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Implantable Optical Neural Interface

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Smart Sensors and Systems

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Abstract

For more than several decades, due to the rapid development of sophisticated electronics, the electrical neural interface has become the most popular method for recording and modulating neural activity in nerve systems. The electrical neural interface has been successfully applied to implantable neural prosthetic systems such as cochlear implant, deep brain stimulation system, artificial retina, and so on. Recently, in order to overcome the limitations of electrical methods for neural interface, novel optical technologies have been developed and applied to neuroscience research. Overall, the optical neural interfaces can be categorized into the intrinsic and the extrinsic methods depending on the modification of natural nerve system. For example, infrared neural stimulation (INS) and optogenetic neural stimulation are the typical methods for intrinsic and extrinsic neural interfaces, respectively. In addition to the optogenetic stimulation, it is also possible to monitor neural activity from specific neurons genetically modified to express activity-correlated fluorescence signals. Therefore, the optogenetic neural recording enables the detection of activity from specific types of neurons. Despite the fascinating advantages, to date, the use of the optical neural interface is limited only to the neuroscience research not for clinical purposes. In this chapter, the state-of-art technologies in optical neural interface are reviewed from the aspects of both neurobiology and engineering. In addition, the challenges to realize the clinical use of optical neural interfaces are discussed.

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References

  1. Shepherd GM (2004) The synaptic organization of the brain, 5th edn. Oxford University Press, New York

    Book  Google Scholar 

  2. Pinaud R, Terleph TA, Tremere LA, Phan ML, Dagostin AA, Leão RM et al (2008) Inhibitory network interactions shape the auditory processing of natural communication signals in the songbird auditory forebrain. J Neurophysiol 100:441–455

    Article  Google Scholar 

  3. Zhou M, Liang F, Xiong XR, Li L, Li H, Xiao Z et al (2014) Scaling down of balanced excitation and inhibition by active behavioral states in auditory cortex. Nat Neurosci 17:841–850

    Google Scholar 

  4. Pinto L, Dan Y (2015) Cell-type-specific activity in prefrontal cortex during goal-directed behavior. Neuron 87:437–450

    Google Scholar 

  5. Roche JP, Hansen MR (2015) On the horizon: cochlear implant technology. Otolaryngol Clin North Am 48:1097–1116

    Article  Google Scholar 

  6. Kilgard MP, Merzenich MM (1998) Cortical map reorganization enabled by nucleus basalis activity. Science 279:1714–1718

    Article  Google Scholar 

  7. Zrenner E (2002) Will retinal implants restore vision? Science 295:1022–1025

    Google Scholar 

  8. Zhang Y, Hakes JJ, Bonfield SP, Yan J (2005) Corticofugal feedback for auditory midbrain plasticity elicited by tones and electrical stimulation of basal forebrain in mice. Eur J Neurosci 22:871–879

    Article  Google Scholar 

  9. Lim H, Anderson D (2006) Auditory cortical responses to electrical stimulation of the inferior colliculus: implications for an auditory midbrain implant. J Neurophysiol 96:975–988

    Article  Google Scholar 

  10. Thompson AC, Stoddart PR, Jansen ED (2014) Optical stimulation of neurons. Curr Mol Imaging 3:162–177

    Article  Google Scholar 

  11. Frostig RD, Lieke EE, Ts’o DY, Grinvald A (1990) Cortical functional architecture and local coupling between neuronal activity and the microcirculation revealed by in vivo high-resolution optical imaging of intrinsic signals. Proc Natl Acad Sci 87:6082–6086

    Article  Google Scholar 

  12. Malonek D, Grinvald A (1996) Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping. Science 272:551

    Article  Google Scholar 

  13. Kim SA, Byun KM, Lee J, Kim J, Kim D-G, Baac H et al (2008) Optical measurement of neural activity using surface plasmon resonance. Opt Lett 33:914–916

    Article  Google Scholar 

  14. Kim SA, Kim SJ, Moon H, Jun SB (2012) In vivo optical neural recording using fiber-based surface plasmon resonance. Opt Lett 37:614–616

    Article  Google Scholar 

  15. Lazebnik M, Marks DL, Potgieter K, Gillette R, Boppart SA (2003) Functional optical coherence tomography for detecting neural activity through scattering changes. Opt Lett 28:1218–1220

