Materials and technologies for soft implantable neuroprostheses

Abstract

Implantable neuroprostheses are engineered systems designed to restore or substitute function for individuals with neurological deficits or disabilities. These systems involve at least one uni- or bidirectional interface between a living neural tissue and a synthetic structure, through which information in the form of electrons, ions or photons flows. Despite a few notable exceptions, the clinical dissemination of implantable neuroprostheses remains limited, because many implants display inconsistent long-term stability and performance, and are ultimately rejected by the body. Intensive research is currently being conducted to untangle the complex interplay of failure mechanisms. In this Review, we emphasize the importance of minimizing the physical and mechanical mismatch between neural tissues and implantable interfaces. We explore possible materials solutions to design and manufacture neurointegrated prostheses, and outline their immense therapeutic potential.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Structure and anatomy of the nervous system.
Figure 2: Mechanical mismatch between the nervous tissues and man-made implantable electrodes.
Figure 3: Compliant and multimodal neural interfaces for the brain.
Figure 4: Compliant and multimodal interfaces for the spinal cord and the peripheral nerves.
Figure 5: Mechanosensitivity and foreign body reaction in the central nervous system.
Figure 6: Functions with compliant neural interfaces.

References

  1. 1

    Hochberg, L. R. et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485, 372–375 (2012).

    CAS  Article  Google Scholar 

  2. 2

    Bouton, C. E. et al. Restoring cortical control of functional movement in a human with quadriplegia. Nature 533, 247–250 (2016).

    CAS  Google Scholar 

  3. 3

    Barrese, J. C. et al. Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates. J. Neural Engineer. 10, 066014 (2013).

    Google Scholar 

  4. 4

    Barrese, J. C., Aceros, J. & Donoghue, J. P. Scanning electron microscopy of chronically implanted intracortical microelectrode arrays in non-human primates. J. Neural Engineer. 13, 026003 (2016).

    Google Scholar 

  5. 5

    Sanchez, J. C., Alba, N., Batich, C. & Carney, P. R. Structural modifications in chronic microwire electrodes for cortical neuroprosthetics: a case study. IEEE Trans. Neural Syst. Rehabil. Eng. 14, 217–212 (2006).

    Google Scholar 

  6. 6

    Sankar, V. et al. Electrode impedance analysis of chronic tungsten microwire neural implants: understanding abiotic vs. biotic contributions. Front. Neuroeng. 7, http://dx.doi.org/10.3389/fneng.2014.00013 (2014).

  7. 7

    Jorfi, M., Skousen, J. L., Weder, C. & Capadona, J. R. Progress towards biocompatible intracortical microelectrodes for neural interfacing applications. J. Neural Eng. 12, 011001 (2015).

    Google Scholar 

  8. 8

    Jeong, J.-W. et al. Soft materials in neuroengineering for hard problems in neuroscience. Neuron 86, 175–186 (2015).

    CAS  Google Scholar 

  9. 9

    Lee, J. H., Kim, H., Kim, J. H. & Lee, S.-H. Soft implantable microelectrodes for future medicine: prosthetics, neural signal recording and neuromodulation. Lab Chip 16, 959–976 (2016).

    CAS  Google Scholar 

  10. 10

    Prodanov, D. & Delbeke, J. Mechanical and biological interactions of implants with the brain and their impact on implant design. Front. Neurosci. 10, http://dx.doi.org/10.3389/fnins.2016.00011 (2016).

  11. 11

    Jones, E. G. & Rakic, P. Radial columns in cortical architecture: it is the composition that counts. Cerebral Cortex 20, 2261–2264 (1984).

    Google Scholar 

  12. 12

    Bailey, S. A., Zidell, R. H. & Perry, R. W. Relationships between organ weight and body/brain weight in the rat: what is the best analytical endpoint? Toxicol. Pathol. 32, 448–466 (2004).

