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Multiscale and Multimodal Imaging for Connectomics

Chapter
Part of the Progress in Optical Science and Photonics book series (POSP, volume 5)

Abstract

Recent advances in optical imaging tools for mapping the structural and functional connectomes have greatly augmented our understanding of the brains. The brain is a multilayered and multicompartmental organ where the structures possess multiple length scales, ranging from nanometer (single synapses) to centimeter (whole intact organ), and its functions take place at multiple timescales, ranging from sub-milliseconds (synaptic events) to years (behavioral changes). Therefore, neuroscientists need to image neurocircuits not only at nanometric spatial resolution but also in millisecond time frame in large brain volumes to adequately study neuronal functions. An ideal tool for brain imaging should provide high speed, high resolution, and high contrast with deep penetration in large tissue volumes and sufficient molecular specificity. Toward this end, recent progresses in the optical brain imaging technologies have allowed extracting unprecedented insights into brain. In this chapter, we discuss the various imaging modalities aiming for high-throughput brain imaging, as well as the challenges encountered in imaging the connectome.

Notes

Acknowledgements

We would like to acknowledge the Ministry of Science and Technology (MOST), Taiwan, and University Grants Commission (UGC), India, for their support to the biophotonics research projects at NYMU and JBC (UGC Grant No. F.5-376/2014-15/MRP/NERO/2181).

References

  1. 1.
    C.I. Bargmann, E. Marder, From the connectome to brain function. Nat. Methods 10(6), 483–490 (2013)Google Scholar
  2. 2.
    M. Kaiser, Neuroanatomy: connectome connects fly and mammalian brain networks. Curr. Biol. 25(10), R416–R418 (2015)Google Scholar
  3. 3.
    S. Herculano-Houzel, The human brain in numbers: a linearly scaled-up primate brain. Front. Hum. Neurosci. 3, 31 (2009)Google Scholar
  4. 4.
    A.S. Chiang et al., Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. Curr. Biol. 21(1), 1–11 (2011)MathSciNetGoogle Scholar
  5. 5.
    M. Helmstaedter, Cellular-resolution connectomics: challenges of dense neural circuit reconstruction. Nat. Methods 10(6), 501–507 (2013)Google Scholar
  6. 6.
    L. Silvestri, A.A. Mascaro, J. Lotti, L. Sacconi, F.S. Pavone, Advanced optical techniques to explore brain structure and function. J. Innovative Opt. Health Sci. 6(1), 1230002 (2013)Google Scholar
  7. 7.
    A.E. Pereda, Electrical synapses and their functional interactions with chemical synapses. Nat. Rev. Neurosci. 15(4), 250–263 (2014)Google Scholar
  8. 8.
    T.E. Behrens, O. Sporns, Human connectomics. Curr. Opin. Neurobiol. 22(1), 144–153 (2012)Google Scholar
  9. 9.
    J.L. Morgan, J.W. Lichtman, Why not connectomics? Nat. Methods 10(6), 494–500 (2013)Google Scholar
  10. 10.
    J. Yao, L.V. Wang, Photoacoustic brain imaging: from microscopic to macroscopic scales. Neurophotonics 1(1), 011003 (2014)Google Scholar
  11. 11.
    L. Degenhardt et al., Global burden of disease attributable to illicit drug use and dependence: findings from the Global Burden of Disease Study 2010. Lancet 382(9904), 1564–1574 (2010)Google Scholar
  12. 12.
    T. Vos et al., Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380(9859), 2163–2196 (2012)Google Scholar
  13. 13.
    J.W. Lichtman, W. Denk, The big and the small: challenges of imaging the brain’s circuits. Science 334(6056), 618–623 (2011)Google Scholar
  14. 14.
    O. Sporns, Making sense of brain network data. Nat. Methods 10(6), 491–493 (2013)Google Scholar
  15. 15.
    V.M. Ho, J.A. Lee, K.C. Martin, The cell biology of synaptic plasticity. Science 334(6056), 623–628 (2011)Google Scholar
  16. 16.
    C.I. Bargmann, Beyond the connectome: how neuromodulators shape neural circuits. BioEssays 34(6), 458–465 (2012)Google Scholar
  17. 17.
    B. Alvarez-Castelao, E.M. Schuman, The regulation of synaptic protein turnover. J. Biol. Chem. 290(48), 28623–28630 (2015)Google Scholar
  18. 18.
    M.P. Monopoli et al., Temporal proteomic profile of memory consolidation in the rat hippocampal dentate gyrus. Proteomics 11(21), 4189–4201 (2011)Google Scholar
  19. 19.
    S.J. Sigrist, B.L. Sabatini, Optical super-resolution microscopy in neurobiology. Cur. Opin. Neurobiol. 22(1), 86–93 (2012)Google Scholar
  20. 20.
    B. Asrican et al., Next-generation transgenic mice for optogenetic analysis of neural circuits. Front. Neural Circuit 7 (2013)Google Scholar
  21. 21.
    W. Denk, K. Svoboda, Photon upmanship: techreview why multiphoton imaging is more than a gimmick. Neuron 18, 351–357 (1997)Google Scholar
  22. 22.
    N. Korogod, C.C. Petersen, G.W. Knott, Ultrastructural analysis of adult mouse neocortex comparing aldehyde perfusion with cryo fixation. Elife 4, e05793 (2015)Google Scholar
  23. 23.
    B. Hammond et al., Toxicological evaluation of proteins introduced into food crops. Crit. Rev. Toxicol. 43(Sup2), 25–42 (2013)MathSciNetGoogle Scholar
  24. 24.
    C. Asbury, Brain Imaging Technologies and Their Applications in Neuroscience (The Dana Foundation, New York, 2011), pp. 1–45Google Scholar
  25. 25.
    R.C. Craddock et al., Imaging human connectomes at the macroscale. Nat. Methods 10(6), 524–539 (2013)Google Scholar
  26. 26.
    D. Le Bihan, M. Iima, Diffusion magnetic resonance imaging: what water tells us about biological tissues. PLoS Biol. 13(7), e1002203 (2015)Google Scholar
  27. 27.
    B.A. Mueller, K.O. Lim, L. Hemmy, J. Camchong, Diffusion MRI and its role in neuropsychology. Neuropsychol. Rev. 25(3), 250–271 (2015)Google Scholar
  28. 28.
    R.B. Buxton, The physics of functional magnetic resonance imaging (fMRI). Rep. Prog. Phys. 76(9), 096601 (2013)Google Scholar
  29. 29.
    M. Helmstaedter, K.L. Briggman, W. Denk, 3D structural imaging of the brain with photons and electrons. Curr. Opin. Neurobiol. 18(6), 633–641 (2008)Google Scholar
  30. 30.
    A. Dani, B. Huang, New resolving power for light microscopy: applications to neurobiology. Curr. Opin. Neurobiol. 20(5), 648–652 (2010)Google Scholar
  31. 31.
    J.G. White, E. Southgate, J.N. Thomson, S. Brenner, The structure of the nervous system of the nematode Caenorhabditis elegans: the mind of a worm. Phil. Trans. R. Soc. Lond 314, 1–340 (1986)Google Scholar
  32. 32.
    K.L. Briggman, D.D. Bock, Volume electron microscopy for neuronal circuit reconstruction. Curr. Opin. Neurobiol. 22(1), 154–161 (2012)Google Scholar
  33. 33.
    M. Gregorini, J. Wang, X.S. Xie, R.A. Milligan, A. Engel, Three-dimensional reconstruction of bovine brain V-ATPase by cryo-electron microscopy and single particle analysis. J. Struct. Biol. 158(3), 445–454 (2007)Google Scholar
  34. 34.
    L. Silvestri, A. Bria, L. Sacconi, G. Iannello, F.S. Pavone, Confocal light sheet microscopy: micron-scale neuroanatomy of the entire mouse brain. Opt. Express 20(18), 20582–20598 (2012)Google Scholar
  35. 35.
    M.B. Ahrens, M.B. Orger, D.N. Robson, J.M. Li, P.J. Keller, Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat. Methods 10(5), 413–420 (2013)Google Scholar
  36. 36.
    R. Kawakami et al., Visualizing hippocampal neurons with in vivo two-photon microscopy using a 1030 nm picosecond pulse laser. Sci. Rep. 3, srep01014 (2013)Google Scholar
  37. 37.
