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Inner speech in motor cortex and implications for speech neuroprostheses by Erin M. Kunz & Benyamin Abramovich Krasa & Foram Kamdar & Donald T. Avansino & Nick Hahn & Seonghyun Yoon & Akansha Singh & Samuel R. Nason-Tomaszewski & Nicholas S. Card & Justin J. Jude & Brandon G. Jacques & Payton H. Bechefsky & Carrina Iacobacci &... instant download

  • SKU: EBN-238018396
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Authors:Erin M. Kunz & Benyamin Abramovich Krasa & Foram Kamdar & Donald T. Avansino & Nick Hahn & Seonghyun Yoon & Akansha Singh & Samuel R. Nason-Tomaszewski & Nicholas S. Card & Justin J. Jude & Brandon G. Jacques & Payton H. Bechefsky & Carrina Iacobacci &...
Pages:updating ...
Year:2025
Publisher:x
Language:english
File Size:10.46 MB
Format:pdf
Categories: Ebooks

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Inner speech in motor cortex and implications for speech neuroprostheses by Erin M. Kunz & Benyamin Abramovich Krasa & Foram Kamdar & Donald T. Avansino & Nick Hahn & Seonghyun Yoon & Akansha Singh & Samuel R. Nason-Tomaszewski & Nicholas S. Card & Justin J. Jude & Brandon G. Jacques & Payton H. Bechefsky & Carrina Iacobacci &... instant download

Cell, Corrected proof. doi:10.1016/j.cell.2025.06.015

SUMMARYSpeech brain-computer interfaces (BCIs) show promise in restoring communication to people with paralysis but have also prompted discussions regarding their potential to decode private inner speech. Separately, inner speech may be a way to bypass the current approach of requiring speech BCI users to physically attempt speech, which is fatiguing and can slow communication. Using multi-unit recordings from four participants, we found that inner speech is robustly represented in the motor cortex and that imagined sentences can be decoded in real time. The representation of inner speech was highly correlated with attempted speech, though we also identified a neural ‘‘motor-intent’’ dimension that differentiates the two. We investigated the possibility of decoding private inner speech and found that some aspects of free-form inner speech could be decoded during sequence recall and counting tasks. Finally, we demonstrate high-fidelity strategies that prevent speech BCIs from unintentionally decoding private inner speech.INTRODUCTIONeven their own arm.8–10 Recently, BCIs have restored rapid communication through accurate decoding of handwriting11and speech,12–16 exceeding the rates offered by alternative deBrain-computer interfaces (BCIs) offer a promising solution for restoring lost movement or communication in people with pavices (e.g., eye tracking). Encouragingly, the most recent ralysis due to injury or disease.1 Successful demonstrations demonstration highlights the successful everyday use of a have shown that people with tetraplegia can use neural signals speech neuroprosthesis by a person with Amyotrophic Lateral to control a computer cursor,2–7 manipulate a robotic arm, or Sclerosis (ALS) for open-ended communication.17

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