Welcome to the NEST simulator documentation!¶
NEST is a simulator for spiking neural network models, ideal for networks of any size, for example:
- Models of information processing e.g. in the visual or auditory cortex of mammals,
- Models of network activity dynamics, e.g. laminar cortical networks or balanced random networks,
- Models of learning and plasticity.
- New to NEST?
- Start here at our Getting Started page
- Have an idea of the type of model you need?
- Click on one of the images to access our model directory:
Create complex networks using the Topology Module or the Microcircuit Model:
- Need a different model?
- Check out how you can create you own model here.
- Have a question or issue with NEST?
- See our Getting Help page.
How the documentation is organized¶
- Tutorials show you step by step instructions using NEST. If you haven’t used NEST before, the PyNEST tutorial is a good place to start.
- Example Networks demonstrate the use of dozens of the neural network models implemented in NEST.
- Topical Guides provide deeper insight into several topics and concepts from Parallel Computing to handling Gap Junction Simulations and setting up a topological network.
- Reference Material provides a quick look up of definitions, functions and terms.
- Have you used NEST in an article or presentation? Let us know and we will add it to our list of publications. Find out how to cite NEST in your work.
- If you have any comments or suggestions, please share them on our Mailing List.
- Want to contribute code? Check out our Developer Space to get started!
- For more info about our larger community and the history of NEST check out the NEST Initiative website