    Article  Google Scholar 

  16. Stepnoski R, LaPorta A, Raccuia-Behling F, Blonder G, Slusher R, Kleinfeld D (1991) Noninvasive detection of changes in membrane potential in cultured neurons by light scattering. Proc Natl Acad Sci 88:9382–9386

    Article  Google Scholar 

  17. Shevelev IA (1998) Functional imaging of the brain by infrared radiation (thermoencephaloscopy). Prog Neurobiol 56:269–305

    Article  Google Scholar 

  18. Wells J, Kao C, Jansen ED, Konrad P, Mahadevan-Jansen A (2005) Application of infrared light for in vivo neural stimulation. J Biomed Opt 10:064003

    Article  Google Scholar 

  19. Tan X, Rajguru S, Young H, Xia N, Stock SR, Xiao X et al (2015) Radiant energy required for infrared neural stimulation. Sci Rep 5:13273

    Article  Google Scholar 

  20. Wells J, Konrad P, Kao C, Jansen ED, Mahadevan-Jansen A (2007) Pulsed laser versus electrical energy for peripheral nerve stimulation. J Neurosci Methods 163:326–337

    Article  Google Scholar 

  21. Izzo AD, Walsh JT Jr, Ralph H, Webb J, Bendett M, Wells J et al (2008) Laser stimulation of auditory neurons: effect of shorter pulse duration and penetration depth. Biophys J 94:3159–3166

    Article  Google Scholar 

  22. Huang H, Delikanli S, Zeng H, Ferkey DM, Pralle A (2010) Remote control of ion channels and neurons through magnetic-field heating of nanoparticles. Nat Nanotechnol 5:602–606

    Article  Google Scholar 

  23. Richter CP, Matic AI, Wells JD, Jansen ED, Walsh JT Jr (2011) Neural stimulation with optical radiation. Laser Photonics Rev 5:68–80

    Article  Google Scholar 

  24. Shapiro MG, Homma K, Villarreal S, Richter CP, Bezanilla F (2012) Infrared light excites cells by changing their electrical capacitance. Nat Commun 3:736

    Article  Google Scholar 

  25. Wells J, Kao C, Konrad P, Milner T, Kim J, Mahadevan-Jansen A et al (2007) Biophysical mechanisms of transient optical stimulation of peripheral nerve. Biophys J 93:2567–2580

    Article  Google Scholar 

  26. Duke AR, Jenkins MW, Lu H, McManus JM, Chiel HJ, Jansen ED (2013) Transient and selective suppression of neural activity with infrared light. Sci Rep 3:2600

    Article  Google Scholar 

  27. Katz EJ, Ilev IK, Krauthamer V, Kim do H, Weinreich D (2010) Excitation of primary afferent neurons by near-infrared light in vitro. Neuroreport 21:662–666

    Article  Google Scholar 

  28. Jaque D, Martinez Maestro L, del Rosal B, Haro-Gonzalez P, Benayas A, Plaza JL et al (2014) Nanoparticles for photothermal therapies. Nanoscale 6:9494–9530

    Article  Google Scholar 

  29. Carvalho-de-Souza JL, Treger JS, Dang B, Kent SB, Pepperberg DR, Bezanilla F (2015) Photosensitivity of neurons enabled by cell-targeted gold nanoparticles. Neuron 86:207–217

    Article  Google Scholar 

  30. Eom K, Kim J, Choi JM, Kang T, Chang JW, Byun KM et al (2014) Enhanced infrared neural stimulation using localized surface plasmon resonance of gold nanorods. Small 10:3853–3857

    Article  Google Scholar 

  31. Yong J, Needham K, Brown WG, Nayagam BA, McArthur SL, Yu A et al (2014) Gold-nanorod-assisted near-infrared stimulation of primary auditory neurons. Adv Healthc Mater 3:1862–1868

    Article  Google Scholar 

  32. Yoo S, Hong S, Choi Y, Park JH, Nam Y (2014) Photothermal inhibition of neural activity with near-infrared-sensitive nanotransducers. ACS Nano 8:8040–8049

