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High-Speed, Random-Access Multiphoton Microscopy for Monitoring Synaptic and Neuronal Activity in 3D in Behaving Animals

  • Mate Marosi
  • Gergely Szalay
  • Gergely Katona
  • Balázs RózsaEmail author
Protocol
Part of the Neuromethods book series (NM, volume 148)

Abstract

Understanding neural computation requires methods for three-dimensional readout of neural activity simultaneously on somatic and dendritic scales. Random-access point scanning offers measurement speed increased by several orders of magnitude compared to classical raster scanning methods; however, it is highly sensitive to sample movements during behavior, when fluorescence information could be completely lost due to dislocation of the point of interest. Volume scanning, on the other hand, is insensitive to even relatively large movements, but the scanning speed can be as low as 0.1–1 Hz for full 3D volumes, which is insufficient for recording fast Ca2+ activity. The 3D Drift acousto-optical (AO) scanning method can extend each scanning point of random-access AO point scanning to small 3D line, surface, or volume elements for fast recording of complex neuronal activity in vitro and in vivo, allowing free selection of any portion of the volume measured that can help finding the optimal trade-off between point scanning and full-volume scans. The video-like information, of the volume or surface elements measured, allows offline motion correction even during behavior and brain movement.

In this chapter, fast 3D measurement of over 150 dendritic spines with 3D lines, over 100 somata with squares and cubes, or multiple spiny dendritic segments with surface and volume elements in awake and behaving animals will be demonstrated.

Keywords

Two-photon microscopy Acousto-optical scanning Calcium imaging In vivo 3D functional imaging AO 3D Drift scanning 

Notes

Acknowledgments

The authors thank Linda Judák for the in vivo recordings and Alexa Bojdán for contributing to the figures.

Conflict of Interest

Dr. Gergely Katona and Dr. Balázs Rózsa are founders of Femtonics Ltd. Balázs Rózsa is a member of its scientific advisory board.

