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” : https://doi.org/10.7554/eLife.95135.3 . 1/x
Comments
Log in with your Bluesky account to leave a comment
#NeuroML is a standard and software ecosystem for data-driven biophysically detailed #ComputationalModelling endorsed by the @incforg.bsky.social and #CoMBINE, and includes a large community of users and software developers. 2/x
While our main source of information on the brain—how/what/where/why/when it does things—are “wet” experiments, models and theory are necessary to combine the many specific, isolated findings that experiments generate into coherent theories of brain function. 3/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
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
This is great but it also means that researchers need to learn each of these individually to use them. It also means that tools and models developed for one don’t necessarily work for others and need to be manually converted. This is often a non-trivial task and limits model reuse. 6/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
Comments