Welcome to the NetPyNE homepage!

NetPyNE is an open-source Python package to facilitate the development, parallel simulation, analysis, and optimization of biological neuronal networks using the NEURON simulator. See our recent publication in eLife for more details.

To make NetPyNE more accessible, we have released a (beta version) graphical user interface (GUI). The GUI is freely available at gui.netpyne.org with documentation here.

For a detailed overview of NetPyNE, including an interactive tutorial utilizing the GUI, please see our CNS*2020 tutorial: Building mechanistic multiscale models: from molecules to networks using NEURON and NetPyNE. The complete video is available here and slides are available here.

Check out our latest tutorial: Virtual Environments, Jupyter Notebooks, and NetPyNE basics. The video is available here and the notebook is available here .

Join our NetPyNE mailing list to receive updates on version releases and other major announcements. Get your questions answered and participate in the NetPyNE community at the NetPyNE forum or the NetPyNE section of the NEURON forum.

NetPyNE is available as a resource through Neuroscience Gateway Portal (NSG); Open Source Brain (OSB) ; Human Brain Project (HBP) EBRAINS; NIH SPARC initiative.

The NetPyNE source code is available on GitHub.

Table of Contents

• About NetPyNE
  • Major Features
  • Questions, suggestions, and contributions
  • Code of conduct
  • Publications
  • Courses
  • Current funding
  • Governance structure
  • Project roadmap
• Installation
  • Requirements
  • Install the latest released version of NetPyNE via pip (Recommended)
  • Upgrade to the latest released version of NetPyNE via pip
  • Install the development version of NetPyNE via GitHub and pip
  • Use a browser-based online version of NetPyNE GUI (beta version)
  • Installation Troubleshooting
• NetPyNE Tutorial
  • Tutorial 1: Quick and easy example
  • Tutorial 2: Network parameters
  • Tutorial 3: Adding a compartment (dendrite) to cells
  • Tutorial 4: Using a simplified cell model (Izhikevich)
  • Tutorial 5: Position- and distance-based connectivity
  • Tutorial 6: Adding stimulation to the network
  • Tutorial 7: Modifying the instantiated network interactively
  • Tutorial 8: Running batch simulations
  • Tutorial 9: Recording and plotting LFPs
  • Tutorial 10: Network with Reaction-Diffusion (RxD)
• User Documentation
  • Model components and structure
  • Network parameters
  • Simulation configuration
  • Recording configuration
  • Package functions
  • NetPyNE data model (structure of instantiated network and output data)
  • Importing externally-defined cell models
  • Parameter Optimization of a Simple Neural Network Using An Evolutionary Algorithm
• Package Reference
• NetPyNE Modeling Specification v1.0
  • Overview of Specification
  • Authors and contributors
  • Network parameters