Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity
Open accessAbstract
We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 μm 3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.
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A high clustering coefficient and an over-representation of highly connected motifs suggest that the local structure of the brain displays a high degree of non-randomness.
“A high clustering coefficient and an over-representation of highly connected motifs suggest that the local structure of the brain displays a high degree of non-randomness, consistent with previous studies in C. elegans7,21 and in the mouse cortex11,24,25.”
From Network statistics of the whole-brain connectome of Drosophila (2024) · cites this paper as [11]
The Results section reports high clustering and overrepresentation of highly connected motifs relative to an Erdős–Rényi model, but says these patterns are largely predicted by a degree-preserving configuration model. It concludes that nonrandomness of cortical connectivity is subtler than commonly supposed; the Discussion cautions against calling cortical motifs highly “nonrandom.” (LLM, conf=0.88)
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Cites
Adam: A Method for Stochastic Optimization
Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946 · see citing works
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430 · see citing works
Self-citationPyTorch: An Imperative Style, High-Performance Deep Learning Library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al. (2019) · arXiv · doi:10.48550/arxiv.1912.01703 · Cited by 31,473 · see citing works
Advances in neural information processing systems 7
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90463-0 · Cited by 14,759 · see citing works
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460 · see citing works
Self-citationNetwork motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368 · see citing works
seaborn: statistical data visualization
Waskom, M. (2021) · Journal of Open Source Software · doi:10.21105/joss.03021 · Cited by 7,310 · see citing works
Statsmodels: Econometric and Statistical Modeling with Python
Seabold, S., & Perktold, J. (2010) · Proceedings of the Python in Science Conferences · doi:10.25080/majora-92bf1922-011 · Cited by 6,673 · see citing works
Modeling by shortest data description
Rissanen, J. (1978) · Automatica · doi:10.1016/0005-1098(78)90005-5 · Cited by 6,011 · see citing works
(1987) · Medical Entomology and Zoology · Cited by 2,512 · see citing works
Berridge, M. J. (1998) · Neuron · doi:10.1016/s0896-6273(00)80510-3 · Cited by 2,189 · see citing works
On the Convergence of Adam and Beyond
Reddi, S. J., Kale, S., & Kumar, S. (2019) · arXiv · doi:10.48550/arxiv.1904.09237 · Cited by 1,771 · see citing works
Synaptic Energy Use and Supply
Harris, J. J., Jolivet, R., & Attwell, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.019 · Cited by 1,747 · see citing works
2013 IEEE 10th International Symposium on Biomedical Imaging
(2013) · doi:10.1109/isbi20048.2013 · Cited by 1,637 · see citing works
Highly nonrandom features of synaptic connectivity in local cortical circuits
Song, S., Sjöström, P. J., Reigl, M., Nelson, S., & Chklovskii, D. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030068 · Cited by 1,512 · see citing works
The importance of dendritic mitochondria in the morphogenesis and plasticity of spines and synapses
Li, Z., Okamoto, K.-I., Hayashi, Y., & Sheng, M. (2004) · Cell · doi:10.1016/j.cell.2004.11.003 · Cited by 1,498 · see citing works
Self-organization of orientation sensitive cells in the striate cortex
Malsburg, C. V. D. (1973) · Kybernetik · doi:10.1007/bf00288907 · Cited by 1,444 · see citing works
(1976) · Medical Entomology and Zoology · Cited by 1,328 · see citing works
Gilbert, E. N. (1959) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177706098 · Cited by 1,122 · see citing works
Highly selective receptive fields in mouse visual cortex
Niell, C. M., & Stryker, M. P. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.0623-08.2008 · Cited by 1,081 · see citing works
A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster
Zheng, Z., Lauritzen, J. S., Perlman, E., Robinson, C. G., Nichols, M., Milkie, D., Torrens, O., Price, J., Fisher, C. B., Sharifi, N., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.019 · Cited by 1,050 · see citing works
Saturated Reconstruction of a Volume of Neocortex
Kasthuri, N., Hayworth, K. J., Berger, D. R., Schalek, R. L., Conchello, J. A., Knowles-Barley, S., Lee, D., Vázquez-Reina, A., Kaynig, V., Jones, T. R., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.054 · Cited by 1,044 · see citing works
Self-citationSimultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data
Pnevmatikakis, E. A., Soudry, D., Gao, Y., Machado, T. A., Merel, J., Pfau, D., Reardon, T. R., Mu, Y., Lacefield, C., Yang, W., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.037 · Cited by 1,035 · see citing works
Self-citationThe functional diversity of retinal ganglion cells in the mouse
Baden, T., Berens, P., Franke, K., Román Rosón, M., Bethge, M., & Euler, T. (2016) · Nature · doi:10.1038/nature16468 · Cited by 999 · see citing works
Connectomic reconstruction of the inner plexiform layer in the mouse retina
Helmstaedter, M., Briggman, K. L., Turaga, S. C., Jain, V., Seung, H. S., & Denk, W. (2013) · Nature · doi:10.1038/nature12346 · Cited by 997 · see citing works
Self-citationTrakEM2 Software for Neural Circuit Reconstruction
Cardona, A., Saalfeld, S., Schindelin, J., Arganda‐Carreras, I., Preibisch, S., Longair, M., Tomančák, P., Hartenstein, V., & Douglas, R. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038011 · Cited by 989 · see citing works
Recurrent Excitation in Neocortical Circuits
Douglas, R. J., Christof Koch, A., Mahowald, M. A., Martin, K. A. C., & Suarez, H. H. (1995) · Science · doi:10.1126/science.7638624 · Cited by 985 · see citing works
Markram, H., Lübke, J., Frotscher, M., Roth, A., & Sakmann, B. (1997) · The Journal of Physiology · doi:10.1113/jphysiol.1997.sp022031 · Cited by 960 · see citing works
Megı́as, M., Emri, Z., Freund, T. F., & Gulyás, A. I. (2001) · Neuroscience · doi:10.1016/s0306-4522(00)00496-6 · Cited by 950 · see citing works
Whole-animal connectomes of both Caenorhabditis elegans sexes
Cook, S. J., Jarrell, T. A., Brittin, C. A., Wang, Y., Bloniarz, A. E., Yakovlev, M. A., Nguyen, K. C. Q., Tang, L. T.-H., Bayer, E. A., Duerr, J. S., et al. (2019) · Nature · doi:10.1038/s41586-019-1352-7 · Cited by 921 · see citing works
Wiring specificity in the direction-selectivity circuit of the retina
Briggman, K. L., Helmstaedter, M., & Denk, W. (2011) · Nature · doi:10.1038/nature09818 · Cited by 883 · see citing works
Structural Properties of the Caenorhabditis elegans Neuronal Network
Varshney, L. R., Chen, B. L., Paniagua, E., Hall, D. H., & Chklovskii, D. B. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001066 · Cited by 867 · see citing works
Oligodendrocytes: Myelination and Axonal SupportPreprint
Simons, M., & Nave, K. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a020479 · Cited by 862 · see citing works
Functional specificity of local synaptic connections in neocortical networks
Ko, H., Hofer, S. B., Pichler, B., Buchanan, K. A., Sjöström, P. J., & Mrsic‐Flogel, T. D. (2011) · Nature · doi:10.1038/nature09880 · Cited by 861 · see citing works
Network anatomy and in vivo physiology of visual cortical neurons
Bock, D. D., Lee, W.-C. A., Kerlin, A., Andermann, M. L., Hood, G., Wetzel, A. W., Yurgenson, S., Soucy, E. R., Kim, H. S., & Reid, R. C. (2011) · Nature · doi:10.1038/nature09802 · Cited by 851 · see citing works
Self-citationDendritic integration of excitatory synaptic input
Magee, J. C. (2000) · Nature reviews. Neuroscience · doi:10.1038/35044552 · Cited by 737 · see citing works
A synaptic organizing principle for cortical neuronal groups
Perin, R., Berger, T. K., & Markram, H. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016051108 · Cited by 718 · see citing works
Transitivity in Structural Models of Small Groups
Holland, P. W., & Leinhardt, S. (1971) · Comparative Group Studies · doi:10.1177/104649647100200201 · Cited by 664 · see citing works
Neuronal variability: noise or part of the signal?
