Nerve transfers offer a variety of therapeutic possibilities in modern extremity reconstruction, such as treating peripheral nerve injuries, neuromas, phantom limb pain, improving prosthetic control, or restoring function following spinal cord injuries (Aszmann et al., 2015; Farina et al., 2017; Dumanian et al., 2019; Van Zyl et al., 2019). Compared to conventional nerve repair modalities, nerve transfers are capable of bypassing slow peripheral nerve regeneration (Terzis and Papakonstantinou, 2000), thus preventing irreversible muscle fibrosis before reinnervation (Mackinnon and Novak, 1999). For this purpose, nearby nerves with a sufficient axonal load and lesser functional importance are neurotomized and transferred to the injured nerve (Oberlin et al., 1994; Bertelli et al., 1997). Because of overall faster regeneration and better functional outcomes compared to nerve grafting, this surgical procedure has been able to improve the devastating effects of peripheral nerve and brachial plexus lesions, which have otherwise often led to long-term health impairment and subsequent socioeconomic costs (Mackinnon and Novak, 1999; Terzis and Papakonstantinou, 2000; Bergmeister et al., 2020). Additionally, they are used in a procedure termed targeted muscle reinnervation (TMR) to improve myoelectric prosthetic control (Kuiken et al., 2009; Kapelner et al., 2016), treat neuromas or phantom limb pain (Mioton et al., 2020). Here, amputated nerves within an extremity stump are transferred to residual stump muscles, thus significantly improving the recording of neural activity about motor intent and the control of myoelectric prostheses. Generally, one donor nerve is transferred to one target muscle head and this concept has been well studied with high clinical success (Kuiken et al., 2009; Aszmann et al., 2015; Farina et al., 2017). The use of multiple nerve transfers to a single target muscle may further enhance TMR surgery. It could provide additional neuroprosthetic signals and overcome certain limitations in neuromuscular interfacing. Furthermore, transferring multiple nerves to a single target muscle may facilitate neuroma treatment, as not only one but multiple nerves are implanted in a muscle graft or residual limb muscle in an extremity stump (Herr et al., 2021).

Although several nerve transfer models have been established (Kuiken et al., 1995; Bergmeister et al., 2016; Aman et al., 2019b), none of them has investigated multiple peripheral nerve transfers in the upper extremity. Only one model where multiple donor nerves are used to restore muscle function in the rat hindlimb has been described (Kuiken et al., 1995). However, as most nerve injuries occur in the upper extremity, an upper extremity model for experimental investigation of this concept is needed (Scholz et al., 2009).

In this study, we propose a surgical nerve transfer model to allow the transfer of multiple donor nerves to a single muscle head and we validate this model in the rat forelimb. This model allows for reliable analyses with all standard neurophysiological investigations of the motor unit for possible implementation of this concept to clinical application.

The present study provides a robust and easily accessible model for surgical DNTs to a single target muscle in the rat’s upper extremity. We offer detailed step-by-step instructions on how to reproduce this model, including potential pitfalls. For comparison, the model also offers a description of a SNT to the same target muscle. We employed nerve crush, neurotomy, behavioral analysis, and retrograde labeling which indicated that neuromuscular regeneration of two donor nerves occurred into one target muscle.

To our knowledge, only one rat model for multiple peripheral innervation of a single target has been described. However, that previous model was for the lower extremity and did not provide a detailed description for step-by-step reproduction of the model (Kuiken et al., 1995). Hindlimb models do not adequately represent the physiology of upper extremity nerve transfers and TMR procedures. The key differences between upper and lower extremities are amount of usage of the limbs, complexity of movement, weight-bearing, and of course sensorimotor circuitry. This notion is supported by the clinical discrepancy between the excellent outcomes for upper extremity compared to the poor outcomes for lower extremity nerve transfers (Ray et al., 2016). Furthermore, most nerve transfers are currently conducted in the upper extremity for both nerve reconstruction and prosthetic control. We already established single peripheral nerve transfer models in the upper extremity (Bergmeister et al., 2016; Aman et al., 2019b), which were considered for developing this novel model. For this purpose, we conducted anatomical dissections in eight rat cadavers to design the DNT concept to allow tension-free approximation of the two motor nerves to the target biceps muscle. Theoretically, many other target muscles are also feasible due to the sufficient length of both the UN and AIN. However, the biceps muscle provides an optimal target that is accessible for all standard structural and functional analyses and accurately represents a surgical target in clinical nerve transfer scenarios as well.

