Petascale neural circuit reconstruction: automated methods
Open accessAbstract
3D electron microscopy (EM) has been successful at mapping invertebrate nervous systems, but the approach has been limited to small chunks of mammalian brains. To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels as axon, dendrite, soma, and other semantic categories, and detect synapses and assign them to presynaptic and postsynaptic segments. The output of neuronal boundary detection is segmented by mean affinity agglomeration with semantic and size constraints. Pipeline operations are implemented by leveraging distributed and cloud computing. Intermediate results of the pipeline are held in cloud storage, and can be effortlessly viewed as images, which aids debugging. We applied the pipeline to create an automated reconstruction of an EM image volume spanning four visual cortical areas of a mouse brain. Code for the pipeline is publicly available, as is the reconstructed volume.
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Computational advances have now closed this gap and FAFB images were accurately aligned with a new approach that leverages convolutional nets.
“Computational advances have now closed this gap107 and FAFB images were accurately aligned with a new approach that leverages convolutional nets108.”
From Neuronal wiring diagram of an adult brain (2024) · cites this paper as [107]
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Tools for connectomic reconstruction and analysis of a female <i>Drosophila</i> ventral nerve cord
Azevedo, A., Lesser, E., Phelps, J. S., Mark, B., Elabbady, L., Kuroda, S., Sustar, A., Moussa, A., Kandelwal, A., Dallmann, C. J., et al. (2022) · doi:10.1101/2022.12.15.520299 · Cited by 120 · see citing works
“We then used convolutional neural networks (CNNs) to segment the dataset into neurons and fragments of neurons (Macrina et al., 2021) and to predict synapse locations ( Figure 1c ), as well as pre-and post-synaptic partners (Buhmann et al., 2021).”
MethodSelf-citationConnectomics of predicted Sst transcriptomic types in mouse visual cortex
Gamlin, C. R., Schneider-Mizell, C. M., Mallory, M., Elabbady, L., Gouwens, N. W., Williams, G., Mukora, A., Dalley, R. A., Bodor, Á. L., Brittain, D., et al. (2025) · Nature · doi:10.1038/s41586-025-08805-6 · Cited by 31 · see citing works
Self-citationPerisomatic ultrastructure efficiently classifies cells in mouse cortex
Elabbady, L., Seshamani, S., Mu, S., Mahalingam, G., Schneider-Mizell, C. M., Bodor, Á. L., Bae, J. A., Brittain, D., Buchanan, J., Bumbarger, D. J., et al. (2025) · Nature · doi:10.1038/s41586-024-07765-7 · Cited by 23 · see citing works
Self-citationFast imaging of millimeter-scale areas with beam deflection transmission electron microscopy
Zheng, Z., Own, C. S., Wanner, A., Koene, R. A., Hammerschmith, E. W., Silversmith, W., Kemnitz, N., Lu, R., Tank, D. W., & Seung, H. S. (2024) · Nature Communications · doi:10.1038/s41467-024-50846-4 · Cited by 23 · see citing works
Self-citationSyConn2: dense synaptic connectivity inference for volume electron microscopy
Schubert, P. J., Dorkenwald, S., Januszewski, M., Klimesch, J., Svara, F., Mancu, A., Ahmad, H., Fee, M. S., Jain, V., & Kornfeld, J. M. R. (2022) · Nature Methods · doi:10.1038/s41592-022-01624-x · Cited by 20 · see citing works
Self-citationElabbady, L., Seshamani, S., Mu, S., Mahalingam, G., Schneider-Mizell, C. M., Bodor, Á. L., Bae, J. A., Brittain, D., Buchanan, J., Bumbarger, D. J., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.20.499976 · Cited by 19 · see citing works
Self-citationThe synaptic architecture of layer 5 thick tufted excitatory neurons in mouse visual cortex
Bodor, A. L., Schneider-Mizell, C. M., Zhang, C., Elabbady, L., Mallen, A., Bergeson, A., Brittain, D., Buchanan, J., Bumbarger, D. J., Dalley, R. A., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02004-2 · Cited by 17 · see citing works
Self-citationNondestructive X-ray tomography of brain tissue ultrastructure
Bosch, C., Aidukas, T., Holler, M., Pacureanu, A., Müller, E. A., Peddie, C. J., Zhang, Y., Cook, P., Collinson, L., Bunk, O., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02891-0 · Cited by 15 · see citing works
Boelts, J., Harth, P., Gao, R., Udvary, D., Yáñez, F., Baum, D., Hege, H., Oberlaender, M., & Macke, J. H. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011406 · Cited by 13 · see citing works
