SpringerLink
Log in

Somatosensory Neuromodulation with a Focus Towards Clinical Systems

  • Reference work entry
  • First Online:
Handbook of Neuroengineering

  • 221 Accesses

Abstract

Neuromodulation of the somatosensory nervous system is an effective tool to restore sensory feedback to individuals with sensory deficits, treat chronic pain, and study sensory processing pathways. This chapter presents an overview on neuromodulation techniques for somatosensation focused on clinical systems implemented in humans. The first section briefly reviews the key physiology of tactile and proprioceptive sensation. The second section describes different technologies and methods for evoking somatosensory percepts with electrical stimulation. The third section explains how to elicit and shape sensation produced by neurostimulation, drawing on key insights from recent research in human studies of neuroprostheses. This section is divided into the four perceptual dimensions of sensation: location, intensity, quality, and timing. We present the neural coding principles underlying each perceptual dimension in the normal sensory system, along with strategies to modulate each perceptual dimension with neural stimulation. The last section provides an overview of clinical applications of electrically evoked somatosensation, highlighted by an example in rehabilitation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

Abbreviations

APC:

Anterior parietal cortex

DBS:

Deep brain stimulation

DRG:

Dorsal root ganglion

ECoG:

Electrocorticography

FINE:

Flat interface nerve electrode

fMRI:

Functional magnetic resonance imaging

ICMS:

Intracortical microstimulation

JND:

Just noticeable difference

LIFE:

Longitudinal intrafascicular electrode

LTMR:

Low-threshold mechanoreceptor

MEG:

Magnetoencephalography

PA:

Pulse amplitude

PC:

Pacinian corpuscle (rapidly adapting type II)

PF:

Pulse frequency

PW:

Pulse width

RA:

Rapidly adapting

RAI:

Rapidly adapting type I

RAII:

Rapidly adapting type II

S1:

Primary somatosensory cortex

SA:

Slowly adapting

SAI:

Slowly adapting type I

SAII:

Slowly adapting type II

SCS:

Spinal cord stimulation

TIME:

Transverse intrafascicular electrode

USEA:

Utah slant microelectrode array

Vc:

Ventrocaudal nucleus of the thalamus

References

  1. Kandel, E.R., Schwartz, J.H., Jessell, T.M., et al.: Principles of Neural Science, 5th edn. McGraw-Hill Companies, Inc, New York City (2013)

    Google Scholar 

  2. Abraira, V.E., Ginty, D.D.: The sensory neurons of touch. Neuron. 79, 618–639 (2013). https://doi.org/10.1016/j.neuron.2013.07.051

    Article  Google Scholar 

  3. 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). https://doi.org/10.1038/nrn2621

    Article  Google Scholar 

  4. Johansson, R.S., Vallbo, A.B.: Tactile sensory coding in the glabrous skin of the human hand. Trends Neurosci. 6, 27–32 (1983). https://doi.org/10.1016/0166-2236(83)90011-5

    Article  Google Scholar 

  5. Proske, U., Gandevia, S.C.: The proprioceptive senses: their roles in signaling body shape, body position and movement, and muscle force. Physiol. Rev. 92, 1651–1697 (2012). https://doi.org/10.1152/physrev.00048.2011

    Article  Google Scholar 

  6. Löken, L.S., Wessberg, J., Morrison, I., et al.: Coding of pleasant touch by unmyelinated afferents in humans. Nat. Neurosci. 12, 547–548 (2009). https://doi.org/10.1038/nn.2312

    Article  Google Scholar 

  7. McGlone, F., Wessberg, J., Olausson, H.: Discriminative and affective touch: sensing and feeling. Neuron. 82, 737–755 (2014)

    Google Scholar 

  8. Delhaye, B.P., Long, K.H., Bensmaia, S.J.: Neural basis of touch and proprioception in primate cortex. Compr. Physiol. 8, 1575–1602 (2018). https://doi.org/10.1002/cphy.c170033

    Article  Google Scholar 

  9. Grigg, P.: Peripheral neural mechanisms in proprioception. J. Sport Rehabil. 3, 2–17 (1994)

    Google Scholar 

  10. Gustafson, K.J., Pinault, G.C.J., Neville, J.J., et al.: Fascicular anatomy of human femoral nerve: implications for neural prostheses using nerve cuff electrodes. J. Rehabil. Res. Dev. 46, 973–984 (2009). https://doi.org/10.1682/JRRD.2008.08.0097

    Article  Google Scholar 

  11. Brill, N.A., Tyler, D.J.: Quantification of human upper extremity nerves and fascicular anatomy. Muscle Nerve. 56, 463–471 (2017). https://doi.org/10.1002/mus.25534

    Article  Google Scholar 

  12. Grinberg, Y., Schiefer, M.A., Tyler, D.J., Gustafson, K.J.: Fascicular perineurium thickness, size, and position affect model predictions of neural excitation. IEEE Trans. Neural Syst. Rehabil. Eng. 16, 572–581 (2008). https://doi.org/10.1109/TNSRE.2008.2010348

    Article  Google Scholar 

  13. Haberberger, R.V., Barry, C., Dominguez, N., et al.: Human dorsal root ganglia. Front. Cell. Neurosci. 13, 1–17 (2019). https://doi.org/10.3389/fncel.2019.00271

    Article  Google Scholar 

  14. Weiss, N., Ohara, S., Johnson, K.O., Lenz, F.A.: The human thalamic somatic sensory nucleus [Ventral caudal (Vc)] shows neuronal mechanoreceptor-like responses to optimal stimuli for peripheral mechanoreceptors. J. Neurophysiol. 101, 1033–1042 (2009). https://doi.org/10.1152/jn.90990.2008

    Article  Google Scholar 

  15. Loutit, A.J., Vickery, R.M., Potas, J.R.: Functional organization and connectivity of the dorsal column nuclei complex reveals a sensorimotor integration and distribution hub. J. Comp. Neurol., 1–34 (2020). https://doi.org/10.1002/cne.24942

  16. Dijkerman, H.C., de Haan, E.H.F.: Somatosensory processes subserving perception and action. Behav. Brain Sci. 30, 189–201 (2007). https://doi.org/10.1017/S0140525X07001392

    Article  Google Scholar 

  17. McFadyen, J., Dolan, R.J., Garrido, M.I.: The influence of subcortical shortcuts on disordered sensory and cognitive processing. Nat. Rev. Neurosci., 1–13 (2020). https://doi.org/10.1038/s41583-020-0287-1

  18. Kandel, E.R.: From nerve cells to cognition: the internal representations of space and action. Princ. Neural Sci., 370–391 (2013)

    Google Scholar 

  19. Jones, L.A., Tan, H.Z.: Application of psychophysical techniques to haptic research. IEEE Trans. Haptics. 6, 268–284 (2013). https://doi.org/10.1109/TOH.2012.74

    Article  Google Scholar 

  20. Gescheider, G.A.: Psychophysics: The Fundamentals, 3rd edn. Lawrence Erlbaum Associates, Inc, Mahway (1997)

    Google Scholar 

  21. Ortiz-Catalan, M., Brånemark, R., Håkansson, B., Delbeke, J.: On the viability of implantable electrodes for the natural control of artificial limbs: review and discussion. Biomed. Eng. Online. 11, 33 (2012). https://doi.org/10.1186/1475-925X-11-33

    Article  Google Scholar 

  22. Günter, C., Delbeke, J., Ortiz-catalan, M.: Safety of long-term electrical peripheral nerve stimulation: review of the state of the art. 8, 1–16 (2019). https://doi.org/10.1186/s12984-018-0474-8

  23. Forst, J.C., Blok, D.C., Slopsema, J.P., et al.: Surface electrical stimulation to evoke referred sensation. J. Rehabil. Res. Dev. 52, 397–406 (2015). https://doi.org/10.1682/JRRD.2014.05.0128

    Article  Google Scholar 

  24. Perovic, M., Stevanovic, M., Jevtic, T., et al.: Electrical stimulation of the forearm: a method for transmitting sensory signals from the artificial hand to the brain. J. Autom. Control. 21, 13–18 (2013). https://doi.org/10.2298/JAC1301013P

    Article  Google Scholar 

  25. Dietrich, C., Walter-Walsh, K., Preissler, S., et al.: Sensory feedback prosthesis reduces phantom limb pain: proof of a principle. Neurosci. Lett. 507, 97–100 (2012). https://doi.org/10.1016/j.neulet.2011.10.068

    Article  Google Scholar 

  26. Geng, B., Jensen, W.: Human ability in identification of location and pulse number for electrocutaneous stimulation applied on the forearm. J. Neuroeng. Rehabil. 11, 97 (2014). https://doi.org/10.1186/1743-0003-11-97

