Publications from the MICrONS Datasets

Primary Publications

  • Dense calcium imaging combined with co-registered high-resolution electron microscopy reconstruction of the brain of the same mouse provide a functional connectomics map of tens of thousands of neurons of a region of the primary cortex and higher visual areas.

    DOI 10.1038/s41586-025-08790-w

    The MICrONS Consortium

  • Using volumetric electron microscopy, the authors map and analyze the structure of cortical inhibition with synaptic resolution across a column of visual cortex.

    DOI 10.1038/s41586-024-07780-8

    Casey M. Schneider-Mizell, Agnes L. Bodor … Nuno Maçarico da Costa

  • The MICrONS mouse visual cortex dataset shows that neurons with similar response properties preferentially connect, a pattern that emerges within and across brain areas and layers, and independently emerges in artificial neural networks where these ‘like-to-like’ connections prove important for task performance.

    DOI 10.1038/s41586-025-08840-3

    Zhuokun Ding, Paul G. Fahey …Andreas S. Tolias

  • A foundation model trained on neural activity of visual cortex from multiple mice accurately predicts responses to video stimuli and cell types, dendritic features and connectivity within the MICrONS functional connectomics dataset.

    DOI 10.1038/s41586-025-08829-y

    Eric Y. Wang, Paul G. Fahey …Andreas S. Tolias

  • An analysis demonstrates that quantitative measurements of perisomatic ultrastructure features of neurons can be used to categorize them into cell types.

    DOI 10.1038/s41586-024-07765-7

    Leila Elabbady, Sharmishtaa Seshamani, Forrest Collman

  • The authors use Patch-seq and electron microscopy datasets to relate synaptic connectivity to the transcriptomic cell type of different types of inhibitory neuron.

    DOI 10.1038/s41586-025-08805-6

    Clare R. Gamlin, Casey M. Schneider-Mizell … Staci A. Sorensen

  • Excitatory neurons in the neocortex exhibit considerable morphological diversity, yet their organizational principles remain a subject of ongoing research. Here, the authors use unsupervised learning to show that most excitatory neuron morphologies in the mouse visual cortex form a continuum, with notable exceptions in deeper layers.

    DOI 0.1038/s41467-025-58763-w

    Marissa A. Weis, Stelios Papadopoulos … Alexander S. Ecker

  • Neural Decomposition (NEURD) is a software package that decomposes neuronal data from high-resolution electron microscopy volumes into feature-rich graph representations to facilitate analysis for neuroscience research.

    DOI 10.1038/s41586-025-08660-5

    Brendan Celii, Stelios Papadopoulos … Jacob Reimer

  • The Connectome Annotation Versioning Engine (CAVE) is a platform for proofreading, annotating and analyzing datasets reaching the petascale. Currently, CAVE is used for electron microscopy datasets, but it can potentially be used for other large-scale datasets.

    DOI 10.1038/s41592-024-02426-z

    Sven DorkenwaldCasey M. Schneider-MizellForrest Collman

Scientists present the largest, most detailed, functional wiring diagram of a mammalian brain to date—a milestone for neuroscience achieved by a global consortium of scientists. Understanding how the brain works – its parts, the way it is organized, how neurons are connected – scientists can better understand what happens when things go wrong in disease. The Machine Intelligence from Cortical Networks (MICrONS) Project took seven years and is considered one of the most challenging neuroscience experiment ever attempted. The findings are presented in a suite of ten papers published in the Nature family of journals

This video was made by Tyler Sloan, Ph.D., at ‪@quorumetrix

Phase 3 Preprints (cortical cubic millimeter MM3)

  • Thomas Macrina, Kisuk Lee, Ran Lu, Nicholas L. Turner, Jingpeng Wu, Sergiy Popovych, William Silversmith, Nico Kemnitz, et al. Correspondence: H. Sebastian Seung

    bioRxiv 2021.08.04.455162

    doi: 10.1101/2021.08.04.455162

  • Zhiwei Ding, Dat T. Tran, et al. Correspondence: Andreas S. Tolias.

    bioRxiv 2023.03.15.532836

    doi: 10.1101/2023.03.15.532836

  • Jiakun Fu, et al. Correspondence: Andreas S. Tolias, Katrin Franke.

    bioRxiv 2023.03.13.532473

    doi: 10.1101/2023.03.13.532473

  • Paul G. Fahey, et al. Correspondence: Jacob Reimer, Andreas S. Tolias.

    bioRxiv 745323

    doi: 10.1101/745323

  • Agnes L. Bodor, et al. Correspondence: Nuno Maçarico da Costa

    bioRxiv 2023.10.18.562531

    doi: 10.1101/2023.10.18.562531

Phase 1 (cortical layer 2/3)

  • Nicholas L. Turner, Thomas Macrina, J. Alexander Bae, Runzhe Yang, Alyssa M. Wilson, Casey Schneider-Mizell, Kisuk Lee1, Ran Lu, Jingpeng Wu, Agnes L. Bodor, Adam A. Bleckert, Derrick Brittain, Emmanouil Froudarakis, Sven Dorkenwald, Forrest Collman, Nico Kemnitz, et al.

    This is the flagship paper for MICrONS Phase 1.

    Cell, Volume 185, Issue 6, 2022, Pages 1082-1100.e24

    doi: 10.1016/j.cell.2022.01.023

  • Carolyn M. Ott, Russel Torres, et al.

    bioRxiv 2023.10.31.564838

    doi: 10.1101/2023.10.31.564838

  • JoAnn Buchanan, et al.

    PNAS 2022 119 (48) e2202580119

    doi: 10.1073/pnas.2202580119

  • Sven Dorkenwald, Nicholas L. Turner, Thomas Macrina, Kisuk Lee, Ran Lu, Jingpeng Wu, Agnes L. Bodor, Adam A. Bleckert, Derrick Brittain, et al.

    eLife 11:e76120

    doi: 10.7554/eLife.76120

  • Casey Schneider-Mizell, Agnes L. Bodor, Forrest Collman, Derrick Brittain, Adan Bleckert, Sven Dorkenwald, Nicholas L. Turner, Thomas Macrina, Kisuk Lee, Ran Lu, Jingpeng Wu, et al.

    eLife 10:e73783

    doi: 10.7554/eLife.73783

  • Pengcheng Zhou, et al.

    bioRxiv 2020.03.25.007468

    doi: 10.1101/2020.03.25.007468

  • Nicholas Turner, Kisuk Lee, Ran Lu, Jingpeng Wu, Dodam Ih, H. Sebastian Seung.

    arXiv:1904.09947

    doi: 10.48550/arXiv.1904.09947

Non-Consortium Publications

publications from labs or researchers outside the core MICrONS Consortium, using MICrONS data.

If you have a publication using Phase 1 or Phase 3 data and would like it listed here, submit a MICrONS Publication form.

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