rougier/neurosciences — explained in plain English
Analysis updated 2026-07-17 · repo last pushed 2015-02-09
Run a working implementation of a published neuroscience model instead of translating equations from a paper yourself.
Tweak parameters of an existing model to see how neurons or learning behavior change.
Use a clean reference implementation as a starting point for your own computational neuroscience research.
| rougier/neurosciences | coleam00/harness-engineering-demo | color4-alt/citecheck | |
|---|---|---|---|
| Stars | 31 | 31 | 31 |
| Language | Python | Python | Python |
| Last pushed | 2015-02-09 | — | — |
| Maintenance | Dormant | — | — |
| Setup difficulty | moderate | moderate | easy |
| Complexity | 3/5 | 3/5 | 2/5 |
| Audience | researcher | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
README is minimal and doesn't clearly document which models are included or how to run each one.
A Python collection of runnable code implementations for computational neuroscience models from published research papers, so you can experiment with them directly.
Mainly Python. The stack also includes Python.
Dormant — no commits in 2+ years (last push 2015-02-09).
License details not mentioned in the explanation.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
double-check against the repo, no cap.