    Google Scholar 

  13. 13

    Koo, B. B. et al. Age-related effects on cortical thickness patterns of the rhesus monkey brain. Neurobiol. Aging 33, 200.e23–200.e31 (2012).

    Google Scholar 

  14. 14

    Herculano-Houzel, S. in In The Light of Evolution: Volume VI: Brain and Behavior Ch. 8 (eds Striedter, G. F., Avise, J. C. & Ayala, F. J. ) 127–148 (National Academies Press, 2013).

    Google Scholar 

  15. 15

    Tallinen, T. et al. On the growth and form of cortical convolutions. Nat. Phys. 12, 588–593 (2016).

    CAS  Google Scholar 

  16. 16

    Wagshul, M. E., Eide, P. K. & Madsen, J. R. The pulsating brain: a review of experimental and clinical studies of intracranial pulsatility. Fluids Barriers CNS 8, http://dx.doi.org/10.1186/2045-8118-8-5 (2011).

  17. 17

    Harrison, D. E., Cailliet, R., Harrison, D. D., Troyanovich, S. J. & Harrison, S. O. A review of biomechanics of the central nervous system — Part I: spinal canal deformations resulting from changes in posture. J. Manipulative Physiol. Ther. 22, 227–234 (1999).

    CAS  Google Scholar 

  18. 18

    Bashkatov, A. N. et al. Glucose and mannitol doffusion in human dura mater. Biophys. J. 85, 3310–3318 (2003).

    CAS  Google Scholar 

  19. 19

    Galasha, F. O. et al. A new type of recording chamber with an easy-toexchange microdrive array for chronic recordings in macaque monkeys. J. Neurophysiol. 105, 3092–3105 (2011).

    Google Scholar 

  20. 20

    Minev, I. R. et al. Biomaterials. Electronic dura mater for long-term multimodal neural interfaces. Science 347, 159–163 (2015).

    CAS  Google Scholar 

  21. 21

    Nicholson, K. J. & Winkelstein, B. A. in Neural Tissue Biomechanics Ch. 10 (ed. Bilston, L. E. ) 203–229 (Springer, 2011).

    Google Scholar 

  22. 22

    Polikov, V. S., Tresco, P. A. & Reichert, W. M. Response of brain tissue to chronically implanted neural electrodes. J. Neurosci. Methods 148, 1–18 (2005).

    Google Scholar 

  23. 23

    Franze, K., Janmey, P. A. & Guck, J. Mechanics in neuronal development and repair. Annu. Rev. Biomed. Eng. 15, 227–251 (2013).

    CAS  Google Scholar 

  24. 24

    Ulrich, T. & Kumar, S. in Mechanobiology Handbook 391–411 (CRC Press, 2011).

    Google Scholar 

  25. 25

    Bernick, K. B., Prevost, T. P., Suresh, S. & Socrate, S. Biomechanics of single cortical neurons. Acta Biomater. 7, 1210–1219 (2011).

    Google Scholar 

  26. 26

    Lu, Y.-B. et al. Viscoelastic properties of individual glial cells and neurons in the CNS. Proc. Natl Acad. Sci. USA 103, 17759–17764 (2006).

    CAS  Google Scholar 

  27. 27

    Zou, S. et al. Force spectroscopy measurements show that cortical neurons exposed to excitotoxic agonists stiffen before showing evidence of bleb damage. PLoS One 8, e73499 (2013).

    CAS  Google Scholar 

  28. 28

    Grevesse, T., Dabiri, B. E., Parker, K. K. & Gabriele, S. Opposite rheological properties of neuronal microcompartments predict axonal vulnerability in brain injury. Sci. Rep. 5, 9475 (2015).

    CAS  Google Scholar 

  29. 29

    Bray, D. Mechanical tension produced by nerve cells in tissue culture. J. Cell Sci. 37, 391–410 (1979).

