Serial Multiphoton Tomography and Analysis of Volumetric Images of the Mouse Brain

  • Denise M. O. RamirezEmail author
  • Apoorva D. Ajay
  • Mark P. Goldberg
  • Julian P. Meeks
Part of the Neuromethods book series (NM, volume 148)


Mapping the structural and synaptic organization of the central nervous system is fundamental to a principled understanding of neural circuit development and function and an important goal of modern neuroscience. A plethora of new imaging technologies and computational advances have made whole-brain mapping studies more widely accessible. One such volumetric imaging method is known as serial two-photon tomography (STPT). STPT is an automated block-face imaging method in which a brain or other whole-organ specimen is repetitively imaged using multiphoton illumination and physically sectioned using an integrated vibratome. The resultant tile images are stitched in two dimensions to form mosaic whole-section images, and the mosaic images need only be stacked in three dimensions to generate a whole-brain volumetric image. Automated image analysis pipelines may then be employed to mine quantitative information at the whole-brain scale across large cohorts of experimental animals. Here, we describe our methods optimized in the University of Texas Southwestern Whole Brain Microscopy Facility for STPT using the TissueCyte1000 platform and a custom pipeline for whole-brain image analysis including registration into the Allen Institute Common Coordinate Framework version 3.0 (CCF 3.0). Included is a description of the inclusion of supervised machine learning using a voxel-wise random forest model for classification of features of interest, including cell bodies and subcellular structures. The rapidly advancing pace of STPT and other complementary methods for whole-brain mapping and systematic analysis has the potential to generate transformative insights into brain circuitry in both health and disease.


TissueCyte Volumetric imaging Automated image analysis Block-face imaging Serial two-photon tomography Connectomics 



The University of Texas Southwestern Whole Brain Microscopy Facility is funded by the Texas Institute of Brain Injury and Repair (TIBIR) and receives additional support from the University of Texas Southwestern Department of Neurology and Neurotherapeutics and the University of Texas Southwestern Center for Alzheimer’s and Neurodegenerative Disease (CAND). We would like to thank Drs. Amy Bernard, Anh Ho, Lydia Ng, and Hongkui Zeng of the Allen Institute for Brain Science for helpful discussions and training in TissueCyte operations and data analysis. We also thank Drs. Timothy Ragan, Phil Knodle, and Adam Bleckert of TissueVision, Inc. for assistance in optimizing Autostitcher performance.


  1. 1.
    Zeng H (2018) Mesoscale connectomics. Curr Opin Neurobiol 50:154–162PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Cazemier JL, Clasca F, Tiesinga PH (2016) Connectomic analysis of brain networks: novel techniques and future directions. Front Neuroanat 10:110PubMedPubMedCentralCrossRefGoogle Scholar
  3. 3.
    Helmstaedter M, Briggman KL, Turaga SC, Jain V, Seung HS, Denk W (2013) Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500:168–174CrossRefGoogle Scholar
  4. 4.
    Kasthuri N, Hayworth KJ, Berger DR, Schalek RL, Conchello JA, Knowles-Barley S, Lee D, Vazquez-Reina A, Kaynig V, Jones TR, Roberts M, Morgan JL, Tapia JC, Seung HS, Roncal WG, Vogelstein JT, Burns R, Sussman DL, Priebe CE, Pfister H, Lichtman JW (2015) Saturated reconstruction of a volume of neocortex. Cell 162:648–661PubMedCrossRefPubMedCentralGoogle Scholar
  5. 5.
    White JG, Southgate E, Thomson JN, Brenner S (1986) The structure of the nervous system of the nematode Caenorhabditis elegans. Philos Trans R Soc Lond B Biol Sci 314:1–340CrossRefGoogle Scholar
  6. 6.
    Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 102:9673–9678PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 1124:1–38CrossRefGoogle Scholar
  8. 8.
