Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
20 Feb 2024
Historique:
received: 20 07 2023
accepted: 17 01 2024
medline: 21 2 2024
pubmed: 21 2 2024
entrez: 20 2 2024
Statut: epublish

Résumé

Artificial communication with the brain through peripheral nerve stimulation shows promising results in individuals with sensorimotor deficits. However, these efforts lack an intuitive and natural sensory experience. In this study, we design and test a biomimetic neurostimulation framework inspired by nature, capable of "writing" physiologically plausible information back into the peripheral nervous system. Starting from an in-silico model of mechanoreceptors, we develop biomimetic stimulation policies. We then experimentally assess them alongside mechanical touch and common linear neuromodulations. Neural responses resulting from biomimetic neuromodulation are consistently transmitted towards dorsal root ganglion and spinal cord of cats, and their spatio-temporal neural dynamics resemble those naturally induced. We implement these paradigms within the bionic device and test it with patients (ClinicalTrials.gov identifier NCT03350061). He we report that biomimetic neurostimulation improves mobility (primary outcome) and reduces mental effort (secondary outcome) compared to traditional approaches. The outcomes of this neuroscience-driven technology, inspired by the human body, may serve as a model for advancing assistive neurotechnologies.

Identifiants

pubmed: 38378671
doi: 10.1038/s41467-024-45190-6
pii: 10.1038/s41467-024-45190-6
doi:

Banques de données

ClinicalTrials.gov
['NCT03350061']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1151

Subventions

Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 759998
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 197271
Organisme : Gebert Rüf Stiftung (Gebert Rüf Foundation)
ID : GRS-096/21
Organisme : Saint Petersburg State University (St. Petersburg State University)
ID : 93022925/94030803

Informations de copyright

© 2024. The Author(s).

