Evidence map›Paper›PMID 33236720›Full record

ArticleJournal of neural engineering2020

Decoding spoken English from intracortical electrode arrays in dorsal precentral gyrus.

Guy H Wilson, Sergey D Stavisky, Francis R Willett, Donald T Avansino, Jessica N Kelemen, Leigh R Hochberg, Jaimie M Henderson, Shaul Druckmann, Krishna V Shenoy

Registry-linked trialAbstract read
In one paragraph

Article in Journal of neural engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00912041 (BrainGate2), which is not on this map. Cited by 46 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 1 pooled it
–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.

NCT00912041 narecruitingnot on this map

BrainGate2: Feasibility Study of an Intracortical Neural Interface System for Persons With Tetraplegia

TypeinterventionalSponsorLeigh R. Hochberg, MD, PhD.Ran2009 to 2038Enrolled27ConditionsTetraplegia, Spinal Cord Injuries, Amyotrophic Lateral Sclerosis, Brain Stem InfarctionsArmsPlacement of the BrainGate2 sensor(s) into the motor-related cortex
3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Review
  12. Article
  13. Encoding of speech modes and loudness in ventral precentral gyrus.bioRxiv : the preprint server for biology · 2025
    Article
  14. Orbitofrontal High-Gamma Reflects Spike-Dissociable Value and Decision Mechanisms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  15. Article
  16. Decoding semantics from natural speech using human intracranial EEG.bioRxiv : the preprint server for biology · 2025
    Article
  17. Article
  18. Acoustic Inspired Brain-to-Sentence Decoder for Logosyllabic Language.Cyborg and bionic systems (Washington, D.C.) · 2025
    Article
  19. Article
  20. Speech motor cortex enables BCI cursor control and click.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Guy H WilsonNeurosciences Graduate Program, Stanford University, Stanford, CA, United States of America.ORCID 0000-0003-0961-1994
Sergey D StaviskyDepartment of Neurosurgery, Stanford University, Stanford, CA, United States of America.ORCID 0000-0002-5238-0573
Francis R WillettDepartment of Neurosurgery, Stanford University, Stanford, CA, United States of America.ORCID 0000-0002-2652-8511
Donald T AvansinoDepartment of Neurosurgery, Stanford University, Stanford, CA, United States of America.ORCID 0000-0002-7974-0153
Jessica N KelemenDepartment of Neurology, Harvard Medical School, Boston, MA, United States of America.ORCID 0000-0002-2779-0431
Leigh R HochbergDepartment of Neurology, Harvard Medical School, Boston, MA, United States of America.ORCID 0000-0003-0261-2273
Jaimie M HendersonDepartment of Neurosurgery, Stanford University, Stanford, CA, United States of America.ORCID 0000-0002-3276-2267
Shaul DruckmannWu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America.ORCID 0000-0003-0068-3377
Krishna V ShenoyWu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, United States of America.ORCID 0000-0003-1534-9240

Funding

Engaging new cognitive and motor signals to improve communication prosthesesR01DC014034 · NIDCD · STANFORD UNIVERSITY · PI JAIMIE M HENDERSON · 2015 to 2026
$8.2M
Restoring Communication with an Intracortical Neural Interface SystemR01DC009899 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI HOCHBERG, LEIGH R · 2009 to 2017
$7.0M
Understanding the Neural Basis of Volitional State through Continuous Recordings in HumansU01NS098968 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S · 2016 to 2018
$4.7M
Intuitive, complete neural control of tablet computers for communicationU01DC017844 · NIDCD · BROWN UNIVERSITY · PI HOCHBERG, LEIGH R · 2019 to 2025
$4.3M
High-Bandwidth Wireless Interfaces for Continuous Human Intracortical RecordingUH2NS095548 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI HOCHBERG, LEIGH R, NURMIKKO, ARTO · 2015 to 2019
$3.7M
Toward an Animal Model of Freely Moving HumansR01NS066311 · NINDS · STANFORD UNIVERSITY · PI BLACK, MICHAEL J, SHENOY, KRISHNA V · 2009 to 2012
$2.9M
Dissecting distributed representations by advanced population activity analysis methods and modelingR01EB028171 · NIBIB · STANFORD UNIVERSITY · PI DRUCKMANN, SHAUL · 2019 to 2019
$1.1M
NIBIB NIH HHS R01 EB028171NICHD NIH HHS N01 HD053403NIDCD NIH HHS R01 DC009899NIDCD NIH HHS R01 DC014034NIDCD NIH HHS U01 DC017844NINDS NIH HHS R01 NS066311NINDS NIH HHS U01 NS098968NINDS NIH HHS UH2 NS095548RRD VA I01 RX002295RRD VA I50 RX002864
6 · The paper itself

Abstract

objectiveTo evaluate the potential of intracortical electrode array signals for brain-computer interfaces (BCIs) to restore lost speech, we measured the performance of decoders trained to discriminate a comprehensive basis set of 39 English phonemes and to synthesize speech sounds via a neural pattern matching method. We decoded neural correlates of spoken-out-loud words in the 'hand knob' area of precentral gyrus, a step toward the eventual goal of decoding attempted speech from ventral speech areas in patients who are unable to speak. APPROACH: Neural and audio data were recorded while two BrainGate2 pilot clinical trial participants, each with two chronically-implanted 96-electrode arrays, spoke 420 different words that broadly sampled English phonemes. Phoneme onsets were identified from audio recordings, and their identities were then classified from neural features consisting of each electrode's binned action potential counts or high-frequency local field potential power. Speech synthesis was performed using the 'Brain-to-Speech' pattern matching method. We also examined two potential confounds specific to decoding overt speech: acoustic contamination of neural signals and systematic differences in labeling different phonemes' onset times. MAIN

resultsA linear decoder achieved up to 29.3% classification accuracy (chance = 6%) across 39 phonemes, while an RNN classifier achieved 33.9% accuracy. Parameter sweeps indicated that performance did not saturate when adding more electrodes or more training data, and that accuracy improved when utilizing time-varying structure in the data. Microphonic contamination and phoneme onset differences modestly increased decoding accuracy, but could be mitigated by acoustic artifact subtraction and using a neural speech onset marker, respectively. Speech synthesis achieved r = 0.523 correlation between true and reconstructed audio. SIGNIFICANCE: The ability to decode speech using intracortical electrode array signals from a nontraditional speech area suggests that placing electrode arrays in ventral speech areas is a promising direction for speech BCIs.

Indexed as

Brain-Computer InterfacesSpeechElectrodesHandHumansLanguage

Identifiers

PMID33236720
PMCPMC8293867

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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.