    Oh SW, Harris JA, Ng L, Winslow B, Cain N, Mihalas S, Wang Q, Lau C, Kuan L, Henry AM, Mortrud MT, Ouellette B, Nguyen TN, Sorensen SA, Slaughterbeck CR, Wakeman W, Li Y, Feng D, Ho A, Nicholas E, Hirokawa KE, Bohn P, Joines KM, Peng H, Hawrylycz MJ, Phillips JW, Hohmann JG, Wohnoutka P, Gerfen CR, Koch C, Bernard A, Dang C, Jones AR, Zeng H (2014) A mesoscale connectome of the mouse brain. Nature 508:207–214PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Jiang X, Shen S, Cadwell CR, Berens P, Sinz F, Ecker AS, Patel S, Tolias AS (2015) Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350:aac9462PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Denk W, Strickler JH, Webb WW (1990) Two-photon laser scanning fluorescence microscopy. Science 248:73–76PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    Neil MA, Juskaitis R, Wilson T (1997) Method of obtaining optical sectioning by using structured light in a conventional microscope. Opt Lett 22:1905–1907PubMedCrossRefPubMedCentralGoogle Scholar
  12. 12.
    Mertz J (2011) Optical sectioning microscopy with planar or structured illumination. Nat Methods 8:811–819PubMedCrossRefPubMedCentralGoogle Scholar
  13. 13.
    Ragan T, Kadiri LR, Venkataraju KU, Bahlmann K, Sutin J, Taranda J, Arganda-Carreras I, Kim Y, Seung HS, Osten P (2012) Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat Methods 9:255–258PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Economo MN, Clack NG, Lavis LD, Gerfen CR, Svoboda K, Myers EW, Chandrashekar J (2016) A platform for brain-wide imaging and reconstruction of individual neurons. Elife 5:e10566PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Seiriki K, Kasai A, Hashimoto T, Schulze W, Niu M, Yamaguchi S, Nakazawa T, Inoue KI, Uezono S, Takada M, Naka Y, Igarashi H, Tanuma M, Waschek JA, Ago Y, Tanaka KF, Hayata-Takano A, Nagayasu K, Shintani N, Hashimoto R, Kunii Y, Hino M, Matsumoto J, Yabe H, Nagai T, Fujita K, Matsuda T, Takuma K, Baba A, Hashimoto H (2017) High-speed and scalable whole-brain imaging in rodents and primates. Neuron 94:1085–1100PubMedCrossRefPubMedCentralGoogle Scholar
  16. 16.
    Gong H, Zeng S, Yan C, Lv X, Yang Z, Xu T, Feng Z, Ding W, Qi X, Li A, Wu J, Luo Q (2013) Continuously tracing brain-wide long-distance axonal projections in mice at a one-micron voxel resolution. Neuroimage 74:87–98PubMedCrossRefPubMedCentralGoogle Scholar
  17. 17.
    Gong H, Xu D, Yuan J, Li X, Guo C, Peng J, Li Y, Schwarz LA, Li A, Hu B, Xiong B, Sun Q, Zhang Y, Liu J, Zhong Q, Xu T, Zeng S, Luo Q (2016) High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. Nat Commun 7:12142PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Dorn JF, Danuser G, Yang G (2008) Computational processing and analysis of dynamic fluorescence image data. Methods Cell Biol 85:497–538PubMedCrossRefPubMedCentralGoogle Scholar
  19. 19.
    Sabouri-Ghomi M, Wu Y, Hahn K, Danuser G (2008) Visualizing and quantifying adhesive signals. Curr Opin Cell Biol 20:541–550PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Kvilekval K, Fedorov D, Obara B, Singh A, Manjunath BS (2010) Bisque: a platform for bioimage analysis and management. Bioinformatics 26:544–552PubMedCrossRefPubMedCentralGoogle Scholar
  21. 21.
    Peng H, Ruan Z, Long F, Simpson JH, Myers EW (2010) V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nat Biotechnol 28:348–353PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Tsai CL, Lister JP, Bjornsson CS, Smith K, Shain W, Barnes CA, Roysam B (2011) Robust, globally consistent and fully automatic multi-image registration and montage synthesis for 3-D multi-channel images. J Microsc 243:154–171PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Eliceiri KW, Berthold MR, Goldberg IG, Ibanez L, Manjunath BS, Martone ME, Murphy RF, Peng H, Plant AL, Roysam B, Stuurman N, Swedlow JR, Tomancak P, Carpenter AE (2012) Biological imaging software tools. Nat Methods 9:697–710PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Burel JM, Besson S, Blackburn C, Carroll M, Ferguson RK, Flynn H, Gillen K, Leigh R, Li S, Lindner D, Linkert M, Moore WJ, Ramalingam B, Rozbicki E, Tarkowska A, Walczysko P, Allan C, Moore J, Swedlow JR (2015) Publishing and sharing multi-dimensional image data with OMERO. Mamm Genome 26:441–447PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Freeman J (2015) Open source tools for large-scale neuroscience. Curr Opin Neurobiol 32:156–163PubMedCrossRefPubMedCentralGoogle Scholar
  26. 26.
