Evidence map›Paper›PMID 41920737›Full record

ArticleCell reports2026

Decoding intended speech with an intracortical brain-computer interface in a person with long-standing anarthria and locked-in syndrome.

Justin J 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 and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Premotor cortex uses a compositional neural geometry to plan words.bioRxiv : the preprint server for biology · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Justin J JudeCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; School of Engineering, Brown University, Providence, RI, USA. Electronic address: jjude@mgh.harvard.edu.
Stephanie HaroSchool of Engineering, Brown University, Providence, RI, USA.
Hadar Levi-AharoniCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; School of Engineering, Brown University, Providence, RI, USA.
Hiroaki HashimotoCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
Alexander J AcostaCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Nicholas S CardDepartment of Neurological Surgery, University of California, Davis, Davis, CA, USA.
Maitreyee WairagkarDepartment of Neurological Surgery, University of California, Davis, Davis, CA, USA.
David M BrandmanDepartment of Neurological Surgery, University of California, Davis, Davis, CA, USA.
Sergey D StaviskyDepartment of Neurological Surgery, University of California, Davis, Davis, CA, USA.
Ziv M WilliamsDepartment of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Boston, MA, USA; Harvard Medical School, Program in Neuroscience, Boston, MA, USA.
Sydney S CashCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
John D SimeralSchool of Engineering, Brown University, Providence, RI, USA; VA Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA; Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA.
Leigh R HochbergCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; School of Engineering, Brown University, Providence, RI, USA; VA Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA; Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA.
Daniel B RubinCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.

Funding

Neuroscience Resident Research ProgramR25NS065743 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, WILLIAMS, ZIV · 2009 to 2023
$11.8M
Intuitive, complete neural control of tablet computers for communicationU01DC017844 · NIDCD · BROWN UNIVERSITY · PI HOCHBERG, LEIGH R · 2019 to 2025
$4.3M
Understanding and restoring speech production using an intracortical brain-computer interfaceDP2DC021055 · NIDCD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI STAVISKY, SERGEY · 2022 to 2025
$2.3M
Neural control of speech generation in human motor cortexK23DC021297 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI DANIEL B RUBIN · 2023 to 2026
$786k
NIDCD NIH HHS DP2 DC021055NIDCD NIH HHS K23 DC021297NIDCD NIH HHS U01 DC017844NINDS NIH HHS R25 NS065743RRD VA I01 RX002295RRD VA I01 RX004820RRD VA I50 RX002864
6 · The paper itself

Abstract

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 long-standing 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 attained an extensive characterization of neural signals underlying speech in a person with locked-in syndrome and identify 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 to augment decoding at the sentence level. These results demonstrate that usable speech decoding from motor cortex may be feasible in people with anarthria and ventilator dependence.

Indexed as

amyotrophic lateral sclerosisBCI communicationCP: neuroscienceintracortical brain-computer interfaceslanguage encodinglocked-in syndromelongstanding anarthriaspeech decoding

Identifiers

PMID41920737
PMCPMC13335209

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.