Stein, R. B., Gossen, E. R., & Jones, K. E. (2005) · Nature reviews. Neuroscience · doi:10.1038/nrn1668 · Cited by 658 · see citing works
Orientation Selectivity in Macaque V1: Diversity and Laminar Dependence
Ringach, D. L., Shapley, R. M., & Hawken, M. J. (2002) · Journal of Neuroscience · doi:10.1523/jneurosci.22-13-05639.2002 · Cited by 653 · see citing works
Local Calcium Signaling in Neurons
Augustine, G. J., Santamarı́a, F., & Tanaka, K. (2003) · Neuron · doi:10.1016/s0896-6273(03)00639-1 · Cited by 603 · see citing works
Ultrastructural evidence for synaptic scaling across the wake/sleep cycle
de Vivo, L., Bellesi, M., Marshall, W., Bushong, E. A., Ellisman, M. H., Tononi, G., & Cirelli, C. (2017) · Science · doi:10.1126/science.aah5982 · Cited by 574 · see citing works
Slow dynamics and high variability in balanced cortical networks with clustered connections
Litwin-Kumar, A., & Doiron, B. (2012) · Nature Neuroscience · doi:10.1038/nn.3220 · Cited by 530 · see citing works
Functional organization of excitatory synaptic strength in primary visual cortex
Cossell, L., Iacaruso, M. F., Muir, D. R., Houlton, R., Sader, E., Ko, H., Hofer, S. B., & Mrsic‐Flogel, T. D. (2015) · Nature · doi:10.1038/nature14182 · Cited by 529 · see citing works
Fast online deconvolution of calcium imaging data
Friedrich, J. H., Zhou, P., & Paninski, L. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005423 · Cited by 517 · see citing works
Self-citationAnatomy and function of an excitatory network in the visual cortex
Lee, W.-C. A., Bonin, V., Reed, M., Graham, B. J., Hood, G., Glattfelder, K. J., & Reid, R. C. (2016) · Nature · doi:10.1038/nature17192 · Cited by 511 · see citing works
Self-citationHeterogeneity in the pyramidal network of the medial prefrontal cortex
Wang, Y., Markram, H., Goodman, P. H., Berger, T. K., Ma, J., & Goldman-Rakic, P. S. (2006) · Nature Neuroscience · doi:10.1038/nn1670 · Cited by 503 · see citing works
Contacts between the endoplasmic reticulum and other membranes in neurons
Wu, Y., Whiteus, C., Xu, C. S., Hayworth, K. J., Weinberg, R. J., Hess, H. F., & Camilli, P. V. D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1701078114 · Cited by 481 · see citing works
Gulyás, A. I., Megı́as, M., Emri, Z., & Freund, T. F. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-22-10082.1999 · Cited by 476 · see citing works
Space–time wiring specificity supports direction selectivity in the retina
EyeWirers, T., Kim, J. S., Greene, M. J., Zlateski, A., Lee, K., Richardson, M., Turaga, S. C., Purcaro, M., Balkam, M., Robinson, A., et al. (2014) · Nature · doi:10.1038/nature13240 · Cited by 450 · see citing works
Self-citationOrigin of microglia: current concepts and past controversies
Ginhoux, F., & Prinz, M. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a020537 · Cited by 446 · see citing works
The emergence of functional microcircuits in visual cortex
Ko, H., Cossell, L., Baragli, C., Antolík, J., Claudia Clopath, A., Hofer, S. B., & Mrsic‐Flogel, T. D. (2013) · Nature · doi:10.1038/nature12015 · Cited by 438 · see citing works
Diverse coupling of neurons to populations in sensory cortex
Okun, M., Steinmetz, N. A., Cossell, L., Iacaruso, M. F., Ko, H., Barthó, P., Moore, T., Hofer, S. B., Mrsic‐Flogel, T. D., Carandini, M., et al. (2015) · Nature · doi:10.1038/nature14273 · Cited by 428 · see citing works
Regional Dendritic and Spine Variation in Human Cerebral Cortex: a Quantitative Golgi Study
Jacobs, B. (2001) · Cerebral Cortex · doi:10.1093/cercor/11.6.558 · Cited by 423 · see citing works
Morphological Basis of Long-Term Habituation and Sensitization in Aplysia
Bailey, C. H., & Chen, M. (1983) · Science · doi:10.1126/science.6828885 · Cited by 420 · see citing works
Pericytes and Neurovascular Function in the Healthy and Diseased Brain
Brown, L. S., Foster, C. G., Courtney, J.-M., King, N. E., Howells, D. W., & Sutherland, B. A. (2019) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2019.00282 · Cited by 406 · see citing works
Differentiation and death of premyelinating oligodendrocytes in developing rodent brain
Trapp, B. D., Nishiyama, A., Cheng, D., & Macklin, W. (1997) · The Journal of Cell Biology · doi:10.1083/jcb.137.2.459 · Cited by 395 · see citing works
Structural Components of Synaptic Plasticity and Memory ConsolidationPreprint
Bailey, C. H., Kandel, E. R., & Harris, K. M. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a021758 · Cited by 393 · see citing works
Mitochondrial Trafficking to Synapses in Cultured Primary Cortical Neurons
Chang, D. T. W., Honick, A. S., & Reynolds, I. J. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.1012-06.2006 · Cited by 391 · see citing works
Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation
Turaga, S. C., Murray, J. F., Jain, V., Roth, F., Helmstaedter, M., Briggman, K., Denk, W., & Seung, H. S. (2010) · Neural Computation · doi:10.1162/neco.2009.10-08-881 · Cited by 376 · see citing works
Self-citationDistal Initiation and Active Propagation of Action Potentials in Interneuron Dendrites
Martina, M., Vida, I., & Jonas, P. (2000) · Science · doi:10.1126/science.287.5451.295 · Cited by 375 · see citing works
Spatially Stable Mitochondrial Compartments Fuel Local Translation during Plasticity
Rangaraju, V., Lauterbach, M. A., & Schuman, E. M. (2019) · Cell · doi:10.1016/j.cell.2018.12.013 · Cited by 355 · see citing works
Branch Input Resistance and Steady Attenuation for Input to One Branch of a Dendritic Neuron Model
Rall, W., & Rinzel, J. (1973) · Biophysical Journal · doi:10.1016/s0006-3495(73)86014-x · Cited by 352 · see citing works
Courchet, J., Lewis, T. L., Lee, S., Courchet, V., Liou, D.-Y., Aizawa, S., & Polleux, F. (2013) · Cell · doi:10.1016/j.cell.2013.05.021 · Cited by 351 · see citing works
Self-citationTuned thalamic excitation is amplified by visual cortical circuits
Lien, A. D., & Scanziani, M. (2013) · Nature Neuroscience · doi:10.1038/nn.3488 · Cited by 339 · see citing works
Dense connectomic reconstruction in layer 4 of the somatosensory cortex
Motta, A., Berning, M., Boergens, K. M., Staffler, B., Beining, M., Loomba, S., Hennig, P., Wissler, H., & Helmstaedter, M. (2019) · Science · doi:10.1126/science.aay3134 · Cited by 333 · see citing works
Large-volume en-bloc staining for electron microscopy-based connectomics
Hua, Y., Laserstein, P., & Helmstaedter, M. N. (2015) · Nature Communications · doi:10.1038/ncomms8923 · Cited by 330 · see citing works
Elastic volume reconstruction from series of ultra-thin microscopy sections
Saalfeld, S., Fetter, R., Cardona, A., & Tomancak, P. (2012) · Nature Methods · doi:10.1038/nmeth.2072 · Cited by 329 · see citing works
State Dependence of Noise Correlations in Macaque Primary Visual Cortex
Ecker, A. S., Berens, P., Cotton, R. J., Subramaniyan, M., Denfield, G. H., Cadwell, C. R., Smirnakis, S. M., Bethge, M., & Tolias, A. S. (2014) · Neuron · doi:10.1016/j.neuron.2014.02.006 · Cited by 323 · see citing works
Self-citationBourne, J. N., & Harris, K. M. (2011) · Hippocampus · doi:10.1002/hipo.20768 · Cited by 318 · see citing works
Geometry and structural plasticity of synaptic connectivity
Stepanyants, A., Hof, P. R., & Chklovskii, D. B. (2002) · Neuron · doi:10.1016/s0896-6273(02)00652-9 · Cited by 312 · see citing works
Synaptic Economics: Competition and Cooperation in Synaptic Plasticity
Miller, K. D. (1996) · Neuron · doi:10.1016/s0896-6273(00)80169-5 · Cited by 307 · see citing works
High-contrast en bloc staining of neuronal tissue for field emission scanning electron microscopy
Tapia, J. C., Kasthuri, N., Hayworth, K. J., Schalek, R., Lichtman, J. W., Smith, S. J., & Buchanan, J. (2012) · Nature Protocols · doi:10.1038/nprot.2011.439 · Cited by 296 · see citing works
Self-citationFlyWire: online community for whole-brain connectomics
Dorkenwald, S., McKellar, C. E., Macrina, T., Kemnitz, N., Lee, K., Lu, R., Wu, J., Popovych, S., Mitchell, E., Nehoran, B., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01330-0 · Cited by 289 · see citing works
Self-citationUltrastructural Analysis of Hippocampal Neuropil from the Connectomics Perspective
Mishchenko, Y., Hu, T., Špaček, J., Mendenhall, J. M., Harris, K. M., & Chklovskii, D. B. (2010) · Neuron · doi:10.1016/j.neuron.2010.08.014 · Cited by 277 · see citing works
Dendritic morphology of pyramidal neurones of the visual cortex of the rat: III. Spine distributions
Larkman, A. U. (1991) · The Journal of Comparative Neurology · doi:10.1002/cne.903060209 · Cited by 274 · see citing works