    Niedworok CJ, Brown AP, Jorge Cardoso M, Osten P, Ourselin S, Modat M, Margrie TW (2016) aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data. Nat Commun 7:11879PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Berger DR, Seung HS, Lichtman JW (2018) VAST (Volume Annotation and Segmentation Tool): efficient manual and semi-automatic labeling of large 3D image stacks. Front Neural Circuits 12:88PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Bohland JW, Wu C, Barbas H, Bokil H, Bota M, Breiter HC, Cline HT, Doyle JC, Freed PJ, Greenspan RJ, Haber SN, Hawrylycz M, Herrera DG, Hilgetag CC, Huang ZJ, Jones A, Jones EG, Karten HJ, Kleinfeld D, Kotter R, Lester HA, Lin JM, Mensh BD, Mikula S, Panksepp J, Price JL, Safdieh J, Saper CB, Schiff ND, Schmahmann JD, Stillman BW, Svoboda K, Swanson LW, Toga AW, Van Essen DC, Watson JD, Mitra PP (2009) A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale. PLoS Comput Biol 5:e1000334PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Cowan WM (1998) The emergence of modern neuroanatomy and developmental neurobiology. Neuron 20:413–426PubMedCrossRefPubMedCentralGoogle Scholar
  30. 30.
    Madisen L, Zwingman TA, Sunkin SM, Oh SW, Zariwala HA, Gu H, Ng LL, Palmiter RD, Hawrylycz MJ, Jones AR, Lein ES, Zeng H (2010) A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat Neurosci 13:133–140PubMedCrossRefPubMedCentralGoogle Scholar
  31. 31.
    Taniguchi H, He M, Wu P, Kim S, Paik R, Sugino K, Kvitsiani D, Fu Y, Lu J, Lin Y, Miyoshi G, Shima Y, Fishell G, Nelson SB, Huang ZJ (2011) A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex. Neuron 71:995–1013PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Nassi JJ, Cepko CL, Born RT, Beier KT (2015) Neuroanatomy goes viral! Front Neuroanat 9:80PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Jeong M, Kim Y, Kim J, Ferrante DD, Mitra PP, Osten P, Kim D (2016) Comparative three-dimensional connectome map of motor cortical projections in the mouse brain. Sci Rep 6:20072PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Pan C, Cai R, Quacquarelli FP, Ghasemigharagoz A, Lourbopoulos A, Matryba P, Plesnila N, Dichgans M, Hellal F, Erturk A (2016) Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat Methods 13:859–867PubMedCrossRefPubMedCentralGoogle Scholar
  35. 35.
    Mano T, Albanese A, Dodt HU, Erturk A, Gradinaru V, Treweek JB, Miyawaki A, Chung K, Ueda HR (2018) Whole-brain analysis of cells and circuits by tissue clearing and light-sheet microscopy. J Neurosci 38:9330–9337PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Murakami TC, Mano T, Saikawa S, Horiguchi SA, Shigeta D, Baba K, Sekiya H, Shimizu Y, Tanaka KF, Kiyonari H, Iino M, Mochizuki H, Tainaka K, Ueda HR (2018) A three-dimensional single-cell-resolution whole-brain atlas using CUBIC-X expansion microscopy and tissue clearing. Nat Neurosci 21:625–637PubMedCrossRefPubMedCentralGoogle Scholar
  37. 37.
    Swanson LW, Lichtman JW (2016) From Cajal to connectome and beyond. Annu Rev Neurosci 39:197–216PubMedCrossRefPubMedCentralGoogle Scholar
  38. 38.