References

  1. 1.
    Danilatos GD (1991) Review and outline of environmental SEM at present. J Microsc 162:391–402.  https://doi.org/10.1111/j.1365-2818.1991.tb03149.x CrossRefGoogle Scholar
  2. 2.
    Kerr JND, Denk W (2008) Imaging in vivo: watching the brain in action. Nat Rev Neurosci 9:195CrossRefGoogle Scholar
  3. 3.
    Kherlopian AR, Song T, Duan Q et al (2008) A review of imaging techniques for systems biology. BMC Syst Biol 2:74CrossRefGoogle Scholar
  4. 4.
    Svoboda K, Yasuda R (2006) Principles of two-photon excitation microscopy and its applications to neuroscience. Neuron 50:823–839CrossRefGoogle Scholar
  5. 5.
    Lichtman JW, Magrassi L, Purves D (1987) Visualization of neuromuscular junctions over periods of several months in living mice. J Neurosci 7:1215–1222CrossRefGoogle Scholar
  6. 6.
    Denk W, Strickler JH, Webb WW (1990) Two-photon laser scanning fluorescence microscopy. Science 248:73–76.  https://doi.org/10.1126/science.2321027 CrossRefPubMedGoogle Scholar
  7. 7.
    Benninger RKP, Piston DW (2013) Two-photon excitation microscopy for the study of living cells and tissues. Curr Protoc Cell Biol Chapter 4:Unit 4.11.1-24.  https://doi.org/10.1002/0471143030.cb0411s59
  8. 8.
    Helmchen F, Denk W (2005) Deep tissue two-photon microscopy. Nat Methods 2:932–940CrossRefGoogle Scholar
  9. 9.
    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.  https://doi.org/10.1117/1.3646209 CrossRefPubMedGoogle Scholar
  10. 10.
    Theer P, Hasan MT, Denk W (2003) Two-photon imaging to a depth of 1000 μm in living brains by use of a Ti:Al2O3 regenerative amplifier. Opt Lett 28:1022–1024.  https://doi.org/10.1364/OL.28.001022 CrossRefPubMedGoogle Scholar
  11. 11.
    Stosiek C, Garaschuk O, Holthoff K, Konnerth A (2003) In vivo two-photon calcium imaging of neuronal networks. Proc Natl Acad Sci U S A 100:7319–7324.  https://doi.org/10.1073/pnas.1232232100 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Ohki K, Chung S, Ch YH et al (2005) Functional imaging with cellular resolution reveals precise micro- architecture in visual cortex. Nature 433:597–603.  https://doi.org/10.1055/s-2004-818954 CrossRefPubMedGoogle Scholar
  13. 13.
    Peron SP, Freeman J, Iyer V et al (2015) A cellular resolution map of barrel cortex activity during tactile behavior. Neuron 86:783–799.  https://doi.org/10.1016/j.neuron.2015.03.027 CrossRefPubMedGoogle Scholar
  14. 14.
    Dombeck DA, Khabbaz AN, Collman F et al (2007) Imaging large-scale neural activity with cellular resolution in awake, mobile mice. Neuron 56:43–57.  https://doi.org/10.1016/j.neuron.2007.08.003 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Miyawaki A (2011) Proteins on the move: insights gained from fluorescent protein technologies. Nat Rev Mol Cell Biol 12:656–668CrossRefGoogle Scholar
  16. 16.
    Mostany R, Miquelajauregui A, Shtrahman M, Portera-Cailliau C (2014) Two-photon excitation microscopy and its applications in neuroscience. Methods Mol Biol 1251:25–42.  https://doi.org/10.1007/978-1-4939-2080-8_2 CrossRefGoogle Scholar
  17. 17.
    Scanziani M, Häusser M (2009) Electrophysiology in the age of light. Nature 461:930–939CrossRefGoogle Scholar
  18. 18.
    Katona G, Szalay G, Maák P et al (2012) Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes. Nat Methods 9:201–208.  https://doi.org/10.1038/nmeth.1851 CrossRefPubMedGoogle Scholar
  19. 19.
    Khodagholy D, Gelinas JN, Thesen T et al (2015) NeuroGrid: recording action potentials from the surface of the brain. Nat Neurosci 18:310–315.  https://doi.org/10.1038/nn.3905 CrossRefPubMedGoogle Scholar
  20. 20.
    Poirazi P, Brannon T, Mel BW (2003) Pyramidal neuron as two-layer neural network. Neuron 37:989–999.  https://doi.org/10.1016/S0896-6273(03)00149-1 CrossRefPubMedGoogle Scholar
  21. 21.
    Polsky A, Mel BW, Schiller J (2004) Computational subunits in thin dendrites of pyramidal cells. Nat Neurosci 7:621–627.  https://doi.org/10.1038/nn1253 CrossRefPubMedGoogle Scholar
  22. 22.
    Losonczy A, Magee JC (2006) Integrative properties of radial oblique dendrites in hippocampal CA1 pyramidal neurons. Neuron 50:291–307.  https://doi.org/10.1016/j.neuron.2006.03.016 CrossRefPubMedGoogle Scholar
  23. 23.
    Johnston D, Narayanan R (2008) Active dendrites: colorful wings of the mysterious butterflies. Trends Neurosci 31:309–316CrossRefGoogle Scholar
  24. 24.
    Nikolenko V (2008) SLM microscopy: scanless two-photon imaging and photostimulation using spatial light modulators. Front Neural Circuits 2.  https://doi.org/10.3389/neuro.04.005.2008