    Article  Google Scholar 

  33. Barnard JE, Welch FV (1936) Fluorescence microscopy with high powers. J R Microsc Soc 56:361–364

    Article  Google Scholar 

  34. Abramowitz M (1993) Fluorescence microscopy. Olympus America, New York

    Google Scholar 

  35. Shimomura O, Johnson FH, Saiga Y (1962) Extraction, purification and properties of aequorin, a bioluminescent protein from the luminous hydromedusan, aequorea. J Cell Comp Physiol 59:223–239

    Article  Google Scholar 

  36. Helmchen F, Denk W (2005) Deep tissue two-photon microscopy. Nat Methods 2:932–940

    Article  Google Scholar 

  37. Kerr JND, Denk W (2008) Imaging in vivo: watching the brain in action. Nat Rev Neurosci 9:195–205

    Article  Google Scholar 

  38. Rothschild G, Nelken I, Mizrahi A (2010) Functional organization and population dynamics in the mouse primary auditory cortex. Nat Neurosci 13:353–360

    Article  Google Scholar 

  39. Roberts TF, Tschida KA, Klein ME, Mooney R (2010) Rapid spine stabilization and synaptic enhancement at the onset of behavioural learning. Nature 463:948–952

    Article  Google Scholar 

  40. Clancy KB, Koralek AC, Costa RM, Feldman DE, Carmena JM (2014) Volitional modulation of optically recorded calcium signals during neuroprosthetic learning. Nat Neurosci 17:807–809

    Article  Google Scholar 

  41. Helmchen F, Fee MS, Tank DW, Denk W (2001) A miniature head-mounted two-photon microscope. Neuron 31:903–912

    Article  Google Scholar 

  42. Flusberg BA, Jung JC, Cocker ED, Anderson EP, Schnitzer MJ (2005) In vivo brain imaging using a portable 3.9 gram two-photon fluorescence microendoscope. Opt Lett 30:2272–2274

    Article  Google Scholar 

  43. Sawinski J, Denk W (2007) Miniature random-access fiber scanner for in vivo multiphoton imaging. J Appl Phys 102:034701

    Article  Google Scholar 

  44. Engelbrecht CJ, Johnston RS, Seibel EJ, Helmchen F (2008) Ultra-compact fiber-optic two-photon microscope for functional fluorescence imaging in vivo. Opt Express 16:5556–5564

    Article  Google Scholar 

  45. Sawinski J, Wallace DJ, Greenberg DS, Grossmann S, Denk W, Kerr JND (2009) Visually evoked activity in cortical cells imaged in freely moving animals. Proc Natl Acad Sci U S A 106:19557–19562

    Article  Google Scholar 

  46. Piyawattanametha W, Cocker ED, Burns LD, Barretto RPJ, Jung JC, Ra H et al (2009) In vivo brain imaging using a portable 2.9 g two-photon microscope based on a microelectromechanical systems scanning mirror. Opt Lett 34:2309–2311

    Article  Google Scholar 

  47. Jung JC, Schnitzer MJ (2003) Multiphoton endoscopy. Opt Lett 28:902–904

    Article  Google Scholar 

  48. Levene MJ, Dombeck DA, Kasischke KA, Molloy RP, Webb WW (2004) In vivo multiphoton microscopy of deep brain tissue. J Neurophysiol 91:1908–1912

    Article  Google Scholar 

  49. Jung JC, Mehta AD, Aksay E, Stepnoski R, Schnitzer MJ (2004) In vivo mammalian brain imaging using one- and two-photon fluorescence microendoscopy. J Neurophysiol 92:3121–3133

    Article  Google Scholar 

  50. Llewellyn ME, Barretto RPJ, Delp SL, Schnitzer MJ (2008) Minimally invasive high-speed imaging of sarcomere contractile dynamics in mice and humans. Nature 454:784–788

    Google Scholar 

  51. Bocarsly ME, Jiang W-c, Wang C, Dudman JT, Ji N, Aponte Y (2015) Minimally invasive microendoscopy system for in vivo functional imaging of deep nuclei in the mouse brain. Biomed Opt Express 6:4546–4556

