Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Neural recording and modulation technologies

Nature Reviews Materials volume 2, Article number: 16093 (2017) Cite this article

Subjects

Abstract

In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Clinical impact of the diseases and injuries of the nervous system and physiological guidelines for designing neural interfaces.
Figure 2: Historical view of neural interface research.
Figure 3: Mechanisms of neural-probe failure.
Figure 4: Examples of approaches intended to overcome the foreign-body response and increase the resolution of neural interfaces.
Figure 5: Probes for bidirectional communication with neural circuits.
Figure 6: Tissue penetration by optical, ultrasonic and magnetic signals.
Figure 7: Micro- and nanoprobes for intracellular recordings.
Figure 8: Nanomaterials as local transducers of external stimuli.

References

  1. Dorsey, E. R. et al. Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology 68, 384–386 (2007).

    Article  CAS  Google Scholar 

  2. Adelman, G., Rane, S. G. & Villa, K. F. The cost burden of multiple sclerosis in the United States: a systematic review of the literature. J. Med. Econ. 16, 639–647 (2013).

    Article  Google Scholar 

  3. Greenberg, P. E. et al. The economic burden of depression in the United States: how did it change between 1990 and 2000? J. Clin. Psychiatry 64, 1465–1475 (2003).

    Google Scholar 

  4. Mathers, C. D. & Loncar, D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 3, e442 (2006).

    Article  Google Scholar 

  5. Tracey, K. J. Reflex control of immunity. Nat. Rev. Immunol. 9, 418–428 (2009).

    Article  CAS  Google Scholar 

  6. Kandel, E. R., Schwartz, J. H. & Jessell, T. M. Principles of Neural Science 4th edn (McGraw-Hill Medical, 2000).

    Google Scholar 

  7. Azevedo, F. A. et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J. Comp. Neurol. 513, 532–541 (2009).

    Article  Google Scholar 

  8. Haydon, P. G. Glia: listening and talking to the synapse. Nat. Rev. Neurosci. 2, 185–193 (2001).

    Article  CAS  Google Scholar 

  9. Barres, B. A. The mystery and magic of glia: a perspective on their roles in health and disease. Neuron 60, 430–440 (2008).

    Article  CAS  Google Scholar 

  10. Pakkenberg, B. et al. Aging and the human neocortex. Exp. Gerontol. 38, 95–99 (2003).

    Article  Google Scholar 

  11. Wemmie, J. A., Taugher, R. J. & Kreple, C. J. Acid-sensing ion channels in pain and disease. Nat. Rev. Neurosci. 14, 461–471 (2013).

    Article  CAS  Google Scholar 

  12. Patapoutian, A. et al. ThermoTRP channels and beyond: mechanisms of temperature sensation. Nat. Rev. Neurosci. 4, 529–539 (2003).

    Article  CAS  Google Scholar 

  13. Jordt, S. E., McKemy, D. D. & Julius, D. Lessons from peppers and peppermint: the molecular logic of thermosensation. Curr. Opin. Neurobiol. 13, 487–492 (2003).

    Article  CAS  Google Scholar 

  14. Delmas, P., Hao, J. & Rodat-Despoix, L. Molecular mechanisms of mechanotransduction in mammalian sensory neurons. Nat. Rev. Neurosci. 12, 139–153 (2011).

    Article  CAS  Google Scholar 

  15. Strumwasser, F. Long-term recording from single neurons in brain of unrestrained mammals. Science 127, 469–470 (1958). This article is the first report of a chronic recording of isolated action potentials in the brain of a freely moving mammal (a ground squirrel).

    Article  CAS  Google Scholar 

  16. Sakmann, B. & Neher, E. Patch clamp techniques for studying ionic channels in excitable membranes. Annu. Rev. Physiol. 46, 455–472 (1984).

    Article  CAS  Google Scholar 

  17. Campbell, P. K., Jones, K. E., Huber, R. J., Horch, K. W. & Normann, R. A. A silicon-based, three-dimensional neural interface: manufacturing processes for an intracortical electrode array. IEEE Trans. Biomed. Eng. 38, 758–768 (1991). This article presents an early conceptual demonstration of the Utah array.

    Article  CAS  Google Scholar 

  18. Drake, K. L., Wise, K. D., Farraye, J., Anderson, D. J. & BeMent, S. L. Performance of planar multisite microprobes in recording extracellular single-unit intracortical activity. IEEE Trans. Biomed. Eng. 35, 719–732 (1988). In this article, Michigan probes were applied to record neural activity.

    Article  CAS  Google Scholar 

  19. McNaughton, B. L., O'Keefe, J. & Barnes, C. A. The stereotrode: a new technique for simultaneous isolation of several single units in the central nervous system from multiple unit records. J. Neurosci. Methods 8, 391–397 (1983).

    Article  CAS  Google Scholar 

  20. Gray, C. M., Maldonado, P. E., Wilson, M. & McNaughton, B. Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. J. Neurosci. Methods 63, 43–54 (1995). Combining four microwires into a tetrode arrangement was shown to yield superior identification of isolated action potentials.

    Article  CAS  Google Scholar 

  21. Fee, M. S. & Leonardo, A. Miniature motorized microdrive and commutator system for chronic neural recording in small animals. J. Neurosci. Methods 112, 83–84 (2001).

    Article  CAS  Google Scholar 

  22. Herry, C. et al. Switching on and off fear by distinct neuronal circuits. Nature 454, 600–606 (2008).

    Article  CAS  Google Scholar 

  23. Wilson, M. A. & McNaughton, B. L. Reactivation of hippocampal ensemble memories during sleep. Science 265, 676–679 (1994).

