Biophysically detailed standardized neuronal modelling with NeuroML: ecosystem updates and pre-print

Dear all,

This is to alert you to the availability of exciting new resources for the model description language NeuroML and a recently posted bioRxiv preprint on the ecosystem of NeuroML-compliant tools for data-driven modelling of neurons and circuits.

In the preprint (doi:, we provide a major update on the current scope of the NeuroML standard, the software ecosystem and describe the newly extended online resources for helping researchers incorporate NeuroML into their modelling work. We show how the modular nature and hierarchical structure of NeuroMLv2, combined with the flexibility of coding in Python, has created a powerful “building block” approach for constructing standardised models from scratch. Moreover, we illustrate how the ecosystem of NeuroML compliant tools supports users at all stages of the model development life cycle. This includes automated model validation, advanced analysis, visualisation, and sharing/reuse of models. The paper demonstrates how NeuroML unifies and standardises the diverse approaches to biologically-detailed computational modelling of neural systems, by enabling an ecosystem of interoperable tools that support the FAIR principles and promotes open, transparent and reproducible science.

In the newly updated NeuroML online resources ( we provide tutorials on how to use NeuroML to build, validate and share standardised models together with extensive documentation on this INCF approved community standard.

We hope you find these resources useful for your modelling work.

On behalf of the NeuroML community,
Ankur Sinha, Padraig Gleeson (@pgleeson) , and Angus Silver.