Can generative AI accelerate neuroscience? Excited to share MoGen at ICLR 2026!🧠 We use point cloud flow matching to generate high-fidelity 3D neuron fragments, capturing intricate details like dendritic spines.

Applications are now open for our Junior Theoretical Neuroscientists Workshop which will take place July 21 - 24, 2026 at the Center for Computational Neuroscience @flatironinstitute.org Learn more and apply by April 15 at www.simonsfoundation.org/event/jrwork...

Junior Theoretical Neuroscientists Workshop

Junior Theoretical Neuroscientists Workshop on Simons Foundation

simonsfoundation.org

Our paper “Multifidelity Simulation-based Inference for Computationally Expensive Simulators” has been accepted at ICLR 2026! 🥳 We hope this can be a practical solution for anyone analysing and doing inference on computationally expensive simulators. Paper: openreview.net/pdf?id=bj0dc...

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

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...

arxiv.org

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...

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 ...

nature.com

“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...

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...

biorxiv.org

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!

Jan-Matthis Lueckmann@janmatthis.bsky.social · last yr.

⚡️ 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 🧠🧪

⚡️ 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

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

sbi - Simulation-based inference@sbi-devs.bsky.social · 2y ago

🙏 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! 🙌