GSoC 2022 Project Idea 9.1: Open source, cross simulator, large scale cortical models in NeuroML and PyNN (175/350 h)

An increasing number of studies are using large scale network models incorporating realistic connectivity to understand information processing in cortical structures. High performance computational resources are becoming more widely available to computational neuroscientists for this type of modelling and general purpose, well tested simulation environments such as NEURON and NEST are widely used. New, well annotated experimental data and detailed compartmental models are becoming available from the large scale brain initiatives. However, the majority of neuronal models which have been published over the past number of years are only available in simulator specific formats, illustrating a subset of features associated with the original studies.

This work will involve converting a number of published large scale network models into open, simulator independent formats such as NeuroML and PyNN and testing them across multiple simulator implementations. They will be made freely available to the community through the Open Source Brain repository ( for reuse, modification and extension.

Skills required: Python; XML; open source development; a background in computational/theoretical neuroscience and/or large scale modelling experience.


  1. Select a number of large scale cortical network models for the conversion & testing process (e.g. from ModelDB).

  2. Convert network structure and cell/synaptic properties to NeuroML and/or PyNN. Where appropriate use the simulator independent specification in LEMS to specify cell/synapse dynamics & to allow mapping to simulators. Implementing extensions to PyNN, NeuroML or other tools may be required.

  3. Make models available on the Open Source Brain repository, along with documentation and references.

Note: this project is suitable for a half-time or full-time commitment by the GSoC contributor, with the scope of the model conversion scaled as appropriate.

Mentors: Padraig Gleeson @pgleeson (lead), Ankur Sinha @sanjayankur31

Tech keywords: Python, XML, networks, modelling, simulation


Thanks @malin !

All candidates, please feel free to reach out to us here if you have any questions at all.

Hi Ankur,

I am really interested in this project. Please let me know how to proceed with this.


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Hi @Shayan_Shafquat. To get an idea of what will be involved, see the description for last year’s project here: GSoC 2021 project idea 12.1: Open source, cross simulator, large scale cortical models in NeuroML and PyNN - #4 by pgleeson.

I’ll post updated info after INCF gets approved as an organisation in a few weeks.


Advice for OSB GSoC 2022 applicants

Background reading

Read the Open Source Brain paper as well as the LEMS/NeuroML2 paper (have a look too at the libNeuroML, NeuroML v1 and PyNN papers).

Browse the OSB website, including help pages .

Have a good look at the outcomes of previous years’ OSB GSoC projects:

Joglekar et al. 2018

Mejias et al. 2016

del Molino et al. 2017


CA1 network

Thalamocortical column

Migliore et al. 2014, Olfactory Bulb 3D

Izhikevich model

Pinsky Rinzel CA3 model

Pospischil et al. 2008

Suggested activities prior to application

Sign up to GitHub if you’re not already there.

Create an OSB user account & link your GitHub account to it.

Have a look at some of the OSB projects (either on or those mentioned above), and try cloning the model and installing associated simulators locally.

Make a minor pull request to an existing OSB project on GitHub that you find interesting (e.g. small update to README/documentation).

Assemble a list of cortical models from ModelDB or from the literature to include with your application, which you think would be of benefit to the community if they were converted to NeuroML/PyNN.

If you find a project there particularly relevant, feel free to set up a personal GitHub repository for it and start adding code/documentation there.

Please share the draft of your application early to allow feedback before the application deadline!

Essential information to include in your application:

  1. The list of potential models to convert as discussed above
  2. Details on the course currently being followed and a link to the course webpage.
  3. What are your time commitments during the coding period? Please be specific about this, work/exam commitments etc. Are you planning any vacations this summer? How many classes are you taking this summer?
  4. How many hours per week will you be able to spend on this project?
  5. If you have any evidence of your coding abilities (e.g. contributions to open-source projects) and/or background in neuroscience, please let us know about it. Send links to specific public repositories showing commits by you.
  6. Details of any previous experience in computational modelling.

Hi Padraig and Ankur,

I am a graduate student in computational neuroscience. This project sounds very interesting to me, and I feel like my skill sets in both computational neuroscience and computer science make me a good fit! If I would like to do half-time commitment, how many models for conversion would be expected?


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Hi @zee, thanks for your interest. For a half time project, the applicant would need to have hands on experience in computational modelling in neuroscience to be able to hit the ground running, as well as demonstrable open source experience.

In such a case it would probably be one or two models to be converted, e.g. start with one which has begun already, e.g. and then convert another from scratch.

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Hi Padraig and Ankur,
I am a third year PhD student in computational neuroscience with the Bernstein Network of Computational Neuroscience in Germany. I work with large scale network simulations using NEST and am familiar with several other simulation platforms as well. I am very interested in applying and being a part of this project as a part-time contributor. Please let me know how I can move forward with this.
Best regards,
Swathi Anil

University of Freiburg, Germany

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Hi @SwathiAnil , please see the initial information give above and please let us know if you have any queries.

Thanks for your interest @SwathiAnil.
A nice project might be to round up more published (cortical) models in NEST, get them in to PyNN format and look at expressing them in more structured declarative formats using NeuroMLlite for example. The Potjans and Diesmann model has been well covered (athough needs some work to ensure it’s fully tested on NEST3…), and there has been some discussion around the macaque cortex model:

Note though, our preference would be for a full time project in this area.

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Thank you @pgleeson! The information here is really helpful in preparing the proposal.
The project seems interesting but unfortunately I came to know about INCF very late, nevertheless I will try my best to put up a proposal (still in draft phase) worth reading.

I have a small query, as mentioned in your post to include list of cortical models from ModelDB. I want to know it is just a list or detailed information about each model should be included and ideally how many models should be taken for the project.

Hi @rahulsonkar, thanks for your interest in the project. You don’t need to give lots of details, just say why you think the model is important to convert, and how much effort you think it would take to convert it. It’s fine to just discuss 2-3 in the proposal, the actual number will depend on how the work proceeds, but what we’re really looking for is your understanding of what the project will entail and how the NeuroML models will be useful to others in the community.

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Hi @pgleeson and @sanjayankur31,

Just wanted to say thanks for the initial information and precise answers to fellow contributors’ questions! It helped me to get a deeper insight into what the project entails.

I find this project both important and interesting. Unfortunately, I only realized about both the GSoC deadline and INCF a couple of days ago through an email. But, extremely happy to have found it at least! Advance apologies for the not so refined proposal.

Best, Anuja

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Thanks @anujanegi, glad you found it interesting.

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Hi @pgleeson @sanjayankur31,
Is this too late to sign up to contribute to this project? I also just found out about GSoC a couple days ago and unfortunately miss the official deadline.
Thank you,

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Hi @15awn00, yes, I’m afraid it’s too late for GSoC this year.

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