Références

Raspopovic, S., Valle, G. & Petrini, F. M. Sensory feedback for limb prostheses in amputees. Nat. Mater. https://doi.org/10.1038/s41563-021-00966-9 (2021).
Edwards, C. A., Kouzani, A., Lee, K. H. & Ross, E. K. Neurostimulation devices for the treatment of neurologic disorders. Mayo Clin. Proc. 92, 1427–1444 (2017).
pubmed: 28870357 doi: 10.1016/j.mayocp.2017.05.005
Raspopovic, S. Advancing limb neural prostheses. Science 370, 290–291 (2020).
pubmed: 33060348 doi: 10.1126/science.abb1073
Bensmaia, S. J., Tyler, D. J. & Micera, S. Restoration of sensory information via bionic hands. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-020-00630-8 (2020).
Flesher, S. N. et al. A brain-computer interface that evokes tactile sensations improves robotic arm control. Science 372, 831–836 (2021).
pubmed: 34016775 pmcid: 8715714 doi: 10.1126/science.abd0380
Wang, Y., Yang, X., Zhang, X., Wang, Y. & Pei, W. Implantable intracortical microelectrodes: reviewing the present with a focus on the future. Microsyst. Nanoeng. 9, 1–17 (2023).
pubmed: 36597511 pmcid: 9805458 doi: 10.1038/s41378-022-00451-6
Petrini, F. M. et al. Sensory feedback restoration in leg amputees improves walking speed, metabolic cost and phantom pain. Nat. Med 25, 1356–1363 (2019).
pubmed: 31501600 doi: 10.1038/s41591-019-0567-3
Petrini, F. M. et al. Six-month assessment of a hand prosthesis with intraneural tactile feedback. Ann. Neurol. 85, 137–154 (2019).
pubmed: 30474259 doi: 10.1002/ana.25384
Ortiz-Catalan, M., Mastinu, E., Sassu, P., Aszmann, O. & Brånemark, R. Self-contained neuromusculoskeletal arm prostheses. N. Engl. J. Med. 382, 1732–1738 (2020).
pubmed: 32348644 doi: 10.1056/NEJMoa1917537
Tan, D. W. et al. A neural interface provides long-term stable natural touch perception. Sci. Transl. Med 6, 257ra138 (2014).
pubmed: 25298320 pmcid: 5517305 doi: 10.1126/scitranslmed.3008669
Nanivadekar, A. C. et al. Closed-loop stimulation of lateral cervical spinal cord in upper-limb amputees to enable sensory discrimination: a case study. Sci. Rep. 12, 17002 (2022).
pubmed: 36220864 pmcid: 9553970 doi: 10.1038/s41598-022-21264-7
Chandrasekaran, S. et al. Sensory restoration by epidural stimulation of the lateral spinal cord in upper-limb amputees. eLife 9, e54349 (2020).
pubmed: 32691733 pmcid: 7373432 doi: 10.7554/eLife.54349
Wagner, F. B. et al. Targeted neurotechnology restores walking in humans with spinal cord injury. Nature 563, 65–71 (2018).
pubmed: 30382197 doi: 10.1038/s41586-018-0649-2
Angeli, C. A. et al. Recovery of over-ground walking after chronic motor complete spinal cord injury. N. Engl. J. Med. 379, 1244–1250 (2018).
pubmed: 30247091 doi: 10.1056/NEJMoa1803588
Gill, M. L. et al. Neuromodulation of lumbosacral spinal networks enables independent stepping after complete paraplegia. Nat. Med. 24, 1677–1682 (2018).
pubmed: 30250140 doi: 10.1038/s41591-018-0175-7
Tabot, G. A. et al. Restoring the sense of touch with a prosthetic hand through a brain interface. Proc. Natl Acad. Sci. USA 110, 18279–18284 (2013).
pubmed: 24127595 pmcid: 3831459 doi: 10.1073/pnas.1221113110
Salas, M. A. et al. Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation. eLife Sci. 7, e32904 (2018).
doi: 10.7554/eLife.32904
Flesher, S. N. et al. Intracortical microstimulation of human somatosensory cortex. Sci. Transl. Med. 8, 361ra141–361ra141 (2016).
pubmed: 27738096 doi: 10.1126/scitranslmed.aaf8083
Clemente, F. et al. Intraneural sensory feedback restores grip force control and motor coordination while using a prosthetic hand. J. Neural Eng. 16, 026034 (2019).
pubmed: 30736030 doi: 10.1088/1741-2552/ab059b
Schiefer, M., Tan, D., Sidek, S. M. & Tyler, D. J. Sensory feedback by peripheral nerve stimulation improves task performance in individuals with upper limb loss using a myoelectric prosthesis. J. Neural Eng. 13, 016001 (2016).
pubmed: 26643802 doi: 10.1088/1741-2560/13/1/016001
Mastinu, E. et al. Neural feedback strategies to improve grasping coordination in neuromusculoskeletal prostheses. Sci. Rep. 10, 11793 (2020).
pubmed: 32678121 pmcid: 7367346 doi: 10.1038/s41598-020-67985-5
Valle, G. et al. Hand control with invasive feedback is not impaired by increased cognitive load. Front. Bioeng. Biotechnol. 8, 287 (2020).
Johansson, R. S. & Flanagan, J. R. Coding and use of tactile signals from the fingertips in object manipulation tasks. Nat. Rev. Neurosci. 10, 345–359 (2009).
