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#neuroml

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Ankur Sinha "FranciscoD"

#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.

Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.

docs.neuroml.org/NeuroMLOrg/Ou

CC #AcademicChatter

docs.neuroml.orgOutreach and training — NeuroML Documentation
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Ankur Sinha "FranciscoD"

#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x

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Ankur Sinha "FranciscoD"

#NeuroML supports all stages of the modelling life-cycle with a vast ecosystem of software tools: creating (#pyNeuroML, #neuroConstruct, #NEURON, #NetPyNE, #PyNN, #N2A), validating (pyNeuroML, #OMV, #SciUnit), visualising (pyNeuroML, #OSB, #NeuroML-DB), simulating (#NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN), model fitting/optimisation (#NeuroTune, #BluePyOpt, NetPyNE), sharing and reusing of models (OSB, NeuroML-DB, #NeuroMorpho.org). 7/x

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Ankur Sinha "FranciscoD"

#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.

Figure showing different model components provided by NeuroML
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Ankur Sinha "FranciscoD"

#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. So, researchers only need to learn how to use NeuroML and then choose what simulator they want to run their model in. NeuroML-compliant tools will take care of the rest, “under the hood”. 4/x

Schematic showing how one would use Python and NeuroML to build and simulate models.
Public
Ankur Sinha "FranciscoD"

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/eLife.95135.3

#NeuroML is a standard and software ecosystem for data-driven biophysically detailed #ComputationalModelling endorsed by the @INCF and CoMBINE, and includes a large community of users and software developers.

#Neuroscience #ComputationalNeuroscience #ComputationalModelling 1/x

An image with the NeuroML logo in the middle and the different steps of the model building life cycle around it: create, validate, visualize, simulate, fit, share, re-use.
Public
Ankur Sinha "FranciscoD"

#Standardized #NeuroML model of the day (2024-09-11):

Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties, Hay et al 2011

See if on #OpenSourceBrain here:

v1.opensourcebrain.org/project

and on #GitHub here: github.com/OpenSourceBrain/L5b

#ComputationalNeuroscience #ComputationalModelling #Neuroscience #Cortex #Layer5B #FAIR #OpenScience #AcademicChatter

Learn more about NeuroML here: docs.neuroml.org

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Mike Hucka

A long time ago, I coauthored the first version of an exchange format for computational models in neuroscience. This first version of NeuroML was later almost entirely revised by collaborators (for the better!), and its users and the community they created has continued to grow thanks to the hard work of those collaborators. They have a new preprint summarizing the #NeuroML ecosystem:
biorxiv.org/content/10.1101/20

#ComputationalBiology#Neuroscience#ComputationalNeuroscience
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