    Liu JY, Ellis M, Brooke-Ball H, De Tisi J, Eriksson SH, Brandner S, Sisodiya SM, Thom M (2014) High-throughput, automated quantification of white matter neurons in mild malformation of cortical development in epilepsy. Acta Neuropathol Commun 2:72PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Lugo-Hernandez E, Squire A, Hagemann N, Brenzel A, Sardari M, Schlechter J, Sanchez-Mendoza EH, Gunzer M, Faissner A, Hermann DM (2017) 3D visualization and quantification of microvessels in the whole ischemic mouse brain using solvent-based clearing and light sheet microscopy. J Cereb Blood Flow Metab 37:3355–3367PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Luo Y, Wang A, Liu M, Lei T, Zhang X, Gao Z, Jiang H, Gong H, Yuan J (2017) Label-free brainwide visualization of senile plaque using cryo-micro-optical sectioning tomography. Opt Lett 42:4247–4250PubMedCrossRefPubMedCentralGoogle Scholar
  41. 41.
    Whitesell JD, Buckley AR, Knox JE, et al. (2019) Whole brain imaging reveals distinct spatial patterns of amyloid beta deposition in three mouse models of Alzheimer’s disease. J Comp Neurol 527:2122–2145.Google Scholar
  42. 42.
    Grandjean J, Zerbi V, Balsters JH, Wenderoth N, Rudin M (2017) Structural basis of large-scale functional connectivity in the mouse. J Neurosci 37:8092–8101PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Bienkowski MS, Bowman I, Song MY, Gou L, Ard T, Cotter K, Zhu M, Benavidez NL, Yamashita S, Abu-Jaber J, Azam S, Lo D, Foster NN, Hintiryan H, Dong HW (2018) Integration of gene expression and brain-wide connectivity reveals the multiscale organization of mouse hippocampal networks. Nat Neurosci 21:1628–1643PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Weber MT, Arena JD, Xiao R, Wolf JA, Johnson VE (2018) Clarity reveals a more protracted temporal course of axon swelling and disconnection than previously described following traumatic brain injury. Brain Pathol 29:437–450. CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Carmichael ST, Kathirvelu B, Schweppe CA, Nie EH (2017) Molecular, cellular and functional events in axonal sprouting after stroke. Exp Neurol 287:384–394PubMedCrossRefPubMedCentralGoogle Scholar
  46. 46.
    Harris NG, Verley DR, Gutman BA, Thompson PM, Yeh HJ, Brown JA (2016) Disconnection and hyper-connectivity underlie reorganization after TBI: a rodent functional connectomic analysis. Exp Neurol 277:124–138PubMedCrossRefPubMedCentralGoogle Scholar
  47. 47.
    Fornito A, Zalesky A, Breakspear M (2015) The connectomics of brain disorders. Nat Rev Neurosci 16:159–172PubMedCrossRefPubMedCentralGoogle Scholar
  48. 48.
    Zheng T, Yang Z, Li A, Lv X, Zhou Z, Wang X, Qi X, Li S, Luo Q, Gong H, Zeng S (2013) Visualization of brain circuits using two-photon fluorescence micro-optical sectioning tomography. Opt Express 21:9839–9850PubMedCrossRefPubMedCentralGoogle Scholar
  49. 49.
    Chen BC, Legant WR, Wang K, Shao L, Milkie DE, Davidson MW, Janetopoulos C, Wu XS, Hammer JA 3rd, Liu Z, English BP, Mimori-Kiyosue Y, Romero DP, Ritter AT, Lippincott-Schwartz J, Fritz-Laylin L, Mullins RD, Mitchell DM, Bembenek JN, Reymann AC, Bohme R, Grill SW, Wang JT, Seydoux G, Tulu US, Kiehart DP, Betzig E (2014) Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution. Science 346:1257998PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Watson AM, Rose AH, Gibson GA, Gardner CL, Sun C, Reed DS, Lam LKM, St Croix CM, Strick PL, Klimstra WB, Watkins SC (2017) Ribbon scanning confocal for high-speed high-resolution volume imaging of brain. PLoS One 12:e0180486PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Spalteholz W (1914) Über das Durchsichtigmachen von menschlichen und tierischen Präparaten (About the transparency-generation of human and animal preparations). S. Hirzel, LeipzigGoogle Scholar
  52. 52.
    Richardson DS, Lichtman JW (2015) Clarifying tissue clearing. Cell 162:246–257PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Susaki EA, Ueda HR (2016) Whole-body and whole-organ clearing and imaging techniques with single-cell resolution: toward organism-level systems biology in mammals. Cell Chem Biol 23:137–157PubMedCrossRefPubMedCentralGoogle Scholar
  54. 54.
