A new release of #PyNeuroML is available. Please update to get the latest fixes and features. #NeuroML #ComputationalModelling #ComputationalNeuroscience

```
pip install --upgrade pyneuroml
```

In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:

https://github.com/NeuralEnsemble/libNeuroML/pull/208/files

#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR

#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.

https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code

CC #AcademicChatter

Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9

#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

#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

You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x

#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.

#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

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

#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

Update on what I did from weeks 27-36 this year:

https://ankursinha.in/2024/09/06/week-27-36-update.html

#NeuroML #ComputationalNeuroscience #Fedora #OpenSourceBrain #GoogleSummerOfCode #ComputationalModelling #AcademicChatter #FOSS #OpenScience

You can also get it from #NeuroML-DB here:

https://neuroml-db.org/model_info?model_id=NMLCL000073

#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:

https://v1.opensourcebrain.org/projects/l5bpyrcellhayetal2011

and on #GitHub here: https://github.com/OpenSourceBrain/L5bPyrCellHayEtAl2011

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

Learn more about NeuroML here: https://docs.neuroml.org

The latest release of #PyNeuroML, 1.3.9, includes `pynml-swc2nml` for conversion of #SWC neuronal morphologies to #NeuroML. Also accessible via the API:

https://pyneuroml.readthedocs.io/en/development/pyneuroml.swc.html#pyneuroml.swc.ExportNML.convert_swc_to_neuroml

Install it using pip:

https://pypi.org/project/pyNeuroML/1.3.9/

#NeuroML #ComputationalNeuroscience #NeuronalModelling #FAIR #Neuroscience #AcademicChatter

Join us for the #NeuroML tutorial at #CNS2024Natal in July to learn how to construct and simulate standardised data driven biophysically detailed models of neuronal networks:

https://docs.neuroml.org/Events/202407-CNS2024.html

#ComputationalNeuroscience #Neuroscience #Tutorials #AcademicChatter

Finally got around to restarting my blogging activities: Just regular updates for now:

Week 19 update
https://ankursinha.in/2024/05/10/week-19-update.html
#Fedora #ComputationalNeuroscience #NeuroML #GSoC #Neuroscience

How's Friday going folks? I've been working on standardising the #Purkinje Cell model from Zang et al 2018 to #NeuroML. Exported the morphology already, on to the converting the individual Ion channels next.

You can use the converted bits from here: https://github.com/sanjayankur31/ZangEtAl2018/tree/development

#Neuroscience #ComputationalNeuroscience #Modelling #ComputationalModelling #Cerebellum

Version 1.2.0 of #pyNeuroML, the #Python package for working with #NeuroML models, has been released, brings more bugfixes and better support for #SBML

https://github.com/NeuroML/pyNeuroML/releases/tag/v1.2.0

#NeuroML #ComputationalNeuroscience #Neuroscience #Standardisation #FAIR

Sharing from birdsite:

https://x.com/NeuroML/status/1735322341192638543?s=20

Announcing a comprehensive review of the current state of the model development language and associated tools: The #NeuroML ecosystem for standardized multi-scale modeling in #neuroscience

#ComputationalNeuroscience

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:
https://www.biorxiv.org/content/10.1101/2023.12.07.570537v1

#ComputationalBiology #Neuroscience #ComputationalNeuroscience #OpenScience #Science