Type a coordinate: jump to it in minnie65, identify the nearest cell + its neighbours, and load the cell and nucleus in 3D.
Or paste x, y, z into the x field — it splits automatically.
Great for learning what a cell type looks like (a new random example loads each click), or for quickly finding a cell that still needs a first identification.
On identify, the cell (root ID) and its nucleus are loaded automatically, so both segmentation layers switch on even if unchecked.
Select any combination of cell type(s), vessel proximity, glia-limitans proximity, white-matter-border proximity, and/or cortical layer, then download the matching cells (with coordinates and root/nucleus IDs) as an Excel file.
The "user-reported" and "totally unclassified" options require a brief internet fetch to check which cells already have a report on file.
Restricts matches to cells in the Allen Institute's manually-classified V1 column (allen_v1_column_types_slanted_ref / aibs_column_nonneuronal_ref). "Any member" matches every column cell regardless of type (including pericytes/vascular); "Neuronal members" and "non-vascular, non-neuronal members" (glia and other non-neuronal calls, excluding pericytes) are narrower and can be checked together to match either. Check "Include V1 column boundary" below to also draw the column's outline in the 3D view.
Layer filtering re-estimates each candidate cell's cortical depth on the fly and can take a few seconds for large result sets.
Two diagonal corners per box, in the same voxel coordinates as the main search box above (X/Y at 4 nm/voxel, Z at 40 nm/voxel). Either diagonal works — order doesn't matter. Add as many boxes as you like; a cell matches if it falls inside any of them. Matching cells within 10 µm of a traced vessel will include the vessel type and distance in the download. You can paste x, y, z into either corner's x field — it splits automatically, just like the main coordinate field above.
Draws Søren's hand-traced vessel centerlines as colour-coded 3D line annotations in the viewer opened below, one independently-toggleable layer per category you check here. Distinct from "Include vasculature outline" above, which shows the pre-segmented vessel mesh rather than the actual tracing. The tracing data is hosted separately (not embedded in this file) and is only fetched for the categories you check, cached in this browser tab after the first load — requires network access.
Opens a zoomed-out 3D view (nuclei + segmentation by default) sized and centred to fit every matching cell. Each cell type gets its own colour-coded layer (e.g. red = mural cells, purple = astrocytes, green = microglia) plus its own nuclei layer (always blue), so you can switch individual types on/off from Neuroglancer's layer panel. "Include vasculature outline" adds the traced vessel mesh (Img65 + Img35) as its own toggleable layer. "Include EM imagery" adds the raw EM layer(s) so you can inspect ultrastructure directly, not just the segmentation -- off by default since EM tiles are heavier to load. Normally it adds Img65 and/or Img35, whichever the matched cells actually fall in; if either vasculature overlay is on it adds both, since the vessels span the whole imaged volume rather than just the minnie65 predicted region. "Include V1 column boundary" adds a green wireframe outline of the Allen Institute's manually-classified V1 column (a derived envelope, not an official published shape -- see the "V1 column" filters below for selecting its member cells). If "Limit to region(s)" is on, each box is drawn as its own colour-matched, toggleable outline layer too.
Grubb, “Ultrastructure of precapillary sphincters and the neurovascular unit,” Vascular Biology 5, VB-23-0011 (2023).
Grubb, “Ultrastructure of the brain waste-clearance pathway,” bioRxiv preprint (2023), not yet peer-reviewed.
Grubb, Chaddha, Lippincott-Schwartz, Ott & Mughal, “Pericyte and Endothelial Primary Cilia and Centrioles have Disparate Organization Across the Brain Microvasculature,” bioRxiv preprint (2025), not yet peer-reviewed.
Morris, Foster, Sutherland & Grubb, “Microglia contact cerebral vasculature through gaps between astrocyte endfeet,” Journal of Cerebral Blood Flow & Metabolism 44(12), 1472–1486 (2024).
Pericyte subtype naming (ensheathing / mesh / thin-strand) and the arteriole–capillary transition zone: Grant, Hartmann, Underly, Berthiaume, Bhat & Shih, “Organizational hierarchy and structural diversity of microvascular pericytes in adult mouse cortex,” J Cereb Blood Flow Metab 39(3), 411–425 (2019).
Pericyte subtype criteria used by this tool’s guided identification, tested against serial block-face SEM (circumferential coverage, cross-sectional area shared with the endothelium, peg-and-socket density, and ECM extensions unique to ensheathing pericytes): Abdelazim et al., “Pericyte heterogeneity identified by 3D ultrastructural analysis of the microvessel wall,” Frontiers in Physiology 13:1016382 (2022). Note that these subtypes grade into one another rather than forming discrete classes — see the Grubb 2023 review above, which argues the transitional mural cells are better described simply as contractile vs non-contractile, and which is why the guided tree always offers a plain “Pericyte” option.
Cell type predictions & dataset: The MICrONS Consortium, “Functional connectomics spanning multiple areas of mouse visual cortex,” Nature 640, 435–447 (2025).
