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Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/31281157-91ce-4dd0-afe5-7b86100e28f4/Figure+2_v4.png Roadmap - Make it stand out Image credit: Julia Kuhl. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/8a304c50-b15d-4cf0-beef-639f19047a6c/m2_m3%404x+%281%29.png Roadmap - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.e11.bio/home daily 1.0 2025-10-23 https://www.e11.bio/news daily 0.75 2025-10-02 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/e105926a-3f80-4588-9aa2-e5cca6fda9dc/Screen+Shot+2024-05-13+at+2.21.49+PM.png News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/edb56beb-4d37-45fe-bc5b-fedac075aa5f/p-3-90684882-schmidt-futures-is-launching-new-startup-like-organizations-to-take-on-gaps-in-scientific-research.jpg News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/f0aa8cd5-0d90-42ad-8572-670319ab5623/Screen+Shot+2024-05-15+at+4.49.24+PM.png News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/2ea7f4dc-e735-46fc-8b45-044a9bfa7bcb/Screen+Shot+2024-05-15+at+4.53.44+PM.png News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/ea734943-87ee-4a36-8596-f57c12796ef4/GettyImages-1377064482-technology%2Bdata.jpeg News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/87f6b4a0-69ad-47e8-896d-f2020e48b6a0/Asimov.jpg News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/faf75ef3-676e-4efd-8997-9901a4c92b7c/MIT-FROzone-01-press_0.jpg News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/7be817ee-60ca-495e-811d-58182c592913/Screenshot+2024-12-03+at+6.44.07%E2%80%AFAM.png News https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/a686f8e4-fbac-4f8e-b456-3856da50bee9/Screenshot+2025-10-01+at+7.54.43%E2%80%AFAM.png https://www.e11.bio/blog/volara daily 0.75 2025-05-29 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/41527e95-f0c7-4b4a-94b3-475cf61b17e3/bg3.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/3ea6979f-cf0b-4b5b-a9de-19cb651cbeeb/Diagram-transparent+bg3.png Volara - Make it stand out This diagram visualizes the lifetime of a block in Volara. On the left we are reading array and/or graph data with optional padding for a specific block. This data is then processed, and written to the output on the right. For every block processed we also mark it done in a separate Zarr. Once each worker completes a block, it will fetch the next. This process continues until the full input dataset has been processed. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/f97d4ac3-c4ff-4f61-ad00-34236059404b/performance.png Volara - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.e11.bio/terms-of-use daily 0.75 2025-06-06 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/e3d028f9-6286-40e8-9eeb-d50d2f29654d/CC_BY-SA_icon.svg.png https://www.e11.bio/blog daily 0.75 2025-10-21 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/1733200530143-2F7OHY8GUXZM4ZGM41ZJ/neurons_black_smaller+file.png Blog https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/3ee1321c-a669-432a-a54f-d45e8be85371/Screenshot+2025-08-21+at+4.58.11%E2%80%AFPM.png Blog https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/41527e95-f0c7-4b4a-94b3-475cf61b17e3/bg3.png Blog https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/8e9c8d7d-c4a9-45a4-ace9-487bdd93e118/Still%2B2025-08-07%2B133324_6.15.1.png Blog https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/7ab72bf1-43d0-4578-a1c3-bc65f1fff959/aws+logo.png Blog https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/8e9c8d7d-c4a9-45a4-ace9-487bdd93e118/Still%2B2025-08-07%2B133324_6.15.1.png https://www.e11.bio/jeff-chen daily 0.75 2025-06-09 https://www.e11.bio/jinyoung-lee daily 0.75 2025-06-09 https://www.e11.bio/tech daily 0.75 2025-10-24 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/379efa11-7a38-462e-8c34-6f32588be60d/Screenshot+2025-09-30+at+6.14.44%E2%80%AFPM.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/76028d23-9046-4aa7-989f-023cdf115a91/Screenshot+2025-09-30+at+6.14.13%E2%80%AFPM.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/d4602501-44a6-45f0-8ff1-6158466eb056/neuroglancer-screenshot-w2243px-h1231px-at-1_31_2025-3_28_45+PM.jpg https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/5b8c3c39-d56b-4bad-8c81-08d857bcd921/Screenshot+2025-09-30+at+6.15.17%E2%80%AFPM.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/ac73acdb-9db8-4043-8c67-ff13f70981ad/neuroglancer-screenshot-w1938px-h1231px-at-1_31_2025-3_35_53+PM.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/394d45a7-080f-4ed3-ab42-0278db90dedb/addgene-logo-white.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/31922366-a40d-4452-ae85-d475c2fd848d/github.