    CAS  Google Scholar 

  30. 30

    Dennerll, T. J., Joshi, H. C., Steel, V. L., Buxbaum, R. E. & Heidemann, S. R. Tension and compression in the cytoskeleton of PC-12 neurites. II: Quantitative measurements. J. Cell Biol. 107, 665–674 (1988).

    CAS  Google Scholar 

  31. 31

    Dennerll, T. J., Lamoureux, P., Buxbaum, R. E. & Heidemann, S. R. The cytomechanics of axonal elongation and retraction. J. Cell Biol. 109, 3073–3083 (1989).

    CAS  Google Scholar 

  32. 32

    Bernal, R., Pullarkat, P. A. & Melo, F. Mechanical properties of axons. Phys. Rev. Lett. 99, 018301 (2007).

    Google Scholar 

  33. 33

    MacDonald, R. B. et al. Müller glia provide essential tensile strength to the developing retina. J. Cell Biol. 210, 1075–1083 (2015).

    CAS  Google Scholar 

  34. 34

    O'Toole, M., Lamoureux, P. & Miller, K. E. A physical model of axonal elongation: force, viscosity, and adhesions govern the mode of outgrowth. Biophys. J. 94, 2610–2620 (2008).

    CAS  Google Scholar 

  35. 35

    Jagielska, A. et al. Mechanical environment modulates biological properties of oligodendrocyte progenitor cells. Stem Cells Dev. 21, 2905–2914 (2012).

    CAS  Google Scholar 

  36. 36

    Lu, Y.-B. et al. Reactive glial cells: increased stiffness correlates with increased intermediate filament expression. FASEB J. 25, 624–631 (2011).

    CAS  Google Scholar 

  37. 37

    Vergara, D. et al. Biomechanical and proteomic analysis of INF- β-treated astrocytes. Nanotechnology 20, 455106 (2009).

    Google Scholar 

  38. 38

    Miller, W. J. et al. Mechanically induced reactive gliosis causes ATP-mediated alterations in astrocyte stiffness. J. Neurotrauma 26, 789–797 (2009).

    Google Scholar 

  39. 39

    Novak, U. & Kaye, A. H. Extracellular matrix and the brain: components and function. J. Clin. Neurosci. 7, 280–290 (2000).

    CAS  Google Scholar 

  40. 40

    Galtrey, C. M., Kwok, J. C. F., Carulli, D., Rhodes, K. E. & Fawcett, J. W. Distribution and synthesis of extracellular matrix proteoglycans, hyaluronan, link proteins and tenascin-R in the rat spinal cord. Eur. J. Neurosci. 27, 1373–1390 (2008).

    Google Scholar 

  41. 41

    Barros, C. S., Franco, S. J. & Müller, U. Extracellular matrix: functions in the nervous system. Cold Spring Harb. Perspect. Biol. 3, a005108 (2011).

    Google Scholar 

  42. 42

    Gaudet, A. D. & Popovich, P. G. Extracellular matrix regulation of inflammation in the healthy and injured spinal cord. Exp. Neurol. 258, 24–34 (2014).

    CAS  Google Scholar 

  43. 43

    Swift, J. et al. Nuclear lamin-A scales with tissue stiffness and enhances matrix-directed differentiation. Science 341, 1240104 (2013).

    Google Scholar 

  44. 44

    Syková, E. & Nicholson, C. Diffusion in brain extracellular space. Physiol. Rev. 88, 1277–1340 (2008).

    Google Scholar 

  45. 45

    Hemphill, M. A., Dauth, S., Yu, C. J., Dabiri, B. E. & Parker, K. K. Traumatic brain injury and the neuronal microenvironment: a potential role for neuropathological mechanotransduction. Neuron 85, 1177–1192 (2015).

    CAS  Google Scholar 

  46. 46

    Pogoda, K. et al. Compression stiffening of brain and its effect on mechanosensing by glioma cells. New J. Phys. 16, 075002 (2014).