    M.N. Economo et al., A platform for brain-wide imaging and reconstruction of individual neurons. eLife 5, e10566 (2016)Google Scholar
  38. 38.
    S.W. Hell et al., Handbock of Biological Confocal Microscopy (Springer, New York, 2006), pp. 571–579Google Scholar
  39. 39.
    S.W. Hell et al., The 2015 super-resolution microscopy roadmap. J. Phys. D Appl. Phys. 48(44), 44300 (2015)Google Scholar
  40. 40.
    D.J. Smith, Ultimate resolution in the electron microscope? Mater. Today 11, 30–38 (2008)Google Scholar
  41. 41.
    S.C. Sidenstein et al., Multicolour multilevel STED nanoscopy of actin/spectrin organization at synapses. Sci. Rep. 6, 26725 (2016)Google Scholar
  42. 42.
    P.A. Santi, Light sheet fluorescence microscopy: a review. J. Histochem. Cytochem. 59(2), 129–138 (2011)Google Scholar
  43. 43.
    J.D. Manton, E.J. Rees, triSPIM: light sheet microscopy with isotropic super-resolution. Opt. Lett. 41(18), 4170–4173 (2016)Google Scholar
  44. 44.
    R. Heintzmann, G. Ficz, Breaking the resolution limit in light microscopy. Briefings in Funct. Genomics 5(4), 289–301 (2006)Google Scholar
  45. 45.
    X.L. Deán-Ben, H. López-Schier, D. Razansky, Optoacoustic micro-tomography at 100 volumes per second. Sci. Rep. 7(1), 6850 (2017)Google Scholar
  46. 46.
    Z. Wu et al., Multi-photon microscopy in cardiovascular research. Methods 130, 79–89 (2017)Google Scholar
  47. 47.
    Y. Chen et al., Review of advanced imaging techniques. J Pathol Inform 3, 22 (2012)Google Scholar
  48. 48.
    G. Follain, L. Mercier, N. Osmani, S. Harlepp, J.G. Goetz, Seeing is believing–multi-scale spatio-temporal imaging towards in vivo cell biology. J. Cell Sci. 130(1), 23–38 (2017)Google Scholar
  49. 49.
    M. Maglione, S.J. Sigrist, Seeing the forest tree by tree: super-resolution light microscopy meets the neurosciences. Nat. Neurosci. 16(7), 790–797 (2013)Google Scholar
  50. 50.
    L. Schermelleh, R. Heintzmann, H. Leonhardt, A guide to super-resolution fluorescence microscopy. J. Cell Biol. 190(2), 165–175 (2010)Google Scholar
  51. 51.
    S. Zhang et al., Diagnosis of gastroesophageal reflux disease using real-time magnetic resonance imaging. Scientific reports 5, 12112 (2015)Google Scholar
  52. 52.
    X.L. Deán-Ben et al., Functional optoacoustic neuro-tomography for scalable whole-brain monitoring of calcium indicators. Light Sci. Appl. 5(12), e16201 (2016)Google Scholar
  53. 53.
    Z. Zhi, W. Qin, J. Wang, W. Wei, R.K. Wang, 4D optical coherence tomography-based micro-angiography achieved by 1.6-MHz FDML swept source. Opt. Lett. 40(8), 1779–1782 (2015)Google Scholar
  54. 54.
    S. Choi et al., Development of a high speed laser scanning confocal microscope with an acquisition rate up to 200 frames per second. Opt. Express 21(20), 23611–23618 (2013)Google Scholar
  55. 55.
    A.D. Grand, S. Bonfig, Selecting a microscope based on imaging depth. Olympus https://www.photonics.com/a57114/Selecting_a_Microscope_Based_on_Imaging_Depth. Accessed: 11 Jan 2018
  56. 56.
  57. 57.
    K. Bahlmann et al., Multifocal multiphoton microscopy (MMM) at a frame rate beyond 600 Hz. Opt. Express 15(17), 10991–10998 (2007)Google Scholar
  58. 58.
    R. Tomer et al., SPED light sheet microscopy: fast mapping of biological system structure and function. Cell 163(7), 1796–1806 (2015)Google Scholar
  59. 59.
    R. Schmidt et al., Spherical nanosized focal spot unravels the interior of cells. Nat. Methods 5(6), 539–544 (2008)Google Scholar
  60. 60.
    J. Schneider et al., Ultrafast, temporally stochastic STED nanoscopy of millisecond dynamics. Nat. Methods 12(9), 827–830 (2015)Google Scholar
  61. 61.
    M.A. Lauterbach, E. Ronzitti, J.R. Sternberg, C. Wyart, V. Emiliani, Fast calcium imaging with optical sectioning via HiLo microscopy. PLoS ONE 10(12), e0143681 (2015)Google Scholar
  62. 62.
    F. Huang et al., Video-rate nanoscopy using sCMOS camera-specific single-molecule localization algorithms. Nat. Methods 10(7), 653–658 (2013)Google Scholar
  63. 63.
    M. Fernández-Suárez, A.Y. Ting, Fluorescent probes for super-resolution imaging in living cells. Nat. Rev. Mol. Cell Biol. 9(12), 929–943 (2008)Google Scholar
  64. 64.
    T.V. Truong, W. Supatto, D.S. Koos, J.M. Choi, S.E. Fraser, Deep and fast live imaging with two-photon scanned light-sheet microscopy. Nat. Methods 8(9), 757–760 (2011)Google Scholar
  65. 65.
    V. Westphal, S.W. Hell, Nanoscale resolution in the focal plane of an optical microscope. Phys. Rev. Lett. 94(14), 143903 (2005)Google Scholar
  66. 66.
    E. Betzig et al., Imaging intracellular fluorescent proteins at nanometer resolution. Science 313(5793), 1642–1645 (2006)Google Scholar
  67. 67.
    M.G. Gustafsson, Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. PNAS 102(37), 13081–13086 (2005)Google Scholar
  68. 68.
    F. Chen, P.W. Tillberg, E.S. Boyden, Expansion microscopy. Science 347(6221), 543–548 (2015)Google Scholar
  69. 69.
    T. Zimmermann, J. Rietdorf, R. Pepperkok, Spectral imaging and its applications in live cell microscopy. FEBS Lett. 546(1), 87–92 (2003)Google Scholar
  70. 70.
    L. Wei et al., Super-multiplex vibrational imaging. Nature 544(7651), 465–470 (2017)Google Scholar
  71. 71.
    W. Supatto, T.V. Truong, D. Débarre, E. Beaurepaire, Advances in multiphoton microscopy for imaging embryos. Curr. Opin. Genet. Dev. 21(5), 538–548 (2011)Google Scholar
  72. 72.
    K. Wang, N.G. Horton, K. Charan, C. Xu, Advanced fiber soliton sources for nonlinear deep tissue imaging in biophotonics. IEEE J. Sel. Top. Quantum Electron. 20(2), 50–60 (2014)Google Scholar
  73. 73.
    T.F. Holekamp, D. Turaga, T.E. Holy, Fast three-dimensional fluorescence imaging of activity in neural populations by objective-coupled planar illumination microscopy. Neuron 57(5), 661–672 (2008)Google Scholar
  74. 74.
    A.S. Chiang et al., Three-dimensional mapping of brain neuropils in the cockroach, Diploptera punctata. J. Comp. Neurol. 440(1), 1–11 (2001)MathSciNetGoogle Scholar
  75. 75.
    E.A. Susaki et al., Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protocols 10(11), 1709–1727 (2015)Google Scholar
  76. 76.
    K. Chung, K. Deisseroth, CLARITY for mapping the nervous system. Nat. Methods 10(6), 508–513 (2013)Google Scholar
  77. 77.
    S. Liu et al., Three-dimensional, isotropic imaging of mouse brain using multi-view deconvolution light sheet microscopy. J. Innovative Opt. Health Sci. 10(5), 1743006 (2017)MathSciNetGoogle Scholar
  78. 78.
    N. Ji, H. Shroff, H. Zhong, E. Betzig, Advances in the speed and resolution of light microscopy. Curr. Opin. Neurobiol. 18(6), 605–616 (2008)Google Scholar
  79. 79.
  80. 80.
  81. 81.
    G. McConnell et al., A novel optical microscope for imaging large embryos and tissue volumes with sub-cellular resolution throughout. Elife 5, e18659 (2016)Google Scholar
  82. 82.