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/8365b250-0d64-45dd-ae79-b5e18ae3e8b6/Untitled-1.png https://www.e11.bio/julia-lyudchik daily 0.75 2025-06-16 https://www.e11.bio/victor-holmes daily 0.75 2025-09-09 https://www.e11.bio/blog/prism daily 0.75 2025-10-02 https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/bec02e19-c360-43a7-970b-58d54b6528e0/Still+2025-08-07+133324_6.15.1.png https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/1cb2d94b-6854-4815-bead-45ceb7d5078e/subway2.png PRISM - Make it stand out Figure 1: Subway map analogy illustrating the use of protein barcodes for automated segmentation. Top panels: Map from the London Underground. Bottom panels: Image of tissue from the hippocampal CA3 region. The left panels show single-color representations while the right panels display multiple channels or barcodes. Scale bar: 20 μm (pre-expansion). https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/31281157-91ce-4dd0-afe5-7b86100e28f4/Figure+2_v4.png PRISM - Make it stand out Figure 2: Overview of PRISM technology. Protein Barcoding: Cells in brain tissue are barcoded as they receive random combinations of antigenically distinct proteins. Expansion Microscopy (and iterative staining): Tissue is expanded to improve imaging resolution resolution, and multiplexed through multiple rounds of antibody staining and imaging. AI reconstruction: The 3D structure of neurons is reconstructed by AI tools. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/09ba5d4d-ef00-4e6c-b0e1-7e1f07b5dc3c/full+render.png PRISM - Make it stand out Figure 3: 3D rendering of a 10 million cubic micron volume of mouse hippocampal CA2/CA3 at a 35 x 35 x 80 nm voxel size. Colors from left to center demonstrate labeling of neurons with unique combinations of the 18 protein bits. Pink and cyan points at the right edge show synapses identified via stained synaptic markers. Enlarged circles at top (left to right) highlight four different aspects of the dataset: the first and second compare a grayscale (eGFP) single-plane image to the same multi-colored image labeled with 18 protein bits. The third demonstrates 3D neuron tracing segments using 18-bit protein barcodes. The fourth shows synapse reconstructions using the presynaptic active zone marker Bassoon and the postsynaptic excitatory scaffold protein PSD95. Scale bar: 10 µm pre-expansion. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/717010f7-69b1-43db-8292-315f54f93b86/barcoding.png PRISM - Make it stand out Figure 4: Structure of protein bits; combinatorial protein barcoding via stochastic AAV infection. Stochastic infection leads to the expression of random combinations of protein bits. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/80d53da4-d5f3-4bb7-9f92-bdd9f8c457fa/barcode_fig.png PRISM - Make it stand out Figure 5: Barcode staining of cells. Top: Individual cells are classified into presence or absence for each protein bit to create a binary matrix. The image at left shows 13 cell bodies, the image at center shows the staining for the 13 cells (in rows) for the 18 protein bits (columns), the graph at right shows the binary result. Bottom: descriptive statistics across all somas in the dataset. The figure at left shows protein bit expression fractions. The center figure shows the distribution for the total number of expressed protein bits. The right figure quantifies the uniqueness of observed barcodes. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/10b88a07-1b3b-4396-91ec-7620229a0c6f/neuroglancer_raw.png PRISM - Make it stand out Interactive Figure 1: Interactive visualization of the 18 channel barcoded raw data. The left panel visualizes each channel individually (channels can be cycled through). The right panel shows all channels visualized with a multi-channel shader. Colors can be randomly cycled using seeds and the individual channel colors/intensities can be tuned. Tutorial. May load slowly. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/0c127aff-9ef0-4846-ba6c-3308d3c86cbc/arlo+image.png PRISM - Make it stand out Figure 6: We first “enhance” the barcodes by learning to predict the average barcode per neuron. We then project the enhanced barcodes (18 channels, ranging from 0 to 1) into a more uniform space (24 channels, ranging from -1 to 1). Images are RGB-color encoded for visualization. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/a5156e83-b917-44c2-9fdb-2d1ca94ee77b/neuroglancer_raw_enhanced.png PRISM - Make it stand out Interactive Figure 2: Interactive visualization of raw (left) vs enhanced (right) barcodes. Tutorial. May load slowly. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/d927fdf2-b717-48a3-9db2-371c492b3c45/networks.png PRISM - Make it stand out Figure 7: Overview of segmentation pipeline. Barcodes are enhanced and projected into a uniform space, and affinities are then computed from this embedding (via the dot product). Separately, we use the enhanced barcodes as input to a traditional shape-based affinity pipeline. We then combine these two affinities and use them as input to a blockwise segmentation pipeline. Additionally we use the barcodes to learn a binary mask of neurons in which barcodes are expressing, in order to prevent false merges against the background signal. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/e3e04d60-ba59-48b2-9ae2-7f71f6b565fb/arlo+image+2.png PRISM - Make it stand out Figure 8: Barcodes help improve segmentation when used as input to affinity pipeline compared to grayscale (GFP) baseline. The top row shows an example ground truth neuron (a segment generated around a ground truth skeleton), and the corresponding segments from GFP and barcode affinity segmentations (>= 50% overlap with ground truth segment). The bottom row shows segmentation accuracy using common evaluation metrics. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/4e0a459d-1d3d-41ea-b3c4-b08aafdc6b95/Screenshot+2025-10-01+at+9.37.41%E2%80%AFAM.png PRISM - Make it stand out Interactive Figure 3: Interactive visualization of a subset of selected segments demonstrating how barcodes help to decrease false merges in initial affinity segmentation. Middle panel shows several falsely merged segments. Left panel shows overlapping (>=50%) “ground truth” segments. Right panel shows overlapping barcode affinity segments. Tutorial. May load slowly. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/01110aec-d787-4418-aaf7-f2578218a2b1/barcode_relabeling.png PRISM - Make it stand out Figure 9: Overview of barcode relabeling strategy. Example shows two neurons in which the segmentation produced falsely split segments. We skeletonize these segments and assign the per-segment average barcode to the graph nodes. Then, in a spatial window, we compute edge weights based on the distance between barcodes. We then cluster these edges, and use the resulting lookup table to relabel the split segments. A nice feature about this approach is that the clustering and relabeling can be done in the same way as the affinity pipeline. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/7b2fc79c-effc-4b41-8bca-d5274833d1be/arlo+image+6.png PRISM - Make it stand out Figure 10: Example neuron with resulting mesh from the affinity segmentation and corresponding barcode-relabeled meshes. Barcodes allow for the main fiber to be reconnected alongside the complex dendritic bouton structures across spatial gaps. By relabeling the segments using barcodes, we were able to decrease the false split rate with minimal increases to the false merges (which are due to barcode collisions). Importantly, this accuracy increases with the number of barcodes used for matching. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/33a605e7-8003-4d03-a974-22895df56386/Screenshot+2025-10-01+at+9.45.29%E2%80%AFAM.png PRISM - Make it stand out Interactive Figure 4: Interactive visualization of a subset of barcode relabeled segments. Left panel shows barcode affinity segments (417) which belong to three neurons. While the barcodes help to decrease the false merges in the initial affinity segmentation, there are unavoidable false splits. Right panel shows resulting segments after relabeling these segments using the barcode information. Tutorial. May load slowly. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/c1b92763-242b-47c9-a48a-b4e7ca0c60f7/arlo+image+4.png PRISM - Make it stand out Figure 11: Schematic of ML synapse detection and assignment. Left: 3D volume of detected overlapping PSD95 (magenta) and Bassoon (cyan) labels. The center of each detected label is shown as a solid sphere. Center: a blown-up example pair of PSD95 and Bassoon labels alone, top, or assigned to a segmented neuronal morphology, bottom. Right: same 3D volume shown on the left but only showing label markers that could be assigned to the dendrite rendered in yellow. Right: Example of a proofread pyramidal neuron with assigned excitatory synapses (magenta). https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/eed5d1ca-4999-44bb-b001-c1b3bff1447c/arlo+image+5.png PRISM - Make it stand out Figure 12: Example of a thorny excrescence on a CA3 dendrite. Top left: Composite image showing a single protein-bit channel (gray), PSD95 (magenta), and Bassoon (cyan) antibody labeling. Top right: 3D reconstruction of the same stretch of dendrite. The arrow highlights the location of the thorny excrescence (TE) shown on the left. Bottom center: The volume of the TEs mapped on a single dendrite encoded by color. Bottom left: Observed correlation between TE volume and the number of detected postsynaptic densities. Bottom right: Observed correlation between each TE’s volume and the volume of TEs on the same dendrite within 5 μm. Gray dashed lines indicate the best-fit linear regression. Statistical significance is given as r=Pearson correlation coefficient, ***: p<0.001. https://images.squarespace-cdn.com/content/v1/6155c5f99a5b713379cc93a1/1d4d1355-6831-4f92-8b9b-61af3db8a889/neuroglancer_neurons_markers.png PRISM - Make it stand out Interactive Figure 5: Interactive visualization of raw barcodes using multichannel shader (left), and channel-wise (right). Right panel also shows bassoon and PSD95 markers. Tutorial. 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