    Google Scholar 

  47. 47

    Javid, S., Rezaei, A. & Karami, G. A micromechanical procedure for viscoelastic characterization of the axons and ECM of the brainstem. J. Mechan. Behav. Biomed. Mater. 30, 290–299 (2014).

    Google Scholar 

  48. 48

    Cheng, S., Clarke, E. C. & Bilston, L. E. Rheological properties of the tissues of the central nervous system: a review. Med. Eng. Phys. 30, 1318–1337 (2008).

    Google Scholar 

  49. 49

    Goriely, A. et al. Mechanics of the brain: perspectives, challenges, and opportunities. Biomech. Model. Mechanobiol. 14, 931–965 (2015).

    Google Scholar 

  50. 50

    Fallenstein, G. T., Hulce, V. D. & Melvin, J. W. Dynamic mechanical properties of human brain tissue. J. Biomech. 2, 217–226 (1969).

    CAS  Google Scholar 

  51. 51

    Ommaya, A. K. Mechanical properties of tissues of the nervous system. J. Biomech. 1, 137–138 (1968).

    Google Scholar 

  52. 52

    Chatelin, S., Constantinesco, A. & Willinger, R. Fifty years of brain tissue mechanical testing: from in vitro to in vivo investigations. Biorheology 47, 255–276 (2010).

    Google Scholar 

  53. 53

    Koser, D. E., Moeendarbary, E., Hanne, J., Kuerten, S. & Franze, K. CNS cell distribution and axon orientation determine local spinal cord mechanical properties. Biophys. J. 108, 2137–2147 (2015).

    CAS  Google Scholar 

  54. 54

    Franze, K. et al. Spatial mapping of the mechanical properties of the living retina using scanning force microscopy. Soft Matter 7, 3147–3154 (2011).

    CAS  Google Scholar 

  55. 55

    Budday, S. et al. Mechanical properties of gray and white matter brain tissue by indentation. J. Mechan. Behav. Biomed. Mater. 46, 318–330 (2015).

    Google Scholar 

  56. 56

    Elkin, B. S., Azeloglu, E. U., Costa, K. D. & Morrison, B. Mechanical heterogeneity of the rat hippocampus measured by atomic force microscope indentation. J. Neurotrauma 24, 812–822 (2007).

    Google Scholar 

  57. 57

    Elkin, B. S., Ilankovan, A. I. & Morrison, B. A detailed viscoelastic characterization of the p17 and adult rat brain. J. Neurotrauma 28, 2235–2244 (2011).

    Google Scholar 

  58. 58

    MacManus, D. B., Pierrat, B., Murphy, J. G. & Gilchrist, M. D. Dynamic mechanical properties of murine brain tissue using micro-indentation. J. Biomech. 48, 3213–3218 (2015).

    CAS  Google Scholar 

  59. 59

    Prange, M. T. & Margulies, S. S. Regional, directional, and age-dependent properties of the brain undergoing large deformation. J. Biomech. Eng. 124, 244–252 (2002).

    Google Scholar 

  60. 60

    Christ, A. F. et al. Mechanical difference between white and gray matter in the rat cerebellum measured by scanning force microscopy. J. Biomech. 43, 2986–2992 (2010).

    Google Scholar 

  61. 61

    Ichihara, K., Taguchi, T. & Shimada, Y. Gray matter of the bovine cervical spinal cord is mechanically more rigid and fragile than the white matter. J. Neurotrauma 18, 361–367 (2001).

    CAS  Google Scholar 

  62. 62

    Shreiber, D. I., Hao, H. & Elias, R. A. Probing the influence of myelin and glia on the tensile properties of the spinal cord. Biomech. Model. Mechanobiol. 8, 311–321 (2009).

    Google Scholar 

  63. 63

    Schregel, K. K. et al. Demyelination reduces brain parenchymal stiffness quantified in vivo by magnetic resonance elastography. Proc. Natl Acad. Sci. USA 109, 6650–6655 (2012).