    T. Panier, S.A. Romano, R. Olive, T. Pietri, G. Sumbre, R. Candelier, G. Debrégeas, Fast functional imaging of multiple brain regions in intact zebrafish larvae using selective plane illumination microscopy. Front. Neural Circuits 7, 65 (2013)Google Scholar
  83. 83.
    N. George, Spinning disk vs. laser-scanning confocal microscopes. Photonics Spectra 38, 69–75 (2004)Google Scholar
  84. 84.
    K.H. Kim et al., Multifocal multiphoton microscopy based on multianode photomultiplier tubes. Opt. Express 15(18), 11658–11678 (2007)Google Scholar
  85. 85.
    L.V. Wang, S. Hu, Photoacoustic tomography: in vivo imaging from organelles to organs. Science 335(6075), 1458–1462 (2012)Google Scholar
  86. 86.
    J. Lefebvre, A. Castonguay, P. Pouliot, M. Descoteaux, F. Lesage, Whole mouse brain imaging using optical coherence tomography: reconstruction, normalization, segmentation, and comparison with diffusion MRI. Neurophotonics 4(4), 041501 (2017)Google Scholar
  87. 87.
    E. Osiac et al., Optical coherence tomography as a promising imaging tool for brain investigations. Rom. J. Morphol. Embryol. 55(2), 507–512 (2014)Google Scholar
  88. 88.
    J. Men et al., Optical coherence tomography for brain imaging and developmental biology. IEEE J. Sel. Top. Quantum Electron. 22(4), 120–132 (2016)Google Scholar
  89. 89.
    B. Huang, H. Babcock, X. Zhuang, Breaking the diffraction barrier: super-resolution imaging of cells. Cell 143(7), 1047–1058 (2010)Google Scholar
  90. 90.
    L.W. Swanson, J.W. Lichtman, From Cajal to connectome and beyond. Annu. Rev. Neurosci. 39, 197–216 (2016)Google Scholar
  91. 91.
    B.N. Giepmans, S.R. Adams, M.H. Ellisman, R.Y. Tsien, The fluorescent toolbox for assessing protein location and function. Science 312(5771), 217–224 (2006)Google Scholar
  92. 92.
    F. Lagugné-Labarthet, Y.R. Shen, in Optical Imaging and Microscopy. ed. by P. Török, F.-J. Kao. Springer Series in Optical Sciences, vol. 87 (Springer, Berlin, Heidelberg, 2007), vol. 2, pp. 237–268Google Scholar
  93. 93.
    M.J. Sanderson, I. Smith, I. Parker, M.D. Bootman, Fluorescence microscopy. Cold Spring Harbor Protoc. 10, 2131 (2014).  https://doi.org/10.1101/pdb.top071795CrossRefGoogle Scholar
  94. 94.
    J.A. Conchello, J.W. Lichtman, Optical sectioning microscopy. Nat. Methods 2(12), 920 (2005)Google Scholar
  95. 95.
    M. Symms, H.R. Jäger, K. Schmierer, T.A. Yousry, A review of structural magnetic resonance neuroimaging. J. Neurol. 75(9), 1235–1244 (2004)Google Scholar
  96. 96.
    X. Wang et al., Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain. Nat. Biotech. 21(7), 803–806 (2003)Google Scholar
  97. 97.
    X. Tao et al., in Proceedings of SPIE: Neural Imaging and Sensing (SPIE, 2017), vol. 10051, p. 100510RGoogle Scholar
  98. 98.
    M. Minsky, Memoir on inventing the confocal scanning microscope. Scanning 10(4), 128–138 (1988)MathSciNetGoogle Scholar
  99. 99.
    C.J.R. Sheppard, A. Choudhury, Image formation in the scanning microscope. J. Mod. Optic. 24(10), 1051–1073 (1977)Google Scholar
  100. 100.
    R.H. Webb, Confocal optical microscopy. Rep. Prog. Phys. 59(3), 427 (1996)Google Scholar
  101. 101.
    C. Cremer, B.R. Masters, Resolution enhancement techniques in microscopy. Eur. Phys. J. H 38(3), 281–344 (2013)Google Scholar
  102. 102.
    G. Cox, C.J. Sheppard, Practical limits of resolution in confocal and non-linear microscopy. Microsc. Res. Tech. 63(1), 18–22 (2004)Google Scholar
  103. 103.
    B.R. Masters, M. Böhnke, Three-dimensional confocal microscopy of the living human eye. Annu. Rev. Biomed. Eng. 4(1), 69–91 (2002)Google Scholar
  104. 104.
    P.V. Ravichandra, H. Vemisetty, K. Deepthi, S. Jayaprada Reddy, D. Ramkiran, Comparative evaluation of marginal adaptation of BiodentineTM and other commonly used root end filling materials-an invitro study. J. Clin. Diagn. Res.—JDCR 8(3), 243 (2014)Google Scholar
  105. 105.
    N.S. Claxton, T.J. Fellers, N.W. Davidson, Laser scanning confocal microscopy. Department of Optical Microscopy and Digital Imaging, Florida State University, Tallahassee (2006). http://www.olympusconfocal.com/theory/LSCMIntro.pdf
  106. 106.
    J. Jonkman, C.M. Brown, Any way you slice it—A comparison of confocal microscopy techniques. J. Biomol. Tech.: JBT 26(2), 54 (2015)Google Scholar
  107. 107.
    M. Petráň, M. Hadravský, M.D. Egger, R. Galambos, Tandem-scanning reflected-light microscope. JOSA 58(5), 661–664 (1968)Google Scholar
  108. 108.
    G. De Luca, R. Breedijk, R. Hoebe, S. Stallinga, E. Manders, Re-scan confocal microscopy (RCM) improves the resolution of confocal microscopy and increases the sensitivity. Methods Appl. Fluores. 5(1), 015002 (2017)Google Scholar
  109. 109.
    G.M. De Luca et al., Re-scan confocal microscopy: scanning twice for better resolution. Biomed. Opt. Express 4(11), 2644–2656 (2013)Google Scholar
  110. 110.
    R. Engelmann, T. Anhut, I. Kleppe, K. Weisshart, Airyscanning: Evoking the full potential of confocal microscopy. Imaging Microsc. 3, 20–21 (2014)Google Scholar
  111. 111.
    J. Huff, The Airyscan detector from ZEISS: confocal imaging with improved signal-to-noise ratio and super-resolution. Nat. Methods 12(12), 1–2 (2015)Google Scholar
  112. 112.
    T. Azuma, T. Kei, Super-resolution spinning-disk confocal microscopy using optical photon reassignment. Opt. Express 23(11), 15003–15011 (2015)Google Scholar
  113. 113.
    J. Huff, The fast mode for ZEISS LSM 880 with Airyscan: high-speed confocal imaging with super-resolution and improved signal-to-noise ratio. Nat. Methods 13(11), I-II (2016)Google Scholar
  114. 114.
    M.D. Egger, M. Petran, New reflected-light microscope for viewing unstained brain and ganglion cells. Science 157(3786), 305–307 (1967)Google Scholar
  115. 115.
    M. Dailey, G. Marrs, J. Satz, M. Waite, Concepts in imaging and microscopy: Exploring biological structure and function with confocal microscopy. Biol. Bull. 197(2), 115–122 (1999)Google Scholar
  116. 116.
    T. Hosokawa, D.A. Rusakov, T.V. Bliss, A. Fine, Repeated confocal imaging of individual dendritic spines in the living hippocampal slice: evidence for changes in length and orientation associated with chemically induced LTP. J. Neurosci. 15(8), 5560–5573 (1995)Google Scholar
  117. 117.
    A. Villringer et al., Confocal laser microscopy to study microcirculation on the rat brain surface in vivo. Brain Res. 504(1), 159–160 (1989)Google Scholar
  118. 118.
    P.V. Belichenko, A. Dahlström, Studies on the 3-dimensional architecture of dendritic spines and varicosities in human cortex by confocal laser scanning microscopy and Lucifer yellow microinjections. J. Neurosci. Methods 57(1), 55–61 (1995)Google Scholar
  119. 119.
    T.R. Brazelton, F.M. Rossi, G.I. Keshet, H.M. Blau, From marrow to brain: expression of neuronal phenotypes in adult mice. Science 290(5497), 1775–1779 (2000)Google Scholar
  120. 120.