High-accuracy neurite reconstruction for high-throughput neuroanatomy
Helmstaedter, M. N., Briggman, K. L., & Denk, W. T. (2011) · Nature Neuroscience · doi:10.1038/nn.2868 · Cited by 271 · see citing works
The Fuzzy Logic of Network Connectivity in Mouse Visual Thalamus
Morgan, J., Berger, D. R., Wetzel, A. W., & Lichtman, J. W. (2016) · Cell · doi:10.1016/j.cell.2016.02.033 · Cited by 270 · see citing works
Motile axonal mitochondria contribute to the variability of presynaptic strength
Sun, T., Qiao, H., Pan, P.-Y., Chen, Y., & Sheng, Z.-H. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.06.040 · Cited by 263 · see citing works
Digital Museum of Retinal Ganglion Cells with Dense Anatomy and Physiology
Bae, J. A., Mu, S., Kim, J. S., Turner, N. L., Tartavull, I., Kemnitz, N., Jordan, C. S., Norton, A. D., Silversmith, W. M., Prentki, R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.04.040 · Cited by 263 · see citing works
Self-citationLewis, T. L., Kwon, S.-K., Lee, A., Shaw, R., & Polleux, F. (2018) · Nature Communications · doi:10.1038/s41467-018-07416-2 · Cited by 260 · see citing works
Self-citationLoewenstein, Y., Kuras, A., & Rumpel, S. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.6130-10.2011 · Cited by 256 · see citing works
Species-specific wiring for direction selectivity in the mammalian retina
Ding, H., Smith, R. G., Poleg-Polsky, A., Diamond, J. S., & Briggman, K. L. (2016) · Nature · doi:10.1038/nature18609 · Cited by 253 · see citing works
Penalized-distance volumetric skeleton algorithm
Bitter, I., Kaufman, A. E., & Sato, M. (2001) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/2945.942688 · Cited by 251 · see citing works
Structure and function of a neocortical synapse
Holler, S., Köstinger, G., Martin, K. A. C., Schuhknecht, G. F. P., & Stratford, K. J. (2021) · Nature · doi:10.1038/s41586-020-03134-2 · Cited by 249 · see citing works
Spatial Profile of Excitatory and Inhibitory Synaptic Connectivity in Mouse Primary Auditory Cortex
Levy, R. B., & Reyes, A. D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.5158-11.2012 · Cited by 249 · see citing works
Configuring Random Graph Models with Fixed Degree Sequences
Fosdick, B. K., Larremore, D. B., Nishimura, J., & Ugander, J. (2018) · SIAM Review · doi:10.1137/16m1087175 · Cited by 246 · see citing works
Funke, J., Tschopp, F., Grisaitis, W., Sheridan, A., Singh, C., Saalfeld, S., & Turaga, S. C. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2835450 · Cited by 219 · see citing works
Berger, D. R., Seung, H. S., & Lichtman, J. W. (2018) · Frontiers in Neural Circuits · doi:10.3389/fncir.2018.00088 · Cited by 217 · see citing works
Self-citationFunctional connectomics spanning multiple areas of mouse visual cortex
The MICrONS Consortium, Bae, J. A., Baptiste, M., Bishop, C. A., Bodor, A. L., Brittain, D., Buchanan, J., Bumbarger, D. J., Castro, M. A., Celii, B., et al. (2021) · doi:10.1101/2021.07.28.454025 · Cited by 214 · see citing works
Self-citationThe fractions of short- and long-range connections in the visual cortex
Stepanyants, A., Martinez, L. M., Ferecskó, A. S., & Kisvárday, Z. F. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810390106 · Cited by 208 · see citing works
Kwon, S., Sando, R. C., Lewis, T. L., Hirabayashi, Y., Maximov, A., & Polleux, F. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002516 · Cited by 201 · see citing works
Self-citationDickey, A. S., & Strack, S. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3159-11.2011 · Cited by 197 · see citing works
Superhuman Accuracy on the SNEMI3D Connectomics ChallengePreprint
Lee, K., Zung, J., Li, P. H., Jain, V., & Seung, H. S. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.00120 · Cited by 196 · see citing works
Self-citationQuantitative 3D Mapping of the Human Skeletal Muscle Mitochondrial Network
Vincent, A. E., White, K., Davey, T., Philips, J., Ogden, R. T., Lawless, C., Warren, C., Hall, M. G., Ng, Y. S., Falkous, G., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.01.010 · Cited by 195 · see citing works
Connectivity map of bipolar cells and photoreceptors in the mouse retina
Behrens, C., Schubert, T., Haverkamp, S., Euler, T., & Berens, P. (2016) · eLife · doi:10.7554/elife.20041 · Cited by 185 · see citing works
CDeep3M—Plug-and-Play cloud-based deep learning for image segmentation
Haberl, M. G., Churas, C., Tindall, L., Boassa, D., Phan, S., Bushong, E. A., Madany, M., Akay, R., Deerinck, T. J., Peltier, S. T., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0106-z · Cited by 181 · see citing works
Rich cell-type-specific network topology in neocortical microcircuitry
Gal, E., London, M., Globerson, A., Ramaswamy, S., Reimann, M., Muller, E. B., Markram, H., & Segev, I. (2017) · Nature Neuroscience · doi:10.1038/nn.4576 · Cited by 180 · see citing works
The Diversity of Cortical Inhibitory Synapses
Kubota, Y., Karube, F., Nomura, M., & Kawaguchi, Y. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00027 · Cited by 180 · see citing works
Development of direction selectivity in mouse cortical neurons
Rochefort, N. L., Narushima, M., Grienberger, C., Marandi, N., Hill, D. N., & Konnerth, A. (2011) · Neuron · doi:10.1016/j.neuron.2011.06.013 · Cited by 178 · see citing works
Popov, V. I., Medvedev, N. I., Davies, H. A., & Stewart, M. G. (2005) · The Journal of Comparative Neurology · doi:10.1002/cne.20682 · Cited by 175 · see citing works
López‐Doménech, G., Higgs, N., Vaccaro, V., Roš, H., Arancibia‐Cárcamo, I. L., MacAskill, A. F., & Kittler, J. T. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.09.004 · Cited by 174 · see citing works
Benavides‐Piccione, R., Fernaud-Espinosa, I., Robles, V., Yuste, R., & DeFelipe, J. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs154 · Cited by 173 · see citing works
Untangling GABAergic wiring in the cortical microcircuit
Kubota, Y. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.10.003 · Cited by 172 · see citing works
Abbott, L. F., Bock, D. D., Callaway, E. M., Denk, W., Dulac, C., Fairhall, A. L., Fiete, I., Harris, K. M., Helmstaedter, M., Jain, V., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.010 · Cited by 172 · see citing works
Self-citation(1987) · Europe PMC (PubMed Central) · Cited by 168 · see citing works
Huang, L., Knoblich, U., Ledochowitsch, P., Lecoq, J. A., Reid, R. C., de Vries, S. E. J., Buice, M. A., Murphy, G. J., Waters, J., Christof Koch, A., et al. (2021) · eLife · doi:10.7554/elife.51675 · Cited by 167 · see citing works
Self-citationLinear transformation of thalamocortical input by intracortical excitation
Li, Y.-T., Ibrahim, L. A., Liu, B., Zhang, L. I., & Tao, H. W. (2013) · Nature Neuroscience · doi:10.1038/nn.3494 · Cited by 165 · see citing works
Self-citationStructured dendritic inhibition supports branch-selective integration in CA1 pyramidal cells
Bloss, E. B., Cembrowski, M. S., Karsh, B., Colonell, J., Fetter, R. D., & Spruston, N. (2016) · Neuron · doi:10.1016/j.neuron.2016.01.029 · Cited by 164 · see citing works
Spontaneous and evoked synaptic rewiring in the neonatal neocortex
Bé, J.-V. L., & Markram, H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604691103 · Cited by 159 · see citing works
Is cortical connectivity optimized for storing information?
Brunel, N. (2016) · Nature Neuroscience · doi:10.1038/nn.4286 · Cited by 154 · see citing works
Oligodendrocyte precursor cells ingest axons in the mouse neocortex
Buchanan, J., Elabbady, L., Collman, F., Jorstad, N. L., Bakken, T. E., Ott, C. M., Glatzer, J. C., Bleckert, A., Bodor, Á. L., Brittain, D., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2202580119 · Cited by 154 · see citing works
Self-citationYin, W., Brittain, D., Borseth, J., Scott, M. E., Williams, D., Perkins, J., Own, C. S., Murfitt, M. F., Torres, R., Kapner, D., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18659-3 · Cited by 152 · see citing works
Self-citationSmith, H., Bourne, J. N., Cao, G., Chirillo, M. A., Ostroff, L. E., Watson, D. J., & Harris, K. M. (2016) · eLife · doi:10.7554/elife.15275 · Cited by 146 · see citing works
Ultrastructurally smooth thick partitioning and volume stitching for large-scale connectomics
Hayworth, K. J., Xu, C. S., Lu, Z., Knott, G. W., Fetter, R. D., Tapia, J. C., Lichtman, J. W., & Hess, H. F. (2015) · Nature Methods · doi:10.1038/nmeth.3292 · Cited by 144 · see citing works
Density and morphology of dendritic spines in mouse neocortex.