    Article  CAS  Google Scholar 

  24. Bartels, J. et al. Neurotrophic electrode: method of assembly and implantation into human motor speech cortex. J. Neurosci. Methods 174, 168–176 (2008).

    Article  Google Scholar 

  25. Hochberg, L. R. et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442, 164–171 (2006). This article demonstrates the use of neural signals from the brain of a patient with tetraplegia to control a prosthetic arm.

    Article  CAS  Google Scholar 

  26. Buzsaki, G. et al. High-frequency network oscillation in the hippocampus. Science 256, 1025–1027 (1992).

    Article  CAS  Google Scholar 

  27. Wise, K. D. Silicon microsystems for neuroscience and neural prostheses. IEEE Eng. Med. Biol. Mag. 24, 22–29 (2005).

    Article  Google Scholar 

  28. Yazicioglu, F. et al. Ultra-high-density in vivo neural probes. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2032–2035 (2014).

  29. Scholten, K. & Meng, E. Materials for microfabricated implantable devices: a review. Lab Chip 15, 4256–4272 (2015).

    Article  CAS  Google Scholar 

  30. Nicolelis, M. A. L. Brain–machine interfaces to restore motor function and probe neural circuits. Nat. Rev. Neurosci. 4, 417–422 (2003).

    Article  CAS  Google Scholar 

  31. Donoghue, J. P. Connecting cortex to machines: recent advances in brain interfaces. Nat. Neurosci. 5, 1085–1088 (2002).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  33. Ward, M. P., Rajdev, P., Ellison, C. & Irazoqui, P. P. Toward a comparison of microelectrodes for acute and chronic recordings. Brain Res. 1282, 183–200 (2009).

    Article  CAS  Google Scholar 

  34. 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). A comprehensive review article that summarized the biological failure modes seen in chronically implanted neural probes.

    Article  Google Scholar 

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

    Article  Google Scholar 

  36. Kozai, T. D. Y. et al. Brain tissue responses to neural implants impact signal sensitivity and intervention strategies. ACS Chem. Neurosci. 6, 48–67 (2015).

    Article  CAS  Google Scholar 

  37. Lee, H., Bellamkonda, R. V., Sun, W. & Levenston, M. E. Biomechanical analysis of silicon microelectrode-induced strain in the brain. J. Neural Eng. 2, 81–89 (2005).

    Article  Google Scholar 

  38. Lind, G., Linsmeier, C. E. & Schouenborg, J. The density difference between tissue and neural probes is a key factor for glial scarring. Sci. Rep. 3, 2942 (2013).

    Article  Google Scholar 

  39. Szarowski, D. H. et al. Brain responses to micro-machined silicon devices. Brain Res. 983, 23–35 (2003).

    Article  CAS  Google Scholar 

  40. Saxena, T. et al. The impact of chronic blood–brain barrier breach on intracortical electrode function. Biomaterials 34, 4703–4713 (2013).

    Article  CAS  Google Scholar 

  41. Kotzar, G. et al. Evaluation of MEMS materials of construction for implantable medical devices. Biomaterials 23, 2737–2750 (2002).

    Article  CAS  Google Scholar 

  42. Chapman, C. A. R. et al. Nanoporous gold as a neural interface coating: effects of topography, surface chemistry, and feature size. ACS Appl. Mater. Interfaces 7, 7093–7100 (2015).

    Article  CAS  Google Scholar 

  43. Zhong, Y. & Bellamkonda, R. V. Dexamethasone-coated neural probes elicit attenuated inflammatory response and neuronal loss compared to uncoated neural probes. Brain Res. 1148, 15–27 (2007).

    Article  CAS  Google Scholar 

  44. Azemi, E. et al. Surface immobilization of neural adhesion molecule L1 for improving the biocompatibility of chronic neural probes: in vitro characterization. Acta Biomater. 4, 1208–1217 (2008).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  46. Aregueta-Robles, U. A. et al. Organic electrode coatings for next-generation neural interfaces. Front. Neuroeng. 7, 15 (2014).

    Article  CAS  Google Scholar 

  47. Kim, D. H., Wiler, J. A., Anderson, D. J., Kipke, D. R. & Martin, D. C. Conducting polymers on hydrogel-coated neural electrode provide sensitive neural recordings in auditory cortex. Acta Biomater. 6, 57–62 (2010).

    Article  CAS  Google Scholar 

  48. Green, R. A., Lovell, N. H. & Poole-Warren, L. A. Cell attachment functionality of bioactive conducting polymers for neural interfaces. Biomaterials 30, 3637–3644 (2009).

    Article  CAS  Google Scholar 

  49. Viventi, J. et al. Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nat. Neurosci. 14, 1599–1605 (2011).

    Article  CAS  Google Scholar 

  50. Kim, B. J. et al. 3D Parylene sheath neural probe for chronic recordings. J. Neural Eng. 10, 045002 (2013).

    Article  CAS  Google Scholar 

  51. Kuo, J. T. W. et al. Novel flexible Parylene neural probe with 3D sheath structure for enhancing tissue integration. Lab Chip 13, 554–561 (2012).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  53. Delivopoulos, E. et al. Concurrent recordings of bladder afferents from multiple nerves using a microfabricated PDMS microchannel electrode array. Lab Chip 12, 2540–2551 (2012).

    Article  CAS  Google Scholar 

  54. Lacour, S. P. et al. Flexible and stretchable micro-electrodes for in vitro and in vivo neural interfaces. Med. Biol. Eng. Comput. 48, 945–954 (2010).

    Article  Google Scholar 

  55. Srinivasan, A. et al. Microchannel-based regenerative scaffold for chronic peripheral nerve interfacing in amputees. Biomaterials 41, 151–165 (2015).