    H.J. Romijn et al., Double immunolabeling of neuropeptides in the human hypothalamus as analyzed by confocal laser scanning fluorescence microscopy. J. Histochem. Cytochem. 47(2), 229–235 (1999)Google Scholar
  121. 121.
    A. Rodriguez et al., Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods 30(1), 94–105 (2003)Google Scholar
  122. 122.
    Y. Takahara, N. Matsuki, Y. Ikegaya, Nipkow confocal imaging from deep brain tissues. J. Integr. Neurosci. 10(1), 121–129 (2011)Google Scholar
  123. 123.
    R.C. Gutierre, D. Vannucci Campos, R.A. Mortara, A.A. Coppi, R.M. Arida, Reflection imaging of China ink-perfused brain vasculature using confocal laser-scanning microscopy after clarification of brain tissue by the Spalteholz method. J. Anat. 230(4), 601–606 (2017)Google Scholar
  124. 124.
    W. Spalteholz, Uber das Durchsichtigmachen von menschlichen und tierischen Praparaten (S. Hierzel, Leipzig, 1914)Google Scholar
  125. 125.
    A. Azaripour et al., A survey of clearing techniques for 3D imaging of tissues with special reference to connective tissue. Prog. Histochem. Cytoc. 51(2), 9–23 (2016)Google Scholar
  126. 126.
    C. Grienberger, A. Konnerth, Imaging calcium in neurons. Neurons 73(5), 862–885 (2002).  https://doi.org/10.1016/j.neuron.2012.02.011Google Scholar
  127. 127.
    A. Ustione, D.W. Piston, A simple introduction to multiphoton microscopy. J. Microsc. 243(3), 221–226 (2011)Google Scholar
  128. 128.
    S.W. Hell et al., Three-photon excitation in fluorescence microscopy. J. Biomed. Opt. 1(1), 71–74 (1996)MathSciNetGoogle Scholar
  129. 129.
    B.A. Wilt et al., Advances in light microscopy for neuroscience. Annu. Rev. Neurosci. 32, 435–506 (2009)Google Scholar
  130. 130.
    J. Tønnesen, U.V. Nägerl, Superresolution imaging for neuroscience. Exp. Neurol. 242, 33–40 (2013)Google Scholar
  131. 131.
    J.B. Ding, K.T. Takasaki, B.L. Sabatini, Supraresolution imaging in brain slices using stimulated-emission depletion two-photon laser scanning microscopy. Neuron 63(4), 429–437 (2009)Google Scholar
  132. 132.
    J. Rietdorf, E.H.K. Stelzer, in Handbook Of Biological Confocal Microscopy, ed. by J.P. Pawley (Springer, Boston, MA, 2006)Google Scholar
  133. 133.
    M.G. Gustafsson, D.A. Agard, J.W. Sedat, I5 M: 3D widefield light microscopy with better than 100 nm axial resolution. J. Microsc. 195(1), 10–16 (1999)Google Scholar
  134. 134.
    J. Bewersdorf, R. Schmidt, S.W. Hell, Comparison of I5 M and 4Pi-microscopy. J. Microsc. 222(2), 105–117 (2006)MathSciNetGoogle Scholar
  135. 135.
    M.A. Lauterbach, C. Eggeling, in Super-Resolution Microscopy Techniques in the Neurosciences ed. by E.F. Fornasiero, S.O. Rizzoli. Neuromethods, vol. 86 (Humana Press, Totowa, NJ, 2014), pp. 41–71.  https://doi.org/10.1007/978-1-62703-983-3_3
  136. 136.
    A. Egner, S.W. Hell, Fluorescence microscopy with super-resolved optical sections. Trends Cell Biol. 15(4), 207–215 (2005)Google Scholar
  137. 137.
    C.G. Galbraith, J.A. Galbraith, Super-resolution microscopy at a glance. J. Cell Sci. 124(10), 1607–1611 (2011)Google Scholar
  138. 138.
    C.J.R. Sheppard, Resolution and super-resolution. Microsc. Res. Tech. 80, 590–598 (2017)Google Scholar
  139. 139.
    L. Möckl, D.C. Lamb, C. Bräuchle, Super-resolved fluorescence microscopy: nobel prize in chemistry 2014 for Eric Betzig, Stefan Hell, and William E. Moerner. Angewandte Chemie Int. Ed. 53(51), 13972–13977 (2014)Google Scholar
  140. 140.
    The nobel prize in chemistry. Press Release (2014). https://www.nobelprize.org/nobel_prizes/chemistry/laureates/2014/press.html. Accessed 8 Oct 2014
  141. 141.
    G. Keiser, Biophotonics: Concepts to Applications (Springer, Singapore, 2016)Google Scholar
  142. 142.
    S.W. Hell, J. Wichmann, Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy. Opt. Lett. 19(11), 780–782 (1994)Google Scholar
  143. 143.
    S.W. Hell, Toward fluorescence nanoscopy. Nat. Biotechnol. 21(11), 1347–1355 (2003)Google Scholar
  144. 144.
    M.G. Gustafsson, Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy. J. Microsc. 198(2), 82–87 (2000)Google Scholar
  145. 145.
    S.T. Hess, T.P. Girirajan, M.D. Mason, Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys. J. 91(11), 4258–4272 (2006)Google Scholar
  146. 146.
    M.J. Rust, M. Bates, X. Zhuang, Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3(10), 793–796 (2006)Google Scholar
  147. 147.
    B. Huang, M. Bates, X. Zhuang, Super-resolution fluorescence microscopy. Annu. Rev. Biochem. 78, 993–1016 (2009)Google Scholar
  148. 148.
    B. Huang, Super-resolution optical microscopy: multiple choices. Curr. Opin. Chem. Biol. 14(1), 10–14 (2010)Google Scholar
  149. 149.
    M. Heilemann, Fluorescence microscopy beyond the diffraction limit. J. Biotechnol. 149(4), 243–251 (2010)Google Scholar
  150. 150.
    B.O. Leung, K.C. Chou, Review of super-resolution fluorescence microscopy for biology. Appl. Spectrosc. 65(9), 967–980 (2011)Google Scholar
  151. 151.
    T.J. Gould, S.T. Hess, Nanoscale biological fluorescence imaging: Breaking the diffraction barrier. Methods Cell Biol. 89, 329–358 (2008)Google Scholar
  152. 152.
    T.A. Klar, S.W. Hell, Subdiffraction resolution in far-field fluorescence microscopy. Opt. Lett. 24(14), 954–956 (1999)Google Scholar
  153. 153.
    G. Donnert et al., Macromolecular-scale resolution in biological fluorescence microscopy. PNAS 103(31), 11440–11445 (2006)Google Scholar
  154. 154.
    E. Rittweger, K.Y. Han, S.E. Irvine, C. Eggeling, S.W. Hell, STED microscopy reveals crystal colour centres with nanometric resolution. Nat. Photonics 3(3), 144–147 (2009)Google Scholar
  155. 155.
    M. Dyba, S.W. Hell, Focal spots of size λ/23 open up far-field florescence microscopy at 33 nm axial resolution. Phys. Rev. Lett. 88(16), 163901 (2002)Google Scholar
  156. 156.
    M. Hofmann, C. Eggeling, S. Jakobs, S.W. Hell, Breaking the diffraction barrier in fluorescence microscopy at low light intensities by using reversibly photoswitchable proteins. PNAS 102(49), 17565–17569 (2005)Google Scholar
  157. 157.
    S.W. Hell, Far-field optical nanoscopy. Science 316(5828), 1153–1158 (2007)Google Scholar
  158. 158.
    E. D’Este et al., Subcortical cytoskeleton periodicity throughout the nervous system. Sci. Rep. 6, 22741 (2016)Google Scholar
  159. 159.
    M.A. Schwentker, H. Bock, M. Hofmann, S. Jakobs, J. Bewersdorf, C. Eggeling, S.W. Hell, Wide-field subdiffraction RESOLFT microscopy using fluorescent protein photoswitching. Microsc. Res. Tech. 70, 269–280 (2007).  https://doi.org/10.1002/jemt.20443Google Scholar
  160. 160.
    S. Bretschneider, C. Eggeling, S.W. Hell, Breaking the diffraction barrier in fluorescence microscopy by optical shelving. Phys. Rev. Lett. 98(21), 218103 (2007)Google Scholar
  161. 161.