Ballesteros-Yáñez, I., Benavides-Piccione, R., Elston, G. N., Yuste, R., & DeFelipe, J. (2006) · Neuroscience · doi:10.1016/j.neuroscience.2005.11.038 · Cited by 143 · see citing works
Dendritic morphology of pyramidal neurones of the visual cortex of the rat: I. Branching patterns
Larkman, A. U. (1991) · The Journal of Comparative Neurology · doi:10.1002/cne.903060207 · Cited by 142 · see citing works
The role of neuronal identity in synaptic competition
Kasthuri, N., & Lichtman, J. W. (2003) · Nature · doi:10.1038/nature01836 · Cited by 141 · see citing works
Historical review: Mitochondria and calcium: ups and downs of an unusual relationship
Carafoli, E. (2003) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(03)00053-7 · Cited by 140 · see citing works
Area-Specific Features of Pyramidal Neurons—a Comparative Study in Mouse and Rhesus Monkey
Gilman, J. P., Medalla, M., & Luebke, J. I. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw062 · Cited by 140 · see citing works
Machines that learn to segment images: a crucial technology for connectomics
Jain, V., Seung, H. S., & Turaga, S. C. (2010) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2010.07.004 · Cited by 140 · see citing works
Self-citationEmerging roles of mitochondria in synaptic transmission and neurodegeneration
Lee, A., Hirabayashi, Y., Kwon, S., Lewis, T. L., & Polleux, F. (2018) · Current Opinion in Physiology · doi:10.1016/j.cophys.2018.03.009 · Cited by 138 · see citing works
Self-citationAutomated synaptic connectivity inference for volume electron microscopy
Dorkenwald, S., Schubert, P. J., Killinger, M. F., Urban, G., Mikula, S., Svara, F., & Kornfeld, J. (2017) · Nature Methods · doi:10.1038/nmeth.4206 · Cited by 132 · see citing works
Self-citationA fourth type of neuroglial cell in the adult central nervous system
Peters, A. (2004) · Journal of Neurocytology · doi:10.1023/b:neur.0000044195.64009.27 · Cited by 131 · see citing works
Greene, M., Kim, J. S., & Seung, H. S. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.02.001 · Cited by 131 · see citing works
Self-citationBinary and analog variation of synapses between cortical pyramidal neurons
Dorkenwald, S., Turner, N. L., Macrina, T., Lee, K., Lu, R., Wu, J., Bodor, A. L., Bleckert, A. A., Brittain, D., Kemnitz, N., et al. (2019) · doi:10.1101/2019.12.29.890319 · Cited by 130 · see citing works
Self-citationAxonal synapse sorting in medial entorhinal cortex
Schmidt, H., Gour, A., Straehle, J., Boergens, K. M., Brecht, M., & Helmstaedter, M. N. (2017) · Nature · doi:10.1038/nature24005 · Cited by 129 · see citing works
Long-Term Potentiation Requires a Rapid Burst of Dendritic Mitochondrial Fission during Induction
Divakaruni, S. S., Dyke, A. M. V., Chandra, R., LeGates, T. A., Contreras, M., Dharmasri, P. A., Higgs, H. N., Lobo, M. K., Thompson, S. M., & Blanpied, T. A. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.025 · Cited by 126 · see citing works
Dendritic Branch Typing and Spine Expression Patterns in Cortical Nonpyramidal Cells
Kawaguchi, Y., Karube, F., & Kubota, Y. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhj015 · Cited by 125 · see citing works
Single excitatory axons form clustered synapses onto CA1 pyramidal cell dendrites
Bloss, E. B., Cembrowski, M. S., Karsh, B., Colonell, J. I., Fetter, R. D., & Spruston, N. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0084-6 · Cited by 125 · see citing works
Binary and analog variation of synapses between cortical pyramidal neurons
Dorkenwald, S., Turner, N. L., Macrina, T., Lee, K., Lu, R., Wu, J., Bodor, Á. L., Bleckert, A., Brittain, D., Kemnitz, N., et al. (2022) · eLife · doi:10.7554/elife.76120 · Cited by 123 · see citing works
Self-citationTEASAR: tree-structure extraction algorithm for accurate and robust skeletons
Sato, M., Bitter, I., Bender, M. A., Kaufman, A. E., & Nakajima, M. (2002) · Pacific Conference on Computer Graphics and Applications · doi:10.1109/pccga.2000.883951 · Cited by 123 · see citing works
Progress and remaining challenges in high-throughput volume electron microscopy
Kornfeld, J. M. R., & Denk, W. T. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.04.030 · Cited by 117 · see citing works
Differential Structure of Hippocampal CA1 Pyramidal Neurons in the Human and Mouse
Benavides‐Piccione, R., Regalado-Reyes, M., Fernaud-Espinosa, I., Kastanauskaite, A., Tapia‐González, S., León‐Espinosa, G., Rojo, C., Insausti, R., Segev, I., & DeFelipe, J. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz122 · Cited by 111 · see citing works
Structure and function of axo-axonic inhibition
Schneider-Mizell, C. M., Bodor, A. L., Collman, F., Brittain, D., Bleckert, A. A., Dorkenwald, S., Turner, N. L., Macrina, T., Lee, K., Lu, R., et al. (2021) · eLife · doi:10.7554/elife.73783 · Cited by 111 · see citing works
Self-citationOPA1 loss of function affects in vitro neuronal maturation
Bertholet, A. M., Millet, A. M. C., Guillermin, O., Daloyau, M., Davezac, N., Miquel, M., & Belenguer, P. (2013) · Brain · doi:10.1093/brain/awt060 · Cited by 110 · see citing works
Powerhouse of the mind: mitochondrial plasticity at the synapse
Rossi, M., & Pekkurnaz, G. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.02.001 · Cited by 110 · see citing works
Mitochondrial Ultrastructure Is Coupled to Synaptic Performance at Axonal Release Sites
Cserép, C., Pósfai, B., Schwarcz, A. D., & Dénes, Á. (2018) · eNeuro · doi:10.1523/eneuro.0390-17.2018 · Cited by 106 · see citing works
Cell-type specific innervation of cortical pyramidal cells at their apical dendrites
Karimi, A., Odenthal, J., Drawitsch, F., Boergens, K. M., & Helmstaedter, M. (2020) · eLife · doi:10.7554/elife.46876 · Cited by 103 · see citing works
Search for computational modules in the C. elegansbrain
Reigl, M., Alon, U. S., & Chklovskii, D. B. (2004) · BMC Biology · doi:10.1186/1741-7007-2-25 · Cited by 102 · see citing works
Calì, C., Agus, M., Kare, K., Boges, D. J., Lehväslaiho, H., Hadwiger, M., & Magistretti, P. J. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101696 · Cited by 99 · see citing works
Postnatal connectomic development of inhibition in mouse barrel cortex
Gour, A., Boergens, K. M., Heike, N., Hua, Y., Laserstein, P., Song, K., & Helmstaedter, M. N. (2020) · Science · doi:10.1126/science.abb4534 · Cited by 97 · see citing works
Generating uniformly distributed random networks
Artzy‐Randrup, Y. A., & Stone, L. (2005) · Physical Review E · doi:10.1103/physreve.72.056708 · Cited by 96 · see citing works
Spano, G. M., Banningh, S. W., Marshall, W., de Vivo, L., Bellesi, M., Loschky, S. S., Tononi, G., & Cirelli, C. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0380-19.2019 · Cited by 96 · see citing works
Automatic Mitochondria Segmentation for EM Data Using a 3D Supervised Convolutional Network
Xiao, C., Chen, X., Li, W., Li, L., Wang, L., Xie, Q., & Han, H. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2018.00092 · Cited by 89 · see citing works
Hioki, H., Okamoto, S., Konno, M., Kameda, H., Sohn, J., Kuramoto, E., Fujiyama, F., & Kaneko, T. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2255-12.2013 · Cited by 83 · see citing works
Whitening of odor representations by the wiring diagram of the olfactory bulb
Wanner, A. A., & Friedrich, R. W. (2020) · Nature Neuroscience · doi:10.1038/s41593-019-0576-z · Cited by 79 · see citing works
Elson, G. N., & DeFelipe, J. (2002) · Progress in brain research · doi:10.1016/s0079-6123(02)36012-6 · Cited by 78 · see citing works
A workflow for the automatic segmentation of organelles in electron microscopy image stacks
Perez, A. J., Seyedhosseini, M., Deerinck, T. J., Bushong, E. A., Panda, S., Taşdizen, T., & Ellisman, M. H. (2014) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2014.00126 · Cited by 76 · see citing works
Electron Microscopic Reconstruction of Functionally Identified Cells in a Neural Integrator
Vishwanathan, A., Daie, K., Ramirez, A. D., Lichtman, J. W., Aksay, E. R. F., & Seung, H. S. (2017) · Current Biology · doi:10.1016/j.cub.2017.06.028 · Cited by 74 · see citing works
Self-citationActive Dendrites Reduce Location-Dependent Variability of Synaptic Input Trains