    Article  CAS  Google Scholar 

  56. FitzGerald, J. J. et al. A regenerative microchannel neural interface for recording from and stimulating peripheral axons in vivo. J. Neural Eng. 9, 016010 (2012).

    Article  Google Scholar 

  57. Ware, T. et al. Fabrication of responsive, softening neural interfaces. Adv. Funct. Mater. 22, 3470–3479 (2012).

    Article  CAS  Google Scholar 

  58. Capadona, J. R., Shanmuganathan, K., Tyler, D. J. & Rowan, S. J. Weder, C. Stimuli-responsive polymer nanocomposites inspired by the sea cucumber dermis. Science 319, 1370–1374 (2008).

    Article  CAS  Google Scholar 

  59. Kim, D. H. et al. Flexible and stretchable electronics for biointegrated devices. Annu. Rev. Biomed. Eng. 14, 113–128 (2012).

    Article  CAS  Google Scholar 

  60. Rogers, J. A., Someya, T. & Huang, Y. Materials and mechanics for stretchable electronics. Science 327, 1603–1607 (2010).

    Article  CAS  Google Scholar 

  61. Kim, D. H. et al. Epidermal electronics. Science 333, 838–343 (2011). A pioneering application of flexible and stretchable microcontact-printed electronics for biological sensing.

    Article  CAS  Google Scholar 

  62. Kim, R. H. et al. Waterproof AlInGaP optoelectronics on stretchable substrates with applications in biomedicine and robotics. Nat. Mater. 9, 929–937 (2010).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  66. Guitchounts, G., Markowitz, J. E., Liberti, W. A. & Gardner, T. J. A carbon-fiber electrode array for long-term neural recording. J. Neural Eng. 10, 046016 (2013).

    Article  Google Scholar 

  67. Vitale, F. et al. Neural stimulation and recording with bidirectional, soft carbon nanotube fiber microelectrodes. ACS Nano 9, 4465–4474 (2015).

    Article  CAS  Google Scholar 

  68. Malliaras, G. G. Organic bioelectronics: a new era for organic electronics. Biochim. Biophys. Acta 1830, 4286–4287 (2013).

    Article  CAS  Google Scholar 

  69. Benfenati, V. et al. A transparent organic transistor structure for bidirectional stimulation and recording of primary neurons. Nat. Mater. 12, 672–680 (2013).

    Article  CAS  Google Scholar 

  70. Kawano, K. et al. Degradation of organic solar cells due to air exposure. Sol. Energy Mater. Sol. Cells 90, 3520–3530 (2006).

    Article  CAS  Google Scholar 

  71. Elschner, A., Kirchmeyer, S., Lovenich, W., Merker, U. & Reuter, K. PEDOT: Principles and Applications of an Intrinsically Conductive Polymer (CRC Press, 2010).

    Book  Google Scholar 

  72. Ludwig, K. A. et al. Chronic neural recordings using silicon microelectrode arrays electrochemically deposited with a poly(3,4 ethylenedioxythiophene) (PEDOT) film. J. Neural Eng. 3, 59–70 (2006).

    Article  Google Scholar 

  73. Ludwig, K. A. et al. Poly(3,4 ethylenedioxythiophene) (PEDOT) polymer coatings facilitate smaller neural recording electrodes. J. Neural Eng. 8, 014001 (2011).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  75. Khodagholy, D. et al. NeuroGrid: recording action potentials from the surface of the brain. Nat. Neurosci. 18, 310–315 (2015).

    Article  CAS  Google Scholar 

  76. Castagnola, E. et al. Biologically compatible neural interface to safely couple nanocoated electrodes to the surface of the brain. ACS Nano 7, 3887–3895 (2013).

    Article  CAS  Google Scholar 

  77. 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).

    Article  CAS  Google Scholar 

  78. Tee, B. C. K. et al. A skin-inspired organic digital mechanoreceptor. Science 350, 313–316 (2015).

    Article  CAS  Google Scholar 

  79. Park, J. et al. Electromechanical cardioplasty using a wrapped elasto-conductive epicardial mesh. Sci. Transl. Med. 8, 344ra86 (2016).

    Article  CAS  Google Scholar 

  80. Park, M. et al. Highly stretchable electric circuits from a composite material of silver nanoparticles and elastomeric fibres. Nat. Nanotechnol. 7, 803–809 (2012).

    Article  CAS  Google Scholar 

  81. Abidian, M. R., Corey, J. M., Kipke, D. R. & Martin, D. C. Conducting-polymer nanotubes improve electrical properties, mechanical adhesion, neural attachment, and neurite outgrowth of neural electrodes. Small 6, 421–429 (2010).

    Article  CAS  Google Scholar 

  82. Yao, S. & Zhu, Y. Nanomaterial-enabled stretchable conductors: strategies, materials and devices. Adv. Mater. 27, 1480–1511 (2015).

    Article  CAS  Google Scholar 

  83. Kirkpatrick, S. Percolation and conduction. Rev. Mod. Phys. 45, 574–588 (1973).

    Article  Google Scholar 

  84. Hu, L. et al. Scalable coating and properties of transparent, flexible, silver nanowire electrodes. ACS Nano 4, 2955–2963 (2010).

    Article  CAS  Google Scholar 

  85. Perlmutter, J. S. & Mink, J. W. Deep brain stimulation. Annu. Rev. Neurosci. 29, 229–257 (2006).

    Article  CAS  Google Scholar 

  86. North, R. B. et al. Spinal cord stimulation for chronic, intractable pain: superiority of “multi-channel” devices. Pain 44, 119–130 (1991).

    Article  CAS  Google Scholar 

  87. Holtzheimer, P. E. III & Mayberg, H. S. Deep brain stimulation for treatment-resistant depression. Am. J. Psychiatry 167, 1437–1444 (2010).