    Article  Google Scholar 

  27. Anani, A.B., Ikeda, K., Korner, L.M., Körner, L.M.: Human ability to discriminate various parameters in afferent electrical nerve stimulation with particular reference to prostheses sensory feedback. Med. Biol. Eng. Comput. 15, 363–373 (1977). https://doi.org/10.1007/Bf02457988

    Article  Google Scholar 

  28. Prior, R.E., Lyman, J., Case, P.A., Scott, C.M.: Supplemental sensory feedback for the VA/NU myoelectric hand. Background and preliminary designs. Bull. Prosthet. Res. 101, 170–191 (1976)

    Google Scholar 

  29. Kaczmarek, K.A., Bach-y-Rita, P.: Tactile displays. In: Virtual Environments and Advanced Interface Design, pp. 349–414 (1995)

    Google Scholar 

  30. Kaczmarek, K.A., Webster, J.G., Bach-y-Rita, P., Tompkins, W.J.: Electrotactile and vibrotactile displays for sensory substitution systems. IEEE Trans. Biomed. Eng. 38, 1–16 (1991). https://doi.org/10.1109/10.68204

    Article  Google Scholar 

  31. Naples, G.G., Mortimer, J.T., Scheiner, A., Sweeney, J.D.: A spiral nerve cuff electrode for peripheral nerve stimulation. IEEE Trans. Biomed. Eng. 35, 905–916 (1988). https://doi.org/10.1109/10.8670

    Article  Google Scholar 

  32. Veraart, C., Grill, W.M., Mortimer, J.T.: Selective control of muscle activation with a multipolar nerve cuff electrode. IEEE Trans. Biomed. Eng. 40, 640–653 (1993). https://doi.org/10.1109/10.237694

    Article  Google Scholar 

  33. Tyler, D.J., Durand, D.M.: Functionally selective peripheral nerve stimulation with a flat interface nerve electrode. IEEE Trans. Neural Syst. Rehabil. Eng. 10, 294–303 (2002). https://doi.org/10.1109/TNSRE.2002.806840

    Article  Google Scholar 

  34. Tyler, D.J., Durand, D.M.: Chronic response of the rat sciatic nerve to the flat interface nerve electrode. Ann. Biomed. Eng. 31, 633–642 (2003). https://doi.org/10.1114/1.1569263

    Article  Google Scholar 

  35. Tan, D.W., Schiefer, M.A., Keith, M.W., et al.: A neural interface provides long-term stable natural touch perception. Sci. Transl. Med. 6, 1–12 (2014). https://doi.org/10.1126/scitranslmed.3008669

    Article  Google Scholar 

  36. Freeberg, M.J., Stone, M.A., Triolo, R.J., Tyler, D.J.: The design of and chronic tissue response to a composite nerve electrode with patterned stiffness. J. Neural Eng. 14, 036022 (2017). https://doi.org/10.1088/1741-2552/aa6632

    Article  Google Scholar 

  37. Christie, B.P., Freeberg, M., Memberg, W.D., et al.: Long-term stability of stimulating spiral nerve cuff electrodes on human peripheral nerves. J. Neuroeng. Rehabil. 14, 1–12 (2017). https://doi.org/10.1186/s12984-017-0285-3

    Article  Google Scholar 

  38. Yoshida, K., Pellinen, D., Pivin, D., et al.: Development of the thin-film longitudinal intra-fascicular electrode. Proc. Fifth Annu. Conf. IFESS, 3–5 (2000)

    Google Scholar 

  39. Yoshida, K., Hennings, K., Kammer, S.: Acute performance of the thin-film longitudinal intra-fascicular electrode. First IEEE/RAS-EMBS Int Conf Biomed Robot Biomechatronics. BioRob. 2006, 296–300 (2006). https://doi.org/10.1109/BIOROB.2006.1639102

    Article  Google Scholar 

  40. Lawrence, S.M., Dhillon, G.S., Horch, K.W.: Fabrication and characteristics of an implantable, polymer-based, intrafascicular electrode. J. Neurosci. Methods. 131, 9–26 (2003). https://doi.org/10.1016/S0165-0270(03)00231-0

    Article  Google Scholar 

  41. Dhillon, G.S., Lawrence, S.M., Hutchinson, D.T., Horch, K.W.: Residual function in peripheral nerve stumps of amputees: implications for neural control of artificial limbs. J. Hand Surg. Am. 29, 605–615; discussion 616–8 (2004). https://doi.org/10.1016/j.jhsa.2004.02.006

    Article  Google Scholar 

  42. Lawrence, S.M., Larsen, J.O., Horch, K.W., et al.: Long-term biocompatibility of implanted polymer-based intrafascicular electrodes. J. Biomed. Mater. Res. An Off. J. Soc. Biomater. Japanese Soc. Biomater. Aust. Soc. Biomater. Korean Soc. Biomater. 63, 501–506 (2002). https://doi.org/10.1002/jbm.10303

    Article  Google Scholar 

  43. Boretius, T., Badia, J., Pascual-Font, A., et al.: A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. Biosens. Bioelectron. 26, 62–69 (2010). https://doi.org/10.1016/j.bios.2010.05.010

    Article  Google Scholar 

  44. Raspopovic, S., Capogrosso, M., Petrini, F.M., et al.: Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci. Transl. Med. 6, 222ra19 (2014). https://doi.org/10.1126/scitranslmed.3006820

    Article  Google Scholar 

  45. Normann, R.A., McDonnall, D., Clark, G.A., et al.: Physiological activation of the hind limb muscles of the anesthetized cat using the utah slanted electrode array. Proc. Int. Jt. Conf. Neural Networks. 5, 3103–3108 (2005). https://doi.org/10.1109/IJCNN.2005.1556422

    Article  Google Scholar 

  46. Branner, A., Stein, R.B., Fernandez, E., et al.: Long-term stimulation and recording with a penetrating microelectrode array in cat sciatic nerve. IEEE Trans. Biomed. Eng. 51, 146–157 (2004). https://doi.org/10.1109/TBME.2003.820321

    Article  Google Scholar 

  47. Branner, A., Stein, R.B., Normann, R.A.: Selective stimulation of cat sciatic nerve using an array of varying-length microelectrodes. J. Neurophysiol. 85, 1585–1594 (2001)

    Google Scholar 

  48. Clark, G.A., Wendelken, S., Page, D.M., et al.: Using multiple high-count electrode arrays in human median and ulnar nerves to restore sensorimotor function after previous transradial amputation of the hand. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2014, 1977–1980 (2014). https://doi.org/10.1109/EMBC.2014.6944001

    Article  Google Scholar 

  49. Tyler, D.J., Durand, D.M.: A slowly penetrating interfascicular nerve electrode for selective activation of peripheral nerves. IEEE Trans. Rehabil. Eng. 5, 51–61 (1997)

    Google Scholar 

  50. Liem, L., Russo, M., Huygen, F.J.P.M., et al.: A multicenter, prospective trial to assess the safety and performance of the spinal modulation dorsal root ganglion neurostimulator system in the treatment of chronic pain, 471–482 (2013). https://doi.org/10.1111/ner.12072

  51. Lynch, P.J., Mcjunkin, T., Eross, E., et al.: Case report: successful epiradicular peripheral nerve stimulation of the C2 dorsal root ganglion for postherpetic neuralgia. 2010, 58–61 (2011). https://doi.org/10.1111/j.1525-1403.2010.00307.x

  52. Deer, T.R., Levy, R.M., Kramer, J., et al.: Dorsal root ganglion stimulation yielded higher treatment success rate for complex regional pain syndrome and causalgia at 3 and 12 months: a randomized comparative trial. Pain. 158, 669 (2017)

    Google Scholar 

  53. Weiner, R.L., Yeung, A., Garcia, C.M., et al.: Treatment of FBSS low back pain with a novel percutaneous DRG wireless stimulator: pilot and feasibility study. Pain Med. 17, 1911–1916 (2016). https://doi.org/10.1093/pm/pnw075

    Article  Google Scholar 

  54. Nanivadekar, A.C., Ayers, C.A., Gaunt, R.A., et al.: Selectivity of afferent microstimulation at the DRG using epineural and penetrating electrode arrays. J. Neural Eng. 17 (2020)

    Google Scholar 

  55. Ayers, C.A., Fisher, L.E., Gaunt, R.A., Weber, D.J.: Microstimulation of the lumbar DRG recruits primary afferent neurons in localized regions of lower limb. J. Neurophysiol. 116, 51–60 (2016). https://doi.org/10.1152/jn.00961.2015

    Article  Google Scholar 

  56. Fisher, L.E., Ayers, C.A., Ciollaro, M.: Chronic recruitment of primary afferent neurons by microstimulation in the feline dorsal root ganglia. (2014). https://doi.org/10.1088/1741-2560/11/3/036007