Cook, E. P., & Johnston, D. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.78.4.2116 · Cited by 72 · see citing works
The Fine Structure of the Nervous System: The Neurons and Supporting Cells
Doyle, D. (1978) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.41.2.191-c · Cited by 71 · see citing works
Fully automatic stitching and distortion correction of transmission electron microscope images
Kaynig, V., Fischer, B., Müller, E. A., & Buhmann, J. M. (2010) · Journal of Structural Biology · doi:10.1016/j.jsb.2010.04.012 · Cited by 70 · see citing works
FlyWire: Online community for whole-brain connectomicsPreprint
Dorkenwald, S., McKellar, C. E., Macrina, T., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.30.274225 · Cited by 70 · see citing works
Self-citationHoggarth, A., McLaughlin, A. J., Ronellenfitch, K., Trenholm, S., Vasandani, R., Sethuramanujam, S., Schwab, D. J., Briggman, K. L., & Awatramani, G. B. (2015) · Neuron · doi:10.1016/j.neuron.2015.02.035 · Cited by 68 · see citing works
Asymptotic enumeration of sparse 0–1 matrices with irregular row and column sums
Greenhill, C., McKay, B. D., & Wang, X. (2005) · Journal of Combinatorial Theory Series A · doi:10.1016/j.jcta.2005.03.005 · Cited by 67 · see citing works
Calì, C., Wawrzyniak, M., Becker, C., Maco, B., Cantoni, M., Jorstad, A., Nigro, B., Grillo, F. W., Paola, V. D., Fua, P., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198131 · Cited by 63 · see citing works
Santuy, A., Rodríguez, J., DeFelipe, J., & Merchán-Pérez, Á. (2018) · eNeuro · doi:10.1523/eneuro.0377-17.2017 · Cited by 61 · see citing works
Neuronal activity is not required for the initial formation and maturation of visual selectivity
Hagihara, K. M., Murakami, T., Yoshida, T., Tagawa, Y., & Ohki, K. (2015) · Nature Neuroscience · doi:10.1038/nn.4155 · Cited by 58 · see citing works
Petascale neural circuit reconstruction: automated methods
Macrina, T., Lee, K., Lu, R., Turner, N. L., Wu, J., Popovych, S., Silversmith, W., Kemnitz, N., Bae, J. A., Castro, M. A., et al. (2021) · doi:10.1101/2021.08.04.455162 · Cited by 55 · see citing works
Self-citationUnbiased degree-preserving randomization of directed binary networks
Roberts, E. S., & Coolen, A. C. C. (2012) · Physical Review E · doi:10.1103/physreve.85.046103 · Cited by 54 · see citing works
Image Segmentation by Size-Dependent Single Linkage Clustering of a Watershed Basin GraphPreprint
Zlateski, A., & Seung, H. (2015) · arXiv.org · doi:10.48550/arxiv.1505.00249 · Cited by 53 · see citing works
Self-citationDense Neuron Clustering Explains Connectivity Statistics in Cortical Microcircuits
Klinshov, V. V., Teramae, J.-N., Nekorkin, V. I., & Fukai, T. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094292 · Cited by 52 · see citing works
Lee, K., Turner, N., Macrina, T., Wu, J., Lu, R., & Seung, H. S. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.04.001 · Cited by 52 · see citing works
Self-citationKameda, H., Hioki, H., Tanaka, Y. H., Tanaka, T., Sohn, J., Sonomura, T., Furuta, T., Fujiyama, F., & Kaneko, T. (2012) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2012.08027.x · Cited by 51 · see citing works
Local Connectivity and Synaptic Dynamics in Mouse and Human NeocortexPreprint
Campagnola, L., Seeman, S. C., Chartrand, T., Kim, L., Hoggarth, A., Gamlin, C. R., Ito, S., Trinh, J., Davoudian, P. A., Radaelli, C., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.31.437553 · Cited by 51 · see citing works
Wilson, A. M., Schalek, R. L., Suissa‐Peleg, A., Jones, T. R., Knowles-Barley, S., Pfister, H., & Lichtman, J. W. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.10.081 · Cited by 47 · see citing works
Self-citationDeep and Wide Multiscale Recursive Networks for Robust Image LabelingPreprint
Huang, G. B., & Jain, V. (2013) · International Conference on Learning Representations · doi:10.48550/arxiv.1310.0354 · Cited by 45 · see citing works
Synaptic Partner Assignment Using Attentional Voxel Association Networks
Turner, N. L., Lee, K., Lu, R., Wu, J., Ih, D., & Seung, H. S. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098489 · Cited by 44 · see citing works
Self-citationQuantitative 3D Mapping of the Human Skeletal Muscle Mitochondrial Network
Vincent, A. E., White, K., Davey, T., Philips, J., Ogden, R. T., Lawless, C., Warren, C., Hall, M. G., Ng, Y. S., Falkous, G., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.03.051 · Cited by 42 · see citing works
The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles
Azulay, A., Itskovits, E., & Zaslaver, A. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005021 · Cited by 40 · see citing works
Uniform Sampling of Digraphs with a Fixed Degree Sequence
Berger, A., & Müller‐Hannemann, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16926-7_21 · Cited by 35 · see citing works
Chunkflow: hybrid cloud processing of large 3D images by convolutional nets
Wu, J., Silversmith, W., Lee, K., & Seung, H. S. (2021) · Nature Methods · doi:10.1038/s41592-021-01088-5 · Cited by 31 · see citing works
Self-citationNeuron Geometry Underlies Universal Network Features in Cortical MicrocircuitsPreprint
Gal, E., Perin, R., Markram, H., London, M., & Segev, I. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/656058 · Cited by 30 · see citing works
Yuan, Z., Ma, X., Yi, J., Luo, Z., & Peng, J. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105925 · Cited by 29 · see citing works
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Buchanan, J., Elabbady, L., Collman, F., Jorstad, N. L., Bakken, T. E., Ott, C. M., Glatzer, J. C., Bleckert, A., Bodor, Á. L., Brittan, D., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.29.446047 · Cited by 28 · see citing works
Self-citationZhang, D., Zhang, C., & Stepanyants, A. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.3218-18.2019 · Cited by 27 · see citing works
Neila, P. M., Baumela, L., González‐Soriano, J., Rodríguez, J., DeFelipe, J., & Merchán-Pérez, Á. (2016) · Neuroinformatics · doi:10.1007/s12021-015-9288-z · Cited by 26 · see citing works
Optimal Current Transfer in Dendrites
Bird, A. D., & Cuntz, H. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004897 · Cited by 25 · see citing works
On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes
Vegué, M., Perin, R., & Roxin, A. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0984-17.2017 · Cited by 25 · see citing works
Zhu, Y., Uytiepo, M., Bushong, E. A., Haberl, M. G., Beutter, E., Scheiwe, F., Zhang, W., Chang, L., Luu, D., Chui, B., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2021.108953 · Cited by 22 · see citing works
Yuan, Z., Yi, J., Luo, Z., Jia, Z., & Peng, J. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098328 · Cited by 19 · see citing works
EASE: EM-Assisted Source Extraction from calcium imaging dataPreprint
Zhou, P., Reimer, J., Zhou, D. X., Pasarkar, A., Kinsella, I., Froudarakis, E., Yatsenko, D., Fahey, P. G., Bodor, Á. L., Buchanan, J., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.25.007468 · Cited by 18 · see citing works
Self-citationDeep and Wide Multiscale Recursive Networks for Robust Image LabelingPreprint
Huang, G. B., & Jain, V. (2014) · Cited by 14 · see citing works
Jiang, X., Shen, S., Sinz, F., Reimer, J., Cadwell, C. R., Berens, P., Ecker, A. S., Patel, S., Denfield, G. H., Froudarakis, E., et al. (2016) · Science · doi:10.1126/science.aaf6102 · Cited by 13 · see citing works
Self-citationSwitching edges to randomize networks: what goes wrong and how to fix it
Carstens, C. J., & Horadam, K. J. (2016) · Journal of Complex Networks · doi:10.1093/comnet/cnw027 · Cited by 12 · see citing works
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs
Popovych, S., Buniatyan, D., Zlateski, A., Li, K., & Seung, H. S. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-17795-9_27 · Cited by 6 · see citing works
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Research works printed but not linked: 3
- Campagnola L. (2021) ‘ Connectivity and Synaptic Physiology in the Mouse and Human Neocortex’, bioRxiv. Available at: 10.1101/2021.03.31.437553v1.abstract. · DOI
- Newman M. (2018) Networks. Oxford University Press.
- Stuart G, Spruston N. and Häusser M. (2016) Dendrites. Oxford University Press.