    Article  Google Scholar 

  88. Cogan, S. F. Neural stimulation and recording electrodes. Annu. Rev. Biomed. Eng. 10, 275–309 (2008).

    Article  CAS  Google Scholar 

  89. Kringelbach, M. L., Jenkinson, N., Owen, S. L. F. & Aziz, T. Z. Translational principles of deep brain stimulation. Nat. Rev. Neurosci. 8, 623–635 (2007).

    Article  CAS  Google Scholar 

  90. Anikeeva, P. et al. Optetrode: a multichannel readout for optogenetic control in freely moving mice. Nat. Neurosci. 15, 163–170 (2011).

    Article  CAS  Google Scholar 

  91. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G., & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005). ChR2, a microbial opsin, is used to control neural activity with millisecond optical pulses for the first time, marking the invention of optogenetics.

    Article  CAS  Google Scholar 

  92. Bruegmann, T. et al. Optogenetic control of heart muscle in vitro and in vivo. Nat. Methods 7, 897–900 (2010).

    Article  CAS  Google Scholar 

  93. Magown, P. et al. Direct optical activation of skeletal muscle fibres efficiently controls muscle contraction and attenuates denervation atrophy. Nat. Commun. 6, 8506 (2015).

    Article  CAS  Google Scholar 

  94. Montgomery, K. L. et al. Beyond the brain: optogenetic control in the spinal cord and peripheral nervous system. Sci. Transl. Med. 8, 337rv5 (2016).

    Article  CAS  Google Scholar 

  95. Nagel, G. et al. Channelrhodopsin 2, a directly light-gated cation-selective membrane channel. Proc. Natl Acad. Sci. USA 100, 13940–13945 (2003).

    Article  CAS  Google Scholar 

  96. Zhang, F. et al. The microbial opsin family of optogenetic tools. Cell 147, 1446–1457 (2011).

    Article  CAS  Google Scholar 

  97. Zhang, F. et al. Multimodal fast optical interrogation of neural circuitry. Nature 446, 633–639 (2007).

    Article  CAS  Google Scholar 

  98. Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M. & Deisseroth, K. Optogenetics in neural systems. Neuron 71, 9–34 (2011).

    Article  CAS  Google Scholar 

  99. Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  Google Scholar 

  100. Zhang, J. et al. Integrated device for optical stimulation and spatiotemporal electrical recording of neural activity in light-sensitized brain tissue. J. Neural Eng. 6, 055007 (2009).

    Article  Google Scholar 

  101. Royer, S. et al. Multi-array silicon probes with integrated optical fibers: light-assisted perturbation and recording of local neural circuits in the behaving animal. Eur. J. Neurosci. 31, 2279–2291 (2010).

    Article  Google Scholar 

  102. Kravitz, A. V., Owen, S. F. & Kreitzer, A. C. Optogenetic identification of striatal projection neuron subtypes during in vivo recordings. Brain Res. 1511, 21–32 (2013).

    Article  CAS  Google Scholar 

  103. Buzsá ki, G. et al. Tools for probing local circuits: high-density silicon probes combined with optogenetics. Neuron 86, 92–105 (2015).

    Article  CAS  Google Scholar 

  104. Wu, F. et al. Monolithically integrated μLEDs on silicon neural probes for high-resolution optogenetic studies in behaving animals. Neuron 88, 1136–1148 (2015).

    Article  CAS  Google Scholar 

  105. Lee, J., Ozden, I., Song, Y. K. & Nurmikko, A. V. Transparent intracortical microprobe array for simultaneous spatiotemporal optical stimulation and multichannel electrical recording. Nat. Methods 12, 1157–1162 (2015).

    Article  CAS  Google Scholar 

  106. Kuzum, D. et al. Transparent and flexible low noise graphene electrodes for simultaneous electrophysiology and neuroimaging. Nat. Commun. 5, 5259 (2014).

    Article  CAS  Google Scholar 

  107. Rubehn, B., Wolff, S. B., Tovote, P., Lüthi, A. & Stieglitz, T. A polymer-based neural microimplant for optogenetic applications: design and first in vivo study. Lab Chip 13, 579–588 (2013).

    Article  CAS  Google Scholar 

  108. Kim, T. I. et al. Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science 340, 211–216 (2013).

    Article  CAS  Google Scholar 

  109. van den Brand, R. et al. Restoring voluntary control of locomotion after paralyzing spinal cord injury. Science 336, 1182–1185 (2012).

    Article  CAS  Google Scholar 

  110. Urban, D. J. & Roth, B. L. DREADDs (designer receptors exclusively activated by designer drugs): chemogenetic tools with therapeutic utility. Annu. Rev. Pharmacol. Toxicol. 55, 399–417 (2015). This comprehensive review describes powerful chemogenetic approaches to targeted neuromodulation with DREADDs (designer receptors exclusively activated by designer drugs).

    Article  CAS  Google Scholar 

  111. Jeong, J. W. et al. Wireless optofluidic systems for programmable in vivo pharmacology and optogenetics. Cell 162, 662–674 (2015).

    Article  CAS  Google Scholar 

  112. Muller, R. et al. A minimally invasive 64 channel wireless μECoG implant. IEEE J. Solid-State Circuits 50, 344–359 (2015).

    Article  Google Scholar 

  113. Montgomery, K. L. et al. Wirelessly powered, fully internal optogenetics for brain, spinal and peripheral circuits in mice. Nat. Methods 12, 969–974 (2015).

    Article  CAS  Google Scholar 

  114. Park, S. I. et al. Soft, stretchable, fully implantable miniaturized optoelectronic systems for wireless optogenetics. Nat. Biotechnol. 33, 1280–1286 (2015).