Perisomatic cell-type classification (neuronal + non-neuronal — incl. contributions from Leila Elabbady): Elabbady et al., “Perisomatic ultrastructure efficiently classifies cells in mouse cortex,” Nature 640, 478–486 (2025).
Brain ultrastructure overview: “Brain Ultrastructure: Putting the Pieces Together,” PMC7930431.
Neurovascular volume EM: “Public Volume Electron Microscopy Data: An Essential Resource to Study the Brain Microvasculature,” Frontiers in Cell and Developmental Biology (2022).
Neurotransmitter prediction from synaptic EM: “Neurotransmitter classification from EM images at synaptic sites,” Cell (2024).
Synapse type I/II framework: Gray, E.G., “Axo-somatic and axo-dendritic synapses of the cerebral cortex: an electron microscope study,” J. Anat. 93:420–433 (1959) (foundational; no open-access link).
Cortical layer depth boundaries used for the layer estimate (rescaled proportionally to each location's locally measured pia-to-white-matter thickness, rather than used as fixed absolute microns): Ledderose et al., “Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment,” Cerebral Cortex (2023). Proportional rescaling is used because both this source and MICrONS are chemically (aldehyde) fixed tissue, which is documented to shrink cortex linearly by ~15–18%: Korogod, Petersen & Knott, “Ultrastructural analysis of adult mouse neocortex comparing aldehyde perfusion with cryo fixation,” eLife 4:e05793 (2015).
Fine-grained m-type classification (dendritic-morphology / synaptic-target clusters): Schneider-Mizell et al., “Inhibitory specificity from a connectomic census of mouse visual cortex,” Nature 640, 448–458 (2025).
Excitatory dendritic-morphology map (subtypes as a continuum with L5/L6 exceptions) — basis for the guided excitatory-subtype step: Weis et al., “An unsupervised map of excitatory neuron dendritic morphology in the mouse visual cortex,” Nature Communications 16, 3361 (2025).
Layer 5 thick-tufted (ET) excitatory neurons — thick apical trunk, prominent L1 tuft, thick myelinated axon: Bodor et al., “The synaptic architecture of layer 5 thick tufted excitatory neurons in the visual cortex of mice,” Nature Neuroscience (2025).
Sst (Martinotti) inhibitory subtypes — distal-dendrite targeting, axon myelination & output: Gamlin et al., “Connectomics of predicted Sst transcriptomic types in mouse visual cortex,” Nature 640, 497–505 (2025).
Excitatory projection-neuron classes (IT/ET/NP/CT) and general layer circuitry: Harris & Shepherd, “The neocortical circuit: themes and variations,” Nature Neuroscience 18, 170–181 (2015).
Inhibitory interneuron subtype function (basket/Martinotti/bipolar/neurogliaform cells): Tremblay, Lee & Rudy, “GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits,” Neuron 91, 260–292 (2016).
Microglia function: Nimmerjahn, Kirchhoff & Helmchen, “Resting Microglial Cells Are Highly Dynamic Surveillants of Brain Parenchyma in Vivo,” Science 308, 1314–1318 (2005).
Oligodendrocyte function: Bergles & Richardson, “Oligodendrocyte Development and Plasticity,” Cold Spring Harbor Perspectives in Biology 8, a020453 (2016).
OPC & neurovascular unit function: Pfeiffer, “Reciprocal Interactions between Oligodendrocyte Precursor Cells and the Neurovascular Unit in Health and Disease,” Cells 11, 1954 (2022).
Astrocyte & neurovascular coupling function: Takahashi, “Metabolic Contribution and Cerebral Blood Flow Regulation by Astrocytes in the Neurovascular Unit,” Cells 11, 813 (2022).
Pericyte function: Girolamo et al., “Central Nervous System Pericytes Contribute to Health and Disease,” Cells 11, 1707 (2022).
Leptomeninges anatomy & function: Zedde & Pascarella, “Leptomeninges: Anatomy, Mechanisms of Disease and Neuroimaging,” Neurology International 17, 203 (2025).
Leptomeningeal cell subtypes (arachnoid barrier cell tight junctions; shared, location-defined fibroblast subtypes) — basis for the guided leptomeninges step: Pietilä et al., “Molecular anatomy of adult mouse leptomeninges,” Neuron 111, 3745–3764.e7 (2023).
White matter function: Fields, “White matter in learning, cognition and psychiatric disorders,” Trends in Neurosciences 31, 361–370 (2008).
Nearest-nucleus, IDs & predictions from nucleus_detection_v0 and aibs_metamodel_celltypes_V661 (minnie65 only).
This tool was made by Søren Grubb (Neuroscience Academy Denmark) to make identifying brain cortical cells in electron microscopy easy. It was built using Claude AI. Predictions from the MICrONS consortium are included, but you can help identify cells that lack a prediction, or revise ones already made — identification discrepancies and newly identified cells are shared back with the MICrONS consortium.