    CAS  Google Scholar 

  64. 64

    Elkin, B. S., Ilankovan, A. & Morrison, B. Age-dependent regional mechanical properties of the rat hippocampus and cortex. J. Biomech. Eng. 132, 011010 (2010).

    Google Scholar 

  65. 65

    Sack, I. et al. The impact of aging and gender on brain viscoelasticity. Neuroimage 46, 652–657 (2009).

    Google Scholar 

  66. 66

    de Rooij, R. & Kuhl, E. Constitutive modeling of brain tissue: current perspectives. Appl. Mech. Rev. 68, 010801–010823 (2016).

    Google Scholar 

  67. 67

    McKee, C. T., Last, J. A. & Russell, P. Indentation versus tensile measurements of Young's modulus for soft biological tissues. Tissue Eng. Part B Rev. 17, 155–164 (2011).

    Google Scholar 

  68. 68

    Sridharan, A., Rajan, S. D. & Muthuswamy, J. Long-term changes in the material properties of brain tissue at the implant–tissue interface. J. Neural Eng. 10, 066001 (2013).

    Google Scholar 

  69. 69

    Saxena, T., Gilbert, J., Stelzner, D. & Hasenwinkel, J. Mechanical characterization of the injured spinal cord after lateral spinal hemisection injury in the rat. J. Neurotrauma 29, 1747–1757 (2012).

    Google Scholar 

  70. 70

    Estes, M. S. & McElhaney, J. H. Response of brain tissue of compressive loading. Mech. Eng. 92, 58–61 (1970).

    Google Scholar 

  71. 71

    Goldstein, S. R. & Salcman, M. Mechanical factors in the design of chronic recording intracortical microelectrodes. IEEE Trans. Biomed. Eng. 20, 260–269 (1973).

    CAS  Google Scholar 

  72. 72

    Chew, D. J. et al. A microchannel neuroprosthesis for bladder control after spinal cord injury in rat. Sci. Transl. Med. 5, 210ra155 (2013).

    Google Scholar 

  73. 73

    Sharp, A. A., Ortega, A. M., Restrepo, D., Curran-Everett, D. & Gall, K. In vivo penetration mechanics and mechanical properties of mouse brain tissue at micrometer scales. IEEE Trans.Biomed. Eng. 56, 45–53 (2009).

    Google Scholar 

  74. 74

    Hyunjung, L., Ravi, V. B., Wei, S. & Marc, E. L. Biomechanical analysis of silicon microelectrode-induced strain in the brain. J. Neural Engineer. 2, 81–89 (2005).

    Google Scholar 

  75. 75

    Suo, Z., Ma, W. Y., Gleskova, H. & Wagner, S. Mechanics of rollable and foldable film-on-foil electronics. Appl. Phys. Lett. 74, 1177–1179 (1999).

    CAS  Google Scholar 

  76. 76

    Kim, D.-H. et al. Dissolvable films of silk fibroin for ultrathin conformable biointegrated electronics. Nat. Mater. 9, 511–517 (2010).

    CAS  Google Scholar 

  77. 77

    Matsuo, T. et al. Intrasulcal electrocorticography in macaque monkeys with minimally invasive neurosurgical protocols. Front. Syst. Neurosci. 5, 34 (2011).

    Google Scholar 

  78. 78

    Guo, C. F. Sun, T. Liu, Q. Suo, Z. & Ren, Z. Highly stretchable and transparent nanomesh electrodes made by grain boundary lithography. Nat. Commun. 5, 3121 (2014).

    Google Scholar 

  79. 79

    Fan, J. A. et al. Fractal design concepts for stretchable electronics. Nat. Commun. 5, 3266 (2014).

    Google Scholar 

  80. 80

    Xu, L. et al. 3D multifunctional integumentary membranes for spatiotemporal cardiac measurements and stimulation across the entire epicardium. Nat. Commun. 5, 3329 (2014).