    Article  CAS  Google Scholar 

  115. Seo, D. et al. Model validation of untethered, ultrasonic neural dust motes for cortical recording. J. Neurosci. Methods 244, 114–122 (2015).

    Article  Google Scholar 

  116. Seo, D. et al. Wireless recording in the peripheral nervous system with ultrasonic neural dust. Neuron 91, 529–539 (2016). The first in vivo validation of neural dust motes.

    Article  CAS  Google Scholar 

  117. Spira, M. E. & Hai, A. Multi-electrode array technologies for neuroscience and cardiology. Nat. Nanotechnol. 8, 83–94 (2013).

    Article  CAS  Google Scholar 

  118. Shmoel, N. et al. Multisite electrophysiological recordings by self-assembled loose-patch-like junctions between cultured hippocampal neurons and mushroom-shaped microelectrodes. Sci. Rep. 6, 27110 (2016).

    Article  CAS  Google Scholar 

  119. Kang, M. et al. Subcellular neural probes from single-crystal gold nanowires. ACS Nano 8, 8182–8189 (2014).

    Article  CAS  Google Scholar 

  120. Robinson, J. T. et al. Vertical nanowire electrode arrays as a scalable platform for intracellular interfacing to neuronal circuits. Nat. Nanotechnol. 7, 180–184 (2012).

    Article  CAS  Google Scholar 

  121. Xie, C. et al. Intracellular recording of action potentials by nanopillar electroporation. Nat. Nanotechnol. 7, 185–190 (2012).

    Article  CAS  Google Scholar 

  122. Lin, Z. C. et al. Iridium oxide nanotube electrodes for sensitive and prolonged intracellular measurement of action potentials. Nat. Commun. 5, 3206 (2014).

    Article  CAS  Google Scholar 

  123. Almquist, B. D. & Melosh, N. A. Fusion of biomimetic stealth probes into lipid bilayer cores. Proc. Natl Acad. Sci. USA 107, 5815–5820 (2010).

    Article  Google Scholar 

  124. Patolsky, F. et al. Detection, stimulation, and inhibition of neuronal signals with high-density nanowire transistor arrays. Science 313, 1100–1104 (2006).

    Article  CAS  Google Scholar 

  125. Tian, B. & Lieber, C. M. Synthetic nanoelectronic probes for biological cells and tissues. Annu. Rev. Anal. Chem. 6, 31–51 (2013).

    Article  CAS  Google Scholar 

  126. Duan, X. et al. Intracellular recordings of action potentials by an extracellular nanoscale field-effect transistor. Nat. Nanotechnol. 7, 174–179 (2012).

    Article  CAS  Google Scholar 

  127. Tian, B. et al. Three-dimensional, flexible nanoscale field-effect transistors as localized bioprobes. Science 329, 830–834 (2010).

    Article  CAS  Google Scholar 

  128. Liu, J. et al. Syringe-injectable electronics. Nat. Nanotechnol. 10, 629–636 (2015).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  130. Fu, T. M. et al. Stable long-term chronic brain mapping at the single-neuron level. Nat. Methods 13, 875–882 (2016). A pioneering demonstration of long-term recordings using microstructured electrode meshes with a negligible tissue response.

    Article  CAS  Google Scholar 

  131. Wang, Y. & Guo, L. Nanomaterial-enabled neural stimulation. Front. Neurosci. 10, 69 (2016).

    Google Scholar 

  132. Gao, J., Gu, H. & Xu, B. Multifunctional magnetic nanoparticles: design, synthesis, and biomedical applications. Acc. Chem. Res. 42, 1097–1107 (2009).

    Article  CAS  Google Scholar 

  133. Hu, M. et al. Gold nanostructures: engineering their plasmonic properties for biomedical applications. Chem. Soc. Rev. 35, 1084–1094 (2006).

    Article  CAS  Google Scholar 

  134. Luan, S. et al. Neuromodulation: present and emerging methods. Front. Neuroeng. 7, 27, (2014).

  135. Wells, J. et al. Application of infrared light for in vivo neural stimulation. J. Biomed. Opt. 10, 064003 (2005).

    Article  Google Scholar 

  136. Yizhar, O. et al. Optogenetics in neural systems. Neuron 71, 9–34 (2011).

    Article  CAS  Google Scholar 

  137. Aravanis, A. M. et al. An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology. J. Neural Eng. 4, S143–S156 (2007).

    Article  Google Scholar 

  138. Knopfel, T. Genetically encoded optical indicators for the analysis of neuronal circuits. Nat. Rev. Neurosci. 13, 687–700 (2012).

    Article  CAS  Google Scholar 

  139. Horton, N. G. et al. In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat. Photonics 7, 205–209 (2013).

    Article  CAS  Google Scholar 

  140. Han, F.-F. & Hu, J.-H. in SPAWDA 2015, Symp. Piezoelectricity Acoust. Waves Device Appl. 102–105 (SPAWDA, 2015).

    Book  Google Scholar 

  141. Bystritsky, A. & Korb, A. A review of low-intensity transcranial focused ultrasound for clinical applications. Curr. Behav. Neurosci. Rep. 2, 60–66 (2015).

    Article  Google Scholar 

  142. Legon, W. et al. Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat. Neurosci. 17, 322–329 (2014). Focused ultrasound is used for non-invasive neuromodulation in the cortex of human subjects.

    Article  CAS  Google Scholar 

  143. Mace, E. et al. Functional ultrasound imaging of the brain. Nat. Methods 8, 662–664 (2011).

    Article  CAS  Google Scholar 

  144. Bottomley, P. A. & Andrew, E. R. RF magnetic field penetration, phase shift and power dissipation in biological tissue: implications for NMR imaging. Phys. Med. Biol. 23, 630–643 (1978).