pubmed: 19352402 doi: 10.1038/nrn2621
Raspopovic, S. Neurorobotics for neurorehabilitation. Science 373, 634–635 (2021).
pubmed: 34353946 doi: 10.1126/science.abj5259
Valle, G. et al. Sensitivity to temporal parameters of intraneural tactile sensory feedback. J. Neuroeng. Rehabil. 17, 110 (2020).
pubmed: 32799900 pmcid: 7429895 doi: 10.1186/s12984-020-00737-8
Valle, G. et al. Comparison of linear frequency and amplitude modulation for intraneural sensory feedback in bidirectional hand prostheses. Sci. Rep. 8, 16666 (2018).
pubmed: 30420739 pmcid: 6232130 doi: 10.1038/s41598-018-34910-w
Cimolato, A., Ciotti, F., Kljajić, J., Valle, G. & Raspopovic, S. Symbiotic electroneural and musculoskeletal framework to encode proprioception via neurostimulation: ProprioStim. iScience 26, 106248 (2023).
pubmed: 36923003 pmcid: 10009292 doi: 10.1016/j.isci.2023.106248
Raspopovic, S. et al. Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci. Transl. Med. 6, 222ra19–222ra19 (2014).
pubmed: 24500407 doi: 10.1126/scitranslmed.3006820
Petrini, F. M. et al. Enhancing functional abilities and cognitive integration of the lower limb prosthesis. Sci. Transl. Med. 11, eaav8939 (2019).
pubmed: 31578244 doi: 10.1126/scitranslmed.aav8939
Ortiz-Catalan, M., Hakansson, B. & Branemark, R. An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs. Sci. Transl. Med. 6, 257re6–257re6 (2014).
pubmed: 25298322 doi: 10.1126/scitranslmed.3008933
Saal, H. P. & Bensmaia, S. J. Biomimetic approaches to bionic touch through a peripheral nerve interface. Neuropsychologia 79, 344–353 (2015).
pubmed: 26092769 doi: 10.1016/j.neuropsychologia.2015.06.010
Prochazka, A. Proprioceptive feedback and movement regulation. in Comprehensive Physiology 89–127 (American Cancer Society, 2011). https://doi.org/10.1002/cphy.cp120103 .
Freeman, A. W. & Johnson, K. O. Cutaneous mechanoreceptors in macaque monkey: temporal discharge patterns evoked by vibration, and a receptor model. J. Physiol. 323, 21–41 (1982).
pubmed: 7097573 pmcid: 1250343 doi: 10.1113/jphysiol.1982.sp014059
Abbott, L. F. & Regehr, W. G. Synaptic computation. Nature 431, 796–803 (2004).
pubmed: 15483601 doi: 10.1038/nature03010
Formento, E., D’Anna, E., Gribi, S., Lacour, S. P. & Micera, S. A biomimetic electrical stimulation strategy to induce asynchronous stochastic neural activity. J. Neural Eng. 17, 046019 (2020).
pubmed: 32650319 doi: 10.1088/1741-2552/aba4fc
Torebjörk, H. E. & Ochoa, J. L. Specific sensations evoked by activity in single identified sensory units in man. Acta Physiol. Scand. 110, 445–447 (1980).
pubmed: 7234450 doi: 10.1111/j.1748-1716.1980.tb06695.x
Okorokova, E., He, Q. & Bensmaia, S. J. Biomimetic encoding model for restoring touch in bionic hands through a nerve interface. J. Neural Eng. https://doi.org/10.1088/1741-2552/aae398 (2018).
George, J. A. et al. Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand. Sci. Robot. 4, eaax2352 (2019).
pubmed: 33137773 doi: 10.1126/scirobotics.aax2352
Valle, G. et al. Biomimetic intraneural sensory feedback enhances sensation naturalness, tactile sensitivity, and manual dexterity in a bidirectional prosthesis. Neuron 100, 37–45.e7 (2018).
pubmed: 30244887 doi: 10.1016/j.neuron.2018.08.033
Greenspon, C. M. et al. Biomimetic multi-channel microstimulation of somatosensory cortex conveys high resolution force feedback for bionic hands. bioRxiv https://doi.org/10.1101/2023.02.18.528972 (2023).
Callier, T., Suresh, A. K. & Bensmaia, S. J. Neural coding of contact events in somatosensory cortex. Cereb. Cortex https://doi.org/10.1093/cercor/bhy337 (2019).
Saal, H. P. & Bensmaia, S. J. Touch is a team effort: interplay of submodalities in cutaneous sensibility. Trends Neurosci. 37, 689–697 (2014).
pubmed: 25257208 doi: 10.1016/j.tins.2014.08.012
Carter, A. W., Chen, S. C., Lovell, N. H., Vickery, R. M. & Morley, J. W. Convergence across tactile afferent types in primary and secondary somatosensory cortices. PLoS ONE 9, e107617 (2014).
pubmed: 25215534 pmcid: 4162646 doi: 10.1371/journal.pone.0107617
Pei, Y.-C., Denchev, P. V., Hsiao, S. S., Craig, J. C. & Bensmaia, S. J. Convergence of submodality-specific input onto neurons in primary somatosensory cortex. J. Neurophysiol. 102, 1843–1853 (2009).
pubmed: 19535484 pmcid: 2746774 doi: 10.1152/jn.00235.2009
Suresh, A. K. et al. Sensory computations in the cuneate nucleus of macaques. Proc. Natl Acad. Sci. USA 118, e2115772118 (2021).