The implementation of this model requires an operating microscope, a set of microsurgery tools, and advanced microsurgical skills to achieve reproducible results. In our experience, dissection of the UN in the antebrachium can be performed in a straightforward manner and preservation of the motor branch to the flexor carpi ulnaris muscle, the dorsal sensory branch, and the ulnar artery is easily feasible. Subsequently, transecting the UN as distally as possible allows for tension-free coaptation to the proximal target muscle. Exposure of the MCN’s motor branch to the long head of the biceps is best achieved in the bicipital groove by retracting the overlaying pectoral muscles medially. Here, considerable care must be taken when dividing the two bicep heads to preserve the bicipital artery, which enters the long head in the distal portion and advances in proximal direction. Injury to this vessel has shown to affect functional measures in previous experiments. Another hazard in the DNT model is potential injury of the median vessels in the cubital fossa. To prevent this scenario, special attention is required during the dissection of the median nerve, because the median vessels are either found directly beneath or above the nerve. It is mandatory to dissect the AIN intraneurally to its proximal branching point to enable tension-free coaptation to the original motor point of the biceps. Due to the target to donor nerve diameter discrepancies, we chose to suture the donor nerves to the motor entry point epimysially. In previous models, this approach led to reliable reinnervation of the target muscle (Bergmeister et al., 2019).

Our behavioral observations indicate that the procedures did not cause extraordinary distress or pain under adequate analgesia postoperatively. As early as 1 week after surgery, behavioral testing was carried out in randomly selected individual animals, and all of them achieved the maximum score. Likewise, after a 12-week regeneration period, all animals from both the control and the experimental DNT group achieved the maximum score of Terzis grooming test (Inciong et al., 2000; Video 1). Hence, it seems that two motor nerves of different origins governing the same muscle did not hamper activities of daily living. Additionally, no substantial pain or neuroma pain was evident. When comparing the two procedures, it takes only marginally longer to perform the DNT, while no additional physical stress or motor deficits were observed postoperatively.

The donor nerves reinnervated the target muscle within 12 weeks in all animals as indicated macroscopically during dissection and by the fact that nerve crush or neurotomy induced fasciculations of the muscle (Videos 3 and 4). Likewise, intramuscular retrograde labeling showed the uptake and transport of tracer dye into the motor neuron columns of the two transferred nerves. Retrograde labeling further indicated that the overall number of motor units was reduced to 75.47% in SNT but increased to 119.26% in DNT compared to the untreated control side. Most interestingly, there was a statistically significant increase of 58.02% in motor units following DNT compared to SNT. This suggests that DNT may be more likely to sufficiently innervate muscle fibers and furthermore potentially increase myosignals for prosthetic interfacing, as has been previously shown (Bergmeister et al., 2019).

Interestingly, after 12 weeks, muscle mass of the UN reinnervated muscles only recovered to 80.25% of the contralateral side. This is in contrast with previous studies performed by the authors of this work (Bergmeister et al., 2019). A possible explanation for this mismatch is the difference of the levels at which the UN was cut and transferred in the two studies. Unlike in the previous study where the entire UN was transferred, here the UN was transferred at the wrist level. This may have caused that the donor nerve was not able to fully regenerate the long head of the biceps due to the lower motor axon numbers. Detailed analyses exist for humans, where the UN at wrist level only contains 1226±243 motor axons compared to the entire UN (2670±347) whereas the MCN contains 1601±164 (Gesslbauer et al., 2017). Considering that the muscle mass of double reinnervated muscles regenerated to 98.83%, it appears that the two donor nerves were better able to reinnervate and adequately restore 24.72% more muscle mass than the SNT. This additionally indicates that both SNT and DNT procedures were successful and that DNT with a high axonal load may lead to higher muscle reinnervation and functional regeneration.