    Google Scholar 

  81. 81

    Minev, I. R., Wenger, N., Courtine, G. & Lacour, S. P. Research update: platinum-elastomer mesocomposite as neural electrode coating. APL Mater. 3, 014701 (2015).

    Google Scholar 

  82. 82

    Kang, S.-K. et al. Bioresorbable silicon electronic sensors for the brain. Nature 530, 71–76 (2016).

    CAS  Google Scholar 

  83. 83

    Yu, K. J., Kuzum, D., Hwang, S. W., Kim, B. H. & Juul, H. Bioresorbable silicon electronics for transient spatiotemporal mapping of electrical activity from the cerebral cortex. Nat. Mater. http://dx.doi.org/10.1038/nmat4624 (2016).

  84. 84

    Edell, D. J., Toi, V. V., McNeil, V. M. & Clark, L. D. Factors influencing the biocompatibility of insertable silicon microshafts in cerebral cortex. IEEE Trans. Biomed. Eng. 39, 635–643 (1992).

    CAS  Google Scholar 

  85. 85

    Bjornsson, C. S. et al. Effects of insertion conditions on tissue strain and vascular damage during neuroprosthetic device insertion. J. Neural Engineer. 3, 196–207 (2006).

    CAS  Google Scholar 

  86. 86

    Dryg, I. D. et al. Magnetically inserted neural electrodes: tissue response and functional lifetime. IEEE Trans. Neural Syst. Rehab. 23, 562–571 (2015).

    Google Scholar 

  87. 87

    Kim, T. et al. Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science 12, 211–216 (2013).

    Google Scholar 

  88. 88

    Lee, K. et al. Polyimide based neural implants with stiffness improvement. Sens. Actuators B 102, 67–72 (2004).

    CAS  Google Scholar 

  89. 89

    Ware, T. et al. Three-dimensional flexible electronics enabled by shape memory polymer substrates for responsive neural interfaces. Macromol. Mater. Eng. 297, 1193–1202 (2012).

    CAS  Google Scholar 

  90. 90

    Capadona, J. et al. A versatile approach for the processing of polymer nanocomposites with self-assembled nanofibre templates. Nat. Nanotechnol. 2, 765–769 (2007).

    CAS  Google Scholar 

  91. 91

    Sridharan, A., Nguyen, J. K., Capadona, J. R. & Muthuswamy, J. Compliant intracortical implants reduce strains and strain rates in brain tissue in vivo. J. Neural Eng. 12, 036002 (2015).

    Google Scholar 

  92. 92

    Nguyen, J. K. et al. Mechanically-compliant intracortical implants reduce the neuroinflammatory response. J. Neural Eng. 11, 056014 (2014).

    Google Scholar 

  93. 93

    Karnaushenko, D. et al. Biomimetic microelectronics for regenerative neuronal cuff implants. Adv. Mater. 27, 6797–6805 (2015).

    CAS  Google Scholar 

  94. 94

    Takashi, D. et al. Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces. Nat. Mater. 11, 1065–1073 (2012).

    Google Scholar 

  95. 95

    Canales, A. et al. Multifunctional fibers for simultaneous optical, electrical and chemical interrogation of neural circuits in vivo. Nat. Biotechnol. 33, 277–284 (2015).

    CAS  Google Scholar 

  96. 96

    Lu, C. et al. Polymer fiber probes enable optical control of spinal cord and muscle function in vivo. Adv. Funct. Mater. 24, 6594–6600 (2014).

    CAS  Google Scholar 

  97. 97

    Liu, J. et al. Syringe-injectable electronics. Nat. Nanotechnol. 10, 629636 (2015).

    Google Scholar 

  98. 98

    Xie, C. et al. Three-dimensional macroporous nanoelectronic networks as minimally invasive brain probes. Nat. Mater. 14, 1286–1292 (2015).