  57. Chandrasekaran, S., Nanivadekar, A.C., McKernan, G., et al.: Sensory restoration by epidural stimulation of the lateral spinal cord in upper-limb amputees. elife. 9, 1–26 (2020). https://doi.org/10.7554/eLife.54349

    Article  Google Scholar 

  58. Grider, J., Manchikanti, L., Carayannopoulos, A., et al.: Effectiveness of spinal cord stimulation in chronic spinal pain: a systematic review. Pain Physician. 19, 33–54 (2016)

    Google Scholar 

  59. North, R.B., Kidd, D.H., Petrucci, L., Dorsi, M.J.: Spinal cord stimulation electrode design: a prospective, randomized, controlled trial comparing percutaneous with laminectomy electrodes: Part II – Clinical outcomes. Neurosurgery. 57, 990–995 (2005). https://doi.org/10.1227/01.NEU.0000180030.00167.b9

    Article  Google Scholar 

  60. Villavicencio, A.T., Leveque, J.C., Rubin, L., et al.: Laminectomy versus percutaneous electrode placement for spinal cord stimulation. Neurosurgery. 46, 399–406 (2000). https://doi.org/10.1097/00006123-200002000-00025

    Article  Google Scholar 

  61. Epstein, L.J., Palmieri, M.: Managing chronic pain with spinal cord stimulation. Mt. Sinai J. Med. 79, 123–132 (2012). https://doi.org/10.1002/MSJ

    Article  Google Scholar 

  62. Kiss, Z.H.T., Anderson, T., Hansen, T., et al.: Neural substrates of microstimulation-evoked tingling: a chronaxie study in human somatosensory thalamus. Eur. J. Neurosci. 18, 728–732 (2003). https://doi.org/10.1046/j.1460-9568.2003.02793.x

    Article  Google Scholar 

  63. Heming, E., Sanden, A., Kiss, Z.: Designing a somatosensory neural prosthesis: percepts evoked by different patterns of thalamic stimulation. J. Neural Eng. 064001 (2010). https://doi.org/10.1088/1741-2560/7/6/064001

  64. Heming, E., Choo, R.: Designing a thalamic somatosensory neural prosthesis: consistency and persistence of percepts evoked by electrical stimulation. Neural Syst …. 19, 477–482 (2011)

    Google Scholar 

  65. Tasker, R.R., Kiss, Z.H.T.: The role of the thalamus in functional neurosurgery. Neurosurg. Clin. N. Am. 6, 73–104 (1995)

    Google Scholar 

  66. Hiremath, S.V., Tyler-Kabara, E.C., Wheeler, J.J., et al.: Human perception of electrical stimulation on the surface of somatosensory cortex. PLoS One. 12, 1–16 (2017). https://doi.org/10.1371/journal.pone.0176020

    Article  Google Scholar 

  67. Lee, B., Kramer, D., Salas, M.A., et al.: Engineering artificial somatosensation through cortical stimulation in humans. 12, 1–11 (2018). https://doi.org/10.3389/fnsys.2018.00024

  68. Flesher, S.N., Collinger, J.L., Foldes, S.T., et al.: Intracortical microstimulation of human somatosensory cortex. Sci. Transl. Med. 8, 1–11 (2016). https://doi.org/10.1126/scitranslmed.aaf8083

    Article  Google Scholar 

  69. Armenta Salas, M., Bashford, L., Kellis, S., et al.: Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation. elife. 7, 1–11 (2018). https://doi.org/10.7554/eLife.32904

    Article  Google Scholar 

  70. Fifer, M.S., McMullen, D.P., Thomas, T.M., et al.: Intracortical microstimulation elicits human fingertip sensations. medRxiv, 2020.05.29.20117374 (2020). https://doi.org/10.1101/2020.05.29.20117374

  71. Nowak, L.G., Bullier, J.: Axons, but not cell bodies, are activated by electrical stimulation in cortical gray matter. Exp. Brain Res. 118, 477–488 (1998)

    Google Scholar 

  72. Richardson, A.G., McIntyre, C.C., Grill, W.M.: Modelling the effects of electric fields on nerve fibres: influence of the myelin sheath. Med. Biol. Eng. Comput. 38, 438–446 (2000). https://doi.org/10.1007/BF02345014

    Article  Google Scholar 

  73. Histed, M.H., Ni, A.M., Maunsell, J.H.R.: Insights into cortical mechanisms of behavior from microstimulation experiments. Prog. Neurobiol. 103, 115–130 (2013). https://doi.org/10.1016/j.pneurobio.2012.01.006

    Article  Google Scholar 

  74. McIntyre, C., Grill, W.M.: Selective microstimulation of central nervous system neurons. Ann. Biomed. Eng. 28, 219–233 (2000)

    Google Scholar 

  75. Schiefer, M.A., Tyler, D.J.: Computer models of peripheral nerves. In: Nerves and Nerve Injuries: Volume 2: Pain, Treatment, Injury, Disease, and Future Directions, 1st edn, pp. 1–993. Elsevier Inc. (2015)

    Google Scholar 

  76. Peckham, P.H., Knutson, J.S.: Functional electrical stimulation for neuromuscular applications. Annu. Rev. Biomed. Eng. 7, 327–360 (2005). https://doi.org/10.1146/annurev.bioeng.6.040803.140103

    Article  Google Scholar 

  77. Gorman, P.H., Mortimer, J.T.: The effect of stimulus parameters on the recruitment characteristics of direct nerve stimulation. IEEE Trans. Biomed. Eng. BME. 30, 407–414 (1983). https://doi.org/10.1109/TBME.1983.325041

    Article  Google Scholar 

  78. Mogyoros, I., Kiernan, M.C., Burke, D.: Strength-duration properties of human peripheral nerve. Brain. 119, 439–447 (1996). https://doi.org/10.1093/brain/119.2.439

    Article  Google Scholar 

  79. Gooch, C.L., Doherty, T.J., Chan, K.M., et al.: Motor unit number estimation: a technology and literature review. Muscle Nerve. 50, 884–893 (2014). https://doi.org/10.1002/mus.24442

    Article  Google Scholar 

  80. Corniani, G., Saal, H.P.: Tactile innervation densities across the whole body. J. Neurophysiol. 124(4), 1229–1240 (2020)

    Google Scholar 

  81. Gaines, J., Finn, K., Slopsema, J., et al.: A model of median nerve activation using surface electrical stimulation. J. Comput. Neurosci. 45, 29–43 (2018). https://doi.org/10.1007/s10827-018-0689-5

    Article  Google Scholar 

  82. Rose, T.L., Robblee, L.S.: Electrical stimulation with Pt electrodes. VIII. Electrochemically safe charge injection limits with 0.2 ms pulses. IEEE Trans. Biomed. Eng. 37, 1118–1120 (1990). https://doi.org/10.1109/10.61038

    Article  Google Scholar 

  83. Shannon, R.V.: A model of safe levels for electrical stimulation. IEEE Trans. Biomed. Eng. 39, 424–426 (1992). https://doi.org/10.1109/10.126616

    Article  Google Scholar 

  84. McCreery, D.B., Agnew, W.F., Yuen, T.G.H., Bullara, L.: Charge density and charge per phase as cofactors in neural injury induced by electrical stimulation. IEEE Trans. Biomed. Eng. 37, 996–1001 (1990)

    Google Scholar 

  85. Merrill, D.R., Bikson, M., Jefferys, J.G.R.: Electrical stimulation of excitable tissue: design of efficacious and safe protocols. J. Neurosci. Methods. 141, 171–198 (2005). https://doi.org/10.1016/j.jneumeth.2004.10.020

    Article  Google Scholar 

  86. Ochoa, J., Torebjork, E.: Sensations evoked by intraneural microstimulation of single mechanoreceptor units innervating the human hand. J. Physiol. 342, 633–654 (1983)

    Google Scholar 

  87. Van Den Honert, C., Mortimer, J.T.: A technique for collision block of peripheral nerve: single stimulus analysis. IEEE Trans. Biomed. Eng. 28, 373–378 (1981). https://doi.org/10.1109/TBME.1981.324718

    Article  Google Scholar 

  88. Van Den Honert, C., Mortimer, J.T.: A technique for collision block of peripheral nerve: frequency dependence. IEEE Trans. Biomed. Eng. 28, 379–382 (1981). https://doi.org/10.1109/TBME.1981.324719

    Article  Google Scholar 

  89. Histed, M.H., Bonin, V., Reid, R.C.: Direct activation of sparse, distributed populations of cortical neurons by electrical microstimulation. Neuron. 63, 508–522 (2009). https://doi.org/10.1016/j.neuron.2009.07.016