    Article  CAS  Google Scholar 

  145. Young, J. H., Wang, M. T. & Brezovich, I. A. Frequency/depth-penetration considerations in hyperthermia by magnetically induced currents. Electron. Lett. 16, 358–359 (1980).

    Article  Google Scholar 

  146. Hallett, M. Transcranial magnetic stimulation: a primer. Neuron 55, 187–199 (2007).

    Article  CAS  Google Scholar 

  147. Deng, Z. D., Lisanby, S. H. & Peterchev, A. V. Electric field depth–focality tradeoff in transcranial magnetic stimulation: simulation comparison of 50 coil designs. Brain Stimul. 6, 1–13 (2013).

    Article  Google Scholar 

  148. Matthews, P. M., Honey, G. D. & Bullmore, E. T. Applications of fMRI in translational medicine and clinical practice. Nat. Rev. Neurosci. 7, 732–744 (2006).

    Article  CAS  Google Scholar 

  149. Errico, C. et al. Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging. Nature 527, 499–502 (2015).

    Article  CAS  Google Scholar 

  150. Cho, M. H. et al. A magnetic switch for the control of cell death signalling in in vitro and in vivo systems. Nat. Mater. 11, 1038–1043 (2012).

    Article  CAS  Google Scholar 

  151. Lee, J. H. et al. Magnetic nanoparticles for ultrafast mechanical control of inner ear hair cells. ACS Nano 8, 6590–6598 (2014).

    Article  CAS  Google Scholar 

  152. Pankhurst, Q. A., Thanh, N. T. K., Jones, S. K. & Dobson, J. Progress in applications of magnetic nanoparticles in biomedicine. J. Phys. D: Appl. Phys. 42, 224001 (2009).

    Article  CAS  Google Scholar 

  153. Guduru, R. et al. Magneto-electric nanoparticles to enable field-controlled high-specificity drug delivery to eradicate ovarian cancer cells. Sci. Rep. 3, 2953 (2013).

    Article  Google Scholar 

  154. Lugo, K. et al. Remote switching of cellular activity and cell signaling using light in conjunction with quantum dots. Biomed. Opt. Express 3, 447–454 (2012).

    Article  CAS  Google Scholar 

  155. Pappas, T. C. et al. Nanoscale engineering of a cellular interface with semiconductor nanoparticle films for photoelectric stimulation of neurons. Nano Lett. 7, 513–519 (2007).

    Article  CAS  Google Scholar 

  156. Rowland, C. E. et al. Electric field modulation of semiconductor quantum dot photoluminescence: insights into the design of robust voltage-sensitive cellular imaging probes. Nano Lett. 15, 6848–6854 (2015).

    Article  CAS  Google Scholar 

  157. Marshall, J. D. & Schnitzer, M. J. Optical strategies for sensing neuronal voltage using quantum dots and other semiconductor nanocrystals. ACS Nano 7, 4601–4609 (2013).

    Article  CAS  Google Scholar 

  158. Derfus, A. M., Chan, W. C. & Bhatia, S. N. Probing the cytotoxicity of semiconductor quantum dots. Nano Lett. 4, 11–18 (2004).

    Article  CAS  Google Scholar 

  159. Murphy, C. J. et al. Gold nanoparticles in biology: beyond toxicity to cellular imaging. Acc. Chem. Res. 41, 1721–1730 (2008).

    Article  CAS  Google Scholar 

  160. Yoo, S. et al. Photothermal inhibition of neural activity with near-infrared-sensitive nanotransducers. ACS Nano 8, 8040–8049 (2014).

    Article  CAS  Google Scholar 

  161. Carvalho- de Souza, J. L. et al. Photosensitivity of neurons enabled by cell-targeted gold nanoparticles. Neuron 86, 207–217 (2015).

    Article  CAS  Google Scholar 

  162. Lavoie-Cardinal, F. et al. Gold nanoparticle-assisted all optical localized stimulation and monitoring of Ca2+ signaling in neurons. Sci. Rep. 6, 20619 (2016).

    Article  CAS  Google Scholar 

  163. Nakatsuji, H. et al. Thermosensitive ion channel activation in single neuronal cells by using surface-engineered plasmonic nanoparticles. Angew. Chem. Int. Ed. 54, 11725–11729 (2015).

    Article  CAS  Google Scholar 

  164. Zhang, J., Atay, T. & Nurmikko, A. V. Optical detection of brain cell activity using plasmonic gold nanoparticles. Nano Lett. 9, 519–524 (2009).

    Article  CAS  Google Scholar 

  165. Juluri, B. K. et al. Effects of geometry and composition on charge-induced plasmonic shifts in gold nanoparticles. J. Phys. Chem. C. 112, 7309–7317 (2008).

    Article  CAS  Google Scholar 

  166. Kucsko, G. et al. Nanometre-scale thermometry in a living cell. Nature 500, 54–58 (2013).

    Article  CAS  Google Scholar 

  167. Karaveli, S. et al. Modulation of nitrogen vacancy charge state and fluorescence in nanodiamonds using electrochemical potential. Proc. Natl Acad. Sci. USA 113, 3938–3943 (2016).

    Article  CAS  Google Scholar 

  168. Barry, J. et al. Optical magnetic detection of single-neuron action potentials using quantum defects in diamond. Preprint at https://arxiv.org/abs/1602.01056 (2016).

  169. Zhang, Y. et al. Illuminating cell signaling with near-infrared light-responsive nanomaterials. ACS Nano. 10, 3881–3885 (2016).

    Article  CAS  Google Scholar 

  170. He, L. et al. Near-infrared photoactivatable control of Ca2+ signaling and optogenetic immunomodulation. eLife 4, e10024 (2015).

