Neuroscientists are racing to turn brain waves into speech



Many thousands of people a year could benefit from so-called voice prosthesis. Their cognitive functions remain more or less intact, but they have suffered speech loss due to stroke, the neurodegenerative disorder ALS, and other brain conditions. If successful, researchers hope the technique could be extended to help people who have difficulty vocalizing because of conditions such as cerebral palsy or autism.

The potential of voice neuroprosthesis is beginning to trigger interest among businesses. Precision Neuroscience claims to be capturing higher resolution brain signals than academic researchers, since the electrodes of its implants are more densely packed.

The company has worked with 31 patients and plans soon to collect data from more, providing a potential pathway to commercialization.

Precision received regulatory clearance on April 17 to leave its sensors implanted for up to 30 days at a time. That would enable its scientists to train their system with what could within a year be the “largest repository of high resolution neural data that exists on planet Earth,” said chief executive Michael Mager.

The next step would be to “miniaturize the components and put them in hermetically sealed packages that are biocompatible so they can be planted in the body forever,” Mager said.

Elon Musk’s Neuralink, the best-known brain-computer interface (BCI) company, has focused on enabling people with paralysis to control computers rather than giving them a synthetic voice.

An important obstacle to the development of brain-to-voice technology is the time patients take to learn how to use the system.

A key unanswered question is how much the response patterns in the motor cortex—the part of the brain that controls voluntary actions, including speech—vary between people. If they remained very similar, machine-learning models trained on previous individuals could be used for new patients, said Nick Ramsey, a BCI researcher at University Medical Centre Utrecht.



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