Previous findings (Bergmeister et al., 2019) reported neuroma formation at the insertion point following nerve transfer. These consisted presumably mainly of sensory axons and the surplus of motor neurons which was not able to innervate motor endplates. We did not observe neuroma formation in this study and believe, that this is because the donor nerves comprised only a few sensory axons and the donor-to-recipient ratio of motor axons and targets was more balanced than in the previous study, as mentioned above. Therefore, we assume that no fibers were lost at the insertion site to the muscle, which may have formed a neuroma. Although the question of the optimal donor-to-recipient ratio for optimal outcome remains unsolved, further investigations in this surgical model are ongoing to answer this question and contribute to the surgical refinement of nerve transfers.

The presented nerve transfer model finds broad application in many research fields. It offers the possibility to investigate basic neurophysiology, but also clinical applications of surgical nerve transfers for biological reconstruction. Additionally, the application of the DNT to already established neuromuscular interfacing approaches for bionic reconstruction could be explored. Regenerative peripheral nerve interfaces RPNIs (Vu et al., 2020), for example, are created by implanting transected peripheral nerves into small free muscle grafts, which serve as neuronal control signal amplifiers. Particularly with RPNIs, the DNT could be advantageous as muscle mass is currently constrained by the axonal count and therefore limiting EMG output for neuroprosthetic control. Potentially beneficial applications could also be explored with the agonist-antagonist myoneural interface (AMI) (Srinivasan et al., 2017). An AMI consists of a pair of muscles connected to each other by its tendons whereas the contraction of one causing the stretching of the other and vice versa. The contraction and its EMG signals serve as control signal for the prosthesis and the stretch as afferent proprioceptive feedback.

Another method that could most likely benefit from the DNT is TMR (Kuiken et al., 2009). After amputation, TMR can create additional myosignals to improve basic prosthetic control. In TMR, neuromas within the stump are cut and the healthy fascicles are then transferred to intact muscle segments, after denervation from their original innervation. Earlier studies revealed that EMG technology can record and decipher neuronal signals from those reinnervated areas into signals for prosthetic movement (Bergmeister et al., 2017; Muceli et al., 2019b; Salminger et al., 2019). The biceps’ long head is suitable to perform various EMG examinations, as we have previously shown (Bergmeister et al., 2019; Muceli et al., 2019a). Especially with novel multichannel EMG technology (Muceli et al., 2015), individual motor unit action potentials can potentially be decoded from such signals as we have previously shown in SNT models (Muceli et al., 2019a).

We want to emphasize that this was a first attempt at controlled multiple innervation of a single target in a murine model. Furthermore, we would like to point out that the clinical translatability of validated rat models may require the verification of scalability in larger animal models first (Aman et al., 2019a). An obvious limitation is the lack of investigation of voluntary motor activity since this is not feasible in rats. It remains unclear whether a human could access a single muscle via two different nerves. Another potential limitation of this study is the use of the mixed UN containing both sensory and motor nerve fibers. For better outcomes of surgical nerve transfers, ‘pure’ motor nerves should be preferred, such as the AIN used here, to avoid sensory to motor axon incongruence (Ray et al., 2016). We decided to transfer the UN at a level, where it also contains sensory fibers of the superficial branch because unlike in humans, intraneural fascicular dissection to identify the two branches proximal to Guyon’s canal is impossible due to the intermingling of axons at the level of Guyon’s canal. Uncomplicated dissection, significant transfer leeway, and the lack of better alternatives made the UN the best option.

In conclusion, this study demonstrated that a single target muscle can host two separate donor nerves. Our results suggest that both the SNT and DNT models are suitable for common neurophysiological examinations in peripheral nerve research. The concept of transferring multiple nerves to a single target may improve muscle reinnervation, prosthetic interfacing, neuroma therapy or facilitate phantom limb pain management. Until first clinical interfacing applications can be translated, further EMG analysis and validation are needed to fully understand the neurophysiological changes following multiple nerve transfers.

Muscle mass data have been deposited in Dryad under the DOI: https://doi.org/10.5061/dryad.3j9kd51jb. Retrograde labeling data has been deposited in Dryad under the DOI: https://doi.org/10.5061/dryad.6q573n60c.