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The MICrONS Consortium, Bae, J. A., Baptiste, M., Bishop, C. A., Bodor, A. L., Brittain, D., Buchanan, J., Bumbarger, D. J., Castro, M. A., Celii, B., et al. (2021) · doi:10.1101/2021.07.28.454025 · Cited by 214 · see citing works
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Bae, J. A., Baptiste, M., Baptiste, M. R., Bishop, C. A., Bodor, Á. L., Brittain, D., Brooks, V., Buchanan, J., Bumbarger, D. J., Castro, M. A., et al. (2025) · Nature · doi:10.1038/s41586-025-08790-w · Cited by 197 · see citing works
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Dorkenwald, S., Matsliah, A., Sterling, A. R., Schlegel, P., Yu, S.-C., McKellar, C. E., Lin, A., Costa, M., Eichler, K., Yin, Y., et al. (2023) · doi:10.1101/2023.06.27.546656 · Cited by 149 · see citing works
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Tzilivaki, A., Tukker, J. J., Maier, N., Poirazi, P., Sammons, R. P., & Schmitz, D. (2023) · Neuron · doi:10.1016/j.neuron.2023.06.016 · Cited by 145 · see citing works
Network statistics of the whole-brain connectome of Drosophila
Lin, A., Yang, R., Dorkenwald, S., Matsliah, A., Sterling, A. R., Schlegel, P., Yu, S.-C., McKellar, C. E., Costa, M., Eichler, K., et al. (2024) · Nature · doi:10.1038/s41586-024-07968-y · Cited by 147 · see citing works
“The 236 overrepresentation of reciprocal connections in brains is well 237 established, and our results are consistent with previous obser- 238 vations both in Drosophila (16, 17, 19) and in other species 239 (5, 7, 14, 27, 28, 43).”
InfluentialSelf-citationBinary and analog variation of synapses between cortical pyramidal neurons
Dorkenwald, S., Turner, N. L., Macrina, T., Lee, K., Lu, R., Wu, J., Bodor, Á. L., Bleckert, A., Brittain, D., Kemnitz, N., et al. (2022) · eLife · doi:10.7554/elife.76120 · Cited by 123 · see citing works
Self-citationConrad, R., & Narayan, K. (2023) · Cell Systems · doi:10.1016/j.cels.2022.12.006 · Cited by 116 · see citing works
Lee, A., Kondapalli, C., Virga, D., Lewis, T. L., Koo, S.-Y.-O., Ashok, A., Mairet‐Coello, G., Herzig, S., Foretz, M., Viollet, B., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32130-5 · Cited by 103 · see citing works
Self-citationAxonal energy metabolism, and the effects in aging and neurodegenerative diseases
Yang, S., Park, J. H., & Lu, H.-C. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00634-3 · Cited by 94 · see citing works
Synaptic wiring motifs in posterior parietal cortex support decision-making
Kuan, A. T., Bondanelli, G., Driscoll, L. N., Han, J., Kim, M., Hildebrand, D. G. C., Graham, B. J., Wilson, D. E., Thomas, L. A., Panzeri, S., et al. (2024) · Nature · doi:10.1038/s41586-024-07088-7 · Cited by 78 · see citing works
CAVE: Connectome Annotation Versioning Engine
Dorkenwald, S., Schneider-Mizell, C. M., Brittain, D., Halageri, A., Jordan, C. A., Kemnitz, N., Castro, M. A., Silversmith, W., Maitin-Shepard, J., Troidl, J., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02426-z · Cited by 80 · see citing works
Self-citationStructural neural plasticity evoked by rapid-acting antidepressant interventions
Liao, C., Dua, A. N., Wojtasiewicz, C., Liston, C. M., & Kwan, A. C. (2024) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00876-0 · Cited by 77 · see citing works
Atlas-based data integration for mapping the connections and architecture of the brain
Leergaard, T. B., & Bjaalie, J. G. (2022) · Science · doi:10.1126/science.abq2594 · Cited by 68 · see citing works
Mitochondrial plasticity and synaptic plasticity crosstalk; in health and Alzheimer's disease
Sayehmiri, F., Motamedi, F., Batool, Z., Naderi, N., Shaerzadeh, F., Zoghi, A., Rezaei, O., Khodagholi, F., & Pourbadie, H. G. (2024) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14897 · Cited by 66 · see citing works
Ott, C. M., Torres, R., Kuan, T. S., Kuan, A. T., Buchanan, J., Elabbady, L., Seshamani, S., Bodor, Á. L., Collman, F., Bock, D. D., et al. (2024) · Current Biology · doi:10.1016/j.cub.2024.04.043 · Cited by 56 · see citing works
Self-citationVirga, D. M., Hamilton, S., Osei, B., Morgan, A., Kneis, P., Zamponi, E., Park, N. J., Hewitt, V. L., Zhang, D., Gonzalez, K. C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46463-w · Cited by 59 · see citing works
Self-citationSynaptic architecture of a memory engram in the mouse hippocampus
Uytiepo, M., Zhu, Y., Bushong, E. A., Chou, K., Polli, F. S., Zhao, E., Keun-young Kim, A., Luu, D., Chang, L., Yang, D. U., et al. (2025) · Science · doi:10.1126/science.ado8316 · Cited by 54 · see citing works
Stogsdill, J. A., Harwell, C. C., & Goldman, S. A. (2023) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15004 · Cited by 47 · see citing works
Dense 4D nanoscale reconstruction of living brain tissue
Velicky, P., Miguel, E., Michalska, J. M., Lyudchik, J., Wei, D., Lin, Z., Watson, J. F., Troidl, J., Beyer, J., Ben‐Simon, Y., et al. (2023) · Nature Methods · doi:10.1038/s41592-023-01936-6 · Cited by 43 · see citing works
Beau, M., Herzfeld, D. J., Naveros, F., Hemelt, M. E., D’Agostino, F., Oostland, M., Sánchez‐López, Á., Chung, Y. Y., Maibach, M., Kyranakis, S., et al. (2025) · Cell · doi:10.1016/j.cell.2025.01.041 · Cited by 51 · see citing works
Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit
Peng, Y., Bjelde, A., Aceituno, P. V., Mittermaier, F. X., Planert, H., Grosser, S., Onken, J., Faust, K., Kalbhenn, T., Simon, M., et al. (2024) · Science · doi:10.1126/science.adg8828 · Cited by 45 · see citing works
Petascale pipeline for precise alignment of images from serial section electron microscopy
Popovych, S., Macrina, T., Kemnitz, N., Castro, M., Nehoran, B., Jia, Z., Bae, J. A., Mitchell, E., Mu, S., Trautman, E. T., et al. (2024) · Nature Communications · doi:10.1038/s41467-023-44354-0 · Cited by 39 · see citing works
Self-citationFormation and computational implications of assemblies in neural circuits
Miehl, C., Onasch, S., Festa, D., & Gjorgjieva, J. (2022) · The Journal of Physiology · doi:10.1113/jp282750 · Cited by 38 · see citing works
CAVE: Connectome Annotation Versioning Engine
Dorkenwald, S., Schneider-Mizell, C. M., Brittain, D., Halageri, A., Jordan, C., Kemnitz, N., Castro, M. A., Silversmith, W., Maitin-Shephard, J., Troidl, J., et al. (2023) · doi:10.1101/2023.07.26.550598 · Cited by 79 · see citing works
Self-citationMulti-layered maps of neuropil with segmentation-guided contrastive learning
Dorkenwald, S., Li, P. H., Januszewski, M., Berger, D. R., Maitin-Shepard, J., Bodor, Á. L., Collman, F., Schneider-Mizell, C. M., da Costa, N. M., Lichtman, J. W., et al. (2023) · Nature Methods · doi:10.1038/s41592-023-02059-8 · Cited by 35 · see citing works
Self-citationProbing neural circuit mechanisms in Alzheimer’s disease using novel technologies
Grieco, S. F., Holmes, T. C., & Xu, X. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02018-x · Cited by 34 · see citing works
Falahati, H., Wu, Y., Feuerer, V., Simon, H., & Camilli, P. V. D. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2203750119 · Cited by 32 · see citing works
Isochronic development of cortical synapses in primates and mice
Wildenberg, G., Li, H., Sampathkumar, V., Sorokina, A., & Kasthuri, N. (2023) · Nature Communications · doi:10.1038/s41467-023-43088-3 · Cited by 31 · see citing works
Parvalbumin basket cell myelination accumulates axonal mitochondria to internodes
Kole, K., Voesenek, B. J. B., Brinia, M. E., Petersen, N., & Kole, M. H. P. (2022) · Nature Communications · doi:10.1038/s41467-022-35350-x · Cited by 31 · see citing works
Zinchenko, V., Hugger, J., Uhlmann, V., Arendt, D., & Kreshuk, A. (2023) · eLife · doi:10.7554/elife.80918 · Cited by 30 · see citing works
Karlupia, N., Schalek, R. L., Wu, Y., Meirovitch, Y., Wei, D., Charney, A. W., Kopell, B. H., & Lichtman, J. W. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.01.025 · Cited by 30 · see citing works
Tackling the subsampling problem to infer collective properties from limited data
Levina, A., Priesemann, V., & Zierenberg, J. (2022) · Nature Reviews Physics · doi:10.1038/s42254-022-00532-5 · Cited by 30 · see citing works
Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level
Jiang, T., Gong, H., & Yuan, J. (2023) · Neuroscience Bulletin · doi:10.1007/s12264-023-01112-y · Cited by 26 · see citing works
Durá-Bernal, S., Herrera, B., Lupaşcu, C. A., Marsh, B. M., Gandolfi, D., Marasco, A., Neymotin, S. A., Romani, A., Solinas, S. M. G., Bazhenov, M., et al. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.1236-24.2024 · Cited by 26 · see citing works
Perisomatic 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-citationKim, S. Y., Strucinska, K., Osei, B., Han, K., Kwon, S., & Lewis, T. L. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.1042616 · Cited by 21 · see citing works
Connectivity of single neurons classifies cell subtypes in mouse brains
Liu, L., Yun, Z., Manubens-Gil, L., Chen, H., Xiong, F., Dong, H., Zeng, H., Hawrylycz, M., Ascoli, G. A., & Peng, H. (2025) · Nature Methods · doi:10.1038/s41592-025-02621-6 · Cited by 21 · see citing works