    Article  Google Scholar 

  52. Grienberger C, Konnerth A (2012) Imaging calcium in neurons. Neuron 73:862–885

    Article  Google Scholar 

  53. Cao G, Platisa J, Pieribone VA, Raccuglia D, Kunst M, Nitabach MN (2013) Genetically targeted optical electrophysiology in intact neural circuits. Cell 154:904–913

    Article  Google Scholar 

  54. Mutoh H, Perron A, Akemann W, Iwamoto Y, Knopfel T (2010) Optogenetic monitoring of membrane potentials. Exp Physiol 96:13–18

    Article  Google Scholar 

  55. Gonzalez D, Espino J, Bejarano I, Lopez JJ, Rodriguez AB, Pariente JA (2010) Caspase-3 and -9 are activated in human myeloid HL-60 cells by calcium signal. Mol Cell Biochem 333:151–157

    Article  Google Scholar 

  56. Zhang H, Liu J, Sun S, Pchitskaya E, Popugaeva E, Bezprozvanny I (2015) Calcium signaling, excitability, and synaptic plasticity defects in a mouse model of Alzheimer’s disease. J Alzheimers Dis 45:561–580

    Google Scholar 

  57. Lyons MR, West AE (2011) Mechanisms of specificity in neuronal activity-regulated gene transcription. Prog Neurobiol 94:259–295

    Article  Google Scholar 

  58. Berridge MJ, Lipp P, Bootman MD (2000) The versatility and universality of calcium signalling. Nat Rev Mol Cell Biol 1:11–21

    Article  Google Scholar 

  59. Wachowiak M, Knopfel T (2009) Frontiers in neuroscience optical imaging of brain activity in vivo using genetically encoded probes. In: Frostig RD (ed) In vivo optical imaging of brain function. CRC Press and Taylor & Francis Group, LLC, Boca Raton, FL

    Google Scholar 

  60. Paredes RM, Etzler JC, Watts LT, Zheng W, Lechleiter JD (2008) Chemical calcium indicators. Methods 46:143–151

    Article  Google Scholar 

  61. Pozzan T, Arslan P, Tsien RY, Rink TJ (1982) Anti-immunoglobulin, cytoplasmic free calcium, and capping in B lymphocytes. J Cell Biol 94:335–340

    Article  Google Scholar 

  62. Tsien RY, Pozzan T, Rink TJ (1982) Calcium homeostasis in intact lymphocytes: cytoplasmic free calcium monitored with a new, intracellularly trapped fluorescent indicator. J Cell Biol 94:325–334

    Article  Google Scholar 

  63. Neher E (1995) The use of fura-2 for estimating Ca buffers and Ca fluxes. Neuropharmacology 34:1423–1442

    Article  Google Scholar 

  64. Dittgen T, Nimmerjahn A, Komai S, Licznerski P, Waters J, Margrie TW et al (2004) Lentivirus-based genetic manipulations of cortical neurons and their optical and electrophysiological monitoring in vivo. Proc Natl Acad Sci U S A 101:18206–18211

    Article  Google Scholar 

  65. Monahan PE, Samulski RJ (2000) Adeno-associated virus vectors for gene therapy: more pros than cons? Mol Med Today 6:433–440

    Article  Google Scholar 

  66. Wirth D, Gama-Norton L, Riemer P, Sandhu U, Schucht R, Hauser H (2007) Road to precision: recombinase-based targeting technologies for genome engineering. Curr Opin Biotechnol 18:411–419

    Article  Google Scholar 

  67. Tsai PS, Friedman B, Ifarraguerri AI, Thompson BD, Lev-Ram V, Schaffer CB et al (2003) All-optical histology using ultrashort laser pulses. Neuron 39:27–41

    Article  Google Scholar 

  68. Chemla S, Chavane F (2010) Voltage-sensitive dye imaging: technique review and models. J Physiol Paris 104:40–50

    Article  Google Scholar 

  69. Siegel MS, Isacoff EY (1997) A genetically encoded optical probe of membrane voltage. Neuron 19:735–741

    Article  Google Scholar 

  70. Akemann W, Mutoh H, Perron A, Rossier J, Knöpfel T (2010) Imaging brain electric signals with genetically targeted voltage-sensitive fluorescent proteins. Nat Methods 7:643–649