    CAS  Google Scholar 

  99. 99

    Thomas, J. et al. Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity. Nat. Biotechnol. 34, 320–327 (2016).

    Google Scholar 

  100. 100

    Discher, D. E., Janmey, P. & Wang, Y. L. Cells feel and respond to the stiffness of their substrate. Science 310, 1139–1143 (2005).

    CAS  Google Scholar 

  101. 101

    Georges, P. C., Miller, W. J., Meaney, D. F., Sawyer, E. S. & Janmey, P. A. Matrices with compliance comparable to that of brain tissue select neuronal over glial growth in mixed cortical cultures. Biophys. J. 90, 3012–3018 (2006).

    CAS  Google Scholar 

  102. 102

    Moshayedi, P. et al. The relationship between glial cell mechanosensitivity and foreign body reactions in the central nervous system. Biomaterials 35, 3919–3925 (2014).

    CAS  Google Scholar 

  103. 103

    Bollmann, L. et al. Microglia mechanics: immune activation alters traction forces and durotaxis. Front. Cell. Neurosci. 9, 363 (2015).

    Google Scholar 

  104. 104

    Franze, K. & Guck, J. The biophysics of neuronal growth. Rep. Progress Phys. 73, 094601 (2010).

    Google Scholar 

  105. 105

    Janmey, P. A. & Miller, R. T. Mechanisms of mechanical signaling in development and disease. J. Cell Sci. 124, 9–18 (2011).

    CAS  Google Scholar 

  106. 106

    McWhorter, F. Y., Davis, C. T. & Liu, W. F. Physical and mechanical regulation of macrophage phenotype and function. Cell. Mol. Life Sci. 72, 1303–1316 (2015).

    CAS  Google Scholar 

  107. 107

    Kozai, T. D. Y., Jaquins-Gerstl, A. S., Vazquez, A. L., Michael, A. C. & Cui, X. T. Dexamethasone retrodialysis attenuates microglial response to implanted probes in vivo. Biomaterials 87, 157–169 (2016).

    CAS  Google Scholar 

  108. 108

    Chikar, J. A. et al. The use of a dual PEDOT and RGD-functionalized alginate hydrogel coating to provide sustained drug delivery and improved cochlear implant function. Biomaterials 33, 1982–1990 (2012).

    CAS  Google Scholar 

  109. 109

    Aregueta-Robles, U. A. Woolley, A. J. Poole-Warren, L. A. Lovell, N. H. & Green, R. A. Organic electrode coatings for next-generation neural interfaces. Front. Neuroeng. 7, 15 (2014).

    Google Scholar 

  110. 110

    Khodagholy, D. et al. In vivo recordings of brain activity using organic transistors. Nat. Commun. 4, 1575 (2013).

    Google Scholar 

  111. 111

    Rivnay, J., Owens, R. s. n. M. & Malliaras, G. G. The rise of organic bioelectronics. Chem. Mater. 26, 679–685 (2014).

    CAS  Google Scholar 

  112. 112

    Williamson, A. et al. Controlling epileptiform activity with organic electronic ion pumps. Adv. Mater. 27, 3138–3144 (2015).

    CAS  Google Scholar 

  113. 113

    Jonsson, A. et al. Therapy using implanted organic bioelectronics. Sci. Adv. 1, e1500039 (2015).

    Google Scholar 

  114. 114

    Rylie, A. Green, Baek, Sungchul Poole-Warren, L. A. & Martens, P. J. Conducting polymer-hydrogels for medical electrode applications. Sci. Tech. Adv. Mater. 11, 014107 (2010).

    Google Scholar 

  115. 115

    Montgomery, K. L., Iyer, S. M., Christensen, A. J., Deisseroth, K. & Delp, S. L. Beyond the brain: optogenetic control in the spinal cord and peripheral nervous system. Sci. Transl. Med. 8, 337rv5 (2016).