1. 1. Luft M
   2. Klepetko J
   3. Muceli S
   4. Ibáñez J
   5. Tereshenko V
   6. Festin C
   7. Längle G
   8. Politikou O
   9. Maierhofer U
   10. Farina D
   11. Aszmann O
   12. Bergmeister K

   (2021) Dryad Digital Repository

   Muscle mass of the long head of the biceps following single and double nerve transfer.

   https://doi.org/10.5061/dryad.3j9kd51jb
2. 1. Luft M

   (2021) Dryad Digital Repository

   Labeled motor neurons following single and double nerve reinnervation of the long head of the biceps.

   https://doi.org/10.5061/dryad.6q573n60c

1. 1. Aman M
   2. Bergmeister KD
   3. Festin C
   4. Sporer ME
   5. Russold MF
   6. Gstoettner C
   7. Podesser BK
   8. Gail A
   9. Farina D
   10. Cederna P
   11. Aszmann OC

   (2019a) Experimental testing of bionic peripheral nerve and muscle interfaces: Animal model considerations

   Frontiers in Neuroscience 13:1442.

   https://doi.org/10.3389/fnins.2019.01442

   • PubMed
   • Google Scholar
2. 1. Aman M
   2. Sporer M
   3. Bergmeister K
   4. Aszmann O

   (2019b) Experimentelle Modelle Für Selektive nerventransfers Der oberen extremität: Modellbeschreibung und neurophysiologische Effekte

   Handchirurgie · Mikrochirurgie · Plastische Chirurgie 51:319–326.

   https://doi.org/10.1055/a-0802-8851

   • Google Scholar
3. 1. Aszmann OC
   2. Roche AD
   3. Salminger S
   4. Paternostro-Sluga T
   5. Herceg M
   6. Sturma A
   7. Hofer C
   8. Farina D

   (2015) Bionic reconstruction to restore hand function after brachial plexus injury: A case series of three patients

   Lancet 385:2183–2189.

   https://doi.org/10.1016/S0140-6736(14)61776-1

   • PubMed
   • Google Scholar
4. 1. Bergmeister KD
   2. Aman M
   3. Riedl O
   4. Manzano-Szalai K
   5. Sporer ME
   6. Salminger S
   7. Aszmann OC

   (2016) Experimental nerve transfer model in the rat forelimb

   European Surgery 48:334–341.

   https://doi.org/10.1007/s10353-016-0386-4

   • PubMed
   • Google Scholar
5. 1. Bergmeister KD
   2. Vujaklija I
   3. Muceli S
   4. Sturma A
   5. Hruby LA
   6. Prahm C
   7. Riedl O
   8. Salminger S
   9. Manzano-Szalai K
   10. Aman M
   11. Russold MF
   12. Hofer C
   13. Principe J
   14. Farina D
   15. Aszmann OC

   (2017) Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity

   Frontiers in Neuroscience 11:421.

   https://doi.org/10.3389/fnins.2017.00421

   • PubMed
   • Google Scholar
6. 1. Bergmeister KD
   2. Aman M
   3. Muceli S
   4. Vujaklija I
   5. Manzano-Szalai K
   6. Unger E
   7. Byrne RA
   8. Scheinecker C
   9. Riedl O
   10. Salminger S
   11. Frommlet F
   12. Borschel GH
   13. Farina D
   14. Aszmann OC

   (2019) Peripheral nerve transfers change target muscle structure and function

   Science Advances 5:eaau2956.

   https://doi.org/10.1126/sciadv.aau2956

   • PubMed
   • Google Scholar
7. 1. Bergmeister KD
   2. Große-Hartlage L
   3. Daeschler SC
   4. Rhodius P
   5. Böcker A
   6. Beyersdorff M
   7. Kern AO
   8. Kneser U
   9. Harhaus L

   (2020) Acute and long-term costs of 268 peripheral nerve injuries in the upper extremity

   PLOS ONE 15:e0229530.

   https://doi.org/10.1371/journal.pone.0229530

   • PubMed
   • Google Scholar
8. 1. Bertelli JA
   2. Mira JC

   (1993) Behavioral evaluating methods in the objective clinical assessment of motor function after experimental brachial plexus reconstruction in the rat

