Evidence map›Paper›PMID 40502202›Full record

ArticlebioRxiv : the preprint server for biology2025

Encoding of speech modes and loudness in ventral precentral gyrus.

Aparna Srinivasan, Maitreyee Wairagkar, Carrina Iacobacci, Xianda Hou, Nicholas S Card, Brandon G Jacques, Anna L Pritchard, Payton H Bechefsky, Leigh R Hochberg, Nicholas AuYong and 3 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Aparna SrinivasanDepartment of Neurological Surgery, University of California Davis, Davis, CA, USA.
Maitreyee WairagkarDepartment of Neurological Surgery, University of California Davis, Davis, CA, USA.
Carrina IacobacciDepartment of Neurological Surgery, University of California Davis, Davis, CA, USA.
Xianda HouDepartment of Neurological Surgery, University of California Davis, Davis, CA, USA.
Nicholas S CardDepartment of Neurological Surgery, University of California Davis, Davis, CA, USA.
Brandon G JacquesWallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Anna L PritchardWallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Payton H BechefskyWallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Leigh R HochbergCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Nicholas AuYongWallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Chethan PandarinathWallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, 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.

Funding

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
NIDCD NIH HHS DP2 DC021055
6 · The paper itself

Abstract

The ability to vary the mode and loudness of speech is an important part of the expressive range of human vocal communication. However, the encoding of these behaviors in the ventral precentral gyrus (vPCG) has not been studied at the resolution of neuronal firing rates. We investigated this in two participants who had intracortical microelectrode arrays implanted in their vPCG as part of a speech neuroprosthesis clinical trial. Neuronal firing rates modulated strongly in vPCG as a function of attempted mimed, whispered, normal or loud speech. At the neural ensemble level, mode/loudness and phonemic content were encoded in distinct neural subspaces. Attempted mode/loudness could be decoded from vPCG with an accuracy of 94% and 89% for two participants respectively, and corresponding neural preparatory activity could be detected hundreds of milliseconds before speech onset. We then developed a closed-loop loudness decoder that achieved 94% online accuracy in modulating a brain-to-text speech neuroprosthesis output based on attempted loudness. These findings demonstrate the feasibility of decoding mode and loudness from vPCG, paving the way for speech neuroprostheses capable of synthesizing more expressive speech.

Identifiers

PMID40502202
PMCPMC12154859

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Registered trials

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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.