pubmed: 34853173 pmcid: 8670430 doi: 10.1073/pnas.2115772118
Katic, N. et al. Modeling foot sole cutaneous afferents: FootSim. iScience 26, 105874 (2023).
pubmed: 36636355 doi: 10.1016/j.isci.2022.105874
Valle, G. et al. Mechanisms of neuro-robotic prosthesis operation in leg amputees. Sci. Adv. 7, eabd8354 (2021).
pubmed: 33883127 pmcid: 8059925 doi: 10.1126/sciadv.abd8354
Preatoni, G., Valle, G., Petrini, F. M. & Raspopovic, S. Lightening the perceived weight of a prosthesis with cognitively integrated neural sensory feedback. Curr. Biol. 31, 1–7 (2021).
doi: 10.1016/j.cub.2020.11.069
Abraira, V. E. & Ginty, D. D. The sensory neurons of touch. Neuron 79, 618–639 (2013).
pubmed: 23972592 doi: 10.1016/j.neuron.2013.07.051
Whelan, P. J. Control of locomotion in the decerebrate cat. Prog. Neurobiol. 49, 481–515 (1996).
pubmed: 8895997 doi: 10.1016/0301-0082(96)00028-7
Sprague, J. M. & Chambers, W. W. Control of posture by reticular formation and cerebellum in the intact, anesthetized and unanesthetized and in the decerebrated cat. Am. J. Physiol. 176, 52–64 (1953).
doi: 10.1152/ajplegacy.1953.176.1.52
Greenspon, C. M. et al. Lamina-specific population encoding of cutaneous signals in the spinal dorsal horn using multi-electrode arrays. J. Physiol. 597, 377–397 (2019).
pubmed: 30390415 doi: 10.1113/JP277036
Kashkoush, A. I., Gaunt, R. A., Fisher, L. E., Bruns, T. M. & Weber, D. J. Recording single- and multi-unit neuronal action potentials from the surface of the dorsal root ganglion. Sci. Rep. 9, 2786 (2019).
pubmed: 30808921 pmcid: 6391375 doi: 10.1038/s41598-019-38924-w
Tan, D. W. et al. A neural interface provides long-term stable natural touch perception. Sci. Transl. Med. 6, 257ra138–257ra138 (2014).
pubmed: 25298320 pmcid: 5517305 doi: 10.1126/scitranslmed.3008669
Destexhe, A. & Goldberg, J. A. LFP analysis: overview. Encycl. Comput. Neurosci. 1, 52–55 (2015).
Maling, N. & McIntyre, C. Local field potential analysis for closed-loop neuromodulation. Closed Loop Neurosci. 1, 67–80 (2016).
doi: 10.1016/B978-0-12-802452-2.00005-6
Lenz, F. A. et al. Thermal and pain sensations evoked by microstimulation in the area of human ventrocaudal nucleus. J. Neurophysiol. 70, 200–212 (1993).
pubmed: 8360716 doi: 10.1152/jn.1993.70.1.200
Strzalkowski, N. D. J., Peters, R. M., Inglis, J. T. & Bent, L. R. Cutaneous afferent innervation of the human foot sole: what can we learn from single-unit recordings? J. Neurophysiol. 120, 1233–1246 (2018).
pubmed: 29873612 pmcid: 6171067 doi: 10.1152/jn.00848.2017
Crea, S., Edin, B. B., Knaepen, K., Meeusen, R. & Vitiello, N. Time-discrete vibrotactile feedback contributes to improved gait symmetry in patients with lower limb amputations: case series. Phys. Ther. 97, 198–207 (2017).
pubmed: 28204796 doi: 10.2522/ptj.20150441
Clemente, F., D’Alonzo, M., Controzzi, M., Edin, B. B. & Cipriani, C. Non-invasive, temporally discrete feedback of object contact and release improves grasp control of closed-loop myoelectric transradial prostheses. IEEE Trans. Neural Syst. Rehabilit. Eng. 24, 1314–1322 (2016).
doi: 10.1109/TNSRE.2015.2500586
Graczyk, E. L., Christie, B. P., He, Q., Tyler, D. J. & Bensmaia, S. J. Frequency shapes the quality of tactile percepts evoked through electrical stimulation of the nerves. J. Neurosci. 42, 2052–2064 (2022).
pubmed: 35074865 pmcid: 8916769 doi: 10.1523/JNEUROSCI.1494-21.2021
Pearcey, G. E. P. & Zehr, E. P. We are upright-walking cats: human limbs as sensory antennae during locomotion. Physiology 34, 354–364 (2019).
pubmed: 31389772 doi: 10.1152/physiol.00008.2019
Miller, G. A. The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychol. Rev. 63, 81–97 (1956).
pubmed: 13310704 doi: 10.1037/h0043158
Hughes, C. & Kozai, T. Dynamic amplitude modulation of microstimulation evokes biomimetic onset and offset transients and reduces depression of evoked calcium responses in sensory cortices. Brain Stimul. 16, 939–965 (2023).
pubmed: 37244370 doi: 10.1016/j.brs.2023.05.013
Tomlinson, T. & Miller, L. E. Toward a proprioceptive neural interface that mimics natural cortical activity. Adv. Exp. Med. Biol. 957, 367–388 (2016).
pubmed: 28035576 pmcid: 5452683 doi: 10.1007/978-3-319-47313-0_20
Bensmaia, S. J. & Miller, L. E. Restoring sensorimotor function through intracortical interfaces: progress and looming challenges. Nat. Rev. Neurosci. 15, 313–325 (2014).