  25. 25.
    Grewe BF, Voigt FF, van ‘t Hoff M, Helmchen F (2011) Fast two-layer two-photon imaging of neuronal cell populations using an electrically tunable lens. Biomed Opt Express 2:2035.  https://doi.org/10.1364/BOE.2.002035 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Reddy GD, Saggau P (2005) Fast three-dimensional laser scanning scheme using acousto-optic deflectors. J Biomed Opt 10:064038.  https://doi.org/10.1117/1.2141504 CrossRefPubMedGoogle Scholar
  27. 27.
    Fernández-Alfonso T, Nadella KMNS, Iacaruso MF et al (2014) Monitoring synaptic and neuronal activity in 3D with synthetic and genetic indicators using a compact acousto-optic lens two-photon microscope. J Neurosci Meth 222:69–81.  https://doi.org/10.1016/j.jneumeth.2013.10.021
  28. 28.
    Cheng A, Gonçalves JT, Golshani P et al (2011) Simultaneous two-photon calcium imaging at different depths with spatiotemporal multiplexing. Nat Methods 8:139–142.  https://doi.org/10.1038/nmeth.1552 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Holekamp TF, Turaga D, Holy TE (2008) Fast three-dimensional fluorescence imaging of activity in neural populations by objective-coupled planar illumination microscopy. Neuron 57:661–672.  https://doi.org/10.1016/j.neuron.2008.01.011 CrossRefGoogle Scholar
  30. 30.
    Botcherby EJ, Smith CW, Kohl MM et al (2012) Aberration-free three-dimensional multiphoton imaging of neuronal activity at kHz rates. Proc Natl Acad Sci USA 109:2919–2924.  https://doi.org/10.1073/pnas.1111662109
  31. 31.
    Göbel W, Kampa BM, Helmchen F (2007) Imaging cellular network dynamics in three dimensions using fast 3D laser scanning. Nat Methods 4:73–79.  https://doi.org/10.1038/nmeth989 CrossRefPubMedGoogle Scholar
  32. 32.
    Katona G, Kaszás A, Turi GF et al (2011) Roller Coaster Scanning reveals spontaneous triggering of dendritic spikes in CA1 interneurons. Proc Natl Acad Sci U S A 108:2148–2153.  https://doi.org/10.1073/pnas.1009270108 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Tomer R, Khairy K, Amat F, Keller PJ (2012) Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy. Nat Methods 9:755–763CrossRefGoogle Scholar
  34. 34.
    Wolf S, Supatto W, Debrégeas G et al (2015) Whole-brain functional imaging with two-photon light-sheet microscopy. Nat Methods 12:379–380CrossRefGoogle Scholar
  35. 35.
    Rozsa B, Katona G, Vizi ES et al (2007) Random access three-dimensional two-photon microscopy. Appl Optics 46:1860–1865.  https://doi.org/10.1364/AO.46.001860 CrossRefGoogle Scholar
  36. 36.
    Prevedel R, Yoon YG, Hoffmann M et al (2014) Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy. Nat Methods 11:727–730.  https://doi.org/10.1038/nmeth.2964 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Kong L, Tang J, Little JP et al (2015) Continuous volumetric imaging via an optical phase-locked ultrasound lens. Nat Methods 12:759–762.  https://doi.org/10.1038/nmeth.3476 CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Quirin S, Jackson J, Peterka DS, Yuste R (2014) Simultaneous imaging of neural activity in three dimensions. Front Neural Circuits 8.  https://doi.org/10.3389/fncir.2014.00029
  39. 39.
    Cotton RJ, Froudarakis E, Storer P et al (2013) Three-dimensional mapping of microcircuit correlation structure. Front Neural Circuits 7.  https://doi.org/10.3389/fncir.2013.00151
  40. 40.
    Kaplan A, Friedman N, Davidson N (2001) Acousto-optic lens with very fast focus scanning. Opt Lett 26:1078–1080.  https://doi.org/10.1364/OL.26.001078 CrossRefPubMedGoogle Scholar
  41. 41.
    Greenberg DS, Kerr JND (2009) Automated correction of fast motion artifacts for two-photon imaging of awake animals. J Neurosci Meth 176:1–15.  https://doi.org/10.1016/j.jneumeth.2008.08.020
  42. 42.
    Chen T-W, Wardill TJ, Sun Y et al (2013) Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499:295–300.  https://doi.org/10.1038/nature12354 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Szalay G, Judák L, Katona G et al (2016) Fast 3D imaging of spine, dendritic, and neuronal assemblies in behaving animals. Neuron 92:723–738.  https://doi.org/10.1016/j.neuron.2016.10.002 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Goldey GJ, Roumis DK, Glickfeld LL et al (2014) Removable cranial windows for long-term imaging in awake mice. Nat Prot 9:2515–2538.  https://doi.org/10.1038/nprot.2014.165
  45. 45.
