ArticleThe New England journal of medicine2021
Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria.
Article in The New England journal of medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03698149 (A High-Performance ECoG-based Neural Interface for Communication and Neuroprosthetic Control), which is not on this map. Cited by 210 papers, 2 of them syntheses that pooled it.
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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.
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.
A High-Performance ECoG-based Neural Interface for Communication and Neuroprosthetic Control
Who cites it
210 citing papers in PubMed, 2 syntheses or guidelines pooled it, 549 citations in OpenAlex.
- Artificial intelligence for brain-to-speech decoding in paralysis: a systematic review.BMC medical informatics and decision making · 2026Pooled it
- Toward the Clinical Translation of Implantable Brain-Computer Interfaces for Motor Impairment: Research Trends and Outcome Measures.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Pooled it
- Real-time detection of spoken speech from unlabeled ECoG signals: a pilot study with an ALS participant.Journal of neural engineering · 2025Trial
- Speech motor cortex enables BCI cursor control and click.Journal of neural engineering · 2025Trial
- Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System.Neurology · 2023Trial
- In conversation with Edward Chang.Nature neuroscience · 2026Article
- Noninvasive decoding of typed sentences from human brain activity.Nature neuroscience · 2026Article
- Simultaneous speech and gesture decoding for multimodal communication in paralysis.Nature neuroscience · 2026Article
- A neural architecture for imagined and overt speech motor dynamics.Nature neuroscience · 2026Article
- Measuring motor intent for BCI control-A comparative analysis of signal quality of simultaneously recorded vECoG and scalp EEG.Journal of neural engineering · 2026Article
- Temporally structured motor and auditory representations in covert syllable production.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Speech Brain-Computer Interfaces: A New Pathway for Restoring Communication in Anarthria.Neuroscience bulletin · 2026Article
- Optimal Size of Electrocorticography Grids for Classification of Hand Movements.Neuroinformatics · 2026Article
- Advancing data protections for implantable brain-computer interfaces.Communications medicine · 2026Review
- Shared latent representations of speech production for cross-patient speech decoding.Nature communications · 2026Article
- Sensory-guided human-machine joint learning accelerates the acquisition of motor imagery brain computer interface control.Nature communications · 2026Article
- Perspectives in conducting task-based research in pediatric surgical epilepsy patients.bioRxiv : the preprint server for biology · 2026Article
- Long-term independent use of an intracortical brain-computer interface for speech and cursor control.Nature medicine · 2026Article
- Long-term unsupervised recalibration of cursor-based intracortical brain-computer interfaces using a hidden Markov model.Nature biomedical engineering · 2026Article
- Minimally invasive implantation of scalable high-density cortical microelectrode arrays for multimodal neural decoding and stimulation.Nature biomedical engineering · 2026Article
150 more citing papers are in PubMed but not listed here.
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
Abstract
backgroundTechnology to restore the ability to communicate in paralyzed persons who cannot speak has the potential to improve autonomy and quality of life. An approach that decodes words and sentences directly from the cerebral cortical activity of such patients may represent an advancement over existing methods for assisted communication.
methodsWe implanted a subdural, high-density, multielectrode array over the area of the sensorimotor cortex that controls speech in a person with anarthria (the loss of the ability to articulate speech) and spastic quadriparesis caused by a brain-stem stroke. Over the course of 48 sessions, we recorded 22 hours of cortical activity while the participant attempted to say individual words from a vocabulary set of 50 words. We used deep-learning algorithms to create computational models for the detection and classification of words from patterns in the recorded cortical activity. We applied these computational models, as well as a natural-language model that yielded next-word probabilities given the preceding words in a sequence, to decode full sentences as the participant attempted to say them.
resultsWe decoded sentences from the participant's cortical activity in real time at a median rate of 15.2 words per minute, with a median word error rate of 25.6%. In post hoc analyses, we detected 98% of the attempts by the participant to produce individual words, and we classified words with 47.1% accuracy using cortical signals that were stable throughout the 81-week study period.
conclusionsIn a person with anarthria and spastic quadriparesis caused by a brain-stem stroke, words and sentences were decoded directly from cortical activity during attempted speech with the use of deep-learning models and a natural-language model. (Funded by Facebook and others; ClinicalTrials.gov number, NCT03698149.).
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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 OpenQuestion graph.