Jan-Matthis Lueckmann

Simulation-Based Inference: A Practical Guide A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers a principled framewo...

Simulation-based inference (SBI) has transformed parameter inference across a wide range of domains. To help practitioners get started and make the most of these methods, we joined forces with researchers from many institutions and wrote a practical guide to SBI.

📄 Paper: arxiv.org/abs/2508.12939

Jaxley: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics - Nature Methods Jaxley is a versatile platform for biophysical modeling in neuroscience. It allows efficiently simulating large-scale biophysical models on CPUs, GPUs and TPUs. Model parameters can be optimized with ...

Our work on training biophysical models with Jaxley is now out in @natmethods.nature.com. Led by @deismic.bsky.social, with @philipp.hertie.ai, @ppjgoncalves.bsky.social & @jakhmack.bsky.social et al.

Paper: www.nature.com/articles/s41...

An ion channel omnimodel for standardized biophysical neuron modelling Biophysical neuron modeling is an indispensable tool in neuroscience research, with the combination of diverse ion channel kinetics and morphologies being used to explain various single-neuron propert...

“Mapping ion channel function” doi.org/10.7554/eLif... isn’t exactly a citation slayer, but it’s still one of my favourites (& my first independent project). Today we push pt 2, where we trace code origin & unite almost all channel models in a common expression. Boom! www.biorxiv.org/content/10.1...

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! ⚡️

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.

We'll present our #ICLR2025 spotlight on ZAPBench this afternoon: 📍 Hall 3 #61!

+ special shout-out to @alexbchen.bsky.social who recorded the activity dataset!

Fantastic collaboration between Google Research, HHMI Janelia, and Harvard -- including @michalwj.bsky.social @stardazed0.bsky.social @aleximmer.bsky.social @mishaahrens.bsky.social and many more!

Paper: openreview.net/pdf?id=oCHsD...
Website: google-research.github.io/zapbench

🕸️ Last but not least -- the connectome for this specific 🐟 specimen is currently being reconstructed and will be available at a later date!

🧪 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).

📈 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.

🔬 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.

🧠 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.

ZAPBench ZAPBench evaluates how well different models can predict the activity of over 70,000 neurons in a novel larval zebrafish dataset.

⚡️ 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

🧠🧪

If you use the sbi toolbox, help make it better by sharing your feedback!!