   Journal of Neuroscience Methods 46:203–208.

   https://doi.org/10.1016/0165-0270(93)90068-3

   • PubMed
   • Google Scholar
9. 1. Bertelli JA
   2. Mira JC
   3. Pecot-Dechavassine M
   4. Sebille A

   (1997) Selective motor hyperreinnervation using motor rootlet transfer: an experimental study in rat brachial plexus

   Journal of Neurosurgery 87:79–84.

   https://doi.org/10.3171/jns.1997.87.1.0079

   • PubMed
   • Google Scholar
10. 1. Dumanian GA
    2. Potter BK
    3. Mioton LM
    4. Ko JH
    5. Cheesborough JE
    6. Souza JM
    7. Ertl WJ
    8. Tintle SM
    9. Nanos GP
    10. Valerio IL
    11. Kuiken TA
    12. Apkarian AV
    13. Porter K
    14. Jordan SW

    (2019) Targeted Muscle Reinnervation Treats Neuroma and Phantom Pain in Major Limb Amputees: A Randomized Clinical Trial

    Annals of Surgery 270:238–246.

    https://doi.org/10.1097/SLA.0000000000003088

    • PubMed
    • Google Scholar
11. 1. Farina D
    2. Vujaklija I
    3. Sartori M
    4. Kapelner T
    5. Negro F
    6. Jiang N
    7. Bergmeister K
    8. Andalib A
    9. Principe J
    10. Aszmann OC

    (2017) Man/machine interface based on the discharge timings of spinal motor neurons after targeted muscle reinnervation

    Nature Biomedical Engineering 1:0025.

    https://doi.org/10.1038/s41551-016-0025

    • Google Scholar
12. 1. Gesslbauer B
    2. Hruby LA
    3. Roche AD
    4. Farina D
    5. Blumer R
    6. Aszmann OC

    (2017) Axonal components of nerves innervating the human arm

    Annals of Neurology 82:396–408.

    https://doi.org/10.1002/ana.25018

    • PubMed
    • Google Scholar
13. 1. Guillen J

    (2012)

    FELASA guidelines and recommendations

    Journal of the American Association for Laboratory Animal Science 51:311–321.

    • PubMed
    • Google Scholar
14. 1. Hayashi A
    2. Moradzadeh A
    3. Hunter D
    4. Kawamura D
    5. Puppala V
    6. Tung T
    7. Mackinnon S
    8. Myckatyn T

    (2007) Retrograde Labeling in Peripheral Nerve Research: It Is Not All Black and White

    Journal of Reconstructive Microsurgery 23:381–389.

    https://doi.org/10.1055/s-2007-992344

    • PubMed
    • Google Scholar
15. 1. Herr HM
    2. Clites TR
    3. Srinivasan S
    4. Talbot SG
    5. Dumanian GA
    6. Cederna PS
    7. Carty MJ

    (2021) Reinventing Extremity Amputation in the Era of Functional Limb Restoration

    Annals of Surgery 273:269–279.

    https://doi.org/10.1097/SLA.0000000000003895

    • PubMed
    • Google Scholar
16. 1. Inciong JG
    2. Marrocco WC
    3. Terzis JK

    (2000) Efficacy of intervention strategies in a brachial plexus global avulsion model in the rat

    Plastic and Reconstructive Surgery 105:2059–2071.

    https://doi.org/10.1097/00006534-200005000-00021

    • PubMed
    • Google Scholar
17. 1. Kapelner T
    2. Jiang N
    3. Holobar A
    4. Vujaklija I
    5. Roche AD
    6. Farina D
    7. Aszmann OC

    (2016) Motor Unit Characteristics after Targeted Muscle Reinnervation

    PLOS ONE 11:e0149772.

    https://doi.org/10.1371/journal.pone.0149772

    • PubMed
    • Google Scholar
18. 1. Kuiken TA
    2. Childress DS
    3. Zev Rymer W

    (1995) The hyper-reinnervation of rat skeletal muscle

    Brain Research 676:113–123.

    https://doi.org/10.1016/0006-8993(95)00102-v

    • PubMed
    • Google Scholar
19. 1. Kuiken TA
    2. Li G
    3. Lock BA
    4. Lipschutz RD
    5. Miller LA
    6. Stubblefield KA
    7. Englehart KB

    (2009) Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms

    JAMA 301:619–628.

    https://doi.org/10.1001/jama.2009.116

    • PubMed
    • Google Scholar
20. 1. Mackinnon SE
    2. Novak CB

    (1999)

    Nerve transfers New options for reconstruction following nerve injury

    Hand Clinics 15:643–666.