    Jing D, Zhang S, Luo W, Gao X, Men Y, Ma C, Liu X, Yi Y, Bugde A, Zhou BO, Zhao Z, Yuan Q, Feng JQ, Gao L, Ge WP, Zhao H (2018) Tissue clearing of both hard and soft tissue organs with the PEGASOS method. Cell Res 28:803–818PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Huisken J, Swoger J, Del Bene F, Wittbrodt J, Stelzer EH (2004) Optical sectioning deep inside live embryos by selective plane illumination microscopy. Science 305:1007–1009CrossRefGoogle Scholar
  56. 56.
    Girkin JM, Carvalho M (2018) The light-sheet microscopy revolution. J Opt 20:053002CrossRefGoogle Scholar
  57. 57.
    Dean KM, Fiolka R (2017) Lossless three-dimensional parallelization in digitally scanned light-sheet fluorescence microscopy. Sci Rep 7:9332PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Epp JR, Niibori Y, Liz Hsiang HL, Mercaldo V, Deisseroth K, Josselyn SA, Frankland PW (2015) Optimization of CLARITY for clearing whole-brain and other intact organs. eNeuro 2(3). pii: ENEURO.0022-0015.2015Google Scholar
  59. 59.
    Hama H, Kurokawa H, Kawano H, Ando R, Shimogori T, Noda H, Fukami K, Sakaue-Sawano A, Miyawaki A (2011) Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat Neurosci 14:1481–1488PubMedCrossRefPubMedCentralGoogle Scholar
  60. 60.
    Kim Y, Venkataraju KU, Pradhan K, Mende C, Taranda J, Turaga SC, Arganda-Carreras I, Ng L, Hawrylycz MJ, Rockland KS, Seung HS, Osten P (2015) Mapping social behavior-induced brain activation at cellular resolution in the mouse. Cell Rep 10:292–305PubMedCrossRefPubMedCentralGoogle Scholar
  61. 61.
    Vousden DA, Epp J, Okuno H, Nieman BJ, Van Eede M, Dazai J, Ragan T, Bito H, Frankland PW, Lerch JP, Henkelman RM (2015) Whole-brain mapping of behaviourally induced neural activation in mice. Brain Struct Funct 220:2043–2057PubMedCrossRefPubMedCentralGoogle Scholar
  62. 62.
    Zapiec B, Mombaerts P (2015) Multiplex assessment of the positions of odorant receptor-specific glomeruli in the mouse olfactory bulb by serial two-photon tomography. Proc Natl Acad Sci U S A 112:E5873–E5882PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Quina LA, Tempest L, Ng L, Harris JA, Ferguson S, Jhou TC, Turner EE (2015) Efferent pathways of the mouse lateral habenula. J Comp Neurol 523:32–60PubMedCrossRefPubMedCentralGoogle Scholar
  64. 64.
    Amato SP, Pan F, Schwartz J, Ragan TM (2016) Whole brain imaging with serial two-photon tomography. Front Neuroanat 10:31PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Kim Y, Perova Z, Mirrione MM, Pradhan K, Henn FA, Shea S, Osten P, Li B (2016) Whole-brain mapping of neuronal activity in the learned helplessness model of depression. Front Neural Circuits 10:3PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Li A, Gong H, Zhang B, Wang Q, Yan C, Wu J, Liu Q, Zeng S, Luo Q (2010) Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330:1404–1408PubMedCrossRefPubMedCentralGoogle Scholar
  67. 67.
    Gang Y, Liu X, Wang X, Zhang Q, Zhou H, Chen R, Liu L, Jia Y, Yin F, Rao G, Chen J, Zeng S (2017) Plastic embedding immunolabeled large-volume samples for three-dimensional high-resolution imaging. Biomed Opt Express 8:3583–3596PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9:676–682CrossRefGoogle Scholar
  69. 69.
    Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to ImageJ: 25 years of image analysis. Nat Methods 9:671–675PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Somner C, Straehle C, Kothe U, Hamprecht FA (2011) Ilastik: interactive learning and segmentation toolkit. Proceedings of the Eighth IEEE International Symposium on Biomedical Imaging (ISBI). pp 230–233Google Scholar
  71. 71.
