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Call for community review of the NetPyNE

The purpose of this document is to solicit community feedback on NetPyNE, which was submitted to INCF for endorsement as a standard. The document contains the INCF Standards and Best Practices Committee's review of NetPyNE, and the criteria in which it was evaluated (open, FAIR, testing and implementation, governance, adoption and use, stability and support, and comparison to similar standards). For the next 60 days, we are seeking community feedback on NetPyNE.       

About NetPyNE: 
NetPyNE is an open-source Python package designed for the development, simulation, and analysis of biological neuronal networks. Built on top of the widely used NEURON simulator, NetPyNE is a high-level interface for creating, managing, and simulating complex neural network models using declarative network specification. Integrating all the major steps of the modeling workflow under a single framework, NetPyNE enables users to define their model across scales, from molecules to neurons to circuits. Included are tools for analyzing and visualizing simulation results, which have been used in the rendering of various detailed models of the motor, auditory, and somatosensory thalamocortical circuits, and of spinal cord circuits in various peer-reviewed publications. Users can get started by consulting the comprehensive documentation, tutorials, and examples which have already been generated by the growing NetPyNE community. 

Summary of Discussion: 
NetPyNE conforms to the main criteria outlined by INCF for consideration for endorsement. It is open-source and designed around the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. NetPyNE is well documented with good test coverage and is governed by a volunteer steering committee led by documented goals and standards. There are multiple forums in which NetPyNE users and developers interact. A number of tutorials are available including interactive Jupyter notebooks and YouTube videos. There is a large and growing user community with dozens of ongoing projects utilizing NetPyNE. NetPyNE is currently supported by a five-year grant from the National Institutes of Health (NIH), and we will apply to extend that grant. While there are other INCF SBPs that cover portions of the capabilities, NetPyNE is unique in multiple modeling scales (from molecules to brains) and its breadth of function (import/export, network specification, parallel simulation, variety of analyses, and optimization of parameters). 

The INCF Standards and Best Practices Committee voted to put the NetPyNE format forward for Community Review.

Authors and Affiliations

Standards and Best Practices Committee, International Neuroinformatics Coordinating Facility, December 2023

Competing Interests

No competing interests were disclosed

Letter of support (155.2 KB)



Sam Neymotin

Tue, 01/02/2024 - 19:41

Nathan Kline Institute
NetPyNE is my go-to tool for neuronal network modeling due to its impressive ability to model multiple neural scales easily with its intuitive high level specification, and its efficient code for running intensive numerical simulations on high performance compute systems.

Roman Baravalle

Thu, 01/18/2024 - 19:30

I've started using NetPyNe while in my previous lab at LSUHSC. PReviously we have developed a single compartment cell model of inhibitory cells in medial entorhinal cortex, and a random connectivity network using Brian2. After knowing the power of NetPyNe I move to using it. The translation of the model was pretty straightforward, and since then we could largely improve the model, adding spatial structure to the network, adding realistic models of excitatory cells, and letting the door open to improve both the single cell and the network models. I believe it is an awesome tool!

Craig Kelley

Tue, 01/23/2024 - 03:22

Columbia University
NetPyNE is a great tool for modeling neuronal networks and teaching computational neuroscience. It provides graphical and programming interfaces that allow people with little to no programming experience to meaningfully engage in computational neuroscience, while providing enough scalability and flexibility to be useful in research settings.

Joao Moreira

Fri, 02/09/2024 - 15:43

SUNY Downstate Health Sciences University
NetPyNE is an excellent tool for developing research in Computational Neuroscience. It allows for the development of brain models for the most basic, to highly complex networks.
Its easy-to-use descriptive syntax and the online GUI are great for getting beginners started.
The tool also offers support to the most recent features of the NEURON simulator, such as the Reaction-Diffusion toolbox, to model interactions at the molecular level.
It also supports standardized data-sharing formats, such as the SONATA guidelines.
Overall, NetPyNE is a great tool and has been fundamental in the development of my PhD work.
Competing Interests
I'm part of Dr. Dura-Bernal's lab, the developer of NetPyNE.