Evidence map›Paper›PMID 42085611›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Reinnervation of Muscle Targets Enhances the Separability of Motor Unit Signals Following Peripheral Nerve Transfers.

Kiara N Quinn, Siyu Wang, Lang Qin, Alessandro Ascani Orsini, Kenzi Griffith, Rachana Suresh, Fausto Kang, Pierce L Perkins, Neha Joshi, Alexis L Lowe and 2 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

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

12 authors.

Kiara N QuinnDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0003-3371-300X
Siyu WangDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0009-0008-8760-4945
Lang QinDepartment of Electrical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Alessandro Ascani OrsiniDepartment of Electrical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Kenzi GriffithDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Rachana SureshDepartment of Plastic and Reconstructive Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Fausto KangDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Pierce L PerkinsDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Neha JoshiDeparatment of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, Pune, India.
Alexis L LoweDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Sami TuffahaDepartment of Plastic and Reconstructive Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Nitish V ThakorDepartment of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Funding

Next-Generation Tools to Measure and Manipulate Muscle Activity Across Species and BehaviorsR01NS109237 · NINDS · EMORY UNIVERSITY · PI Muhannad Bakir, Samuel Sober · 2019 to 2026
$3.8M
Center for Advanced Muscle BioElectronics (CAMBER)U24NS126936 · NINDS · EMORY UNIVERSITY · PI Samuel Sober · 2023 to 2026
$3.5M
Johns Hopkins Merkin Peripheral Neuropathy and Nerve Regeneration Center grantJohns Hopkins University Discovery AwardKavli Foundation Neuroscience Discovery Institute Graduate FellowshipNational Science Foundation DGE-2139757NINDS NIH HHS R01 NS109237NINDS NIH HHS U24 NS126936
6 · The paper itself

Abstract

After amputation, advanced prosthetic limbs offer a promising means of restoring motor function. However, state-of-the-art prostheses often rely on aggregate electromyogram (EMG) signals to decode motor intention, which limits their ability to replicate natural limb movements. Decomposing EMG signals into individual motor unit components has shown potential for more natural control, but distinguishing between individual units can be challenging when nearby signals overlap. This study demonstrates that muscle target reinnervation surgeries can naturally increase physical separation between motor unit signals, thereby mitigating this overlap. Reinnervation of individual motor units is evaluated in a rodent hindlimb model after direct nerve-to-muscle implantation. Histological and electrophysiological analyses reveal that structural changes following reinnervation surgery result in beneficial motor unit signal changes, particularly improving spatial separation between motor unit signals compared to those in intact muscle. This spatial separation contributed to fewer instances of complex, overlapping signals in reinnervated muscle recordings. Motor unit signals were leveraged to provide a proof-of-concept of precise control of a virtual prosthesis for the first time after direct nerve-to-muscle implantation surgery. These findings highlight the potential of reinnervated muscle targets as key biological interfaces that facilitate motor unit separation, reducing the burden on decomposition algorithms and improving prosthetic control.

Indexed as

Artificial LimbsMotor NeuronsMuscle, SkeletalNerve RegenerationNerve TransferPeripheral NervesAnimalsElectromyographyFemaleHindlimbRatselectromyogrammotor unitmuscle reinnervation surgeryneuromuscular junctionneuroprostheticprosthesis control

Identifiers

PMID42085611
PMCPMC13335489

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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.