Cambridge FENS-Chen 2026 school posts spiking-net tutorial

An open repository showed up on GitHub with slides and a Colab notebook for a Cambridge neuroscience summer school. That is a small thing, but it is exactly the kind of teaching material release that used to sit behind a login for a week's cohort of PhD students and then quietly vanish.

The repo, cambridge-fens-chen-summer-school-2026, lives under the neural-reckoning organisation on GitHub. According to its README, it contains code and slides for the 2026 FENS Chen Summer School track on 'Learning with spikes', a Jupyter notebook that opens directly in Google Colab, and the deck in both PowerPoint and PDF. Everything is MIT-licensed. The instructor also points readers to their free online course, 'Neuroscience for machine learners', for deeper study.

The surrounding event is the 2026 FENS-Chen Institute Summer Program on AI-Accelerated Neuroscience Discovery and Translation. According to FENS, the program runs 12-18 July 2026 at Cambridge's Department of Applied Mathematics and Theoretical Physics, under scientific leads Zoe Kourtzi (University of Cambridge) and Eleni Vasilaki (University of Sheffield). It is aimed at PhD students, postdocs and MRes students, with registration having closed in February.

The honest caveat is that this is a slide deck and a tutorial notebook, not a research release, and how well the material stands on its own, without the lecturer in the room, is the thing you find out only by working through it. What the reporting on the repo does not tell you is whether the lectures themselves will be recorded and published, or whether other tracks in the program will be released in the same open form.

The forward-looking part is smaller than a summer-school announcement usually implies, but real: as more course leads drop their teaching packs into plain public repos, the gap between a curated European neuroscience track and a self-taught engineer in another timezone gets a little thinner.