Article 667FK Brain-Machine Interface Device Predicts Internal Speech

Brain-Machine Interface Device Predicts Internal Speech

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janrinok
from SoylentNews on (#667FK)

hubie writes:

Preliminary results could ultimately help patients who cannot speak:

New Caltech research is showing how devices implanted into people's brains, called brain-machine interfaces (BMIs), could one day help patients who have lost their ability to speak. In a new study presented at the 2022 Society for Neuroscience conference in San Diego, the researchers demonstrated that they could use a BMI to accurately predict which words a tetraplegic participant was simply thinking and not speaking or miming.

[...] "These new results are promising in the areas of language and communication. We used a BMI to reconstruct speech," says Wandelt, who presented the results at the conference on November 13.

[...] The work is still preliminary but could help patients with brain injuries, paralysis, or diseases such as amyotrophic lateral sclerosis (ALS) that affect speech. "Neurological disorders can lead to complete paralysis of voluntary muscles, resulting in patients being unable to speak or move, but they are still able to think and reason. For that population, an internal speech BMI would be incredibly helpful," Wandelt says.

"We have previously shown that we can decode imagined hand shapes for grasping from the human supramarginal gyrus," says Andersen. "Being able to also decode speech from this area suggests that one implant can recover two important human abilities: grasping and speech."

The researchers also point out that the BMIs cannot be used to read people's minds; the device would need to be trained in each person's brain separately, and they only work when a person focuses on the word.

Journal Reference:
Sarah K. Wandelt, David A. Bjanes, Kelsie Pejsa,et al., Online internal speech decoding from single neurons in a human participant, medRxiv preprint, 2022. DOI: 10.1101/2022.11.02.22281775

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