    Article  Google Scholar 

  90. Rutten, W.L.C., Van Wier, H.J., Put, J.H.M.: Sensitivity and selectivity of intraneural stimulation using a silicon electrode array. IEEE Trans. Biomed. Eng. 38, 192–198 (1991). https://doi.org/10.1109/10.76386

    Article  Google Scholar 

  91. Grill, W.M., Mortimer, J.T.: The effect of stimulus pulse duration on selectivity of neural stimulation. IEEE Trans. Biomed. Eng. 43, 161–166 (1996)

    Google Scholar 

  92. Grill, W.M., Mortimer, J.T.: Non-invasive measurement of the input-output properties of peripheral nerve stimulating electrodes. J. Neurosci. Methods. 65, 43–50 (1996). https://doi.org/10.1016/0165-0270(95)00143-3

    Article  Google Scholar 

  93. Yoshida, K., Horch, K.: Selective stimulation of peripheral nerve fibers using dual intrafascicular electrodes. IEEE Trans. Biomed. Eng. 40, 492–494 (1993). https://doi.org/10.1109/10.243412

    Article  Google Scholar 

  94. Ekedahl, R., Frank, O., Hallin, R.G.: Peripheral afferents with common function cluster in the median nerve and somatotopically innervate the human palm. Brain Res. Bull. 42, 367–376 (1997)

    Google Scholar 

  95. Tyler, D.J., Peterson, E.J., Brill, N., White, K.: Increased selectivity of clinical peripheral nerve interfaces. 2011 5th Int. IEEE/EMBS Conf. Neural Eng. NER 2011, 257–260 (2011). https://doi.org/10.1109/NER.2011.5910536

  96. Brill, N., Tyler, D.: Optimizing nerve cuff stimulation of targeted regions through use of genetic algorithms. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2011, 5811–5814 (2011). https://doi.org/10.1109/IEMBS.2011.6091438

    Article  Google Scholar 

  97. Manola, L., Holsheimer, J.: Technical performance of percutaneous and laminectomy leads analyzed by modeling. Neuromodulation. 7, 231–241 (2004). https://doi.org/10.1111/j.1094-7159.2004.04207.x

    Article  Google Scholar 

  98. Vega-Bermudez, F., Johnson, K.O.: SA1 and RA receptive fields, response variability, and population responses mapped with a probe array. J. Neurophysiol. 81, 2701–2710 (1999). https://doi.org/10.1152/jn.1999.81.6.2701

    Article  Google Scholar 

  99. Johansson, R.S., Vallbo, A.B.: Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. J. Physiol. 286, 283–300 (1979). https://doi.org/10.1113/jphysiol.1979.sp012619

    Article  Google Scholar 

  100. Brown, P.B., Koerber, H.R., Millecchia, R.: From innervation density to tactile acuity: 1. Spatial representation. Brain Res. 1011, 14–32 (2004). https://doi.org/10.1016/j.brainres.2004.03.009

    Article  Google Scholar 

  101. Mancini, F., Bauleo, A., Cole, J., et al.: Whole-body map** of spatial acuity for pain and touch. Ann. Neurol. 75, 917–924 (2014). https://doi.org/10.1002/ana.24179

    Article  Google Scholar 

  102. Novak, C.B., Kelly, L., Mackinnon, S.E.: Sensory recovery after median nerve grafting. J. Hand Surg. Am. 17, 59–68 (1992). https://doi.org/10.1016/0363-5023(92)90114-5

    Article  Google Scholar 

  103. Pasluosta, C., Kiele, P., Stieglitz, T.: Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system. Clin. Neurophysiol. (2017). https://doi.org/10.1016/j.clinph.2017.12.027

  104. Serino, A., Haggard, P.: Touch and the body. Neurosci Bio. 34, 224–236 (2010). https://doi.org/10.1016/j.neubiorev.2009.04.004

    Article  Google Scholar 

  105. Sur, M., Merzenich, M.M., Kaas, J.H.: Magnification, receptive-field area, and “hypercolumn” size in areas 3b and 1 of somatosensory cortex in owl monkeys. J. Neurophysiol. 44, 295–311 (1980). https://doi.org/10.1152/jn.1980.44.2.295

    Article  Google Scholar 

  106. Sunderland, S.: The intraneural topography of the radial, median and ulnar nerves. Brain. 68, 243–298 (1945)

    Google Scholar 

  107. 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. Am. 5, 1–18 (1980). https://doi.org/10.1097/00006534-198011000-00072

    Article  Google Scholar 

  108. Watchmaker, G.P., Gumucio, C.A., Crandall, R.E., et al.: Fascicular topography of the median nerve: a computer based study to identify branching patterns. J. Hand Surg. Am. 16, 53–59 (1991). https://doi.org/10.1016/S0363-5023(10)80013-9

    Article  Google Scholar 

  109. Purves, D., Augustine, G.J., Fitzpatrick, D., et al.: Neuroscience. (2004)

    Google Scholar 

  110. Gaunt, R.A., Hokanson, J.A., Weber, D.J.: Microstimulation of primary afferent neurons in the L7 dorsal root ganglia using multielectrode arrays in anesthetized cats: thresholds and recruitment properties. J. Neural Eng. 6 (2009). https://doi.org/10.1088/1741-2560/6/5/055009

  111. Wessels, W.J.T., Feirabend, H.K.P., Marani, E.: Evidence for a rostrocaudal organization in dorsal root ganglia during development as demonstrated by intra-uterine W G A – H R P injections into the hindlimb of rat fetuses. 54, 273–281 (1990)

    Google Scholar 

  112. Prats-Galino, A., Puigdellívol-Sánchez, A., Ruano-Gil, D., Molander, C.: Representations of hindlimb digits in rat dorsal root ganglia. J. Comp. Neurol. 408, 137–145 (1999). https://doi.org/10.1002/(SICI)1096-9861(19990524)408:1<137::AID-CNE10>3.0.CO;2-3

    Article  Google Scholar 

  113. Aoyagi, Y., Stein, R.B., Branner, A., et al.: Capabilities of a penetrating microelectrode array for recording single units in dorsal root ganglia of the cat. J. Neurosci. Methods. 128, 9–20 (2003). https://doi.org/10.1016/S0165-0270(03)00143-2

    Article  Google Scholar 

  114. Wessels, W.J.T., Feirabend, H.K.P., Marani, E.: The rostrocaudal organization in the dorsal root ganglia of the rat: a consequence of plexus formation? Anat Embryol (Berl). 190, 1–11 (1994). https://doi.org/10.1007/BF00185841

    Article  Google Scholar 

  115. Werner, G., Whitsel, B.L.: The topology of dermatomal projection in the medial lemniscal system. J. Physiol. 192, 123–144 (1967). https://doi.org/10.1113/jphysiol.1967.sp008292

    Article  Google Scholar 

  116. Smith, M.C., Deacon, P.: Topographical anatomy of the posterior columns of the spinal cord in man: the long ascending fibres. Brain. 107, 671–698 (1984). https://doi.org/10.1093/brain/107.3.671

    Article  Google Scholar 

  117. Gardner, E., Martin, J.: Coding of sensory information. In: Principles of Neural Science, pp. 421–429 (2000)

    Google Scholar 

  118. Blankenburg, F., Ruben, J., Meyer, R., et al.: Evidence for a rostral-to-caudal somatotopic organization in human primary somatosensory cortex with mirror-reversal in areas 3b and 1. Cereb. Cortex. 13, 987–993 (2003). https://doi.org/10.1093/cercor/13.9.987

    Article  Google Scholar 

  119. Iwamura, Y., Iriki, A., Tanaka, M.: Bilateral hand representation in the postcentral somatosensory cortex. Nature. 369, 554–556 (1994). https://doi.org/10.1038/369554a0

    Article  Google Scholar 

  120. Iwamura, Y., Tanaka, M., Sakamoto, M., Hikosaka, O.: Converging patterns of finger representation and complex response properties of neurons in area 1 of the first somatosensory cortex of the conscious monkey. Exp. Brain Res. 51, 327–337 (1983). https://doi.org/10.1007/BF00237869

    Article  Google Scholar 

  121. Petrini, F.M., Valle, G., Bumbasirevic, M., et al.: Enhancing functional abilities and cognitive integration of the lower limb prosthesis. Sci. Transl. Med. 11, 8939 (2019)

    Google Scholar 

  122. Charkhkar, H., Shell, C.E., Marasco, P.D., et al.: High-density peripheral nerve cuffs restore natural sensation to individuals with lower-limb amputations. J. Neural Eng. 15, 056002 (2018). https://doi.org/10.1088/1741-2552/aac964

