Decoding intended speech with an intracortical brain-computer interface in a person with longstanding anarthria and locked-in syndrome Article Swipe
Justin Jude
,
Stephanie Haro
,
Hadar Levi-Aharoni
,
Hiroaki Hashimoto
,
Alexander J. Acosta
,
Nicholas S. Card
,
Maitreyee Wairagkar
,
David M. Brandman
,
Sergey D. Stavisky
,
Ziv M. Williams
,
Sydney S. Cash
,
John D. Simeral
,
Leigh R. Hochberg
,
Daniel B. Rubin
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.08.12.668516
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.08.12.668516
Intracortical brain-computer interfaces (iBCIs) for decoding intended speech have provided individuals with ALS and severe dysarthria an intuitive method for high-throughput communication. These advances have been demonstrated in individuals who are still able to vocalize and move speech articulators. Here, we decoded intended speech from an individual with longstanding anarthria, locked-in syndrome, and ventilator dependence due to advanced symptoms of ALS. We found that phonemes, words, and higher-order language units could be decoded well above chance. While sentence decoding accuracy was below that of demonstrations in participants with dysarthria, we are able to attain an extensive characterization of the neural signals underlying speech in a person with locked-in syndrome and through our results identify several directions for future improvement. These include closed-loop speech imagery training and decoding linguistic (rather than phonemic) units from neural signals in middle precentral gyrus. Overall, these results demonstrate that speech decoding from motor cortex may be feasible in people with anarthria and ventilator dependence. For individuals with longstanding anarthria, a purely phoneme-based decoding approach may lack the accuracy necessary to support independent use as a primary means of communication; however, additional linguistic information embedded within neural signals may provide a route to augment the performance of speech decoders.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.08.12.668516
- OA Status
- green
- References
- 66
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413149774
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413149774Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2025.08.12.668516Digital Object Identifier
- Title
-
Decoding intended speech with an intracortical brain-computer interface in a person with longstanding anarthria and locked-in syndromeWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
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2025-08-13Full publication date if available
- Authors
-
Justin Jude, Stephanie Haro, Hadar Levi-Aharoni, Hiroaki Hashimoto, Alexander J. Acosta, Nicholas S. Card, Maitreyee Wairagkar, David M. Brandman, Sergey D. Stavisky, Ziv M. Williams, Sydney S. Cash, John D. Simeral, Leigh R. Hochberg, Daniel B. RubinList of authors in order
- Landing page
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https://doi.org/10.1101/2025.08.12.668516Publisher landing page
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.ncbi.nlm.nih.gov/pmc/articles/12363778Direct OA link when available
- Concepts
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Dysarthria, Locked-in syndrome, Decoding methods, Speech recognition, Computer science, Brain–computer interface, Sentence, Speech production, Neural decoding, Psychology, Electroencephalography, Artificial intelligence, Neuroscience, Telecommunications, PsychiatryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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66Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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