This dataset was the first acquired and analyzed by the initial phase of the project. It is a 250 x 140 x 90 µm volume from layer 2/3 of a P36 male mouse visual cortex imaged at 3.58 x 3.58 x 40 nm resolution with a dense segmentation, proofreading of all dendrites and axons of the 364 excitatory neurons in the volume and a dense synapse detection. 

We are releasing datasets in versions. Each individual version resembles a state of the dense cellular segmentation during proofreading. We are also releasing segmentations of other relevant sub-cellular structures as they become available. Release notes contain detailed documentation on the nature of the tables and state of the dataset for each release.

Release v185.1

Release Notes

Technical descriptions of state of the dataset, proofreading, and known errors in this version.

Interactive Visualization

You can visualize and interact with the dataset via neuroglancer (an online data visualization tool developed by connectomics group at google).
Basic neuroglancer instructions are here.

Neuroglancer links (supports Chrome or Firefox)
Dense segmentation: link.
Nucleus segmentation: link
Mitochondrial segmentation: link
Synaptic Cleft segmentation: link
All segmentations layers combined: link
(note: neuroglancer behavior with multiple segmentation layers can be unintuitive)

Programatic Interaction

The locations of the each of the data layers can be found by double clicking on the corresponding layer label in neuroglancer near the top of the screen. One can download and interact with the data via python, using cloud-volume (see link for instructions), including downloading voxels and meshes.

NOTE: If you are interested in large scale downloading of the data, please contact info@microns-explorer.org. There are real costs to the project that are incurred doing this and there are efficient and inefficient ways to do this.

Synapse Table

This is a table of 3.2 million rows of putative synapses between objects within the volume. It was generated by an automated synapse detection approach (Turner et al 2019). Many of the objects in the dataset are not proofread, and so this cannot be trivially interpreted as a connectivity graph. [link]. Note: contains uint64 values and will not display properly in Excel.

Soma Valence Table

This csv contains the spatial locations of most of the cells with somas in the volume, as well as indication of whether that cell is an excitatory cell, an inhibitory cell, or a glial cell of some type. It furthermore identifies the neurons for which proofreading has been complete, and the soma subgraph for which the analysis in Dorkenwald et al 2019 was based. [link]. Note: contains uint64 values and will not display properly in Excel.

Fixed Meshes of Cells with Soma in the dataset

This set of h5 files contain numpy arrays of mesh vertices, faces, and extra edges that connect disconnected portions of the mesh. (link) These files can be read using MeshParty [documentation).

Proofread Soma Subgraph Synapses

This contains a csv file of synapses which have been further proofread to remove false positive synapses between the excitatory cells with somas in the volume. It also contains the spine head volume measurements. This is the smallest file necessary to recapitulate the analysis in Dorkenwald et al., 2019 (link) Note: contains uint64 values and will not display properly in Excel.

Functional Data

Functional data is not yet available for this release.

Skeletons

We have contributed a subset of the cells to the Brain Imaging Library in swc skeleton format. You read about and download that data from this location on brain-map.org

Structural EM data and segmentation

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). Binary and analog variation of synapses between cortical pyramidal neurons. bioRxiv 2019.12.29.890319; doi: https://doi.org/10.1101/2019.12.29.890319

Schneider-Mizell, C. Bodor, A.L., Collman, F. Brittain,D. Bleckert, AA, Dorkenwald, S., Turner N.L. Macrina, T. Lee, K. Lu, R. Wu, J. et al. (2020)  Chandelier cell anatomy and function suggest a variably distributed but common signal. bioRxiv 2020.03.31.018952v1; doi: https://doi.org/10.1101/2020.03.31.018952

Functional imaging data (not yet available)

Zhou, P. et al. EASE: EM-Assisted Source Extraction from calcium imaging data. bioRxiv 2020.03.25.007468; doi: https://doi.org/10.1101/2020.03.25.007468

Functional Imaging: Emmanouil Froudarakis, Jacob Reimer, Andreas Tolias

Co-registration: Nuno Maçarico da Costa, Adam Bleckert, Marc Takeno

Tissue Preparation: Joann Buchanan, Marc Takeno, Nuno Maçarico da Costa

Sectioning: Agnes Bodor, Adam Bleckert

TEM Design and Maintenance: Derrick Brittain, Clay Reid

TEM Operation: Derrick Brittain, Wenjing Yin, Adam Bleckert, Marc Takeno, Daniel Bumbarger, Nuno Da Costa

EM Stitching and Rough Alignment: Gayathri Mahalingam, Russel Torres, Yang Li, Thomas Macrina, Dodam Ih

EM Fine Alignment: Thomas Macrina, Will Wong

Neuron segmentation: Kisuk Lee, Jingpeng Wu

Agglomeration: Ran Lu

Synapse Detection: Nicholas Turner, Jingpeng Wu

Neuroglancer Frontend: Nico Kemnitz, Manuel Castro

Proofreading Backend: Sven Dorkenwald, Nico Kemnitz, Chris S. Jordan

Cloud Data Interface: William Silversmith, Ignacio Tartavull

Connectome Versioning System: Forrest Collman, Sven Dorkenwald, Casey Schneider Mizell

Proofreading: Agnes Bodor, Nuno Maçarico da Costa, Szi-Chieh Yu, Alyssa Wilson, Sven Dorkenwald, Casey Schneider-Mizell, Forrest Collman

Project Management: Lynne Becker, Shelby Suckow

Scientific Management: Clay Reid, Nuno Da Costa, Andreas S. Tolias, Jacob Reimer, H. Sebastian Seung

IARPA MICrONS Program Management: David A. Markowitz, Jacob Vogelstein