    • PubMed
    • Google Scholar
21. 1. Mioton LM
    2. Dumanian GA
    3. Shah N
    4. Qiu CS
    5. Ertl WJ
    6. Potter BK
    7. Souza JM
    8. Valerio IL
    9. Ko JH
    10. Jordan SW

    (2020) Targeted Muscle Reinnervation Improves Residual Limb Pain, Phantom Limb Pain, and Limb Function: A Prospective Study of 33 Major Limb Amputees

    Clinical Orthopaedics and Related Research 478:2161–2167.

    https://doi.org/10.1097/CORR.0000000000001323

    • PubMed
    • Google Scholar
22. 1. Muceli S
    2. Poppendieck W
    3. Negro F
    4. Yoshida K
    5. Hoffmann KP
    6. Butler JE
    7. Gandevia SC
    8. Farina D

    (2015) Accurate and representative decoding of the neural drive to muscles in humans with multi-channel intramuscular thin-film electrodes

    The Journal of Physiology 593:3789–3804.

    https://doi.org/10.1113/JP270902

    • PubMed
    • Google Scholar
23. 1. Muceli S
    2. Bergmeister KD
    3. Hoffmann KP
    4. Aman M
    5. Vukajlija I
    6. Aszmann OC
    7. Farina D

    (2019a) Decoding motor neuron activity from epimysial thin-film electrode recordings following targeted muscle reinnervation

    Journal of Neural Engineering 16:016010.

    https://doi.org/10.1088/1741-2552/aaed85

    • Google Scholar
24. 1. Muceli S
    2. Poppendieck W
    3. Hoffmann KP
    4. Dosen S
    5. Benito-Leon J
    6. Barroso FO
    7. Pons JL
    8. Farina D

    (2019b) A thin-film multichannel electrode for muscle recording and stimulation in neuroprosthetics applications

    Journal of Neural Engineering 16:026035.

    https://doi.org/10.1088/1741-2552/ab047a

    • Google Scholar
25. 1. Oberlin C
    2. Béal D
    3. Leechavengvongs S
    4. Salon A
    5. Dauge MC
    6. Sarcy JJ

    (1994) Nerve transfer to biceps muscle using a part of ulnar nerve for C5-C6 avulsion of the brachial plexus: anatomical study and report of four cases

    The Journal of Hand Surgery 19:232–237.

    https://doi.org/10.1016/0363-5023(94)90011-6

    • PubMed
    • Google Scholar
26. 1. Percie Du Sert N
    2. Hurst V
    3. Ahluwalia A
    4. Alam S
    5. Avey MT
    6. Baker M
    7. Browne WJ
    8. Clark A
    9. Cuthill IC
    10. Dirnagl U
    11. Emerson M
    12. Garner P
    13. Holgate ST
    14. Howells DW
    15. Karp NA
    16. Lazic SE
    17. Lidster K
    18. Maccallum CJ
    19. Macleod M
    20. Pearl EJ
    21. Petersen OH
    22. Rawle F
    23. Reynolds P
    24. Rooney K
    25. Sena ES
    26. Silberberg SD
    27. Steckler T
    28. Würbel H

    (2020) The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

    PLOS Biology 18:e3000410.

    https://doi.org/10.1371/journal.pbio.3000410

    • PubMed
    • Google Scholar
27. 1. Ray WZ
    2. Chang J
    3. Hawasli A
    4. Wilson TJ
    5. Yang L

    (2016) Motor nerve transfers: a comprehensive review

    Neurosurgery 78:1–26.