    Article  Google Scholar 

  71. Akemann W, Sasaki M, Mutoh H, Imamura T, Honkura N, Knöpfel T (2013) Two-photon voltage imaging using a genetically encoded voltage indicator. Sci Rep 3:2231

    Article  Google Scholar 

  72. Ross WN, Werman R (1987) Mapping calcium transients in the dendrites of Purkinje cells from the guinea-pig cerebellum in vitro. J Physiol 389:319–336

    Article  Google Scholar 

  73. Baker BJ, Kosmidis EK, Vucinic D, Falk CX, Cohen LB, Djurisic M et al (2005) Imaging brain activity with voltage- and calcium-sensitive dyes. Cell Mol Neurobiol 25:245–282

    Article  Google Scholar 

  74. Adelsberger H, Garaschuk O, Konnerth A (2005) Cortical calcium waves in resting newborn mice. Nat Neurosci 8:988–990

    Article  Google Scholar 

  75. Cui G, Jun SB, Jin X, Pham MD, Vogel SS, Lovinger DM et al (2013) Concurrent activation of striatal direct and indirect pathways during action initiation. Nature 494:238–242

    Article  Google Scholar 

  76. Minsky M (1988) Memoir on inventing the confocal scanning microscope. Scanning 10:128–138

    Article  Google Scholar 

  77. Pawley JB (ed) (2006) Handbook of biological confocal microscopy. Springer, Boston, MA

    Google Scholar 

  78. Denk W, Strickler J, Webb WW (1990) Two-photon laser scanning fluorescence microscopy. Science 248:73–76

    Article  Google Scholar 

  79. Kobat D, Horton NG, Xu C (2011) In vivo two-photon microscopy to 1.6-mm depth in mouse cortex. J Biomed Opt 16:106014

    Article  Google Scholar 

  80. Horton NG, Wang K, Kobat D, Clark CG, Wise FW, Schaffer CB et al (2013) In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat Photonics 7:205–209

    Article  Google Scholar 

  81. Flusberg BA, Nimmerjahn A, Cocker ED, Mukamel EA, Barretto RPJ, Ko TH et al (2008) High-speed, miniaturized fluorescence microscopy in freely moving mice. Nat Methods 5:935–938

    Article  Google Scholar 

  82. Barretto RPJ, Messerschmidt B, Schnitzer MJ (2009) In vivo fluorescence imaging with high-resolution microlenses. Nat Methods 6:511–512

    Article  Google Scholar 

  83. Zemelman BV, Lee GA, Ng M, Miesenbock G (2002) Selective photostimulation of genetically chARGed neurons. Neuron 33:15–22

    Article  Google Scholar 

  84. Zemelman BV, Nesnas N, Lee GA, Miesenbock G (2003) Photochemical gating of heterologous ion channels: remote control over genetically designated populations of neurons. Proc Natl Acad Sci U S A 100:1352–1357

    Article  Google Scholar 

  85. Lima SQ, Miesenbock G (2005) Remote control of behavior through genetically targeted photostimulation of neurons. Cell 121:141–152

    Article  Google Scholar 

  86. Boyden ES, Zhang F, Bamberg E, Nagel G, Deisseroth K (2005) Millisecond-timescale, genetically targeted optical control of neural activity. Nat Neurosci 8:1263–1268

    Article  Google Scholar 

  87. Li X, Gutierrez DV, Hanson MG, Han J, Mark MD, Chiel H et al (2005) Fast noninvasive activation and inhibition of neural and network activity by vertebrate rhodopsin and green algae channelrhodopsin. Proc Natl Acad Sci U S A 102:17816–17821

    Article  Google Scholar 

  88. Nagel G, Ollig D, Fuhrmann M, Kateriya S, Musti AM, Bamberg E et al (2002) Channelrhodopsin-1: a light-gated proton channel in green algae. Science 296:2395–2398

    Article  Google Scholar 

  89. Zhao S, Cunha C, Zhang F, Liu Q, Gloss B, Deisseroth K et al (2008) Improved expression of halorhodopsin for light-induced silencing of neuronal activity. Brain Cell Biol 36:141–154

    Article  Google Scholar 

  90. Gradinaru V, Thompson KR, Deisseroth K (2008) eNpHR: a Natronomonas halorhodopsin enhanced for optogenetic applications. Brain Cell Biol 36:129–139

