cortical areas for stimulation.

Main Results:

  • Demonstrated the successful operation of the closed-loop BMI system.
  • Confirmed that mice could detect neuronal spiking in vS1 triggered by artificial somatosensory feedback.
  • Showcased that mice learned a behavioral task using only the BMI's artificial inputs and outputs.

Conclusions:

  • This study presents the first motor BMI with short-latency, intracortical, somatosensory-like feedback.
  • The developed platform is valuable for exploring efficient cortical feedback strategies for future human BMI applications.