    Article  Google Scholar 

  123. Tan, D.W., Schiefer, M.A., Keith, M.W., et al.: Stability and selectivity of a chronic, multi-contact cuff electrode for sensory stimulation in a human amputee. J. Neural Eng. 12, 859–862 (2015). https://doi.org/10.1109/NER.2013.6696070

    Article  Google Scholar 

  124. Clark, G.A., Wendelken, S., Page, D.M., et al.: Using multiple high-count electrode arrays in human median and ulnar nerves to restore sensorimotor function after previous transradial amputation of the hand. 2014 36th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBC. 2014, 1977–1980 (2014). https://doi.org/10.1109/EMBC.2014.6944001

    Article  Google Scholar 

  125. Dhillon, G.S., Krüger, T.B., Sandhu, J.S., et al.: Effects of short-term training on sensory and motor function in severed nerves of long-term human amputees. J. Neurophysiol. 93, 2625–2633 (2005). https://doi.org/10.1152/jn.00937.2004

    Article  Google Scholar 

  126. Muniak, M.A., Ray, S., Hsiao, S.S., et al.: The neural coding of stimulus intensity: linking the population response of mechanoreceptive afferents with psychophysical behavior. J. Neurosci. 27, 11687–11699 (2007). https://doi.org/10.1523/JNEUROSCI.1486-07.2007

    Article  Google Scholar 

  127. Bensmaia, S.J.: Tactile intensity and population codes. Behav. Brain Res. 190, 165–173 (2008). https://doi.org/10.1016/j.bbr.2008.02.044

    Article  Google Scholar 

  128. Graczyk, E.L., Schiefer, M.A., Saal, H.P., et al.: The neural basis of perceived intensity in natural and artificial touch. Sci. Transl. Med. 8, 1–11 (2016). https://doi.org/10.1126/scitranslmed.aaf5187

    Article  Google Scholar 

  129. Gescheider, G.A.: Psychophysical measurement of thresholds. In: Psychophysics: Method, Theory, and Application, pp. 1–37 (1985)

    Google Scholar 

  130. Manfredi, L.R., Baker, A.T., Elias, D.O., et al.: The effect of surface wave propagation on neural responses to vibration in primate glabrous skin. PLoS One. 7, e31203 (2012). https://doi.org/10.1371/journal.pone.0031203

    Article  Google Scholar 

  131. Johnson, K.O.: Reconstruction of population response to a vibratory stimulus in quickly adapting mechanoreceptive afferent fiber population innervating glabrous skin of the monkey. J. Neurophysiol. 37, 48–72 (1974)

    Google Scholar 

  132. Talbot, W.H., Darian-Smith, I., Kornhuber, H.H., Mountcastle, V.B.: The sense of flutter-vibration: comparison of the human capacity with response patterns of mechanoreceptive afferents from the monkey hand. J. Neurophysiol. 31, 301–334 (1968)

    Google Scholar 

  133. Freeman, B.Y.A.W., Johnson, K.: A model accounting for effects of vibratory amplitude on responses of cutaneous mechanoreceptors in macaque monkeys. J. Physiol. 323, 43–64 (1982)

    Google Scholar 

  134. McGlone, F., Reilly, D.: The cutaneous sensory system. Neurosci. Biobehav. Rev. 34, 148–159 (2010). https://doi.org/10.1016/j.neubiorev.2009.08.004

    Article  Google Scholar 

  135. Mountcastle, V.B., Talbot, W.H., Sakata, H., Hyvärinen, J.: Cortical neuronal mechanisms in flutter-vibration studied in unanesthetized monkeys. Neuronal periodicity and frequency discrimination. J. Neurophysiol. 32, 452–484 (1969). https://doi.org/10.1152/jn.1969.32.3.452

    Article  Google Scholar 

  136. Knibestöl, M., Vallbo, B., Knibestol, B.Y.M., Vallbo, A.B.: Intensity of sensation related to activity of slowly adapting mechanoreceptive units in the human hand. J. Physiol. 300, 251–267 (1980). https://doi.org/10.1113/jphysiol.1980.sp013160

    Article  Google Scholar 

  137. Leung, Y.Y., Bensmaia, S.J., Hsiao, S.S., Johnson, K.O.: Time-course of vibratory adaptation and recovery in cutaneous mechanoreceptive afferents. J. Neurophysiol. 94, 3037–3045 (2005). https://doi.org/10.1152/jn.00002.2005

    Article  Google Scholar 

  138. Verrillo, R.T., Gescheider, G.A.: Effect of prior stimulation on vibrotactile thresholds. Sens. Processes. 1, 292–300 (1977)

    Google Scholar 

  139. Gescheider, G.A., Wright, J.H.: Effects of sensory adaptation on the form of the psychophysical magnitude function for cutaneous vibration. J. Exp. Psychol. 77, 308–313 (1968). https://doi.org/10.1037/h0025746

    Article  Google Scholar 

  140. Hollins, M., Goble, A.K., Whitsel, B.L., Tommerdahl, M.: Time course and action spectrum of vibrotactile adaptation. Somatosens. Mot. Res. 7, 205–221 (1990). https://doi.org/10.3109/08990229009144707

    Article  Google Scholar 

  141. Bensmaïa, S.J., Leung, Y.Y., Hsiao, S.S., Johnson, K.O.: Vibratory adaptation of cutaneous mechanoreceptive afferents. J. Neurophysiol. 94, 3023–3036 (2005). https://doi.org/10.1152/jn.00002.2005

    Article  Google Scholar 

  142. Berglund, U., Berglund, B.: Adaptation and recovery in vibrotactile perception. Percept. Mot. Skills. 30, 843–853 (1970)

    Google Scholar 

  143. Hahn, J.F.: Vibrotactile adaptation and recovery measured by two methods. J. Exp. Psychol. 71, 655–658 (1966). https://doi.org/10.1037/h0023094

    Article  Google Scholar 

  144. Brenner, N., Bialek, W., de van Steveninck, R.R.: Adaptive rescaling maximizes information transmission. Neuron. 26, 695–702 (2000)

    Google Scholar 

  145. Ribot-Ciscar, E., Roll, J.P., Tardy-Gervet, M.F., Harlay, F.: Alteration of human cutaneous afferent discharges as the result of long-lasting vibration. J. Appl. Physiol. 80, 1708–1715 (1996)

    Google Scholar 

  146. Whitsel, B.L., Kelly, E.F., Quibrera, M., et al.: Time-dependence of SI RA neuron response to cutaneous flutter stimulation. Somatosens. Mot. Res. 20, 45–69 (2003). https://doi.org/10.1080/0899022031000083834

    Article  Google Scholar 

  147. O’Mara, S., Rowe, M.J., Tarvin, R.P.: Neural mechanisms in vibrotactile adaptation. J. Neurophysiol. 59, 607–622 (1988)

    Google Scholar 

  148. Bostock, B.Y.H., Sears, T.A., Sherratt, R.M.: Spatial distribution of excitability. J. Physiol. 34, 41–58 (1983)

    Google Scholar 

  149. Vallbo, A.B., Johansson, R.S.: Properties of cutaneous mechanoreceptors in the human hand related to touch sensation. Hum. Neurobiol. 3, 3–14 (1984)

    Google Scholar 

  150. Menia, L.L., van Doren, C.L.: Independence of pitch and loudness of an electrocutaneous stimulus for sensory feedback. IEEE Trans. Rehabil. Eng. 2, 197–206 (1994)

    Google Scholar 

  151. Szeto, A.Y.J., Lyman, J., Prior, R.E.: Electrocutaneous pulse rate and pulse width psychometric functions for sensory communications. Hum. Factors J. Hum. Factors Ergon. Soc. 21, 241–249 (1979). https://doi.org/10.1177/001872087902100212

    Article  Google Scholar 

  152. Szeto, A.Y.: Relationship between pulse rate and pulse width for a constant-intensity level of electrocutaneous stimulation. Ann. Biomed. Eng. 13, 373–383 (1985). https://doi.org/10.1007/BF02407767

    Article  Google Scholar 

  153. Szeto, A.Y.J., Saunders, F.A.: Electrocutaneous stimulation for sensory communication in rehabilitation engineering. IEEE Trans. Biomed. Eng. 29, 300–308 (1982). https://doi.org/10.1109/TBME.1982.324948

    Article  Google Scholar 

  154. Flesher, S.N., Downey, J.E., Weiss, J.M., et al.: Restored tactile sensation improves neuroprosthetic arm control. bioRxiv, 653428 (2019). https://doi.org/10.1101/653428

  155. Hughes, C., Flesher, S., Weiss, J., et al.: Perceptual responses to microstimulation frequency are spatially organized in human somatosensory cortex. bioarxiv. (2020). https://doi.org/10.1101/2020.07.16.207506