    S.W. Hell, M. Kroug, Ground-state-depletion fluorescence microscopy: A concept for breaking the diffraction resolution limit. Appl. Phys. B: Lasers Opt. 60(5), 495–497 (1995)Google Scholar
  162. 162.
    S.W. Hell, M. Dyba, S. Jakobs, Concepts for nanoscale resolution in fluorescence microscopy. Curr. Opin. Neurobiol. 14(5), 599–609 (2004)Google Scholar
  163. 163.
    S.W. Hell, Microscopy and its focal switch. Nat. Methods 6(1), 24–32 (2009)MathSciNetGoogle Scholar
  164. 164.
    K.I. Willig, S.O. Rizzoli, V. Westphal, R. Jahn, S.W. Hell, STED microscopy reveals that synaptotagmin remains clustered after synaptic vesicle exocytosis. Nature 440(7086), 935–939 (2006)Google Scholar
  165. 165.
    R.J. Kittel et al., Bruchpilot promotes active zone assembly, Ca2+ channel clustering, and vesicle release. Science 312(5776), 1051–1054 (2006)Google Scholar
  166. 166.
    J.J. Sieber, K.I. Willig, R. Heintzmann, S.W. Hell, T. Lang, The SNARE motif is essential for the formation of syntaxin clusters in the plasma membrane. Biophys. J. 90(8), 2843–2851 (2006)Google Scholar
  167. 167.
    U.V. Nägerl, K.I. Willig, B. Hein, S.W. Hell, T. Bonhoeffer, Live-cell imaging of dendritic spines by STED microscopy. PNAS 105(48), 18982–18987 (2008)Google Scholar
  168. 168.
    S. Fendl, J. Pujol-Martí, J. Ryan, A. Borst, R. Kasper, in Light Microscopy: Methods and Protocols ed. by Y., M.H., H. vol. 1563 (Humana Press, New York, NY, 2017), pp. 143–150Google Scholar
  169. 169.
    S. Berning, K.I. Willig, H. Steffens, P. Dibaj, S.W. Hell, Nanoscopy in a living mouse brain. Science 335(6068), 551 (2012)Google Scholar
  170. 170.
    V. Westphal et al., Video-rate far-field optical nanoscopy dissects synaptic vesicle movement. Science 320(5873), 246–249 (2008)Google Scholar
  171. 171.
    Y. Hua et al., A readily retrievable pool of synaptic vesicles. Nat. Neurosci. 14(7), 833–839 (2011)Google Scholar
  172. 172.
    N.T. Urban, K.I. Willig, S.W. Hell, U.V. Nägerl, STED nanoscopy of actin dynamics in synapses deep inside living brain slices. Biophys. J. 101(5), 1277–1284 (2011)Google Scholar
  173. 173.
    I. Testa et al., Nanoscopy of living brain slices with low light levels. Neuron 75(6), 992–1000 (2012)Google Scholar
  174. 174.
    S.A. Meyer et al., Super-resolution imaging of ciliary microdomains in isolated olfactory sensory neurons using a custom two-color stimulated emission depletion microscope. J. Biomed. Opt. 21(6), 066017 (2016)Google Scholar
  175. 175.
    R. Chéreau, G.E. Saraceno, J. Angibaud, D. Cattaert, U.V. Nägerl, Superresolution imaging reveals activity-dependent plasticity of axon morphology linked to changes in action potential conduction velocity. PNAS 114(6), 1401–1406 (2017)Google Scholar
  176. 176.
    E. D’Este, D. Kamin, F. Balzarotti, S.W. Hell, Ultrastructural anatomy of nodes of Ranvier in the peripheral nervous system as revealed by STED microscopy. PNAS 114(2), E191–E199 (2017)Google Scholar
  177. 177.
    L. Schermelleh et al., Subdiffraction multicolor imaging of the nuclear periphery with 3D structured illumination microscopy. Science 320(5881), 1332–1336 (2008)Google Scholar
  178. 178.
    K. Wicker, in Super-Resolution Microscopy Techniques in the Neurosciences ed. by E.F. Fornasiero, S.O. Rizzoli (Humana Press, 2014), pp. 133–165Google Scholar
  179. 179.
    R. Heintzmann, M.G. Gustafsson, Subdiffraction resolution in continuous samples. Nat. Photonics 3(7), 362–364 (2009)Google Scholar
  180. 180.
    M.G. Gustafsson et al., Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination. Biophys. J. 94(12), 4957–4970 (2008)Google Scholar
  181. 181.
    L. Shao et al., I5S: wide-field light microscopy with 100-nm-scale resolution in three dimensions. Biophys. J. 94(12), 4971–4983 (2008)Google Scholar
  182. 182.
    S. Usuki, T. Takada, K.T. Miura, Optical microscopy with improved resolution using two-beam interference of low-coherence light. Measurement 78, 373–380 (2016)Google Scholar
  183. 183.
    J. Pielage et al., A presynaptic giant ankyrin stabilizes the NMJ through regulation of presynaptic microtubules and transsynaptic cell adhesion. Neuron 58(2), 195–209 (2008)Google Scholar
  184. 184.
    R. Heintzmann, T.M. Jovin, C. Cremer, Saturated patterned excitation microscopy—a concept for optical resolution improvement. J. Opt. Soc. Am. A 19(8), 1599–1609 (2002).  https://doi.org/10.1364/JOSAA.19.001599Google Scholar
  185. 185.
    E.H. Rego et al., Nonlinear structured-illumination microscopy with a photoswitchable protein reveals cellular structures at 50-nm resolution. PNAS 109(3), E135–E143 (2012)Google Scholar
  186. 186.
    X. Long, J. Colonell, A.M. Wong, R.H. Singer, T. Lionnet, Quantitative mRNA imaging throughout the entire Drosophila brain. Nat. Methods 14(7), 703–706 (2017)Google Scholar
  187. 187.
    H. Gong et al., High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. Nature communications 7, 12142 (2016)Google Scholar
  188. 188.
    B. Littleton, K. Lai, D. Longstaff, V. Sarafis, P. Munroe, N. Heckenberg, H. Rubinsztein-Dunlop, Coherent super-resolution microscopy via laterally structured illumination. Micron 38(2), 150–157 (2007)Google Scholar
  189. 189.
    S., H., D.K., W., B., S., D.S., R., in Synapse Development. Methods in Molecular Biology ed. by A., P. vol. 1538 (Humana Press, New York, NY, 2017), pp. 155–167Google Scholar
  190. 190.
    M. Schouten et al., Imaging dendritic spines of rat primary hippocampal neurons using structured illumination microscopy. J. Vis. Exp.: JoVE 87, e51276 (2014)Google Scholar
  191. 191.
    T. Klein, S. Proppert, M. Sauer, Eight years of single-molecule localization microscopy. Histochem. Cell Biol. 141(6), 561–575 (2014)Google Scholar
  192. 192.
    R.E. Thompson, D.R. Larson, W.W. Webb, Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82(5), 2775–2783 (2002)Google Scholar
  193. 193.
    A. Yildiz, P.R. Selvin, Fluorescence imaging with one nanometer accuracy: application to molecular motors. Acc. Chem. Res. 38(7), 574–582 (2005)Google Scholar
  194. 194.
    A. Yildiz et al., Myosin V walks hand-over-hand: single fluorophore imaging with 1.5-nm localization. Science 300(5628), 2061–2065 (2003)Google Scholar
  195. 195.
    S.K. Saka, in Super-Resolution Microscopy Techniques in the Neurosciences ed. by E.F. Fornasiero, S.O. Rizzoli (Humana Press, 2014), pp. 13–40Google Scholar
  196. 196.
    W.E. Moerner, Microscopy beyond the diffraction limit using actively controlled single molecules. J. Microsc. 246(3), 213–220 (2012)Google Scholar
  197. 197.
    J. Lippincott-Schwartz, G.H. Patterson, Photoactivatable fluorescent proteins for diffraction-limited and super-resolution imaging. Trends Cell Biol. 19(11), 555–565 (2009)Google Scholar
  198. 198.
    M. Bates, T.R. Blosser, X. Zhuang, Short-range spectroscopic ruler based on a single-molecule optical switch. Phys. Rev. Lett. 94(10), 108101 (2005)Google Scholar
  199. 199.
    N.C. Verma, C. Rao, C.K. Nandi, Nitrogen-doped biocompatible carbon dot as a fluorescent probe for STORM nanoscopy. J. Phys. Chem. C 122, 8, 4704–4709 (2018)Google Scholar
  200. 200.
