Jan-Matthis Lueckmann
@janmatthis.bsky.social
150 followers 260 following 9 posts
Research scientist at Google in Zurich http://research.google/teams/connectomics PhD from @mackelab.bsky.social
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janmatthis.bsky.social
⚡️ 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

🧠🧪
ZAPBench
ZAPBench evaluates how well different models can predict the activity of over 70,000 neurons in a novel larval zebrafish dataset.
google-research.github.io
Reposted by Jan-Matthis Lueckmann
Reposted by Jan-Matthis Lueckmann
mackelab.bsky.social
New preprint: SBI with foundation models!
Tired of training or tuning your inference network, or waiting for your simulations to finish? Our method NPE-PF can help: It provides training-free simulation-based inference, achieving competitive performance with orders of magnitude fewer simulations! ⚡️
Reposted by Jan-Matthis Lueckmann
michalwj.bsky.social
Wouldn'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.
janmatthis.bsky.social
We'll present our #ICLR2025 spotlight on ZAPBench this afternoon: 📍 Hall 3 #61!
ICLR conference poster on ZAPBench
janmatthis.bsky.social
+ special shout-out to @alexbchen.bsky.social who recorded the activity dataset!
janmatthis.bsky.social
🕸️ Last but not least -- the connectome for this specific 🐟 specimen is currently being reconstructed and will be available at a later date!
janmatthis.bsky.social
🧪 We test a number of SOTA time-series forecasting models to provide baselines. We also explore forecasting activity directly in voxel space in a companion paper (www.arxiv.org/abs/2503.00073).
janmatthis.bsky.social
📈 This dataset forms the core of the Zebrafish Activity Prediction Benchmark (ZAPBench), which uniquely measures progress on forecasting neural activity at full brain scale and single cell resolution in a vertebrate.
janmatthis.bsky.social
🔬 We collected and extensively processed a 4d dataset imaged with a lightsheet microscope. The resulting 3d movie covers over 70,000 neurons of a fish exposed to various visual stimuli.
janmatthis.bsky.social
🧠 How accurately can future neural activity be predicted from past activity at the scale of the whole brain? Larval zebrafish offer a unique opportunity to address this question, as they are currently the only vertebrate species in which whole-brain activity can be recorded at cellular resolution.
janmatthis.bsky.social
⚡️ 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

🧠🧪
ZAPBench
ZAPBench evaluates how well different models can predict the activity of over 70,000 neurons in a novel larval zebrafish dataset.
google-research.github.io
Reposted by Jan-Matthis Lueckmann
jakhmack.bsky.social
If you use the sbi toolbox, help make it better by sharing your feedback!!
sbi-devs.bsky.social
🙏 Please help us improve the SBI toolbox! 🙏

In preparation for the upcoming SBI Hackathon, we’re running a user study to learn what you like, what we can improve, and how we can grow.

👉 Please share your thoughts here: forms.gle/foHK7myV2oaK...

Your input will make a big difference—thank you! 🙌