#neuroml — Public Fediverse posts

Building detailed neuronal models is hard---#NeuroML helps, but there’s still a steep learning curve. We're investigating how #LLMs can be used to create natural language interfaces to improve accessibility:

- #RAG for NeuroML: learn from and query curated information sources
- iterative LLM assisted code/model generation: modelling, validation, and simulation

More details in the post:

https://ankursinha.in/2026/01/30/building-an-ai-assistant-for-computational-modelling-with-neuroml.html

#Neuroscience #ComputationalNeuroscience #AcademicChatter #LangChain

I created a #CookieCutter project template for #ComputationalModelling using #NeuroML

(You can use it for non NeuroML models too, or modify it for your own templates)

More information here:

https://ankursinha.in/2025/09/23/a-cookiecutter-template-to-quickstart-neuroml-modelling-projects.html

#ComputationalNeuroscience #Python #Neuroscience #AcademicChatter

A lot of steps for starting new computational modelling projects in #NeuroML are repeatable and can be automated. So, I created a #Cookiecutter template to quickstart these projects. It includes boilerplate code and implements lots of other recommended/best practices in model and software development. Feedback/suggestions welcome!

https://ankursinha.in/2025/09/23/a-cookiecutter-template-to-quickstart-neuroml-modelling-projects.html

#Neuroscience #ComputationalNeuroscience #Python #Git #AcademicChatter #FAIR #OpenScience #FOSS #SoftwareDevelopment

A new version of the Open Source Brain (#OpenSourceBrain) model validation framework was just released. Please update your installations:

```
pip install -U OSBModelValidation
```

https://github.com/OpenSourceBrain/osb-model-validation/releases/tag/v0.3.9

#OMV is a #Python package that allows you to validate your #NeuroML models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:

https://github.com/OpenSourceBrain/.github/blob/main/testsheet/README.md

#FAIR #ComputationalNeuroscience #Neuroscience #ModelValidation

A new release of PyNeuroML is available, please update your installations:

https://github.com/NeuroML/pyNeuroML/releases

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

#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter

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

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

The #NeuroML ecosystem for standardized multi-scale modeling in neuroscience

#ComputationalNeuroscience #Neuroscience #Modelling #ComputationalModelling #AcademicChatter

New feature coming to PyNeuroML that allows easy visualisation of ion channels on multi-compartmental cells:

https://github.com/NeuroML/pyNeuroML/pull/242

Here's an example summary of the cells of the Human L2/3 cortical micro-circuit:

https://github.com/sanjayankur31/Human-L2-3-Cortical-Microcircuit/blob/feat/neuroml/NeuroML2/cell_plots/Readme.md

#NeuroML #Neuroscience #ComputationalNeuroscience

Please boost:

Please join us for the next open #NeuroML editorial team meeting on March 30 at 1600 UTC:

More information (and meeting link) in the agenda document here:

https://hackmd.io/drmamFWvSMibBA-SiVPWGg

#Neuroscience #OpenScience #ComputationalNeuroscience #INCF

Registration for the Computational Modeling in Biology Network (#COMBINE) #HARMONY meeting is open:

https://co.mbine.org/events/

HARMONY 2023 will be hosted by Herbert Sauro and the Center for Reproducible Biomedical Modeling at the University of Washington, Seattle, WA. It is going to be organized primarily as an in-person meeting, with individual breakout sessions responsible for enabling remote participation as needed.

#Standardisation #NeuroML #ComputationalNeuroscience #ComputationalBiology

NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010941

#NeuroML #ComputationalNeuroscience #Standardisation