Silversmith, W., Zlateski, A., Bae, J. A., Tartavull, I., Kemnitz, N., Wu, J., & Seung, H. S. (2022) · Frontiers in Neural Circuits · doi:10.3389/fncir.2022.977700 · Cited by 21 · 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-citationParisi, M. J., Aimino, M. A., & Mosca, T. J. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100477 · Cited by 20 · see citing works
Postsynaptic mitochondria are positioned to support functional diversity of dendritic spines
Thomas, C. I., Ryan, M. A., Kamasawa, N., & Scholl, B. (2023) · eLife · doi:10.7554/elife.89682.3 · Cited by 19 · see citing works
Enabling electric field model of microscopically realistic brain
Qi, Z., Noetscher, G. M., Miles, A., Weise, K., Knösche, T. R., Cadman, C. R., Potashinsky, A. R., Liu, K., Wartman, W. A., Ponasso, G. N., et al. (2024) · Brain stimulation · doi:10.1016/j.brs.2024.12.1192 · Cited by 19 · see citing works
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. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.20.499976 · Cited by 19 · see citing works
Self-citationPavarino, E. C., Yang, E., Dhanyasi, N., Wang, M. D., Bidel, F., Lu, X., Yang, F., Park, C. F., Renuka, M. B., Drescher, B. D., et al. (2023) · Frontiers in Neural Circuits · doi:10.3389/fncir.2023.952921 · Cited by 18 · see citing works
Synaptic and dendritic architecture of different types of hippocampal somatostatin interneurons
Takács, V. T., Bardóczi, Z., Orosz, Á., Major, Á., Tar, L., Berki, P., Papp, P., Mayer, M. I., Sebők, H., Zsolt, L., et al. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002539 · Cited by 18 · see citing works
Ng, B., Tasaki, S., Greathouse, K. M., Walker, C. K., Zhang, A., Covitz, S. C., Cieslak, M., Weber, A. J., Adamson, A. B., Andrade, J. P., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01788-z · Cited by 20 · see citing works
Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy
Cano-Astorga, N., Plaza-Alonso, S., Turegano-Lopez, M., Rodrigo-Rodríguez, J., Merchan-Perez, A., & DeFelipe, J. (2024) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2024.1348032 · Cited by 17 · see citing works
The 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-citationKar, D., Kim, Y. J., PACKER, O. S., Clark, M. E., Cao, D., Owsley, C. J., Dacey, D. M., & Curcio, C. A. (2023) · Biomedical Optics Express · doi:10.1364/boe.501228 · Cited by 17 · see citing works
A circuit motif for color in the human foveal retina
Kim, Y. J., PACKER, O. S., & Dacey, D. M. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2405138121 · Cited by 17 · see citing works
Visual information is broadcast among cortical areas in discrete channelsPreprint
Yu, Y., Stirman, J. N., Dorsett, C. R., & Smith, S. L. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/469114 · Cited by 21 · see citing works
Infrequent strong connections constrain connectomic predictions of neuronal function
Currier, T. A., & Clandinin, T. R. (2025) · Cell · doi:10.1016/j.cell.2025.05.007 · Cited by 16 · see citing works
Synaptic-resolution connectomics: towards large brains and connectomic screening
Helmstaedter, M. N. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00998-z · Cited by 16 · see citing works
Alipour-Khezri, E., Moqadami, A., Vahed, S. Z., & Barzegari, A. (2025) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2025.118790 · Cited by 15 · see citing works
Spirou, G. A., Kersting, M., Carr, S., Razzaq, B., Pinto, C. Y. A., Dawson, M., Ellisman, M. H., & Manis, P. B. (2023) · eLife · doi:10.7554/elife.83393 · Cited by 15 · see citing works
Dendrite architecture determines mitochondrial distribution patterns in vivo
Donovan, E. J., Agrawal, A., Liberman, N., Kalai, J. I., Adler, A. J., Lamper, A. M., Wang, H. Q., Chua, N. J., Koslover, E. F., & Barnhart, E. L. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114190 · Cited by 15 · see citing works
How to incorporate biological insights into network models and why it matters
Timón, L. B., Ekelmans, P., Kraynyukova, N., Rose, T., Busse, L., & Tchumatchenko, T. (2022) · The Journal of Physiology · doi:10.1113/jp282755 · Cited by 14 · see citing works
Hirabayashi, Y., Lewis, T. L., Du, Y., Zamponi, E., Kneis, P., Jones, J. U., Decker, A., Coceano, G., Alvelid, J., Kikuchi, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.12.579972 · Cited by 15 · see citing works
Self-citationPostsynaptic mitochondria are positioned to support functional diversity of dendritic spines
Thomas, C. I., Ryan, M. A., Kamasawa, N., & Scholl, B. (2023) · eLife · doi:10.7554/elife.89682 · Cited by 26 · 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
ViMO - Visual Analysis of Neuronal Connectivity Motifs
Troidl, J., Warchol, S., Choi, J., Matelsky, J., Dhanyasi, N., Wang, X., Wester, B. A., Wei, D., Lichtman, J. W., Pfister, H., et al. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3327388 · Cited by 14 · see citing works
Distinct dendritic integration strategies control dynamics of inhibition in the neocortex
Morabito, A., Zerlaut, Y., Dhanasobhon, D., Berthaux, E., Pinho, C. M., Tzilivaki, A., Moneron, G., Cathala, L., Poirazi, P., Bacci, A., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.05.029 · Cited by 19 · see citing works
Simulations of cortical networks using spatially extended conductance‐based neuronal models
Haufler, D., Ito, S., Christof Koch, A., & Arkhipov, A. S. (2022) · The Journal of Physiology · doi:10.1113/jp284030 · Cited by 12 · see citing works
Hierarchical Modular Structure of the Drosophila Connectome
Kunin, A. B., Guo, J., Bassler, K. E., Pitkow, X., & Josić́, K. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0134-23.2023 · Cited by 13 · see citing works
New Synapse Detection in the Whole-Brain Connectome of DrosophilaPreprint
Yu, S.-C., Bae, J. A., Matsliah, A., Dorkenwald, S., Gager, J., Hebditch, J., Silverman, B., Willie, K. P., Willie, R., Burke, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.11.664377 · Cited by 13 · see citing works
Self-citationNikhil, K. L., Singhal, B., Granados‐Fuentes, D., Li, J.-S., Kiss, I. Z., & Herzog, E. D. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2520674122 · Cited by 12 · see citing works
Heuvel, F. O., Li, Z., Riedel, D., Halbgebauer, S., Oeckl, P., Mayer, B., Gotzman, N., Shultz, S. R., Semple, B. D., Tumani, H., et al. (2024) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2024-333413 · Cited by 13 · see citing works
Unveiling universal aspects of the cellular anatomy of the brain
Ansell, H. S., & Kovács, I. A. (2024) · Communications Physics · doi:10.1038/s42005-024-01665-y · Cited by 12 · see citing works
Spatial and morphological organization of mitochondria in neurons across a connectome
Sager, G., Pfeiffer, P., Wu, H., Pallasdies, F., Gowers, R. P., Ravikumar, S., Wu, E., Colón‐Ramos, D. A., Schreiber, S., & Clark, D. A. (2025) · Science · doi:10.1126/science.ads6674 · Cited by 18 · see citing works
Connectomic Analysis of Mitochondria in the Central Brain of DrosophilaPreprint
Longden, K. D., Rivlin, P. K., Januszewski, M., Neace, E. R., Scheffer, L. K., Ordish, C., Clements, J., Phillips, E., Smith, N. L., Takemura, S., et al. (2024) · eLife · doi:10.1101/2024.04.21.590464 · Cited by 14 · see citing works
Cyclic structure with cellular precision in a vertebrate sensorimotor neural circuit
Yang, R., Vishwanathan, A., Wu, J., Kemnitz, N., Ih, D., Turner, N., Lee, K., Tartavull, I., Silversmith, W. M., Jordan, C. S., et al. (2023) · Current Biology · doi:10.1016/j.cub.2023.05.010 · Cited by 11 · see citing works
Self-citationWeise, K., Makaroff, S. N., Numssen, O., Bikson, M., & Knösche, T. R. (2025) · Brain stimulation · doi:10.1016/j.brs.2025.02.007 · Cited by 11 · see citing works
Xiong, F., Liu, L., & Peng, H. (2025) · Nature Methods · doi:10.1038/s41592-025-02784-2 · Cited by 15 · see citing works
NeuVue: A scalable and customizable framework for electron microscopy proofreadingPreprint
Xenes, D., Kitchell, L. M., Rivlin, P. K., Martinez, H., Rose, V. A., Bishop, C., Brodsky, R., Celii, B., Joyce, J., Luna, D., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.18.500521 · Cited by 11 · see citing works
Self-citationMost Axonal Mitochondria in Cortical Pyramidal Neurons Lack Mitochondrial DNA and Consume ATPPreprint
Hirabayashi, Y., Lewis, T. L., Du, Y., Virga, D. M., Decker, A., Coceano, G., Alvelid, J., Suga, S., Paul, M. A., Hamilton, S., et al. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4870948 · Cited by 11 · see citing works
Self-citationLinking brain activity across scales with simultaneous opto- and electrophysiology
Hoffmann, A., & Helmchen, F. (2023) · Neurophotonics · doi:10.1117/1.nph.11.3.033403 · Cited by 9 · see citing works
A Scalable Staining Strategy for Whole-Brain ConnectomicsPreprint
Lu, X., Wu, Y., Schalek, R. L., Meirovitch, Y., Berger, D. R., & Lichtman, J. W. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.26.558265 · 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
Regulated exocytosis from astrocytes: a matter of vesicles?
