#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells, but also bits required to build detailed multi-compartmental cells , synapse models, networks/projections, and network inputs such as spike trains and pulse generators 8/x

#NeuroML provides a simulator independent standard and software tools. The idea is that researchers can use NeuroML to build their models, and these models will “just run” in any of the supported simulators. 7/x

A number of software tools are available for construction and simulation of models: #NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN etc.. These have their own features, styles, programming interfaces (APIs). 5/x

If we are to understand the _mechanisms_ underlying various brain processes, we must build data-driven biophysically detailed models of the brain. Models allow us to generate new predictions that can be tested in laboratories—closing the “#neuroscience research loop”. 4/x

We are very happy to provide a consolidated update on the #NeuroML ecosystem in our eLife paper, “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience” : doi.org/10.7554/eLif... . 1/x