    Article  Google Scholar 

  91. Berndt A, Yizhar O, Gunaydin LA, Hegemann P, Deisseroth K (2009) Bi-stable neural state switches. Nat Neurosci 12:229–234

    Article  Google Scholar 

  92. Yizhar O, Fenno LE, Prigge M, Schneider F, Davidson TJ, O'Shea DJ et al (2011) Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature 477:171–178

    Article  Google Scholar 

  93. Madisen L, Mao T, Koch H, Zhuo JM, Berenyi A, Fujisawa S et al (2012) A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing. Nat Neurosci 15:793–802

    Article  Google Scholar 

  94. Madisen L, Garner AR, Shimaoka D, Chuong AS, Klapoetke NC, Li L et al (2015) Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85:942–958

    Article  Google Scholar 

  95. Tsien JZ, Chen DF, Gerber D, Tom C, Mercer EH, Anderson DJ et al (1996) Subregion- and cell type-restricted gene knockout in mouse brain. Cell 87:1317–1326

    Article  Google Scholar 

  96. Bass CE, Grinevich VP, Vance ZB, Sullivan RP, Bonin KD, Budygin EA (2010) Optogenetic control of striatal dopamine release in rats. J Neurochem 114:1344–1352

    Google Scholar 

  97. Witten IB, Lin SC, Brodsky M, Prakash R, Diester I, Anikeeva P et al (2010) Cholinergic interneurons control local circuit activity and cocaine conditioning. Science 330:1677–1681

    Article  Google Scholar 

  98. Han X (2012) Optogenetics in the nonhuman primate. Prog Brain Res 196:215–233

    Article  Google Scholar 

  99. Carter BJ (2005) Adeno-associated virus vectors in clinical trials. Hum Gene Ther 16:541–550

    Article  Google Scholar 

  100. Lin JY, Knutsen PM, Muller A, Kleinfeld D, Tsien RY (2013) ReaChR: a red-shifted variant of channelrhodopsin enables deep transcranial optogenetic excitation. Nat Neurosci 16:1499–1508

    Article  Google Scholar 

  101. Chuong AS, Miri ML, Busskamp V, Matthews GA, Acker LC, Sorensen AT et al (2014) Noninvasive optical inhibition with a red-shifted microbial rhodopsin. Nat Neurosci 17:1123–1129

    Article  Google Scholar 

  102. Zhang J, Laiwalla F, Kim JA, Urabe H, Van Wagenen R, Song YK et al (2009) Integrated device for optical stimulation and spatiotemporal electrical recording of neural activity in light-sensitized brain tissue. J Neural Eng 6:055007

    Article  Google Scholar 

  103. Zhang J, Laiwalla F, Kim JA, Urabe H, Van Wagenen R, Song YK et al (2009) A microelectrode array incorporating an optical waveguide device for stimulation and spatiotemporal electrical recording of neural activity. Conf Proc IEEE Eng Med Biol Soc 2009:2046–2049

    Google Scholar 

  104. Chen S, Pei W, Gui Q, Chen Y, Zhao S, Wang H et al (2013) A fiber-based implantable multi-optrode array with contiguous optical and electrical sites. J Neural Eng 10:046020

    Article  Google Scholar 

  105. Ozden I, Wang J, Lu Y, May T, Lee J, Goo W et al (2013) A coaxial optrode as multifunction write-read probe for optogenetic studies in non-human primates. J Neurosci Methods 219:142–154

    Article  Google Scholar 

  106. Cao H, Gu L, Mohanty SK, Chiao JC (2013) An integrated muLED optrode for optogenetic stimulation and electrical recording. IEEE Trans Biomed Eng 60:225–229

    Article  Google Scholar 

  107. Iwai Y, Honda S, Ozeki H, Hashimoto M, Hirase H (2011) A simple head-mountable LED device for chronic stimulation of optogenetic molecules in freely moving mice. Neurosci Res 70:124–127

    Article  Google Scholar 

  108. Wentz CT, Bernstein JG, Monahan P, Guerra A, Rodriguez A, Boyden ES (2011) A wirelessly powered and controlled device for optical neural control of freely-behaving animals. J Neural Eng 8:046021

