Why use Brian?
Easy to use
Brian has a powerful, easy to understand syntax that can define, run and plot neural models in just a few lines of code.
We have simple guides to get you started with installing and learning Python and Brian, and detailed documentation to help you master everything Brian has to offer.
Detailed biophysical Hodgkin-Huxley model? Reduced two variable leaky integrate-and-fire neuron? A new synapse model that hasn’t been added to other simulators yet?
No problem, just write down the equations in standard mathematical notation and run it.
In 1952 Hodgkin and Huxley simulated their model of the squid giant axon. It took them three weeks using a hand operated Brunsviga mechanical calculator. Fortunately, you don’t have to wait that long. Brian can simulate thousands of neurons in realtime.
Brian is more than ten years old, so you can rely on it giving accurate results. We have an extensive test suite that catches any bugs and makes sure that it runs on all platforms. We continue working on Brian, releasing a new version about every six months.
And, we help you to make sure that your code doesn’t have bugs. If you try to write a dimensionally inconsistent equation, we’ll tell you. If the solver you specified for your differential equations is unstable, we’ll let you know.
Brian has been successfully used in hundreds of modelling studies, many of which have made their code freely available to download online. It’s used for the coding exercises in the popular computational neuroscience textbook Neuronal Dynamics (Gerstner et al.).
Brian also has a vibrant ecosystem of software packages built on top of it.
Download and installation
conda install -c conda-forge brian2or
pip install brian2
For more details, see the installation instructions in the documentation.
Try in the browser
Recommendations for GSoC 2023 applications
Recommendations for GSoC 2022 applications
New release: Brian 2.5
Bug hunt episode 2: a strange file appears
Getting the timing right (scheduling 2)
Getting the timing right (scheduling 1)
Papers using Brian
Models (and older ones)
How to contribute
Institut de la Vision, INSERM, Paris
Imperial College London
- Marcel Stimberg
Institut de la Vision, Sorbonne University, Paris
For a full list of contributors, see the AUTHORS file in the repository. All contributions (not only in the form of code) are listed in the release notes.