    G. Patterson, M. Davidson, S. Manley, J. Lippincott-Schwartz, Superresolution imaging using single-molecule localization. Annu. Rev. Phys. Chem. 61, 345–367 (2010)Google Scholar
  201. 201.
    A. Dani, B. Huang, J. Bergan, C. Dulac, X. Zhuang, Superresolution imaging of chemical synapses in the brain. Neuron 65(8), 843–856 (2010)Google Scholar
  202. 202.
    P. Dedecker, C. Flors, J.I. Hotta, H. Uji-i, J. Hofkens, 3D nanoscopy: bringing biological nanostructures into sharp focus. Angew. Chem. Int. Ed. 46(44), 8330–8332 (2007)Google Scholar
  203. 203.
    M. Bates, B. Huang, X. Zhuang, Super-resolution microscopy by nanoscale localization of photo-switchable fluorescent probes. Curr. Opin. Chem. Biol. 12(5), 505–514 (2008)Google Scholar
  204. 204.
    A. Egner et al., Fluorescence nanoscopy in whole cells by asynchronous localization of photoswitching emitters. Biophys. J. 93(9), 3285–3290 (2007)Google Scholar
  205. 205.
    J. Fölling et al., Fluorescence nanoscopy by ground-state depletion and single-molecule return. Nat. Methods 5(11), 943–945 (2008)Google Scholar
  206. 206.
    A. Sharonov, R.M. Hochstrasser, Wide-field subdiffraction imaging by accumulated binding of diffusing probes. PNAS 103(50), 18911–18916 (2006)Google Scholar
  207. 207.
    M. Heilemann et al., Subdiffraction-resolution fluorescence imaging with conventional fluorescent probes. Angew. Chem. Int. Ed. 47(33), 6172–6176 (2008)Google Scholar
  208. 208.
    S. Schedin-Weiss, I. Caesar, B. Winblad, H. Blom, L.O. Tjernberg, Super-resolution microscopy reveals γ-secretase at both sides of the neuronal synapse. Acta Neuropathol.Commun. 4(1), 29 (2016)Google Scholar
  209. 209.
    N.A. Frost, H. Shroff, H. Kong, E. Betzig, T.A. Blanpied, Single-molecule discrimination of discrete perisynaptic and distributed sites of actin filament assembly within dendritic spines. Neuron 67(1), 86–99 (2010)Google Scholar
  210. 210.
    Y.M. Sigal, C.M. Speer, H.P. Babcock, X. Zhuang, Mapping synaptic input fields of neurons with super-resolution imaging. Cell 163(2), 493–505 (2015)Google Scholar
  211. 211.
    B. Dudok et al., Cell-specific STORM super-resolution imaging reveals nanoscale organization of cannabinoid signaling. Nat. Neurosci. 18(1), 75–86 (2015)Google Scholar
  212. 212.
    J. Zhang, C.M. Carver, F.S. Choveau, M.S. Shapiro, Clustering and Functional Coupling of Diverse Ion Channels and Signaling Proteins Revealed by Super-resolution STORM Microscopy in Neurons. Neuron 92(2), 461–478 (2016)Google Scholar
  213. 213.
    H. Zhong, Applying superresolution localization-based microscopy to neurons. Synapse 69(5), 283–294 (2015)Google Scholar
  214. 214.
    K. Xu, G. Zhong, X. Zhuang, Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science 339(6118), 452–456 (2013)Google Scholar
  215. 215.
    T. Yoshimura, S.R. Stevens, C. Leterrier, M.C. Stankewich, M.N. Rasband, Developmental changes in expression of βIV spectrin splice variants at axon initial segments and nodes of ranvier. Front. Cell. Neurosci. 10, 304 (2017)Google Scholar
  216. 216.
    K. Xu, H.P. Babcock, X. Zhuang, Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton. Nat. Methods 9(2), 185–188 (2012)Google Scholar
  217. 217.
    K.F. Tehrani, J. Xu, Y. Zhang, P. Shen, P. Kner, Adaptive optics stochastic optical reconstruction microscopy (AO-STORM) using a genetic algorithm. Opt. Express 23(10), 13677–13692 (2015)Google Scholar
  218. 218.
    M. Lakadamyali, H. Babcock, M. Bates, X. Zhuang, J. Lichtman, 3D multicolor super-resolution imaging offers improved accuracy in neuron tracing. PLoS ONE 7(1), e30826 (2012)Google Scholar
  219. 219.
    J. Vangindertael et al., Super-resolution mapping of glutamate receptors in C. elegans by confocal correlated PALM. Sci. Rep. 5, 13532 (2015)Google Scholar
  220. 220.
    L. Barna et al., Correlated confocal and super-resolution imaging by VividSTORM. Nat. Protoc. 11(1), 163–183 (2016)Google Scholar
  221. 221.
    T.P. Li, T.A. Blanpied, Control of Transmembrane Protein Diffusion within the Postsynaptic Density Assessed by Simultaneous Single-Molecule Tracking and Localization Microscopy. Front. Synaptic Neurosci. 8, 19 (2016)Google Scholar
  222. 222.
    C.C. Lo, A.S. Chiang, Toward Whole-Body Connectomics. J. Neurosci. 36(45), 11375–11383 (2016)Google Scholar
  223. 223.
    L.L. Looger, O. Griesbeck, Genetically encoded neural activity indicators. Curr. Opin. Neurobiol. 22(1), 18–23 (2012)Google Scholar
  224. 224.
    F. Helmchen, W. Denk, Deep tissue two-photon microscopy. Nat. Methods 2(12), 932–940 (2005)Google Scholar
  225. 225.
    R.K. Benninger, D.W. Piston, Two‐photon excitation microscopy for the study of living cells and tissues. Curr. Protoc. Cell Bio. 4–11 (2013)Google Scholar
  226. 226.
    H.C. Ishikawa-Ankerhold, R. Ankerhold, G.P. Drummen, Advanced fluorescence microscopy techniques—Frap, flip, flap. Fret FLIM. Mol. 17(4), 4047–4132 (2012)Google Scholar
  227. 227.
    T.S. Tkaczyk, Field Guide to Microscopy (SPIE, Bellingham, 2010)Google Scholar
  228. 228.
    T.C. Peter, Two-photon fluorescence light microscopy. Encyclopedia of Life Sciences (2002). http://web.mit.edu/solab/Documents/Assets/So-2PF%20light%20microscopy.pdf
  229. 229.
    F. Helmchen, W. Denk, New developments in multiphoton microscopy. Curr. Opin. Neurobiol. 12(5), 593–601 (2002)Google Scholar
  230. 230.
    A. Diaspro et al., Multi-photon excitation microscopy. Biomed. Eng. Online 5(1), 36 (2006)Google Scholar
  231. 231.
    W. Denk, J.H. Strickler, W.W. Webb, Two-photon laser scanning fluorescence microscopy. Science 248(4951), 73–76 (1990)Google Scholar
  232. 232.
    Y. Mizuta, D. Kurihara, T. Higashiyama, Two-photon imaging with longer wavelength excitation in intact Arabidopsis tissues. Protoplasma 252(5), 1231–1240 (2015)Google Scholar
  233. 233.
    M. Rubart, Two-photon microscopy of cells and tissue. Circ. Res. 95(12), 1154–1166 (2004)Google Scholar
  234. 234.
    M.J. Miller, S.H. Wei, I. Parker, M.D. Cahalan, Two-photon imaging of lymphocyte motility and antigen response in intact lymph node. Science 296(5574), 1869–1873 (2002)Google Scholar
  235. 235.
    P. Bousso, E.A. Robey, Dynamic behavior of T cells and thymocytes in lymphoid organs as revealed by two-photon microscopy. Immunity 21(3), 349–355 (2004)Google Scholar
  236. 236.
    D.W. Piston, in Fluorescence Microscopy: From Principles to Biological Applications, ed. by U. Kubitscheck (Wiley, 2017), pp. 203–242Google Scholar
  237. 237.
    S. Zhuo et al., Label-free monitoring of colonic cancer progression using multiphoton microscopy. Biomed. Opt. Express 2(3), 615–619 (2011)Google Scholar
  238. 238.
    R.M. Williams, W.R. Zipfel, W.W. Webb, Multiphoton microscopy in biological research. Curr. Opin. Chem. Biol. 5(5), 603–608 (2001)Google Scholar
  239. 239.