    Article  Google Scholar 

  109. Warden MR, Cardin JA, Deisseroth K (2014) Optical neural interfaces. Annu Rev Biomed Eng 16:103–129

    Article  Google Scholar 

  110. Davis GW (2006) Homeostatic control of neural activity: from phenomenology to molecular design. Annu Rev Neurosci 29:307–323

    Article  Google Scholar 

  111. Davis GW, Goodman CS (1998) Genetic analysis of synaptic development and plasticity: homeostatic regulation of synaptic efficacy. Curr Opin Neurobiol 8:149–156

    Article  Google Scholar 

  112. Marder E, Prinz AA (2002) Modeling stability in neuron and network function: the role of activity in homeostasis. Bioessays 24:1145–1154

    Article  Google Scholar 

  113. Ginsberg MD, Sternau LL, Globus MY, Dietrich WD, Busto R (1992) Therapeutic modulation of brain temperature: relevance to ischemic brain injury. Cerebrovasc Brain Metab Rev 4:189–225

    Google Scholar 

  114. Pérez-Otaño I, Ehlers MD (2005) Homeostatic plasticity and NMDA receptor trafficking. Trends Neurosci 28:229–238

    Article  Google Scholar 

  115. Turrigiano GG, Nelson SB (2000) Hebb and homeostasis in neuronal plasticity. Curr Opin Neurobiol 10:358–364

    Article  Google Scholar 

  116. Long MA, Fee MS (2008) Using temperature to analyse temporal dynamics in the songbird motor pathway. Nature 456:189–194

    Article  Google Scholar 

  117. Andrasfalvy BK, Zemelman BV, Tang J, Vaziri A (2010) Two-photon single-cell optogenetic control of neuronal activity by sculpted light. Proc Natl Acad Sci U S A 107:11981–11986

    Article  Google Scholar 

  118. Papagiakoumou E, Anselmi F, Bègue A, de Sars V, Glückstad J, Isacoff EY et al (2010) Scanless two-photon excitation of channelrhodopsin-2. Nat Methods 7:848–854

    Article  Google Scholar 

  119. Roberts TF, Gobes SMH, Murugan M, Olveczky BP, Mooney R (2012) Motor circuits are required to encode a sensory model for imitative learning. Nat Neurosci 15:1454–1459

    Google Scholar 

  120. Yizhar O, Fenno LE, Davidson TJ, Mogri M, Deisseroth K (2011) Optogenetics in neural systems. Neuron 71:9–34

    Article  Google Scholar 

  121. Miyashita T, Shao YR, Chung J, Pourzia O, Feldman DE (2013) Long-term channelrhodopsin-2 (ChR2) expression can induce abnormal axonal morphology and targeting in cerebral cortex. Front Neural Circuits 7:8

    Google Scholar 

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Acknowledgments

This work is supported by the Center for Integrated Smart Sensors funded by the Ministry of Science, ICT and Future Planning as the Global Frontier Project (CISS-2012M3A6A6054204) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (NRF-2014R1A2A2A09052449, 2014R1A1A1A05003770).

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Authors and Affiliations

  1. Department of Electronics Engineering, Ewha Womans University, Seoul, 120-750, South Korea

    Sang Beom Jun

  2. Department of Brain & Cognitive Sciences, Ewha Womans University, Seoul, 120-750, South Korea

    Sang Beom Jun

  3. Center for Robotics Research, Robotics and Media Institute, Korea Institute of Science and Technology, Seoul, South Korea

    Yoonseob Lim

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Correspondence to Sang Beom Jun .

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  1. Center for Integrated Smart Sensors, Yuseong-gu, Daejeon, Korea (Republic of)

    Chong-Min Kyung

  2. System LSI Research Center, Kyushu University, Fukuoka, Japan

    Hiroto Yasuura

  3. Circuits and Systems Division, Tsinghua University, Beijing, China

    Yongpan Liu

  4. National Tsing Hua University , Hsichu, Taiwan

    Youn-Long Lin

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Jun, S.B., Lim, Y. (2017). Implantable Optical Neural Interface. In: Kyung, CM., Yasuura, H., Liu, Y., Lin, YL. (eds) Smart Sensors and Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-33201-7_9

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