BCIs currently rely on attempted speech, where patients must try to move the muscles involved in speaking so the brain signals can be decoded. This is exhausting and not patient-friendly.

Researchers at Stanford have now developed a method to decode inner speech, which is what a patient thinks silently, and translate it directly into speech.

However, this approach has a significant drawback that could limit the development of future brain-computer interfaces.

Reference: Kunz, Erin M. et al. Inner speech in motor cortex and implications for speech neuroprostheses. Cell, Volume 188, Issue 17, 4658-4673.e17.

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