  156. Graczyk, E.L., Delhaye, B.P., Schiefer, M.A., et al.: Sensory adaptation to electrical stimulation of the somatosensory nerves. J. Neural Eng. 15 (2018). https://doi.org/10.1088/1741-2552/aab790

  157. Buma, D.G., Buitenweg, J.R., Veltink, P.H.: Intermittent stimulation delays adaptation to electrocutaneous sensory feedback. IEEE Trans. Neural Syst. Rehabil. Eng. 15, 435–441 (2007). https://doi.org/10.1109/TNSRE.2007.903942

    Article  Google Scholar 

  158. Kaczmarek, K.A.: Electrotactile adaptation on the abdomen: preliminary results. IEEE Trans. Rehabil. Eng. 8, 499–505 (2000)

    Google Scholar 

  159. McCreery, D.B., Yuen, T.G.H., Agnew, W.F., Bullara, L.A.: A characterization of the effects on neuronal excitability due to prolonged microstimulation with chronically implanted microelectrodes. IEEE Trans. Biomed. Eng. 44, 931–939 (1997). https://doi.org/10.1109/10.634645

    Article  Google Scholar 

  160. Kim, S., Callier, T., Bensmaia, S.J.: A computational model that predicts behavioral sensitivity to intracortical microstimulation. J. Neural Eng. 14 (2017)

    Google Scholar 

  161. Anani, A.B., Körner, L.M.: Afferent electrical nerve stimulation: human tracking performance relevant to prosthesis sensory feedback. Med. Biol. Eng. 17, 425–434 (1979)

    Google Scholar 

  162. Hollins, M., Faldowski, R., Rao, S., Young, F.: Perceptual dimensions of tactile surface texture: a multidimensional scaling analysis. Percept. Psychophys. 54, 697–705 (1993)

    Google Scholar 

  163. Hollins, M., Bensmaïa, S., Karlof, K., Young, F.: Individual differences in perceptual space for tactile textures: evidence from multidimensional scaling. Percept. Psychophys. 62, 1534–1544 (2000)

    Google Scholar 

  164. Picard, D., Dacremont, C., Valentin, D., Giboreau, A.: Perceptual dimensions of tactile textures. Acta Psychol. 114, 165–184 (2003). https://doi.org/10.1016/j.actpsy.2003.08.001

    Article  Google Scholar 

  165. Bergmann Tiest, W.M., Kappers, A.M.L.: Analysis of haptic perception of materials by multidimensional scaling and physical measurements of roughness and compressibility. Acta Psychol. 121, 1–20 (2006). https://doi.org/10.1016/j.actpsy.2005.04.005

    Article  Google Scholar 

  166. Guest, S., Dessirier, J.M., Mehrabyan, A., et al.: The development and validation of sensory and emotional scales of touch perception. Atten. Percept. Psychophys. 73, 531–550 (2011). https://doi.org/10.3758/s13414-010-0037-y

    Article  Google Scholar 

  167. Saal, H.P., Bensmaia, S.J.: Touch is a team effort: interplay of submodalities in cutaneous sensibility. Trends Neurosci. 37, 689–697 (2014)

    Google Scholar 

  168. Schady, W.J., Torebjörk, H.E., Ochoa, J.L.: Peripheral projections of nerve fibres in the human median nerve. Brain Res. 277, 249–261 (1983)

    Google Scholar 

  169. Wu, G., Ekedahl, R., Stark, B., et al.: Clustering of Pacinian corpuscle afferent fibres in the human median nerve. Exp. Brain Res. 126, 399–409 (1999)

    Google Scholar 

  170. Wu, G., Ekedahl, R., Hallin, R.G.: Clustering of slowly adapting type II mechanoreceptors in human peripheral nerve and skin. Brain. 121(Pt 2), 265–279 (1998)

    Google Scholar 

  171. Roberts, W.J., Elardo, S.M.: Clustering of primary afferent fibers in peripheral nerve fascicles by sensory modality. Brain Res. 370, 149–152 (1986). https://doi.org/10.1016/0006-8993(86)91115-7

    Article  Google Scholar 

  172. Niu, J., Ding, L., Li, J.J., et al.: Modality-based organization of ascending somatosensory axons in the direct dorsal column pathway. J. Neurosci. 33, 17691–17709 (2013). https://doi.org/10.1523/JNEUROSCI.3429-13.2013

    Article  Google Scholar 

  173. Lieber, J.D., Bensmaia, S.J.: High-dimensional representation of texture in somatosensory cortex of primates. Proc. Natl. Acad. Sci. 116 (2019). https://doi.org/10.1073/pnas.1818501116

  174. Pei, Y.-C., Denchev, P.V., Hsiao, S.S., et al.: Convergence of submodality-specific input onto neurons in primary somatosensory cortex. J. Neurophysiol. 102, 1843–1853 (2009). https://doi.org/10.1152/jn.00235.2009

    Article  Google Scholar 

  175. Mountcastle, V.B.: Modality and topographic properties of single neurons of cat’s somatic sensory cortex. J. Neurophysiol. 20, 408–434 (1957)

    Google Scholar 

  176. Mountcastle, V.B.: The columnar organization of the neocortex. Brain: A J. Neurol. 120, 701–722 (1997)

    Google Scholar 

  177. Weber, A.I., Saal, H.P., Lieber, J.D., et al.: Spatial and temporal codes mediate the tactile perception of natural textures. Proc. Natl. Acad. Sci. 110, 17107–17112 (2013). https://doi.org/10.1073/pnas.1305509110

    Article  Google Scholar 

  178. Tanaka, Y., Bergmann Tiest, W.M., Kappers, A.M.L., Sano, A.: Contact force and scanning velocity during active roughness perception. PLoS One. 9 (2014). https://doi.org/10.1371/journal.pone.0093363

  179. Manfredi, L.R., Saal, H.P., Brown, K.J., et al.: Natural scenes in tactile texture. J. Neurophysiol. 111, 1792–1802 (2014). https://doi.org/10.1152/jn.00680.2013

    Article  Google Scholar 

  180. Manfredi, L.R.: The role of vibratory cues in affective responses to tactile textures. Sch Mech Eng. (2010)

    Google Scholar 

  181. Graczyk, E.L., Christie, B.P., He, Q., et al.: Frequency shapes the quality of tactile percepts evoked through electrical stimulation of the nerves. bioRxiv. (2020)

    Google Scholar 

  182. Kim, L.H., Mcleod, R.S., Kiss, Z.H.T.: A new psychometric questionnaire for reporting of somatosensory percepts. J. Neural Eng. 15 (2018)

    Google Scholar 

  183. Valle, G., Iberite, F., Strauss, I., et al.: A psychometric platform to collect somatosensory sensations for neuroprosthetic use Equally author contributors † Corresponding authors. bioRxiv, 2020.07.23.218222 (2020). https://doi.org/10.1101/2020.07.23.218222

  184. Geng, B., Yoshida, K., Petrini, L., Jensen, W.: Evaluation of sensation evoked by electrocutaneous stimulation on forearm in nondisabled subjects. J. Rehabil. Res. Dev. 49, 297–308 (2012)

    Google Scholar 

  185. Davis, T.S., Wark, H.A.C.C., Hutchinson, D.T., et al.: Restoring motor control and sensory feedback in people with upper extremity amputations using arrays of 96 microelectrodes implanted in the median and ulnar nerves. J. Neural Eng. 13, 036001 (2016). https://doi.org/10.1088/1741-2560/13/3/036001

    Article  Google Scholar 

  186. Clip**er, F.F.W., Avery, R., Titus, B.B.R.: A sensory feedback system for an upper-limb amputation prosthesis. Bull. Prosthet. Res., 247–258 (1974)

    Google Scholar 

  187. Graczyk, E.L., Resnik, L., Schiefer, M.A., et al.: Home use of a neural-connected sensory prosthesis provides the functional and psychosocial experience of having a hand again. Sci. Rep. 8, 9866 (2018). https://doi.org/10.1038/s41598-018-26952-x

    Article  Google Scholar 

  188. Cuberovic, I., Gill, A., Resnik, L.J., et al.: Learning of artificial sensation through long-term home use of a sensory-enabled prosthesis. Front. Neurosci. 13, 1–24 (2019). https://doi.org/10.3389/fnins.2019.00853

    Article  Google Scholar 

  189. Saal, H.P., Delhaye, B.P., Rayhaun, B.C., Bensmaia, S.J.: Simulating tactile signals from the whole hand with millisecond precision. Proc. Natl. Acad. Sci. 114, E5693–E5702 (2017). https://doi.org/10.1073/pnas.1704856114