pubmed: 24739786 doi: 10.1038/nrn3724
Tanner, J., Keefer, E., Cheng, J. & Helms Tillery, S. Dynamic peripheral nerve stimulation can produce cortical activation similar to punctate mechanical stimuli. Front. Hum. Neurosci. 17, 1083307 (2023).
Greenspon, C. M. et al. Tessellation of artificial touch via microstimulation of human somatosensory cortex. bioRxiv https://doi.org/10.1101/2023.06.23.545425 (2023).
Zelechowski, M., Valle, G. & Raspopovic, S. A computational model to design neural interfaces for lower-limb sensory neuroprostheses. J. Neuroeng. Rehabil. 17, 24 (2020).
pubmed: 32075654 pmcid: 7029520 doi: 10.1186/s12984-020-00657-7
Raspopovic, S., Petrini, F. M., Zelechowski, M. & Valle, G. Framework for the development of neuroprostheses: from basic understanding by sciatic and median nerves models to bionic legs and hands. Proc. IEEE 105, 34–49 (2017).
doi: 10.1109/JPROC.2016.2600560
Fang, Z.-P. & Mortimer, J. T. Alternate excitation of large and small axons with different stimulation waveforms: an application to muscle activation. Med. Biol. Eng. Comput. 29, 543–547 (1991).
pubmed: 1817219 doi: 10.1007/BF02442328
Jabaley, M. E., Wallace, W. H. & Heckler, F. R. Internal topography of major nerves of the forearm and hand: a current view. J. Hand Surg. 5, 1–18 (1980).
doi: 10.1016/S0363-5023(80)80035-9
Ochoa, J. & Torebjörk, E. Sensations evoked by intraneural microstimulation of single mechanoreceptor units innervating the human hand. J. Physiol. 342, 633–654 (1983).
pubmed: 6631752 pmcid: 1193981 doi: 10.1113/jphysiol.1983.sp014873
Wendelken, S. et al. Restoration of motor control and proprioceptive and cutaneous sensation in humans with prior upper-limb amputation via multiple Utah Slanted Electrode Arrays (USEAs) implanted in residual peripheral arm nerves. J. Neuroeng. Rehabil. 14, 1–17 (2017).
Raja, B., Neptune, R. R. & Kautz, S. A. Quantifiable patterns of limb loading and unloading during hemiparetic gait: relation to kinetic and kinematic parameters. J. Rehabil. Res. Dev. 49, 1293–1304 (2012).
pubmed: 23408212 pmcid: 4910692 doi: 10.1682/JRRD.2011.02.0018
Orendurff, M. S. et al. Gait efficiency using the C-Leg. J. Rehabil. Res. Dev. 43, 239–246 (2006).
pubmed: 16847790 doi: 10.1682/JRRD.2005.06.0095
Miller, W. C., Speechley, M. & Deathe, B. The prevalence and risk factors of falling and fear of falling among lower extremity amputees. Arch. Phys. Med. Rehabilit. 82, 1031–1037 (2001).
doi: 10.1053/apmr.2001.24295
Sions, J. M., Manal, T. J., Horne, J. R., Sarlo, F. B. & Pohlig, R. T. Balance-confidence is associated with community participation, perceived physical mobility, and performance-based function among individuals with a unilateral amputation. Physiother. Theory Pract. 36, 607–614 (2020).
pubmed: 29952694 doi: 10.1080/09593985.2018.1490939
Miller, W. C. & Deathe, A. B. The influence of balance confidence on social activity after discharge from prosthetic rehabilitation for first lower limb amputation. Prosthet. Orthot. Int. 35, 379–385 (2011).
pubmed: 21846808 doi: 10.1177/0309364611418874
Schiefer, M. A., Graczyk, E. L., Sidik, S. M., Tan, D. W. & Tyler, D. J. Artificial tactile and proprioceptive feedback improves performance and confidence on object identification tasks. PLoS ONE 13, e0207659 (2018).
pubmed: 30517154 pmcid: 6281191 doi: 10.1371/journal.pone.0207659
Graczyk, E. L., Gill, A., Tyler, D. J. & Resnik, L. J. The benefits of sensation on the experience of a hand: A qualitative case series. PLoS ONE 14, e0211469 (2019).
pubmed: 30703163 pmcid: 6355013 doi: 10.1371/journal.pone.0211469
De Marchis, C. et al. Characterizing the gait of people with different types of amputation and prosthetic components through multimodal measurements: a methodological perspective. Front. Rehabilit. Sci. 3, 804746 (2022).
de Hemptinne, C. et al. Therapeutic deep brain stimulation reduces cortical phase-amplitude coupling in Parkinson’s disease. Nat. Neurosci. 18, 779–786 (2015).
pubmed: 25867121 pmcid: 4414895 doi: 10.1038/nn.3997
Marsal, S. et al. Non-invasive vagus nerve stimulation for rheumatoid arthritis: a proof-of-concept study. Lancet Rheumatol. 3, e262–e269 (2021).
pubmed: 38279410 doi: 10.1016/S2665-9913(20)30425-2
Donegà, M. et al. Human-relevant near-organ neuromodulation of the immune system via the splenic nerve. Proc. Natl Acad. Sci. USA 118, e2025428118 (2021).