    A.A. Mascaro et al., Multiphoton microscopy in brain imaging, in SPIE BiOS, vol. 932903 (2015)Google Scholar
  240. 240.
    R. Yuste, W. Denk, Dendritic spines as basic functional units of neuronal integration. Nature 375(6533), 682 (1995)Google Scholar
  241. 241.
    W. Denk, M. Sugimori, R. Llinas, Two types of calcium response limited to single spines in cerebellar Purkinje cells. PNAS 92(18), 8279–8282 (1995)Google Scholar
  242. 242.
    J.T. Trachtenberg, B.E. Chen, G.W. Knott, G. Feng, Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nature 420(6917), 788 (2002)Google Scholar
  243. 243.
    G.W. Knott, A. Holtmaat, L. Wilbrecht, E. Welker, K. Svoboda, Spine growth precedes synapse formation in the adult neocortex in vivo. Nat. Neurosci. 9(9), 1117 (2006)Google Scholar
  244. 244.
    C.R. Rose, Y. Kovalchuk, J. Eilers, A. Konnerth, Two-photon Na+ imaging in spines and fine dendrites of central neurons. Pflügers Archiv Eur. J. Physiol. 439(1), 201–207 (1999)Google Scholar
  245. 245.
    C. Stosiek, O. Garaschuk, K. Holthoff, A. Konnerth, In vivo two-photon calcium imaging of neuronal networks. PNAS 100(12), 7319–7324 (2003)Google Scholar
  246. 246.
    C.J. Engelbrecht, R.S. Johnston, E.J. Seibel, F. Helmchen, Ultra-compact fiber-optic two-photon microscope for functional fluorescence imaging in vivo. Opt. Express 16(8), 5556–5564 (2008)Google Scholar
  247. 247.
    F. Helmchen, M.S. Fee, D.W. Tank, W. Denk, A miniature head-mounted two-photon microscope: high-resolution brain imaging in freely moving animals. Neuron 31(6), 903–912 (2001)Google Scholar
  248. 248.
    W. Zong et al., Fast high-resolution miniature two-photon microscopy for brain imaging in freely behaving mice. Nat. Methods 14(7), 713–719 (2017)Google Scholar
  249. 249.
    J.H. Park, W. Sun, M. Cui, High-resolution in vivo imaging of mouse brain through the intact skull. PNAS 112(30), 9236–9241 (2015)Google Scholar
  250. 250.
    X. Sun et al., Two-photon imaging of glutathione levels in intact brain indicates enhanced redox buffering in developing neurons and cells at the cerebrospinal fluid and blood-brain interface. J. Biol. Chem. 281(25), 17420–17431 (2006)Google Scholar
  251. 251.
    S. Bovetti, C. Moretti, T. Fellin, Mapping brain circuit function in vivo using two-photon fluorescence microscopy. Micros. Res. Techn. 77(7), 492–501 (2014)Google Scholar
  252. 252.
    M. Matsuzaki, M. Kondo, K. Kobayashi, M. Ohkura, J. Nakai, Two-photon calcium imaging of medial prefrontal cortex and hippocampus without cortical invasion (2017).  https://doi.org/10.1101/119404
  253. 253.
    R. Kawakami et al., Visualizing hippocampal neurons with in vivo two-photon microscopy using a 1030 nm picosecond pulse laser. Sci. Rep. 3, srep01014 (2013)Google Scholar
  254. 254.
    P. Theer, M.T. Hasan, W. Denk, Two-photon imaging to a depth of 1000 µm in living brains by use of a Ti: Al2O3 regenerative amplifier. Opt. Lett. 28(12), 1022–1024 (2003)Google Scholar
  255. 255.
    D. Kobat, N.G. Horton, C. Xu, In vivo two-photon microscopy to 1.6-mm depth in mouse cortex. J. Biomed. Opt. 16(10), 106014 (2011)Google Scholar
  256. 256.
    A. Birkner, C.H. Tischbirek, A. Konnerth, Improved deep two-photon calcium imaging in vivo. Cell Calcium 64, 29–35 (2017)Google Scholar
  257. 257.
    J.M. Girkin, S. Poland, A.J. Wright, Adaptive optics for deeper imaging of biological samples. Curr. Opin. Biotechnol. 20(1), 106–110 (2009)Google Scholar
  258. 258.
    L. Sherman, J.Y. Ye, O. Albert, T.B. Norris, Adaptive correction of depth-induced aberrations in multiphoton scanning microscopy using a deformable mirror. J. Microsc. 206(1), 65–71 (2002)MathSciNetGoogle Scholar
  259. 259.
    M.A. Neil et al., Adaptive aberration correction in a two-photon microscope. J. Microsc. 200(2), 105–108 (2000)Google Scholar
  260. 260.
    J.C. Jung, A.D. Mehta, E. Aksay, R. Stepnoski, M.J. Schnitzer, In vivo mammalian brain imaging using one-and two-photon fluorescence microendoscopy. J. Neurophysiol. 92(5), 3121–3133 (2004)Google Scholar
  261. 261.
    M.J. Levene, D.A. Dombeck, K.A. Kasischke, R.P. Molloy, W.W. Webb, In vivo multiphoton microscopy of deep brain tissue. J. Neurophysiol. 91(4), 1908–1912 (2004)Google Scholar
  262. 262.
    M.E. Bocarsly et al., Minimally invasive microendoscopy system for in vivo functional imaging of deep nuclei in the mouse brain. Biomed. Opt. Express 6(11), 4546–4556 (2015)Google Scholar
  263. 263.
    R.P. Barretto, B. Messerschmidt, M.J. Schnitzer, In vivo fluorescence imaging with high-resolution microlenses. Nat. Methods 6(7), 511–512 (2009)Google Scholar
  264. 264.
    M. Sato et al., Fast varifocal two-photon microendoscope for imaging neuronal activity in the deep brain. Biomed. Opt. Express 8(9), 4049–4060 (2017)Google Scholar
  265. 265.
    D.G. Ouzounov et al., In vivo three-photon imaging of activity of GCaMP6-labeled neurons deep in intact mouse brain. Nat. Methods 14(4), 388–390 (2017)MathSciNetGoogle Scholar
  266. 266.
    D.L. Wokosin, V.E. Centonze, S. Crittenden, J. White, Three-photon excitation fluorescence imaging of biological specimens using an all-solid-state laser. Bioimaging 4(3), 208–214 (1996)Google Scholar
  267. 267.
    C. Xu, W. Zipfel, J.B. Shear, R.M. Williams, W.W. Webb, Multiphoton fluorescence excitation: new spectral windows for biological nonlinear microscopy. PNAS 93(20), 10763–10768 (1996)Google Scholar
  268. 268.
    N.G. Horton et al., In vivo three-photon microscopy of subcortical structures within an intact mouse brain. Nat. Photonics 7(3), 205–209 (2013)Google Scholar
  269. 269.
    J. Skoch, G.A. Hickey, S.T. Kajdasz, B.T. Hyman, B.J. Bacskai, In vivo imaging of amyloid-ß deposits in mouse brain with multiphoton microscopy, in Amyloid Proteins. Methods in Molecular Biology™ ed. by E.M. Sigurdsson. vol. 299 (Humana Press, 2005).  https://doi.org/10.1385/1-59259-874-9:349
  270. 270.
    J. Dong, R. Revilla-Sanchez, S. Moss, P.G. Haydon, Multiphoton in vivo imaging of amyloid in animal models of Alzheimer’s disease. Neuropharmacology 59(4), 268–275 (2010)Google Scholar
  271. 271.
    D. Vučinić, T.J. Sejnowski, A compact multiphoton 3D imaging system for recording fast neuronal activity. PLoS ONE 2(8), e699 (2007)Google Scholar
  272. 272.
    G.D. Reddy, K. Kelleher, R. Fink, P. Saggau, Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity. Nat. Neurosci. 11(6), 713–720 (2008)Google Scholar
  273. 273.
    N. Callamaras, I. Parker, Construction of a confocal microscope for real-time xy and xz imaging. Cell Calcium 26(6), 271–279 (1999)Google Scholar
  274. 274.
    W. Göbel, B.M. Kampa, F. Helmchen, Imaging cellular network dynamics in three dimensions using fast 3D laser scanning. Nat. Methods 4(1), 73 (2007)Google Scholar
  275. 275.