Gamlin, C. R., Schneider-Mizell, C. M., Mallory, M., Elabbady, L., Gouwens, N. W., Williams, G., Mukora, A., Dalley, R. A., Bodor, Á. L., Brittain, D., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.22.533857 · Cited by 11 · see citing works
Self-citationUnsupervised Domain Adaptation for EM Image Denoising With Invertible Networks
Deng, S., Chen, Y., Huang, W., Zhang, R., & Xiong, Z. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3431192 · Cited by 10 · see citing works
Boulanger-Weill, J., Kämpf, F., Schuhknecht, G. F. P., Schalek, R. L., Garza, R., Petkova, M. D., Vohra, S. K., Wu, Y., Savaliya, J. H., Tiller, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.14.643363 · Cited by 8 · see citing works
The Synaptic Architecture of Layer 5 Thick Tufted Excitatory Neurons in the Visual Cortex of MicePreprint
Bodor, Á. L., Schneider-Mizell, C. M., Zhang, C., Elabbady, L., Mallen, A., Bergeson, A., Brittain, D., Buchanan, J., Bumbarger, D. J., Dalley, R. A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.18.562531 · Cited by 7 · see citing works
Self-citationmsemalign: a pipeline for serial section multibeam scanning electron microscopy volume alignment
Watkins, P. V., Jelli, E., & Briggman, K. L. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1281098 · Cited by 6 · see citing works
Park, S. Y., Sheridan, A., An, B., Jarvis, E., Lyudchik, J., Patton, W., Axup, J. Y., Chan, S., Damstra, H. G. J., Leible, D., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.26.678648 · Cited by 6 · see citing works
Unifying the Electron Microscopy Multiverse through a Large-scale Foundation ModelPreprint
He, L., Shi, R., Wang, W., Fang, G., Cai, Y., & Ма, Л. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.13.648639 · Cited by 5 · see citing works
Accelerating Neuron Reconstruction with PATHFINDERPreprint
Januszewski, M., Templier, T., Hayworth, K. J., Peale, D. R., & Hess, H. F. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.16.654254 · Cited by 5 · see citing works
EM-Compressor: Electron Microscopy Image Compression in Connectomics with Variational Autoencoders
Li, Y., Park, C. F., Xenes, D., Bishop, C. A., Berger, D. R., Samuel, A. D. T., Wester, B. A., Lichtman, J. W., Pfister, H., Li, W., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-77786-8_16 · Cited by 4 · see citing works
Expected affine: A registration method for damaged section in serial sections electron microscopy
Tong, X., Shen, L., Li, L., Chen, X., & Han, H. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.944050 · Cited by 4 · see citing works
High-fidelity Image Restoration of Large 3D Electron Microscopy Volume
Kreinin, Y., Gunn, P., Chklovskii, D. B., & Wu, J. (2024) · Microscopy and Microanalysis · doi:10.1093/mam/ozae098 · Cited by 4 · see citing works
Self-citationWu, J., Turner, N. L., Bae, J. A., Vishwanathan, A., & Seung, H. S. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.828169 · Cited by 4 · see citing works
Self-citationA Novel Semi-automated Proofreading and Mesh Error Detection Pipeline for Neuron ExtensionPreprint
Joyce, J., Chalavadi, R., Chan, J., Tanna, S., Xenes, D., Kuo, N. P., Rose, V. A., Matelsky, J., Kitchell, L. M., Bishop, C. A., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.20.563359 · Cited by 4 · see citing works
Bayesian reconstruction of memories stored in neural networks from their connectivity
Goldt, S., Krząkała, F., Zdeborová, L., & Brunel, N. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010813 · Cited by 3 · see citing works
Invariant synaptic density across speciesPreprint
Castro, A. F., & Cardona, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.18.604056 · Cited by 3 · see citing works
Connectomic Organization of the Suprachiasmatic NucleusPreprint
Liu, J., Yu, J., Shen, L., Chen, X., Ma, L., Zhai, H., Li, L., Zhang, L., Wang, L., Yuan, J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.20.619252 · Cited by 3 · see citing works
Connectome of a human foveal retinaPreprint
Kim, Y. J., PACKER, O. S., Macrina, T., Pollreisz, A., Curcio, C. A., Lee, K., Kemnitz, N., Ih, D., Nguyen, T., Lu, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.05.647403 · Cited by 3 · see citing works
Self-citationZheng, Z., Park, C., Hammerschmith, E. W., Lu, R., Yu, S.-C., Sorek, M., Silverman, B., Jordan, C. S., Sterling, A. R., Silversmith, W., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.09.663979 · Cited by 3 · see citing works