    Royer LA, Weigert M, Gunther U, Maghelli N, Jug F, Sbalzarini IF, Myers EW (2015) ClearVolume: open-source live 3D visualization for light-sheet microscopy. Nat Methods 12:480–481PubMedCrossRefPubMedCentralGoogle Scholar
  72. 72.
    Gleave JA, Lerch JP, Henkelman RM, Nieman BJ (2013) A method for 3D immunostaining and optical imaging of the mouse brain demonstrated in neural progenitor cells. PLoS One 8:e72039PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Hamers-Casterman C, Atarhouch T, Muyldermans S, Robinson G, Hamers C, Songa EB, Bendahman N, Hamers R (1993) Naturally occurring antibodies devoid of light chains. Nature 363:446–448PubMedCrossRefPubMedCentralGoogle Scholar
  74. 74.
    Perruchini C, Pecorari F, Bourgeois JP, Duyckaerts C, Rougeon F, Lafaye P (2009) Llama VHH antibody fragments against GFAP: better diffusion in fixed tissues than classical monoclonal antibodies. Acta Neuropathol 118:685–695PubMedCrossRefPubMedCentralGoogle Scholar
  75. 75.
    Li T, Vandesquille M, Koukouli F, Dudeffant C, Youssef I, Lenormand P, Ganneau C, Maskos U, Czech C, Grueninger F, Duyckaerts C, Dhenain M, Bay S, Delatour B, Lafaye P (2016) Camelid single-domain antibodies: a versatile tool for in vivo imaging of extracellular and intracellular brain targets. J Control Release 243:1–10PubMedCrossRefPubMedCentralGoogle Scholar
  76. 76.
    Tsai PS, Kaufhold JP, Blinder P, Friedman B, Drew PJ, Karten HJ, Lyden PD, Kleinfeld D (2009) Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels. J Neurosci 29:14553–14570PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Sallee CJ, Russell DF (1993) Embedding of neural tissue in agarose or glyoxyl agarose for vibratome sectioning. Biotech Histochem 68:360–368PubMedCrossRefPubMedCentralGoogle Scholar
  78. 78.
    Preibisch S, Saalfeld S, Tomancak P (2009) Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics 25:1463–1465PubMedPubMedCentralCrossRefGoogle Scholar
  79. 79.
    Modat M, Cash DM, Daga P, Winston GP, Duncan JS, Ourselin S (2014) Global image registration using a symmetric block-matching approach. J Med Imaging (Bellingham) 1:024003CrossRefGoogle Scholar
  80. 80.
    Breiman L (2001) Random forests. Mach Learn 45:5–32CrossRefGoogle Scholar
  81. 81.
    Haubold C, Schiegg M, Kreshuk A, Berg S, Koethe U, Hamprecht FA (2016) Segmenting and tracking multiple dividing targets using ilastik. Adv Anat Embryol Cell Biol 219:199–229PubMedCrossRefPubMedCentralGoogle Scholar
  82. 82.
    Barth AL (2007) Visualizing circuits and systems using transgenic reporters of neural activity. Curr Opin Neurobiol 17:567–571PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Reijmers L, Mayford M (2009) Genetic control of active neural circuits. Front Mol Neurosci 2:27PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Guenthner CJ, Miyamichi K, Yang HH, Heller HC, Luo L (2013) Permanent genetic access to transiently active neurons via TRAP: targeted recombination in active populations. Neuron 78:773–784PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Renier N, Adams EL, Kirst C, Wu Z, Azevedo R, Kohl J, Autry AE, Kadiri L, Umadevi Venkataraju K, Zhou Y, Wang VX, Tang CY, Olsen O, Dulac C, Osten P, Tessier-Lavigne M (2016) Mapping of brain activity by automated volume analysis of immediate early genes. Cell 165:1789–1802PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Denise M. O. Ramirez
    • 1
    • 2
    Email author
  • Apoorva D. Ajay
    • 1
    • 2
  • Mark P. Goldberg
    • 1
    • 2
  • Julian P. Meeks
    • 1
    • 2
    • 3
  1. 1.Department of Neurology and NeurotherapeuticsUniversity of Texas Southwestern Medical CenterDallasUSA
  2. 2.Peter O’Donnell, Jr. Brain InstituteUniversity of Texas Southwestern Medical CenterDallasUSA
  3. 3.Department of NeuroscienceUniversity of Texas Southwestern Medical CenterDallasUSA

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