High-resolution serial-section electron microscopy (ssEM) makes it possible to investigate the dense meshwork of axons, dendrites, and synapses that form neuronal circuits1. However, the imaging scale required to comprehensively reconstruct these structures is more than ten orders of magnitude smaller than the spatial extents occupied by networks of interconnected neurons2, some of which span nearly the entire brain. Difficulties in generating and handling data for large volumes at nanoscale resolution have thus restricted vertebrate studies to fragments of circuits. These efforts were recently transformed by advances in computing, sample handling, and imaging techniques1, but high-resolution examination of entire brains remains a challenge. Here, we present ssEM data for the complete brain of a larval zebrafish (Danio rerio) at 5.5 days post-fertilization. Our approach utilizes multiple rounds of targeted imaging at different scales to reduce acquisition time and data management requirements. The resulting dataset can be analysed to reconstruct neuronal processes, permitting us to survey all myelinated axons (the projectome). These reconstructions enable precise investigations of neuronal morphology, which reveal remarkable bilateral symmetry in myelinated reticulospinal and lateral line afferent axons. We further set the stage for whole-brain structure–function comparisons by co-registering functional reference atlases and in vivo two-photon fluorescence microscopy data from the same specimen. All obtained images and reconstructions are provided as an open-access resource.

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We thank D. D. Bock and K.-H. Huang for preliminary studies; L.-H. Ma, M. B. Ahrens, and D. Schoppik for dissection help; E. Raviola, H. S. Kim, J. A. Buchanan, E. J. Benecchi, and S. Ito for histology guidance; K. J. Hayworth, J. L. Morgan, N. Kasthuri, and R. Schalek for ssEM advice; T. Kazimiers and J. A. Bogovic for software assistance at the Harvard CBS Neuroengineering Core; B. L. Shanny, A. M. Roberson, M. A. Afifi, F. Gao, A. D. Wong, F. Camacho Garcia, C. S. Elkhill, T. J. Cawley, R. J. Plummer, K. M. Runci, A. Haddad, P. E. Lewis, I. Odstrcil, A. H. Cohen, and P. I. Petkova for reconstructions; and R. C. Reid, R. I. Wilson, and J. R. Sanes for valuable input. Support was provided by the NIH through NINDS and NIMH to F.E. (DP1NS082121, RC2NS069407, U01NS090449) and W.-C.A.L. (R21NS085320) and the Harvard CBS Neuroengineering Core (P30NS062685), through NIGMS to MMBioS via the Pittsburgh Supercomputing Center (P41GM103712); by the DARPA SIMPLEX program through SPAWAR to R.B. and J.T.V. (N66001-15-C-4041); by the Korea NRF through MSIP (NRF-2015M3A9A7029725) and MOE (NRF-2014R1A1A2058773) to W.-K.J.; and by the NIH (T32MH20017, T32HL007901) and the NSF (IIA-EAPSI-1317014) to D.G.C.H.

Author information

Author notes

    • David Grant Colburn Hildebrand
    • , Russel Miguel Torres
    • , Owen Randlett
    • , George Scott Plummer
    • , Ruben Portugues
    • , Isaac Henry Bianco
    •  & Wei-Chung Allen Lee

    Present addresses: Laboratory of Neural Systems, Rockefeller University, New York, New York, USA (D.G.C.H.); Allen Institute for Brain Science, Seattle, Washington, USA (R.M.T.); Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA (O.R.); Tufts University School of Medicine, Boston, Massachusetts, USA (G.S.P.); Max Planck Institute of Neurobiology, Martinsried, Germany (R.P.); Department of Neuroscience, Physiology, and Pharmacology, University College London, London, UK (I.H.B.); F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Boston, Massachusetts, USA (W.-C.A.L.).

    • Jeff William Lichtman
    •  & Florian Engert

    These authors contributed equally to this work.


  1. Graduate Program in Neuroscience, Division of Medical Sciences, Graduate School of Arts and Sciences, Harvard University, Cambridge, Massachusetts, USA

    • David Grant Colburn Hildebrand
  2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA

    • David Grant Colburn Hildebrand
    • , Russel Miguel Torres
    • , Owen Randlett
    • , George Scott Plummer
    • , Ruben Portugues
    • , Isaac Henry Bianco
    • , Alexander Franz Schier
    • , Jeff William Lichtman
    •  & Florian Engert
  3. Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA

    • David Grant Colburn Hildebrand
    • , Alexander Franz Schier
    • , Jeff William Lichtman
    •  & Florian Engert
  4. Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, USA

    • David Grant Colburn Hildebrand
    • , Russel Miguel Torres
    • , Brett Jesse Graham
    •  & Wei-Chung Allen Lee
  5. Image and Data Analysis Core, Harvard Medical School, Boston, Massachusetts, USA

    • David Grant Colburn Hildebrand
    •  & Marcelo Cicconet
  6. School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea

    • Woohyuk Choi
    • , Tran Minh Quan
    • , Jungmin Moon
    •  & Won-Ki Jeong
  7. Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    • Arthur Willis Wetzel
  8. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA

    • Andrew Scott Champion
    •  & Stephan Saalfeld
  9. Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA

    • Alexander David Baden
    • , Kunal Lillaney
    •  & Randal Burns
  10. Department of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland, USA

    • Joshua Tzvi Vogelstein
  11. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    • Alexander Franz Schier
  12. Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA

    • Alexander Franz Schier
  13. FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, USA

    • Alexander Franz Schier


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F.E. and D.G.C.H. designed experiments. R.P., D.G.C.H., and I.H.B. conducted light microscopy. D.G.C.H. prepared and sectioned samples. D.G.C.H. and G.S.P. completed ssEM. A.W.W., S.S., and D.G.C.H. aligned ssEM. D.G.C.H. and O.R. registered light and ssEM. R.M.T., B.J.G., and D.G.C.H. processed reconstructions. M.C. and D.G.C.H. analysed symmetry. W.C., T.M.Q., J.M., D.G.C.H., and W.-K.J. made visualizations. A.S.C. modified annotation software. A.D.B., K.L., R.B., and J.T.V. provided hosting. F.E., J.W.L., W.-C.A.L., and A.F.S. supplied resources. D.G.C.H., F.E., and J.W.L. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to David Grant Colburn Hildebrand or Florian Engert.