    Article  Google Scholar 

  190. Formento, E., D’anna, E., Gribi, S., et al.: A biomimetic electrical stimulation strategy to induce asynchronous stochastic neural activity. BioRxiv. (2019)

    Google Scholar 

  191. Okorokova, E., He, Q., Bensmaia, S.: Biomimetic encoding model for restoring touch in bionic hands through a nerve interface. J. Neural Eng. 15 (2018) 10pp

    Google Scholar 

  192. Valle, G., Mazzoni, A., Iberite, F., et al.: Biomimetic intraneural sensory feedback enhances sensation naturalness, tactile sensitivity, and manual dexterity in a bidirectional prosthesis. Neuron. 100, 1–9 (2018). https://doi.org/10.1016/j.neuron.2018.08.033

    Article  Google Scholar 

  193. Graczyk, E.L.: Natural Perceptual Characteristics and Psychosocial Impacts of Touch Evoked by Peripheral Nerve Stimulation. Case Western Reserve University (2018)

    Google Scholar 

  194. George, J.A., Kluger, D.T., Davis, T.S., et al.: Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand. Sci Robot. 4, 1–12 (2019). https://doi.org/10.1126/scirobotics.aax2352

    Article  Google Scholar 

  195. Whitsel, B.L., Kelly, E.F., Delemos, K.A., et al.: Stability of rapidly adapting afferent entrainment vs responsivity. Somatosens. Mot. Res. 17, 13–31 (2000). https://doi.org/10.1080/08990220070265

    Article  Google Scholar 

  196. Pongrac, H.: Vibrotactile perception: examining the coding of vibrations and the just noticeable difference under various conditions. Multimed Syst. 13, 297–307 (2007). https://doi.org/10.1007/s00530-007-0105-x

    Article  Google Scholar 

  197. Mountcastle, V.B., Steinmetz, M.A., Romo, R.: Frequency discrimination in the sense of flutter: psychophysical measurements correlated with postcentral events in behaving monkeys. J. Neurosci. 10, 3032–3044 (1990). https://doi.org/10.1523/JNEUROSCI.10-09-03032.1990

    Article  Google Scholar 

  198. Hursh, J.B.: Conduction velocity and diameter of nerve fibers. Am. J. Phys. 127, 131–139 (1939)

    Google Scholar 

  199. Keetels, M., Vroomen, J.: Perception of synchrony between the senses. Neural Bases Multisensory Process Murray MM, 1–61 (2012). https://doi.org/10.1201/b11092-12

  200. Bushara, K.O., Grafman, J., Hallett, M.: Neural correlates of auditory – visual stimulus onset asynchrony detection. J. Neurosci. 21, 300–304 (2001)

    Google Scholar 

  201. Hirsh, I.J., Sherrick, C.E.: Perceived order in different sense modalities. J. Exp. Psychol. 62, 423–432 (1961)

    Google Scholar 

  202. Keetels, M., Vroomen, J.: Temporal recalibration to tactile-visual asynchronous stimuli. Neurosci. Lett. 430, 130–134 (2008). https://doi.org/10.1016/j.neulet.2007.10.044

    Article  Google Scholar 

  203. Zampini, M., Shore, D.I., Spence, C.: Audiovisual prior entry. Neurosci. Lett. 381, 217–222 (2005). https://doi.org/10.1016/j.neulet.2005.01.085

    Article  Google Scholar 

  204. Vatakis, A., Spence, C.: Audiovisual synchrony perception for music, speech, and object actions. 1 (2006). https://doi.org/10.1016/j.brainres.2006.05.078

  205. Vatakis, A., Spence, C.: Audiovisual synchrony perception for speech and music assessed using a temporal order judgment task. 393, 40–44 (2006). https://doi.org/10.1016/j.neulet.2005.09.032

  206. Stekelenburg, J.J., Vroomen, J.: Neural correlates of multisensory integration of ecologically valid audiovisual events. J. Cogn. Neurosci. 19, 1964–1973 (2007)

    Google Scholar 

  207. Conrey, B., Pisoni, D.B., Conrey, B., Pisoni, D.B.: Auditory-visual speech perception and synchrony detection for speech and nonspeech signals. J. Acoust. Soc. Am. 119, 4065–4073 (2006). https://doi.org/10.1121/1.2195091

    Article  Google Scholar 

  208. Reed, T.E., Jensen, A.R.: Conduction velocity in a brain nerve pathway of normal adults correlates with intelligence level. Intelligence. 16, 259–272 (1992)

    Google Scholar 

  209. Moller, A.R., Colletti, V., Fiorino, F.G.: Neural conduction velocity of the human auditory nerve: bipolar recordings from the exposed intracranial portion of the eighth nerve during vestibular nerve section. Electroencephalogr. Clin. Neurophysiol. 92, 316–320 (1994)

    Google Scholar 

  210. Macefield, G., Gandevia, S.C., Burke, D.: Conduction velocities of muscle and cutaneous afferents in the upper and lower limbs of human subjects. Brain. 112, 1519–1532 (1989). https://doi.org/10.1093/brain/112.6.1519

    Article  Google Scholar 

  211. Harrar, V., Harris, L.R.: Simultaneity constancy: detecting events with touch and vision. Exp. Brain Res. 166, 465–473 (2005). https://doi.org/10.1007/s00221-005-2386-7

    Article  Google Scholar 

  212. Eisen, A.: Subject review: the somatosensory evoked potential. Can. J. Neurol. Sci. 9, 65 (1982)

    Google Scholar 

  213. Nakanishi, T., Takita, K., Toyokura, Y.: Somatosensory evoked responses to tactile tap in man. Electroencephalogr. Clin. Neurophysiol. 34, 1–6 (1973). https://doi.org/10.1016/0013-4694(73)90144-2

    Article  Google Scholar 

  214. Gilley, P.M., Sharma, A., Dorman, M., Martin, K.: Developmental changes in refractoriness of the cortical auditory evoked potential. Clin. Neurophysiol. 116, 648–657 (2005). https://doi.org/10.1016/j.clinph.2004.09.009

    Article  Google Scholar 

  215. Woods, D.L., Wyma, J.M., Yund, E.W., et al.: Factors influencing the latency of simple reaction time. 9, 1–12 (2015). https://doi.org/10.3389/fnhum.2015.00131

  216. Jaśkowski, P., Jaroszyk, F., Hojan-Jezierska, D.: Temporal-order judgments and reaction time for stimuli of different modalities. Psychol. Res. 52, 35–38 (1990). https://doi.org/10.1007/BF00867209

    Article  Google Scholar 

  217. Forster, B., Cavina-Pratesi, C., Aglioti, S.M.: Redundant target effect and intersensory facilitation from visual-tactile interactions in simple reaction time. Exp. Brain Res. 143, 480–487 (2002). https://doi.org/10.1007/s00221-002-1017-9

    Article  Google Scholar 

  218. Goodall, E.V., Kosterman, L.M., Holsheimer, J., Struijk, J.J.: Modeling study of activation and propagation delays during stimulation of peripheral nerve fibers with a tripolar cuff electrode. IEEE Trans. Rehabil. Eng. 3, 272–282 (1995)

    Google Scholar 

  219. Wesselink, W.A., Holsheimer, J., Boom, H.B.K.: A model of the electrical behaviour of myelinated sensory nerve fibres based on human data. Med. Biol. Eng. Comput. 37, 228–235 (1999). https://doi.org/10.1007/BF02513291

    Article  Google Scholar 

  220. Callier, T., Brantly, N., Caravalli, A., Bensmaia, S.J.: The frequency of cortical microstimulation shapes artificial touch. bioarxiv. (2019)

    Google Scholar 

  221. Oddo, C.M., Raspopovic, S., Artoni, F., et al.: Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans. elife. 5, 1–27 (2016). https://doi.org/10.7554/eLife.09148

    Article  Google Scholar 

  222. Christie, B., Graczyk, E., Charkhkar, H., et al.: Visuo-tactile synchrony of stimulation-induced sensation and natural somatosensation. J. Neural Eng. 16 (2019)

    Google Scholar 

  223. Ziegler-graham, K., Mackenzie, E.J., Ephraim, P.L., et al.: Estimating the prevalence of limb loss in the United States: 2005 to 2050. 89, 422–429 (2008). https://doi.org/10.1016/j.apmr.2007.11.005

  224. Rybarczyk, B., Behel, J.: Limb loss and body image. In: Psychoprosthetics, pp. 23–31. Springer (2008)

    Google Scholar 

  225. Desmond, D.M.: Co**, affective distress, and psychosocial adjustment among people with traumatic upper limb amputations. J. Psychosom. Res. 62, 15–21 (2007). https://doi.org/10.1016/j.jpsychores.2006.07.027