    https://doi.org/10.1227/NEU.0000000000001029

    • Google Scholar
28. 1. Salminger S
    2. Sturma A
    3. Hofer C
    4. Evangelista M
    5. Perrin M
    6. Bergmeister KD
    7. Roche AD
    8. Hasenoehrl T
    9. Dietl H
    10. Farina D
    11. Aszmann OC

    (2019) Long-term implant of intramuscular sensors and nerve transfers for wireless control of robotic arms in above-elbow amputees

    Science Robotics 4:eaaw6306.

    https://doi.org/10.1126/scirobotics.aaw6306

    • PubMed
    • Google Scholar
29. 1. Scholz T
    2. Krichevsky A
    3. Sumarto A
    4. Jaffurs D
    5. Wirth G
    6. Paydar K
    7. Evans G

    (2009) Peripheral nerve injuries: an international survey of current treatments and future perspectives

    Journal of Reconstructive Microsurgery 25:339–344.

    https://doi.org/10.1055/s-0029-1215529

    • PubMed
    • Google Scholar
30. 1. Srinivasan SS
    2. Carty MJ
    3. Calvaresi PW
    4. Clites TR
    5. Maimon BE
    6. Taylor CR
    7. Zorzos AN
    8. Herr H

    (2017) On prosthetic control: A regenerative agonist-antagonist myoneural interface

    Sci Robot 2:eaan2971.

    https://doi.org/10.1126/scirobotics.aan2971

    • PubMed
    • Google Scholar
31. 1. Terzis JK
    2. Papakonstantinou KC

    (2000) The surgical treatment of brachial plexus injuries in adults

    Plastic and Reconstructive Surgery 106:1097–1122.

    https://doi.org/10.1097/00006534-200010000-00022

    • PubMed
    • Google Scholar
32. 1. Van Zyl N
    2. Hill B
    3. Cooper C
    4. Hahn J
    5. Galea MP

    (2019) Expanding traditional tendon-based techniques with nerve transfers for the restoration of upper limb function in tetraplegia: a prospective case series

    Lancet 394:565–575.

    https://doi.org/10.1016/S0140-6736(19)31143-2

    • Google Scholar
33. 1. Vu PP
    2. Vaskov AK
    3. Irwin ZT
    4. Henning PT
    5. Lueders DR
    6. Laidlaw AT
    7. Davis AJ
    8. Nu CS
    9. Gates DH
    10. Gillespie RB
    11. Kemp SWP
    12. Kung TA
    13. Chestek CA
    14. Cederna PS

    (2020) A regenerative peripheral nerve interface allows real-time control of an artificial hand in upper limb amputees

    Science Translational Medicine 12:eaay2857.

    https://doi.org/10.1126/scitranslmed.aay2857

    • PubMed
    • Google Scholar

Author details

1. Matthias Luft

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9161-4125

2. Johanna Klepetko

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

3. Silvia Muceli

   Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0310-1021

4. Jaime Ibáñez

   1. Department of Bioengineering, Imperial College London, London, United Kingdom
   2. Department of Clinical and Movement Neuroscience, University College London, London, London, United Kingdom
   3. BSICoS Group, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

5. Vlad Tereshenko

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7761-5191

6. Christopher Festin

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Validation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

7. Gregor Laengle

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Validation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1011-3482

8. Olga Politikou

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Validation, Writing – review and editing

   Competing interests

   No competing interests declared

9. Udo Maierhofer

   1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
   2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

10. Dario Farina

    1. Department of Bioengineering, Imperial College London, London, United Kingdom
    2. Department of Clinical and Movement Neuroscience, University College London, London, London, United Kingdom

    Contribution

    Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Resources, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-7883-2697

11. Oskar C Aszmann

    1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    2. Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – review and editing

    Competing interests

    No competing interests declared

12. Konstantin Davide Bergmeister

    1. Clinical Laboratory for Bionic Extremity Reconstruction, Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Vienna, Vienna, Austria
    2. Center for Biomedical Research, Medical University of Vienna, Vienna, Austria
    3. Karl Landsteiner University of Health Sciences, Department of Plastic, Aesthetic and ReconstructiveSurgery, University Hospital St. Poelten, St. Poelten, Austria

    Contribution

    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review and editing

    For correspondence

    kbergmeister@gmail.com

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-3910-9727

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