    Google Scholar 

  116. 116

    Grosenick, L., Marshel, J. H. & Deisseroth, K. Closed-loop and activity-guided optogenetic control. Neuron 86, 106–139 (2015).

    CAS  Google Scholar 

  117. 117

    Jeong, J.-W. et al. Wireless optofluidic systems for programmable in vivo pharmacology and optogenetics. Cell 162, 1–13 (2015).

    Google Scholar 

  118. 118

    Courtine, G. et al. Transformation of nonfunctional spinal circuits into functional states after the loss of brain input. Nat. Neurosci. 12, 1333–1342 (2009).

    CAS  Google Scholar 

  119. 119

    Wenger, N. et al. Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury. Nat. Med. 22, 138–145 (2016).

    CAS  Google Scholar 

  120. 120

    McIntyre, C. C., Chaturvedi, A., Shamir, R. R. & Lempka, S. F. Engineering the next generation of clinical deep brain stimulation technology. Brain Stimul. 8, 21–26 (2015).

    Google Scholar 

  121. 121

    Courtine, G. & Bloch, J. Defining ecological strategies in neuroprosthetics. Neuron 86, 29–33 (2015).

    CAS  Google Scholar 

  122. 122

    Borton, D., Micera, S., Millan, J. d. R. & Courtine, G. Personalized neuroprosthetics. Sci. Transl. Med. 5, 210rv212 (2013).

    Google Scholar 

  123. 123

    Branner, A. & Normann, R. A. A multielectrode array for intrafascicular recording and stimulation in sciatic nerve of cats. Brain Res. Bull. 51, 293–306 (2000).

    CAS  Google Scholar 

  124. 124

    Rubehn, B., Bosman, C., Oostenveld, R., Fries, P. & Stiegltiz, T. S. A. MEMS-based flexible multichannel ECoG-electrode array. J. Neural Eng. 6, 036003 (2009).

    Google Scholar 

  125. 125

    Stieglitz, T., Beutel, H., Schuettler, M. & Meyer, J. U. Micromachined, polyimide-based devices for flexible neural interfaces. Biomed. Microdevices 2, 283–294 (2000).

    Google Scholar 

  126. 126

    Towne, C., Montgomery, K. L., Iyer, S. M., Deisseroth, K. & Delp, S. L. Optogenetic control of targeted peripheral axons in freely moving animals. PLoS One 8, e72691 (2013).

    CAS  Google Scholar 

  127. 127

    Boretius, T. et al. A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. Biosens. Bioelectron. 26, 62–69 (2010).

    CAS  Google Scholar 

  128. 128

    Raspopovic, S. et al. Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci. Transl. Med. 6, 222ra219 (2014).

    Google Scholar 

  129. 129

    Musick, K. M. et al. Chronic multichannel neural recordings from soft regenerative microchannel electrodes during gait. Sci. Rep. 5, 14363 (2015).

    CAS  Google Scholar 

Download references

Acknowledgements

Financial support was provided by the Bertarelli Foundation (SPL), Starting Grants from the European Research Council (ERC 259419 ESKIN (SPL), ERC 261247, Walk Again (GC)), the European Community's Seventh Framework Program (CP-IP 258654, NeuWALK (GC)) and the Alexander-von-Humboldt Foundation (Alexander-von-Humboldt Professorship (JG)). The authors thank A. Goriely, K. Franze, P. Janmey, K. Van Vliet, J. Fawcett, R. Franklin, M. Reimer and J. Bloch for useful discussions.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Stéphanie P. Lacour.

Ethics declarations

Competing interests

The authors declare no competing interests.

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lacour, S., Courtine, G. & Guck, J. Materials and technologies for soft implantable neuroprostheses. Nat Rev Mater 1, 16063 (2016). https://doi.org/10.1038/natrevmats.2016.63

Download citation

Further reading