    Mostany R, Portera-Cailliau C (2008) A craniotomy surgery procedure for chronic brain imaging. J Vis Exp.  https://doi.org/10.3791/680
  46. 46.
    Kaifosh P, Zaremba JD, Danielson NB, Losonczy A (2014) SIMA: Python software for analysis of dynamic fluorescence imaging data. Front Neuroinform 8.  https://doi.org/10.3389/fninf.2014.00080
  47. 47.
    Schiller J, Major G, Koester HJ, Schiller Y (2000) NMDA spikes in basal dendrites of cortical pyramidal neurons. Nature 404:285–289.  https://doi.org/10.1038/35005094 CrossRefPubMedGoogle Scholar
  48. 48.
    Magee JC, Johnston D (2005) Plasticity of dendritic excitability. Curr Opin Neurobiol 15:334–342.  https://doi.org/10.1016/j.conb.2005.05.013 CrossRefPubMedGoogle Scholar
  49. 49.
    Larkum ME, Nevian T, Sandier M et al (2009) Synaptic integration in tuft dendrites of layer 5 pyramidal neurons: a new unifying principle. Science 325:756–760.  https://doi.org/10.1126/science.1171958 CrossRefPubMedGoogle Scholar
  50. 50.
    Chiovini B, Turi GF, Katona G et al (2014) Dendritic spikes induce ripples in parvalbumin interneurons during hippocampal sharp waves. Neuron 82:908–924.  https://doi.org/10.1016/j.neuron.2014.04.004 CrossRefPubMedGoogle Scholar
  51. 51.
    Tran-Van-Minh A, Cazé RD, Abrahamsson T et al (2015) Contribution of sublinear and supralinear dendritic integration to neuronal computations. Front Cell Neurosci 9.  https://doi.org/10.3389/fncel.2015.00067
  52. 52.
    Araya R (2014) Input transformation by dendritic spines of pyramidal neurons. Front Neuroanat 8.  https://doi.org/10.3389/fnana.2014.00141
  53. 53.
    Bloodgood BL, Sabatini BL (2007) Ca(2+) signaling in dendritic spines. Curr Opin Neurobiol 17:345–351. doi: S0959-4388(07)00057-8 [pii]\r10.1016/j.conb.2007.04.003CrossRefGoogle Scholar
  54. 54.
    Harvey CD, Yasuda R, Zhong H, Svoboda K (2008) The spread of Ras activity triggered by activation of a single dendritic spine. Science 321:136–140.  https://doi.org/10.1126/science.1159675 CrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Sjostrom PJ, Rancz EA, Roth A, Hausser M (2008) Dendritic excitability and synaptic plasticity. Physiol Rev 88:769–840.  https://doi.org/10.1152/physrev.00016.2007 CrossRefPubMedGoogle Scholar
  56. 56.
    Larkum ME, Nevian T (2008) Synaptic clustering by dendritic signalling mechanisms. Curr Opin Neurobiol 18:321–331CrossRefGoogle Scholar
  57. 57.
    Kastellakis G, Cai DJ, Mednick SC et al (2015) Synaptic clustering within dendrites: an emerging theory of memory formation. Prog Neurobiol 126:19–35CrossRefGoogle Scholar
  58. 58.
    Olcese U, Iurilli G, Medini P (2013) Cellular and synaptic architecture of multisensory integration in the mouse neocortex. Neuron 79:579–593.  https://doi.org/10.1016/j.neuron.2013.06.010 CrossRefPubMedGoogle Scholar
  59. 59.
    Ikegaya Y, Aaron G, Cossart R et al (2004) Synfire chains and cortical songs: temporal modules of cortical activity. Science 304:559–564.  https://doi.org/10.1126/science.1093173 CrossRefPubMedGoogle Scholar
  60. 60.
    Takahashi N, Kitamura K, Matsuo N et al (2012) Locally synchronized synaptic inputs. Science 335:353–356.  https://doi.org/10.1126/science.1210362 CrossRefPubMedGoogle Scholar
  61. 61.
    Villette V, Malvache A, Tressard T et al (2015) Internally recurring hippocampal sequences as a population template of spatiotemporal information. Neuron 88:357–366.  https://doi.org/10.1016/j.neuron.2015.09.052 CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Klausberger T, Somogyi P (2008) Neuronal diversity and temporal dynamics: the unity of hippocampal circuit operations. Science 321:53–57CrossRefGoogle Scholar
  63. 63.
    Kepecs A, Fishell G (2014) Interneuron cell types are fit to function. Nature 505:318–326CrossRefGoogle Scholar
  64. 64.
    Womelsdorf T, Valiante TA, Sahin NT et al (2014) Dynamic circuit motifs underlying rhythmic gain control, gating and integration. Nat Neurosci 17:1031–1039CrossRefGoogle Scholar
  65. 65.
    Engel J, Thompson PM, Stern JM et al (2013) Connectomics and epilepsy. Curr Opin Neurol 26:186–194CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Mate Marosi
    • 1
  • Gergely Szalay
    • 1
  • Gergely Katona
    • 1
    • 2
  • Balázs Rózsa
    • 1
    • 2
    Email author
  1. 1.3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Hungarian Academy of SciencesBudapestHungary
  2. 2.Two-Photon Measurement Technology Research Group, The Faculty of Information Technology, Pázmány Péter Catholic UniversityBudapestHungary

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