Self-citationVohra, S. K., Eberle, M., Boulanger-Weill, J., Petkova, M. D., Schuhknecht, G. F. P., Herrera, K. J., Kämpf, F., Ruetten, V. M. S., Lichtman, J. W., Engert, F., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.14.664689 · Cited by 2 · see citing works
Putti, E., Faini, G., Dang, J. T.-M., Savaliya, J. H., Eggeler, F., Duroure, K., Vougny, J., Álvarez, G., Pujades, C., Bahl, A., et al. (2026) · Science Advances · doi:10.1126/sciadv.adz4585 · Cited by 2 · see citing works
A new framework for analyzing mass transport in cortical brain tissue at <10 nm resolutionPreprint
Elbert, D. L., & Esguerra, D. P. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.02.646802 · Cited by 1 · see citing works
Lrrns define a visual circuit underlying brightness and contrast perceptionPreprint
Putti, E., Faini, G., Dang, J. T.-M., Eggeler, F., Savaliya, J. H., Duroure, K., Vougny, J., Bahl, A., Lichtman, J. W., Engert, F., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.05.652281 · Cited by 1 · see citing works
Ascending nociceptive pathways drive rapid escape and sustained avoidance in adult DrosophilaPreprint
Jones, J. M., Sustar, A., Mamiya, A., Walling-Bell, S., Chou, G. M., Cook, A. P., & Tuthill, J. C. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.28.684868 · Cited by 1 · see citing works
Mechanisms of robust feature extraction in early visual processing
Molina-Obando, S. (2022) · doi:10.53846/goediss-461
Ahmed, I., Zhang, B.-L., Yue, B., Islam, N., Rahman, M. A., Mithu, M. M., & Tang, X. (2026) · New medicine. · doi:10.61958/nmqv6943
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Self-citationInvariant synaptic density across speciesPreprint
Castro, A. F., & Cardona, A. (2026) · eLife · doi:10.7554/elife.108642
Invariant synaptic density across speciesPreprint
Castro, A. F., & Cardona, A. (2026) · eLife · doi:10.7554/elife.108642.1
- Authors
- Macrina, T., Lee, K., Lu, R., Turner, N. L., Wu, J., Popovych, S., Silversmith, W., Kemnitz, N., Bae, J. A., Castro, M. A., Dorkenwald, S., Halageri, A., Jia, Z., Jordan, C., Li, K., Mitchell, E., Mondal, S. S., Mu, S., Nehoran, B., Wong, W., Yu, S.-C., Bodor, A. L., Brittain, D., Buchanan, J., Bumbarger, D. J., Cobos, E., Collman, F., Elabbady, L., Fahey, P. G., Froudarakis, E., Kapner, D., Kinn, S., Mahalingam, G., Papadopoulos, S., Patel, S., Schneider-Mizell, C. M., Sinz, F. H., Takeno, M., Torres, R., Yin, W., Pitkow, X., Reimer, J., Tolias, A. S., Reid, R. C., Costa, N. M. D., & Seung, H. S.
- Affiliations
- Princeton University (US)
- Allen Institute for Brain Science (US)
- Baylor College of Medicine (US)
- Corresponding author
- Seung, H. Sebastian
- ORCID
- Macrina, Thomas
- Lee, Kisuk
- Lu, Ran
- Turner, Nicholas L.
- Wu, Jingpeng
- Silversmith, William
- Kemnitz, Nico
- Bae, J. Alexander
- Castro, Manuel A.
- Dorkenwald, Sven
- Halageri, Akhilesh
- Jia, Zhen
- Jordan, Chris
- Li, Kai
- Mitchell, Eric
- Mondal, Shanka Subhra
- Mu, Shang
- Nehoran, Barak
- Yu, Szi-chieh
- Brittain, Derrick
- Buchanan, JoAnn
- Bumbarger, Daniel J.
- Collman, Forrest
- Elabbady, Leila
- Fahey, Paul G.
- Froudarakis, Emmanouil
- Kinn, Sam
- Mahalingam, Gayathri
- Papadopoulos, Stelios
- Patel, Saumil
- Schneider-Mizell, Casey M.
- Sinz, Fabian H.
- Takeno, Marc
- Torres, Russel
- Yin, Wenjing
- Pitkow, Xaq
- Reimer, Jacob
- Tolias, Andreas S.
- Reid, R. Clay
- Costa, Nuno Maçarico da
- Seung, H. Sebastian
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2021-08-05
- OpenAlex
- W3189506822
- Cited by
- 55
- References
- 68
- Citations by year
- 2026: 5 · 2025: 20 · 2024: 9 · 2023: 10 · 2022: 8 · 2021: 3
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, other-oa)
- Funders
- National Science Foundation (1552868, CAREER, 1707400)
- Princeton University
- Johns Hopkins University
- G. Harold and Leila Y. Mathers Foundation
- National Institutes of Health (MH114824)
- Intelligence Advanced Research Projects Activity (D16PC00003, D16PC0005, D16PC00004)
- Interior Business Center
- National Institute of Mental Health (U01 MH114824, U01MH117072, RF1MH117815, MH114824, RF1MH123400, U19MH114830)
- National Eye Institute (NEI R01, EY027036, R01EY027036)
- National Institute of Neurological Disorders and Stroke (R01NS104926, U19NS104648, NS104926, NS104648)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- neural circuit reconstruction, serial section electron microscopy, convolutional neural networks, image registration, synapse detection, distributed computing, cloud computing, mouse visual cortex
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