pubmed: 33972441 pmcid: 8157920 doi: 10.1073/pnas.2025428118
Fumero, M. J. et al. A state-of-the-art implementation of a binaural cochlear-implant sound coding strategy inspired by the medial olivocochlear reflex. Hear. Res. 409, 108320 (2021).
pubmed: 34348202 doi: 10.1016/j.heares.2021.108320
Wiboonsaksakul, K. P., Roberts, D. C., Santina, C. C. D. & Cullen, K. E. A prosthesis utilizing natural vestibular encoding strategies improves sensorimotor performance in monkeys. PLOS Biol. 20, e3001798 (2022).
pubmed: 36103550 pmcid: 9473632 doi: 10.1371/journal.pbio.3001798
Mazzoni, A. et al. Morphological neural computation restores discrimination of naturalistic textures in trans-radial amputees. Sci. Rep. 10, 1–14 (2020).
doi: 10.1038/s41598-020-57454-4
Aiello, G., Valle, G. & Raspopovic, S. Recalibration of neuromodulation parameters in neural implants with adaptive Bayesian Optimization. J. Neural Eng. https://doi.org/10.1088/1741-2552/acc975 (2023).
Ciotti, F., Cimolato, A., Valle, G. & Raspopovic, S. Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization. PLOS Comput. Biol. 19, e1011184 (2023).
pubmed: 37228174 pmcid: 10246853 doi: 10.1371/journal.pcbi.1011184
Segil, J. L. & Graczyk, E. L. Measuring embodiment: a review of methods for prosthetic devices. Front. Neurorobot. 16, 902162 (2022).
Hughes, C. L. et al. Perception of microstimulation frequency in human somatosensory cortex. eLife 10, e65128 (2021).
pubmed: 34313221 pmcid: 8376245 doi: 10.7554/eLife.65128
Graczyk, E. L. et al. The neural basis of perceived intensity in natural and artificial touch. Sci. Transl. Med. 8, 362ra142–362ra142 (2016).
pubmed: 27797958 pmcid: 5713478 doi: 10.1126/scitranslmed.aaf5187
Merkulyeva, N. et al. Distribution of spinal neuronal networks controlling forward and backward locomotion. J. Neurosci. 38, 4695–4707 (2018).
pubmed: 29678875 pmcid: 5956987 doi: 10.1523/JNEUROSCI.2951-17.2018
Musienko, P. E. et al. Comparison of operation of spinal locomotor networks activated by supraspinal commands and by epidural stimulation of the spinal cord in cats. J. Physiol. 598, 3459–3483 (2020).
pubmed: 32445488 doi: 10.1113/JP279460
Quian Quiroga, R. & Panzeri, S. Extracting information from neuronal populations: information theory and decoding approaches. Nat. Rev. Neurosci. 10, 173–185 (2009).
pubmed: 19229240 doi: 10.1038/nrn2578
Quiroga, R. Q., Nadasdy, Z. & Ben-Shaul, Y. Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering. Neural Comput. 16, 1661–1687 (2004).
pubmed: 15228749 doi: 10.1162/089976604774201631
Boretius, T. et al. A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. Biosens. Bioelectron. 26, 62–69 (2010).
pubmed: 20627510 doi: 10.1016/j.bios.2010.05.010
Petrusic, I. et al. Plastic changes in the brain after a neuro-prosthetic leg use. Clin. Neurophysiol. https://doi.org/10.1016/j.clinph.2022.04.001 (2022).
Čvančara, P. et al. Stability of flexible thin-film metallization stimulation electrodes: analysis of explants after first-in-human study and improvement of in vivo performance. J. Neural Eng. 17, 046006 (2020).
pubmed: 32512544 doi: 10.1088/1741-2552/ab9a9a
Čvančara, P. et al. On the reliability of chronically implanted thin-film electrodes in human arm nerves for neuroprosthetic applications. bioRxiv https://doi.org/10.1101/653964 (2019).
Guiho, T. et al. Advanced 56 channels stimulation system to drive intrafascicular electrodes. in Converging Clinical and Engineering Research on Neurorehabilitation II. Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016), October 18-21, 2016, Segovia, Spain (ed Ibáñez J, G.-V. J) 2 743–747 (2016).
D’Anna, E. et al. A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback. Sci. Robot. 4, eaau8892 (2019).
pubmed: 33137741 doi: 10.1126/scirobotics.aau8892
Valle, G. et al. A psychometric platform to collect somatosensory sensations for neuroprosthetic use. Front. Med. Technol. 3, 8 (2021).
doi: 10.3389/fmedt.2021.619280
Ortiz-Catalan, M., Wessberg, J., Mastinu, E., Naber, A. & Brånemark, R. Patterned stimulation of peripheral nerves produces natural sensations with regards to location but not quality. IEEE Trans. Med. Robot. Bionics 1, 199–203 (2019).
doi: 10.1109/TMRB.2019.2931758
Valle, G. et al. Multifaceted understanding of human nerve implants to design optimized electrodes for bioelectronics. Biomaterials 291, 121874 (2022).
pubmed: 36334353 doi: 10.1016/j.biomaterials.2022.121874