Calì, C. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1393165 · Cited by 9 · see citing works
Human cerebral organoids: cellular composition and subcellular morphological features
Mateos-Martínez, P., Coronel, R., Sachse, M., González-Sastre, R., Maeso, L., Rodríguez, M. J., Terrón, M. C., López-Alonso, V., & Liste, I. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1406839 · Cited by 9 · see citing works
Ultrastructure of astrocytes using volume electron microscopy: A scoping review
Chiappini, V., Castillo, M. F. V., Biancardi, F., Cunto, F. D., Magistretti, P. J., Vercelli, A., Agus, M., & Calì, C. (2025) · The Journal of Physiology · doi:10.1113/jp287455 · Cited by 9 · see citing works
The structure and function of neural connectomes are shaped by a small number of design principlesPreprint
Haber, A., Wanner, A. A., Friedrich, R. W., & Schneidman, E. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.03.15.532611 · Cited by 9 · see citing works
Topology recapitulates morphogenesis of neuronal dendrites
Liao, M., Bird, A. D., Cuntz, H., & Howard, J. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113268 · Cited by 8 · see citing works
Aird-Rossiter, C., Zhang, H. G., Alexander, D. C., Jones, D. K., & Palombo, M. (2026) · Communications Biology · doi:10.1038/s42003-025-09353-5 · Cited by 8 · see citing works
STDIN: Spatio-temporal distilled interpolation for electron microscope images
Wang, Z., Sun, G., Li, G., Shen, L., Zhang, L., & Han, H. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.037 · Cited by 8 · see citing works
Conrad, R., & Narayan, K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.17.484806 · Cited by 8 · see citing works
Chen, D., Isakova, A., Wan, Z., Wagner, M. J., Wu, Y., & Zhao, B. S. (2026) · Nature Methods · doi:10.1038/s41592-026-03026-9 · Cited by 7 · see citing works
Heller, D. T., Kolson, D. R., Brandebura, A. N., Amick, E. M., Wan, J., Ramadan, J. H., Holcomb, P. S., Liu, S., Deerinck, T. J., Ellisman, M. H., et al. (2023) · The Journal of Comparative Neurology · doi:10.1002/cne.25552 · Cited by 7 · see citing works
Li, Z., Yang, X., Liu, J., Hong, B., Zhang, Y., Zhai, H., Shen, L., Chen, X., Liu, Z., & Han, H. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3409634 · Cited by 7 · see citing works
The Development of Synapses in Mouse and Macaque Primary Sensory CorticesPreprint
Wildenberg, G. A., Li, H., & Kasthuri, N. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.02.15.528564 · Cited by 12 · 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-citationA dendritic substrate for temporal diversity of cortical inhibitionPreprint
Morabito, A., Zerlaut, Y., Dhanasobhon, D., Berthaux, E., Tzilivaki, A., Moneron, G., Cathala, L., Poirazi, P., Bacci, A., DiGregorio, D. A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.09.602783 · Cited by 7 · see citing works
A Modular and Automated Serial Section Collection System for Ultramicrotomy and Subsequent Imaging
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Neuronal PAC1 deletion impairs structural plasticity
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Zhu, J. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112904 · Cited by 6 · see citing works
PyReconstruct: A fully open-source, collaborative successor to Reconstruct
Chirillo, M. A., Falco, J. N., Musslewhite, M. D., Lindsey, L. F., & Harris, K. M. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2505822122 · Cited by 5 · see citing works
A guide to CNN-based dense segmentation of neuronal EM images
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Efficient cell-wide mapping of mitochondria in electron microscopic volumes using webKnossos
Jiang, Y., Wang, H., Boergens, K. M., Rzepka, N., Wang, F., & Hua, Y. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.100989 · Cited by 5 · see citing works
- Authors
- Turner, N. L., Macrina, T., Bae, J. A., Yang, R., Wilson, A. M., Schneider-Mizell, C., Lee, K., Lu, R., Wu, J., Bodor, A. L., Bleckert, A. A., Brittain, D., Froudarakis, E., Dorkenwald, S., Collman, F., Kemnitz, N., Ih, D., Silversmith, W. M., Zung, J., Zlateski, A., Tartavull, I., Yu, S.-C., Popovych, S., Mu, S., Wong, W., Jordan, C. S., Castro, M., Buchanan, J., Bumbarger, D. J., Takeno, M., Torres, R., Mahalingam, G., Elabbady, L., Li, Y., Cobos, E., Zhou, P., Suckow, S., Becker, L., Paninski, L., Polleux, F., Reimer, J., Tolias, A. S., Reid, R. C., da Costa, N. M., & Seung, H. S.
- Affiliations
- Princeton University (US)
- Allen Institute for Brain Science (US)
- Baylor College of Medicine (US)
- Massachusetts Institute of Technology (US)
- Columbia University (US)
- Mortimer B. Zuckerman Mind Brain Behavior Institute (US)
- Corresponding author
- Seung, H. Sebastian
- ORCID
- Turner, Nicholas L.
- Macrina, Thomas
- Bae, J. Alexander
- Yang, Runzhe
- Wilson, Alyssa M.
- Schneider-Mizell, Casey
- Lee, Kisuk
- Lu, Ran
- Wu, Jingpeng
- Bleckert, Adam A.
- Brittain, Derrick
- Froudarakis, Emmanouil
- Dorkenwald, Sven
- Collman, Forrest
- Kemnitz, Nico
- Ih, Dodam
- Silversmith, William M.
- Zung, Jonathan
- Zlateski, Aleksandar
- Tartavull, Ignacio
- Yu, Szi-chieh
- Mu, Shang
- Jordan, Chris S.
- Castro, Manuel
- Buchanan, JoAnn
- Bumbarger, Daniel J.
- Takeno, Marc
- Torres, Russel
- Mahalingam, Gayathri
- Elabbady, Leila
- Li, Yang
- Zhou, Pengcheng
- Becker, Lynne
- Paninski, Liam
- Polleux, Franck
- Reimer, Jacob
- Tolias, Andreas S.
- Reid, R. Clay
- Seung, H. Sebastian
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2022-03
- Volume
- 185
- Issue
- 6
- Pages
- 1082-1100.e24
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC9337909
- OpenAlex
- W4213455879
- Cited by
- 206
- References
- 188
- Citations by year
- 2026: 37 · 2025: 50 · 2024: 49 · 2023: 44 · 2022: 24 · 2021: 1 · 2018: 1
- FWCI
- 18.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 381 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5u01mh114824-05)
- National Institute of Mental Health (U01 MH114824, RF1MH117815, RF1MH123400, T32MH065214)
- National Eye Institute (R01EY027036)
- National Institute of Neurological Disorders and Stroke (R01NS104926, U19NS104648, R01NS107483)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- neocortex, cortical reconstruction, pyramidal neurons, non-pyramidal neurons, astrocytes, microglia, oligodendrocytes, pericytes, cortical vasculature, mitochondria, synaptic organization, visual responses, cortical circuits, electron microscopy
- MeSH terms
- Animals, Microscopy, Electron, Synapses, Organelles, Pyramidal Cells, Neocortex, Mice
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