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Open access

A generalizable speech neuroprosthesis

Zachery M. Fogg N. Card M. Wairagkar Aparna Srinivasan Tyler Singer-Clark Xianda Hou E. Okorokova Hamza Peracha Carrina Iacobacci Tiffany Brailow J. Jude H. Levi-Aharoni Trung Le Domenick M. Mifsud P. Deevi S. R. Nason-Tomaszewski A. L. Pritchard Yunnuo Zhang B. Richards P. Bechefsky Leigh R. Hochberg Ziv M. Williams K. Shahlaie N. AuYong Daniel B. Rubin C. Pandarinath D. M. Brandman S. Stavisky
Jul 2026 · bioRxiv · 0 citations
Biology Medicine

TL;DR

A transformer-based decoder model trained jointly across six intracortical speech BCI participants reveals how to pool intracortical data across people to yield more accurate, generalizable, and rapidly-deployable decoding models.

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