Title: Open source, cross simulator, large scale cortical models in NeuroML and PyNN
Description:
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 (https://v2.opensourcebrain.org) for reuse, modification and extension.
Aims/objectives:
Select a number of large scale cortical network models for the conversion & testing process (e.g. from ModelDB).
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.
Make models available on the Open Source Brain repository, along with documentation and references.
Skill level: Junior+/mid
Required skills: Python; XML; open source development; a background in computational/theoretical neuroscience and/or large scale modelling experience.
Time commitment: Flexible (175/350 h)
Lead mentor: Padraig Gleeson (@pgleeson on GitHub)
Hey, I’m Manish. An open source advocate/enthusiast, a web developer and a sophomore pursuing my bachelor’s in CSE. I’d love to work on this project as I love to explore different fields in tech and apply my knowledge to solve real world problems with like minded peers. Looking forward to contribute to this valuable project and learn so many amazing things along the way.
Hello @pgleeson and @sanjayankur31, I am Arya and I am studying Artificial Intelligence and Machine Learning. I am very intrigued by this problem statement and I am confident that the knowledge and skills I gained from last year’s Computational Neuroscience track in Neuromatch and my course curriculum, will help me better contribute to this project.
I have gone through the links given above. Please let me know what I should do next to start contributing to this project.
Thank you!
Hi @Arya_Itkyal : have you been able to go through the tutorials and create/visualise/run simulations in NeuroML? If not, that’s where you should start—understanding how NeuroML works is critical to converting models into the NeuroML standard format.
Hi @Aman123lug , please go through the tutorials at https://docs.neuroml.org and see how that goes. (please remove your phone number from your comment too—it isn’t needed, and we don’t want you getting spammed by cold callers)
thank you so much for this for any queries any other mailing list is available ? I saw there is Gitter platform should i need to join this? I learned from documentation there are alot of packages to work with neuro ML I choose pyNeuroML for NeuroML. sir i have a doubt i currently reading the docs i am not able to find where the implementation of NeuroML with pyNeuroML can you provide me refrence sir!
Hi @Aman123lug : we don’t really want you to delve into the NeuroML code at this point. The project is about converting published models to the NeuroML format. So you should learn how to use NeuroML, not how to develop it. This is why we suggest you please go through all the tutorials in the documentation
Please see Padraig’s post that I’ve linked to above and go through it—it requires you to do some research into models out there that you may want to work on.
Sir, i was reading the last year idea which is related to this project.
After changing the model format with Neuro ML format need to make model available on Open Source Brain repository, along with documentation and references. I read the docs i want more deep dive into this. and also i want to contribute in this project gsoc 23. i am writing proposal for this i will send you as soon as possible.
How many issues need to solve for selection for this project i read all the documentation and i am writing the proposal for this project. any small contribution matters for selection.
Hey! I’m Arnab, I’m studying computer science student at the University of Edinburgh. I’ve been lurking on this forum and learning for the past few weeks since this project caught my attention.
Although I wasn’t sure this was the best way I could allocate my time and contribute to OSB. I’ve gone through the previous year’s projects and have understood the procedure but it seems daunting to take it on as a contribution before asking the mentors. What’s the best way I could spend my time while contributing and making myself a good fit for this project?
Create an OSB user account & link your GitHub account to it.
Have a look at some of the OSB projects (either on http://www.opensourcebrain.org/projects 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:
The list of potential models to convert as discussed above
Details on the course currently being followed and a link to the course webpage.
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?
How many hours per week will you be able to spend on this project?
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.
Details of any previous experience in computational modelling.