    Article  Google Scholar 

  171. Ibsen, S. et al. Sonogenetics is a non-invasive approach to activating neurons in Caenorhabditis elegans. Nat. Commun. 6, 8264 (2015).

    Article  CAS  Google Scholar 

  172. Marino, A. et al. Piezoelectric nanoparticle-assisted wireless neuronal stimulation. ACS Nano 9, 7678–7689 (2015).

    Article  CAS  Google Scholar 

  173. Dobson, J. Remote control of cellular behaviour with magnetic nanoparticles. Nat. Nanotechnol. 3, 139–143 (2008).

    Article  CAS  Google Scholar 

  174. Ingber, D. E. Cellular mechanotransduction: putting all the pieces together again. FASEB. J. 20, 811–827 (2006).

    Article  CAS  Google Scholar 

  175. Seo, D. et al. A mechanogenetic toolkit for interrogating cell signaling in space and time. Cell 165, 1507–1518 (2016).

    Article  CAS  Google Scholar 

  176. Hughes, S. et al. Selective activation of mechanosensitive ion channels using magnetic particles. J. R. Soc. Interface 5, 855–863 (2008).

    Article  CAS  Google Scholar 

  177. Hoffmann, C. et al. Spatiotemporal control of microtubule nucleation and assembly using magnetic nanoparticles. Nat. Nanotechnol. 8, 199–205 (2013).

    Article  CAS  Google Scholar 

  178. Kim, D. H. et al. Biofunctionalized magnetic-vortex microdiscs for targeted cancer-cell destruction. Nat. Mater. 9, 165–171 (2010).

    Article  CAS  Google Scholar 

  179. Mannix, R. J. et al. Nanomagnetic actuation of receptor-mediated signal transduction. Nat. Nanotechnol. 3, 36–40 (2008).

    Article  CAS  Google Scholar 

  180. Carrey, J., Mehdaoui, B. & Respaud, M. Simple models for dynamic hysteresis loop calculations of magnetic single-domain nanoparticles: application to magnetic hyperthermia optimization. J. Appl. Phys. 109, 083921 (2011).

    Article  CAS  Google Scholar 

  181. Chen, R. et al. Wireless magnetothermal deep brain stimulation. Science 347, 1477–1480 (2015).

    Article  CAS  Google Scholar 

  182. Huang, H. et al. Remote control of ion channels and neurons through magnetic-field heating of nanoparticles. Nat. Nanotechnol. 5, 602–606 (2010). The first application of MNP heating to regulate intracellular calcium with AMFs.

    Article  CAS  Google Scholar 

  183. Stanley, S. A. et al. Radio-wave heating of iron oxide nanoparticles can regulate plasma glucose in mice. Science 336, 604–608 (2012).

    Article  CAS  Google Scholar 

  184. Nair, M. et al. Externally controlled on demand release of anti-HIV drug using magneto-electric nanoparticles as carriers. Nat. Commun. 4, 1707 (2013).

    Article  CAS  Google Scholar 

  185. Guduru, R. et al. Magnetoelectric ‘spin’ on stimulating the brain. Nanomedicine 10, 2051–2061 (2015).

    Article  CAS  Google Scholar 

  186. Shin, T. H. et al. Recent advances in magnetic nanoparticle-based multi-modal imaging. Chem. Soc. Rev. 44, 4501–4516 (2015).

    Article  CAS  Google Scholar 

  187. Davies, G.-L., Kramberger, I. & Davis, J. J. Environmentally responsive MRI contrast agents. Chem. Commun. (Camb.) 49, 9704–9721 (2013).

    Article  CAS  Google Scholar 

  188. Atanasijevic, T. et al. Calcium-sensitive MRI contrast agents based on superparamagnetic iron oxide nanoparticles and calmodulin. Proc. Natl Acad. Sci. USA 103, 14707–14712 (2006).

    Article  CAS  Google Scholar 

  189. Shapiro, M. G. et al. Dynamic imaging with MRI contrast agents: quantitative considerations. Magn. Reson. Imaging 24, 449–462 (2006).

    Article  CAS  Google Scholar 

  190. Rodriguez, E. et al. Magnetic nanosensors optimized for rapid and reversible self-assembly. Chem. Commun. (Camb.) 50, 3595–3598 (2014).

    Article  CAS  Google Scholar 

  191. Lee, T., Cai, L. X., Lelyveld, V. S., Hai, A. & Jasanoff, A. Molecular-level functional magnetic resonance imaging of dopaminergic signaling. Science 344, 533–535 (2014).

    Article  CAS  Google Scholar 

  192. Christiansen, M. G. et al. Magnetically multiplexed heating of single domain nanoparticles. Appl. Phys. Lett. 104, 213103 (2014).

    Article  CAS  Google Scholar 

  193. Wijaya, A. et al. Selective release of multiple DNA oligonucleotides from gold nanorods. ACS Nano 3, 80–86 (2008).

    Article  CAS  Google Scholar 

  194. Chen, R. et al. High-performance ferrite nanoparticles through nonaqueous redox phase tuning. Nano Lett. 16, 1345–1351 (2016).

    Article  CAS  Google Scholar 

  195. Chen, Y. & Liu, L. Modern methods for delivery of drugs across the blood–brain barrier. Adv. Drug Deliv. Rev. 64, 640–665 (2012).

    Article  CAS  Google Scholar 

  196. Salvati, A. et al. Transferrin-functionalized nanoparticles lose their targeting capabilities when a biomolecule corona adsorbs on the surface. Nat. Nanotechnol. 8, 137–143 (2013).

    Article  CAS  Google Scholar 

  197. Tenzer, S. et al. Rapid formation of plasma protein corona critically affects nanoparticle pathophysiology. Nat. Nanotechnol. 8, 772–781 (2013).