Reviewer Information Nature thanks A. Cardona and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information


  1. 1.

    Survey of sections from the 5.5 dpf larval zebrafish series

    Electron micrographs of 17,963 sections acquired at 758.8 × 758.8 × 60 nm3 per voxel to survey sectioning quality and provide a basis for targeting subsequent high-resolution acquisition. Several sections excluded for faster viewing. Scale bar: 250 µm.

  2. 2.

    Section overview volume rendering

    Volume rendering of aligned 758.8 × 758.8 × 60 nm3 per voxel overviews from 17,963 sections shows how much of the 5.5 dpf larval zebrafish was captured with this series. Magenta and yellow planes correspond to reslice planes in Extended Data Fig. 3c. Green plane corresponds to section outlined in Extended Data Fig. 3a. Scale box: 250 µm.

  3. 3.

    Isotropic ssEM through the anterior quarter of the 5.5 dpf larval zebrafish

    Fly-through of aligned 56.4 × 56.4 × 60 nm3 per voxel electron micrographs acquired for 16,000 transverse sections. The resulting image volume contains the anterior quarter and entire brain of a 5.5 dpf larval zebrafish. Several sections excluded for faster viewing. Scale bar: 50 µm.

  4. 4.

    Mauthner cell reconstruction

    Fly-through of aligned 56.4 × 56.4 × 60 nm3 per voxel electron micrographs centred on part of a skeleton reconstruction of the left Mauthner cell (magenta dot) from the 5.5 dpf larval zebrafish ssEM dataset. The video begins at the Mauthner lateral dendrite, proceeds through its soma and axon cap, crosses to the contralateral side, and ends in the spinal cord. Extracting vertical line segments from the centre of these micrographs yielded the contour reslices in Fig. 1a−c. Several sections excluded for faster viewing. Scale bar: 5 µm.

  5. 5.

    Correspondence across light and ssEM datasets

    Fly-through of matched horizontal reslice planes through the 56.4 × 56.4 × 60 nm3 per voxel ssEM dataset (upper) and co-registered 0.637 × 0.637 × 1 µm3 per voxel in vivo two-photon elavl3:GCaMP5G fluorescence dataset (lower) for the 5.5 dpf larval zebrafish. Scale bar: 100 µm.

  6. 6.

    Lateral line primary sensory afferent reconstruction

    Fly-through of the aligned multi-resolution 5.5 dpf larval zebrafish ssEM data centred on part of a skeleton reconstruction of an afferent neuron that innervates a right dorsal neuromast (orange dot). This video contains data from three separate image volumes, starting at 4.0 × 4.0 × 60 nm3 per voxel where the afferent receives input from a neuromast hair cell. The field of view expands to follow the myelinated afferent at 56.4 × 56.4 × 60 nm3 per voxel throughout the periphery. It next magnifies to 18.8 × 18.8 × 60 nm3 per voxel before reaching the soma in the posterior lateral line ganglion and ends in the hindbrain. Scale bar: 1 µm (size changes depending on magnification).

  7. 7.

    Projectome reconstruction

    Volume rendering of the projectome reconstruction formed by annotation of all myelinated axons from the multi-resolution 5.5 dpf larval zebrafish ssEM dataset. The reconstructions are presented within a semi-transparent rendering of the aligned ssEM image volume so that it is possible to reference the positions of the myelinated axons. All reconstructions were manually annotated from the ssEM data. Colours assigned randomly. Scale bar: 100 µm.

  8. 8.

    Bilateral symmetry in the lateral line system

    Volume rendering of lateral line system reconstructions from the multi-resolution 5.5 dpf larval zebrafish ssEM dataset reveal bilateral symmetry in most neuromasts (blue) and the myelinated axons that innervate them. The myelinated axons innervating identified neuromasts (purple) and members of the posterior lateral line nerve (yellow) that likely innervate neuromasts outside the imaged volume are both displayed. Neuromasts have a bilaterally symmetrical counterpart in all but one case (orange) and the myelinated axons innervating them overlap substantially when viewed from the side. Scale bar: 100 µm.

  9. 9.

    Bilateral symmetry in the reticulospinal system

    Volume rendering of the Z-Brain spinal backfill label (red) and reticulospinal axon reconstructions (blue) embedded within semi-transparent 5.5 dpf larval zebrafish ssEM data. Also illustrated is the plane of symmetry (yellow) that was extracted from myelinated axons of identified reticulospinal neurons whose projections formed part of the MLF. Cross-modal registration of the Z-Brain and Zebrafish Brain Browser reference atlases allowed for anatomical characterization of domains within the ssEM dataset and aided in reticulospinal neuron identification. Scale bar: 100 µm.

  10. 10.

    Analysis of symmetry in myelinated axon neighbour relations

    Slice-by-slice 2D symmetry analysis of myelinated axon neighbour relations within the MLF. Angle and distance differences (upper right) were calculated from cross-sectional slices (upper left) through a subset of myelinated axon reconstructions (lower), linearized, and aggregated (middle) for display. The video shows how some panels in Fig. 4 and Extended Data Fig. 9 were constructed.

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