    Article  Google Scholar 

  226. Gallagher, P., Desmond, D., MacLachlan, M.: Psychoprosthetics. (2008)

    Google Scholar 

  227. Frank, R.G., Elliott, T.R.: Handbook of Rehabilitation Psychology. American Psychological Association (2000)

    Google Scholar 

  228. Briggs, W.: The mental health problems and needs of older people following lower-limb amputation. Rev. Clin. Gerontol. 16, 155 (2007). https://doi.org/10.1017/S0959259807002171

    Article  Google Scholar 

  229. Williamson, G.M., Schulz, R., Bridges, M.W., Behan, A.M.: Social and psychological factors in adjustment to limb amputation. J. Soc. Behav. Pers. 9, 249 (1994)

    Google Scholar 

  230. Rybarczyk, B., Nyenhuis, D., Nicholas, J., et al.: Social discomfort and depression in a sample of adults with leg amputations. Arch. Phys. Med. Rehabil. 73, 1169–1173 (1992)

    Google Scholar 

  231. Eaton, W.W.: Epidemiologic evidence on the comorbidity of depression and diabetes. J. Psychosom. Res. 53, 903–906 (2002). https://doi.org/10.1016/S0022-3999(02)00302-1

    Google Scholar 

  232. Blazer, D.G., Kessler, R.C., McGonagle, K.A., Swartz, M.S.: The prevalence and distribution of major depression in a national community sample: the National Comorbidity Survey. Am. J. Psychiatry. 151, 979–986 (1994)

    Google Scholar 

  233. Biddiss, E., Chau, T.: Upper-limb prosthetics: critical factors in device abandonment. Am. J. Phys. Med. Rehabil. 86, 977–987 (2007). https://doi.org/10.1097/PHM.0b013e3181587f6c

    Article  Google Scholar 

  234. Biddiss, E., Chau, T.: Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthetics Orthot. Int. 31, 236–257 (2007)

    Google Scholar 

  235. Atkins, D., Heard, D.C.Y., Donovan, W.H.: Epidemiologic overview of individuals with upper-limb loss and their reported research priorities. J. Prosthetics Orthot. 8, 2–11 (1996)

    Google Scholar 

  236. Peerdeman, B., Boere, D., Witteveen, H., et al.: Myoelectric forearm prostheses: state of the art from a user-centered perspective. J. Rehabil. Res. Dev. 48, 719 (2011). https://doi.org/10.1682/JRRD.2010.08.0161

    Article  Google Scholar 

  237. Burger, H., Vidmar, G.: A survey of overuse problems in patients with acquired or congenital upper limb deficiency. Prosthetics Orthot. Int. 40, 497–502 (2016). https://doi.org/10.1177/0309364615584658

    Article  Google Scholar 

  238. Postema, S.G., Bongers, R.M., Brouwers, M.A., et al.: Musculoskeletal complaints in transverse upper limb reduction deficiency and amputation in the Netherlands: prevalence, predictors, and effect on health. Arch. Phys. Med. Rehabil. 97, 1137–1145 (2016). https://doi.org/10.1016/j.apmr.2016.01.031

    Article  Google Scholar 

  239. Johansson, R., Westling, G.: Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Exp. Brain Res. 56, 550–564 (1984)

    Google Scholar 

  240. Johansson, R.S., Edin, B.B.: Predictive feed-forward sensory control during gras** and manipulation in man. Biomed. Res. 14, 95–106 (1993)

    Google Scholar 

  241. Häger-Ross, C., Johansson, R.S.: Nondigital afferent input in reactive control of fingertip forces during precision grip. Exp. Brain Res. 110, 131–141 (1996). https://doi.org/10.1007/BF00241382

    Article  Google Scholar 

  242. Whitaker, T.A., Simões-Franklin, C., Newell, F.N.: Vision and touch: independent or integrated systems for the perception of texture? Brain Res. 1242, 59–72 (2008). https://doi.org/10.1016/j.brainres.2008.05.037

    Article  Google Scholar 

  243. Srinivasan, M.A., LaMotte, R.H.: Tactual discrimination of softness. J. Neurophysiol. 73, 88–101 (1995). https://doi.org/10.1007/978-3-0348-9016-8_11

    Article  Google Scholar 

  244. Childress, D.S.: Closed-loop control in prosthetic systems: historical perspective. Ann. Biomed. Eng. 8, 293–303 (1980)

    Google Scholar 

  245. Lewis, S., Russold, M.F., Dietl, H., Kaniusas, E.: User demands for sensory feedback in upper extremity prostheses. IEEE Int. Symp. Med. Meas. Appl. Proc. 2012, 1–4 (2012). https://doi.org/10.1109/MeMeA.2012.6226669

    Article  Google Scholar 

  246. Lundberg, M., Hagberg, K., Bullington, J.: My prosthesis as a part of me: a qualitative analysis of living with an osseointegrated prosthetic limb. Prosthetics Orthot. Int. 35, 207–214 (2011). https://doi.org/10.1177/0309364611409795

    Article  Google Scholar 

  247. Hagberg, K., Häggström, E., Jönsson, S., et al.: Osseoperception and osseointegrated prosthetic limbs. Psychoprosthetics, 131–140 (2008)

    Google Scholar 

  248. Vargas, L., Whitehouse, G., Huang, H., et al.: Evoked haptic sensation in the hand with concurrent non-invasive nerve stimulation. IEEE Trans. Biomed. Eng. 66, 2761–2767 (2019). https://doi.org/10.1109/TBME.2019.2895575

    Article  Google Scholar 

  249. D’Anna, E., Petrini, F.M., Artoni, F., et al.: A somatotopic bidirectional hand prosthesis with transcutaneous electrical nerve stimulation based sensory feedback. Sci. Rep. 7, 1–15 (2017). https://doi.org/10.1038/s41598-017-11306-w

    Article  Google Scholar 

  250. Osborn, L.E., Dragomir, A., Betthauser, J.L., et al.: Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain. Sci Robot. 3, eaat3818 (2018). https://doi.org/10.1126/scirobotics.aat3818

    Article  Google Scholar 

  251. Chandrasekaran, S., Nanivadekar, A.C., McKernan, G.P., et al.: Sensory restoration by epidural stimulation of dorsal spinal cord in upper-limb amputees. elife. 9, 1–26 (2020)

    Google Scholar 

  252. Schiefer, M.A., Tan, D.W., Sidik, S.M., et al.: 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). https://doi.org/10.1088/1741-2560/13/1/016001

    Article  Google Scholar 

  253. Horch, K., Meek, S., Taylor, T.G., Hutchinson, D.T.: Object discrimination with an artificial hand using electrical stimulation of peripheral tactile and proprioceptive pathways with intrafascicular electrodes. IEEE Trans. Neural Syst. Rehabil. Eng. 19, 483–489 (2011). https://doi.org/10.1109/TNSRE.2011.2162635

    Article  Google Scholar 

  254. Segil, J.L., Cuberovic, I., Graczyk, E.L., et al.: Combination of simultaneous artificial sensory percepts to identify prosthetic hand postures: a case study. Sci. Rep. 10, 1–15 (2020). https://doi.org/10.1038/s41598-020-62970-4

    Article  Google Scholar 

  255. Mulvey, M.R., Fawkner, H.J., Radford, H.E., Johnson, M.I.: Perceptual embodiment of prosthetic limbs by transcutaneous electrical nerve stimulation. Neuromodulation. 15, 42–46; discussion 47 (2012). https://doi.org/10.1111/j.1525-1403.2011.00408.x

    Article  Google Scholar 

  256. Mulvey, M.R., Radford, H.E., Fawkner, H.J., et al.: Transcutaneous electrical nerve stimulation for phantom pain and stump pain in adult amputees. Pain Pract. 13, 289–296 (2013). https://doi.org/10.1111/j.1533-2500.2012.00593.x

    Article  Google Scholar 

  257. 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, 1–29 (2019). https://doi.org/10.1371/journal.pone.0211469

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA

    Emily L. Graczyk & Dustin J. Tyler

  2. Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, USA

    Emily L. Graczyk & Dustin J. Tyler

Authors
  1. Emily L. Graczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dustin J. Tyler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emily L. Graczyk .

Editor information

Editors and Affiliations

  1. Neuroengineering and Biomedical Instrumentation Laboratory Department of Biomedical Engineering and Department of Electrical and Computer Engineering, Neurology, Johns Hopkins University, Baltimore, MD, USA

    Nitish V. Thakor

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Nature Singapore Pte Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Graczyk, E.L., Tyler, D.J. (2023). Somatosensory Neuromodulation with a Focus Towards Clinical Systems. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-5540-1_92

Download citation

Publish with us

Policies and ethics

Search

Navigation