    Article  CAS  Google Scholar 

  198. Kim, J. A. et al. Role of cell cycle on the cellular uptake and dilution of nanoparticles in a cell population. Nat. Nanotechnol. 7, 62–68 (2012).

    Article  CAS  Google Scholar 

  199. Hynynen, K. et al. Local and reversible blood–brain barrier disruption by noninvasive focused ultrasound at frequencies suitable for trans-skull sonications. Neuroimage 24, 12–20 (2005).

    Article  Google Scholar 

  200. Chertok, B. et al. Iron oxide nanoparticles as a drug delivery vehicle for MRI monitored magnetic targeting of brain tumors. Biomaterials 29, 487–496 (2008).

    Article  CAS  Google Scholar 

  201. van Landeghem, F. K. H. et al. Post-mortem studies in glioblastoma patients treated with thermotherapy using magnetic nanoparticles. Biomaterials 30, 52–57 (2009).

    Article  CAS  Google Scholar 

  202. Tang, J. C. et al. A nanobody-based system using fluorescent proteins as scaffolds for cell-specific gene manipulation. Cell 154, 928–939 (2013).

    Article  CAS  Google Scholar 

  203. Antman-Passig, M. & Shefi, O. Remote magnetic orientation of 3D collagen hydrogels for directed neuronal regeneration. Nano Lett. 16, 2567–2573 (2016).

    Article  CAS  Google Scholar 

  204. Pakulska, M. M., Ballios, B. G. & Shoichet, M. S. Injectable hydrogels for central nervous system therapy. Biomed. Mater. 7, 024101 (2012).

    Article  CAS  Google Scholar 

  205. Shapiro, M. G. et al. Biogenic gas nanostructures as ultrasonic molecular reporters. Nat. Nanotechnol. 9, 311–316 (2014).

    Article  CAS  Google Scholar 

  206. Stanley, S. A. et al. Bidirectional electromagnetic control of the hypothalamus regulates feeding and metabolism. Nature 531, 647–650 (2016).

    Article  CAS  Google Scholar 

  207. Wheeler, M. A. et al. Genetically targeted magnetic control of the nervous system. Nat. Neurosci. 19, 756–761 (2016).

    Article  CAS  Google Scholar 

  208. Chasteen, N. D. & Harrison, P. M. Mineralization in ferritin: an efficient means of iron storage. J. Struct. Biol. 126, 182–194 (1999).

    Article  CAS  Google Scholar 

  209. Meister, M. Physical limits to magnetogenetics. eLife 5, e17210 (2016).

    Article  CAS  Google Scholar 

  210. Komeili, A. et al. Magnetosomes are cell membrane invaginations organized by the actin-like protein MamK. Science 311, 242–245 (2006).

    Article  CAS  Google Scholar 

  211. Kolinko, I. et al. Biosynthesis of magnetic nanostructures in a foreign organism by transfer of bacterial magnetosome gene clusters. Nat. Nanotechnol. 9, 193–197 (2014).

    Article  CAS  Google Scholar 

  212. French, D. D. et al. Health care costs for patients with chronic spinal cord injury in the veterans health administration. J. Spinal Cord Med. 30, 477–481 (2007).

    Article  Google Scholar 

  213. Kowal, S. L. et al. The current and projected economic burden of Parkinson's disease in the United States. Mov. Disord. 28, 311–318 (2013).

    Article  Google Scholar 

  214. Calabresi, P. et al. Direct and indirect pathways of basal ganglia: a critical reappraisal. Nat. Neurosci. 17, 1022–1030 (2014).

    Article  CAS  Google Scholar 

  215. Arber, S. Motorcircuits in action: specification, connectivity, and function. Neuron 74, 975–989 (2012).

    Article  CAS  Google Scholar 

  216. Holstege, G. Descending motor pathways and the spinal motor systemml_ limbic and non-limbic components. Prog. Brain Res. 87, 307–421 (1991).

    Article  CAS  Google Scholar 

  217. Hammerle, H. et al. Biostability of micro-photodiode arrays for subretinal implantation. Biomaterials 23, 797–804 (2002).

    Article  CAS  Google Scholar 

  218. Patrick, E. et al. Corrosion of tungsten microelectrodes used in neural recording applications. J. Neurosci. Methods 198, 158–171 (2011).

    Article  CAS  Google Scholar 

  219. Wang, A. et al. Stability of and inflammatory response to silicon coated with a fluoroalkyl self-assembled monolayer in the central nervous system. J. Biomed. Mater. Res. A. 81, 363–372 (2007).

    Article  CAS  Google Scholar 

  220. Li, W. et al. Corrosion behavior of parylene–metal–parylene thin films in saline. ECS Trans 11, 1–6 (2008).

    Article  Google Scholar 

Download references

Acknowledgements

P.A. is supported by the National Science Foundation (NSF) through a CAREER Award, Center for Materials Science and Engineering, Center for Sensorimotor Neural Engineering, National Institutes for Neurological Disorders and Stroke, National Institute of Mental Health, the Defense Advanced Research Projects Agency, Dresselhaus Fund Award, and the Bose Research Grant.

Author information

Authors and Affiliations

  1. Department of Materials Science and Engineering, and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, 02193, Massachusetts, USA

    Ritchie Chen, Andres Canales & Polina Anikeeva

Authors
  1. Ritchie Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andres Canales
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Polina Anikeeva
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Polina Anikeeva.

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

Chen, R., Canales, A. & Anikeeva, P. Neural recording and modulation technologies. Nat Rev Mater 2, 16093 (2017). https://doi.org/10.1038/natrevmats.2016.93

Download citation

  • Published:

  • DOI: https://doi.org/10.1038/natrevmats.2016.93

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing