Viren Jain
research scientist @ google. connectomics, machine learning, drumming, etc.
- Reposted by Viren JainIt was a privilege to develop the website to showcase the release of this basal ganglia connectome! Congratulations to everyone involved 😊🎉 Check out interactive 3D models, analysis you can perform in your browser, & our interactive matrices; all on the website! songbird-connectomics.org
- Reposted by Viren JainWouldn't it be great if we could not only image large connectomic volumes but also completely reconstruct them? And if a whole mouse brain project didn't cost billions? With the PATHFINDER preprint (www.biorxiv.org/content/10.1...), we preview a future where it doesn't have to.
- Reposted by Viren JainNice, thanks for pointing this out! "Saw the preview, don't have to see the movie" isn't always true. :) The approach is simple and smart and allows one to sidestep the problem of how to losslessly subdivide a whole brain. Good.
- An important addition to the Nature paper, beyond what was shown in the 2024 preprint, is 12 rounds of iterative imaging and sectioning of a LICONN volume, achieving 205 microns in axial extent (native scale) with manual tracing of axons: www.nature.com/articles/s41...
- Nature research paper: Light-microscopy-based connectomic reconstruction of mammalian brain tissue go.nature.com/3YCLkuZ
- Reposted by Viren JainNature research paper: Light-microscopy-based connectomic reconstruction of mammalian brain tissue go.nature.com/3YCLkuZ
- Reposted by Viren JainNew era for brain mapping, latest from Johann Danzl lab in @nature.com. Light-microscopy connectomics is at single-synapse resolution. Engineered hydrogel embedding + expansion, deep learning-based segmentation, and molecularly resolved reconstructions: axons, spines, connectivity, all visible.
- Reposted by Viren JainWe'll present our #ICLR2025 spotlight on ZAPBench this afternoon: 📍 Hall 3 #61!
- ⚡️ Excited to introduce ZAPBench, our #ICLR2025 spotlight: The Zebrafish Activity Prediction Benchmark measures progress in predicting neural activity within an entire vertebrate brain (70k+ neurons!) Explore interactive visualizations, datasets, code + paper: google-research.github.io/zapbench 🧠🧪
- Reposted by Viren JainPredict the zebrafish brain: github.com/google-resea...
- Reposted by Viren Jain⚡️ Excited to introduce ZAPBench, our #ICLR2025 spotlight: The Zebrafish Activity Prediction Benchmark measures progress in predicting neural activity within an entire vertebrate brain (70k+ neurons!) Explore interactive visualizations, datasets, code + paper: google-research.github.io/zapbench 🧠🧪
- Reposted by Viren JainAstounding achievement and even more astounding numbers here
- Harvard and Google AI mapped one cubic millimeter of a human brain. It took up 1.4 petabytes of storage just in pictures of the specimen. So the entire brain would take ~ 1.6 zettabytes of storage, cost $50 billion, and require 140 acres. It would be the largest data center on the planet— one brain.
- TensorStore (github.com/google/tensorstore) has had a huge 2024 and continues to power checkpointing for much of the largest ML work at Google, including Gemini, and support major Google Cloud customers training models on GCP. Read on for some specific 2024 updates!
- The new optionally cooperative distributed b-tree (OCDBT) driver has greatly increased performance on big workloads, and in 2024 we added transactional support to further optimize performance on object storage systems like GCS: github.com/google/tenso...
- New batch read support has significantly improved efficiency when reading from sharded formats like zarr v3 and neuroglancer precomputed: github.com/search?q=rep... and many other general performance and efficiency improvements (e.g. github.com/google/tenso...)
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View full threadFor more background on TensorStore check out the original blog post: research.google/blog/tensors... and reach out to me, jbms@google.com, or github.com/google/tenso... if you have any comments, questions, or suggestions.
- Reposted by Viren JainI just put out v3.5.1 of NGLui, which is a python package for building and parsing data-driven Neuroglancer states. It's a big update, with cool new stuff like annotation tags (at least if you're using a bleeding edge NGL deployment) and much richer parsing.
- Reposted by Viren JainThis paper is incredible. EM level connectomics on a light microscope. www.biorxiv.org/content/10.1...