Auteurs

Giacomo Valle (G)

Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland.

Natalija Katic Secerovic (N)

Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland.
School of Electrical Engineering, University of Belgrade, 11000, Belgrade, Serbia.
The Mihajlo Pupin Institute, University of Belgrade, 11000, Belgrade, Serbia.

Dominic Eggemann (D)

Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland.

Oleg Gorskii (O)

Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia.
Laboratory for Neuromodulation, Pavlov Institute of Physiology, Russian Academy of Sciences, Saint Petersburg, 199034, Russia.
Center for Biomedical Engineering, National University of Science and Technology "MISIS", 119049, Moscow, Russia.

Natalia Pavlova (N)

Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia.

Francesco M Petrini (FM)

SensArs Neuroprosthetics, Saint-Sulpice, CH-1025, Switzerland.

Paul Cvancara (P)

Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Center of Excellence, University of Freiburg, D-79110, Freiburg, Germany.

Thomas Stieglitz (T)

Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center, BrainLinks-BrainTools Center of Excellence, University of Freiburg, D-79110, Freiburg, Germany.

Pavel Musienko (P)

Laboratory for Neuroprosthetics, Institute of Translational Biomedicine, Saint-Petersburg State University, Saint-Petersburg, Russia.
Sirius University of Science and Technology, Neuroscience Program, Sirius, Russia.
Laboratory for Neurorehabilitation Technologies, Life Improvement by Future Technologies Center "LIFT", Moscow, Russia.

Marko Bumbasirevic (M)

Orthopaedic Surgery Department, School of Medicine, University of Belgrade, 11000, Belgrade, Serbia.

Stanisa Raspopovic (S)

Laboratory for Neuroengineering, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland. nesta.fale@gmail.com.

Classifications MeSH