    R. Kurtz, M. Fricke, J. Kalb, P. Tinnefeld, M. Sauer, Application of multiline two-photon microscopy to functional in vivo imaging. J. Neurosci. Methods 151(2), 276–286 (2006)Google Scholar
  276. 276.
    M.L. Castanares, V. Gautam, J. Drury, H. Bachor, V.R. Daria, Efficient multi-site two-photon functional imaging of neuronal circuits. Biomed. Opt. Exp. 7(12), 5325–5334 (2016)Google Scholar
  277. 277.
    M. Dal Maschio, A.M. De Stasi, F. Benfenati, T. Fellin, Three-dimensional in vivo scanning microscopy with inertia-free focus control. Opt. Lett. 36(17), 3503–3505 (2011)Google Scholar
  278. 278.
    E.E. Hoover, J.A. Squier, Advances in multiphoton microscopy technology. Nat. Photonics 7(2), 93–101 (2013)Google Scholar
  279. 279.
    N. Ji, J. Freeman, S.L. Smith, Technologies for imaging neural activity in large volumes. Nat. Neurosci. 19(9), 1154–1164 (2016)Google Scholar
  280. 280.
    O. Garaschuk et al., Optical monitoring of brain function in vivo: from neurons to networks. Pflügers Archiv 453(3), 385–396 (2006)Google Scholar
  281. 281.
    W. Göbel, F. Helmchen, In vivo calcium imaging of neural network function. Physiology 22(6), 358–365 (2007)Google Scholar
  282. 282.
    W. Yang, R. Yuste, In vivo imaging of neural activity. Nat. Methods 14(4), 349–359 (2017)Google Scholar
  283. 283.
    R. David, Milestone 16: Light sheet microscopy: Seeing the light, perpendicularly. Nature (1993).  https://doi.org/10.1038/ncb1951
  284. 284.
    F. Pampaloni, B.J. Chang, E.H. Stelzer, Light sheet-based fluorescence microscopy (LSFM) for the quantitative imaging of cells and tissues. Cell Tissue Res. 360(1), 129–141 (2015)Google Scholar
  285. 285.
    J. Huisken, J. Swoger, F. Del Bene, J. Wittbrodt, E.H. Stelzer, Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305(5686), 1007–1009 (2004)Google Scholar
  286. 286.
    M.W. Adams, A.F. Loftus, S.E. Dunn, M.S. Joens, J.A. Fitzpatrick, Light sheet fluorescence microscopy (LSFM). Curr. Protoc. Cytom. 71, 12–37 (2015)Google Scholar
  287. 287.
    H. Siedentopf, R. Zsigmondy, Uber sichtbarmachung und größenbestimmung ultramikoskopischer teilchen, mit besonderer anwendung auf goldrubingläser. Ann. Phys. 315(1), 1–39 (1902)Google Scholar
  288. 288.
    H.G. Söderbaum, Award ceremony speech. Nobelprize.org (1926). http://www.nobelprize.org/nobel_prizes/chemistry/laureates/1925/press.html
  289. 289.
    A.H. Voie, D.H. Burns, F.A. Spelman, Orthogonal-plane fluorescence optical sectioning: Three-dimensional imaging of macroscopic biological specimens. J. Microsc. 170(3), 229–236 (1993)Google Scholar
  290. 290.
    S. Lindek, R. Pick, E.H. Stelzer, Confocal theta microscope with three objective lenses. Rev. Sci. Instrum. 65(11), 3367–3372 (1994)Google Scholar
  291. 291.
    P.A. Santi, S.B. Johnson, M. Hillenbrand, P.Z. GrandPre, T.J. Glass, J.R. Leger, Thin-sheet laser imaging microscopy for optical sectioning of thick tissues. Biotechniques 46(4), 287 (2009)Google Scholar
  292. 292.
    C.J. Engelbrecht, E.H. Stelzer, Resolution enhancement in a light-sheet-based microscope (SPIM). Opt. Lett. 31(10), 1477–1479 (2006)Google Scholar
  293. 293.
    P. Hoyer et al., Breaking the diffraction limit of light-sheet fluorescence microscopy by RESOLFT. PNAS 113(13), 3442–3446 (2016)Google Scholar
  294. 294.
    R.M. Power, J. Huisken, A guide to light-sheet fluorescence microscopy for multiscale imaging. Nat. Methods 14(4), 360–373 (2017)Google Scholar
  295. 295.
    T.A. Planchon et al., Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat. Methods 8(5), 417–423 (2011)Google Scholar
  296. 296.
    M. Zhao et al., Cellular imaging of deep organ using two-photon Bessel light-sheet nonlinear structured illumination microscopy. Biomed. Opt. Express 5(5), 1296–1308 (2014)Google Scholar
  297. 297.
    F.C. Zanacchi et al., Live-cell 3D super-resolution imaging in thick biological samples. Nat. Methods 8(12), 1047–1049 (2011)Google Scholar
  298. 298.
    F.C. Zanacchi, Z. Lavagnino, M. Faretta, L. Furia, A. Diaspro, Light-sheet confined super-resolution using two-photon photoactivation. PLoS ONE 8(7), e67667 (2013)Google Scholar
  299. 299.
    Y.S. Hu et al., Light-sheet Bayesian microscopy enables deep-cell super-resolution imaging of heterochromatin in live human embryonic stem cells. Optical nanoscopy 2(1), 7 (2013)Google Scholar
  300. 300.
    A. Narasimhan, K.U. Venkataraju, J. Mizrachi, D.F. Albeanu, P. Osten, A high resolution whole brain imaging using Oblique Light Sheet Tomography (2017).  https://doi.org/10.1101/132423
  301. 301.
    P.J. Keller, M.B. Ahrens, J. Freeman, Light-sheet imaging for systems neuroscience. Nat. Methods 12(1), 27–29 (2015)Google Scholar
  302. 302.
    L.A. Royer et al., Adaptive light-sheet microscopy for long-term, high-resolution imaging in living organisms. Nat. Biotech. 34(12), 1267–1278 (2016)Google Scholar
  303. 303.
    R.K. Chhetri, F. Amat, Y. Wan, B.I.L. Höckendorf, W.C. Lemon, P.J. Keller, Whole-animal functional and developmental imaging with isotropic spatial resolution. Nat. Methods 12(12), 1171–1178 (2015)Google Scholar
  304. 304.
    H.U. Dodt et al., Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods 4(4), 331–336 (2007)Google Scholar
  305. 305.
    M. Stefaniuk et al., Light-sheet microscopy imaging of a whole cleared rat brain with Thy1-GFP transgene. Sci. Rep. 6, 28209 (2016)Google Scholar
  306. 306.
    S. Wolf et al., Whole-brain functional imaging with two-photon light-sheet microscopy. Nat. Methods 12(5), 379–380 (2015)Google Scholar
  307. 307.
    L. Silvestri et al., Quantitative neuroanatomy of all Purkinje cells with light sheet microscopy and high-throughput image analysis. Front. Neuroanat. 9, 68 (2015)Google Scholar
  308. 308.
    W. Li et al., in Optics and the Brain (Optical Society of America, 2016), pp. BTu4D-3Google Scholar
  309. 309.
    S.W. Emmons, The beginning of connectomics: a commentary on White et al. (1986) ‘The structure of the nervous system of the nematode Caenorhabditis elegans’. Phil. Trans. R. Soc. B 370(1666), 20140309 (2015)Google Scholar
  310. 310.
    F. Jabr, The connectome debate: is mapping the mind of a worm worth it. Sci. Am. (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Institute of Biophotonics, National Yang-Ming UniversityTaipei 112Taiwan
  2. 2.Department of PhysicsJagannath Barooah CollegeJorhatIndia
  3. 3.Department of Electrical and Computer EngineeringBoston UniversityBostonUSA
  4. 4.Department of Life ScienceBrain Research Center, Institute of Biotechnology, National Tsing Hua UniversityHsinchuTaiwan
  5. 5.Genomics Research Center, Academia SinicaNankang, TaipeiTaiwan
  6. 6.Institute of Physics, Academia SinicaNankang, TaipeiTaiwan
  7. 7.Biomedical Science and Environmental Biology, Kaohsiung Medical UniversityKaohsiungTaiwan
  8. 8.Kavli Institute for Brain and Mind, University of CaliforniaSan Diego, La JollaUSA

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