GSoC 2024 Project Idea 13.3 Incorporate new features into an advanced, cross-platform 3D viewer for NeuroML cells and networks (175h/350h)

NeuroML is a standard for the representation and simulation of biophysically detailed neuronal models. The primary Python package for using NeuroML, PyNeuroML (pyNeuroML — NeuroML Documentation), recently incorporated a new Vispy ( based viewer that allows interactive 3D visualisation of NeuroML networks and detailed cells. This project will extend and improve this 3D viewer to make it more interactive to allow users to gain information about the model that they are visualising, similar to features implemented in neuroConstruct ( and Open Source Brain v1 (


  1. Extend current Vispy PyNeuroML viewer to make it more interactive
    a. Show information about model features “on click” or “on selection” of entities in the visualization
    b. Give easy access to views of cells showing ion channel distributions, segment groups, etc.
    c. Include other information about network models, such as connectivity
  2. Ensure performance with Vispy viewer to allow visualisation of large scale networks.
  3. Embed Vispy viewer into NeuroMLLite-GUI (NeuroMLlite — NeuroML Documentation )
  4. Investigate options for use of Vispy viewer inside Jupyter notebooks/JupyterLab

Skill level: Mid

Required skills: writing packages/libraries in Python following best practices; knowledge of open source software development using Git/GitHub; ability to understand APIs using documentation and examples (PyNeuroML/Vispy)

Optional skills: some knowledge of computational neuroscience and modelling will be useful, but is not necessary.

Time commitment: Flexible (175/350 h)

Lead mentor: Ankur Sinha (@sanjayankur31 on GitHub,

Project website:

Backup mentors: Padraig Gleeson (@pgleeson on GitHub,

Tech keywords: Python, NeuroML, Vispy, PyQT

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Hope you are doing well.
I’m Prahalad Rajagopal, a third-year undergraduate student at SSN College of Engineering, Chennai, majoring in Computer Science. I’m writing to express my deep interest in NeuroML, as it aligns closely with my research experience. I’m very passionate about applying computational methods to study and analyze biological data, and I would love to contribute to any opportunity you might have for the same. I find computational neuroscience especially fascinating, and I’m constantly on the lookout to further expand my knowledge in this field through hands-on experiences. I would love to contribute to NeuroML and make it more accessible to the researchers out there working in this fascinating field.

Regarding my experience, I have strongly pursued my passion for model-building and prediction- I had the opportunity to develop various models such as regression, time series forecasting, as well as NLP(LLMs using langchain), as part of a climate action tool being developed by the EnerG group at the Indian Institute of Technology(IIT), Madras, to extract data from sustainability reports of companies, that are then further analyzed to predict and optimize their renewable energy footprint. My fervor for predictive modeling and computational neuroscience finds further expression in my position as research intern at the Computational Neuroscience Lab at IIT Madras, where we are working on developing a unified neural network model of the Basal Ganglia that can explain the wide variety of symptoms of Parkinson’s Disease…

Additionally, I have worked with medical signal processing, developing various new methods to model, analyze, and encrypt ECG signals, which have applications in biomedicine, computational logic, and cybersecurity. This research work has been published in the International Journal of Information Technology. I have also worked in the domain of graph theory, where I have developed a new concept called strong status domination integrity, and used it to determine the most suitable candidates for drug repositioning in a network of drugs. Most of my projects have been done majorly in Python. I have also studied Software Development using GitHub and also applied it practically on many occasions.

Please find my LinkedIn profile attached below. Should you need any more information, please do let me know and I will be more than happy to provide it to you.

Thank you for your time and consideration.


Prahalad Rajagopal

Thanks @Prahalad_Rajagopal . I’ve replied to you on the other topic :slight_smile:

PS: please do edit your post to remove your phone number from here too.

Hello! My name is Mugdha Behere. I graduated as a Computer Science Engineer in 2018 from Vellore Institute of Technology, Chennai, India. I have recently also completed my Post Graduate Diploma in Computer Science and Artificial Intelligence from Indraprastha Institute of Information Technology, Delhi, India. I wanted to express my interest in contributing to this project because the intersection of computer science and neuroscience has always fascinated me and I feel particularly intrigued by the opportunity to work on this project.

My knowledge of computational neuroscience and my expertise in this area is very limited, but, I can comfortably code in Python. You can have a look at the details of all the projects I completed as a part of my Post Graduate Diploma in Computer Science and Artificial Intelligence here: Portfolio of AI/ML/DL/NLP Projects. I have also been a participant in Hacktoberfest’23 and have hands-on work experience in Open Source Software Development using Git and GitHub. I have also worked as a Trainee Product Engineer at a fintech startup for one year and two months. There my tech stack was: Golang, React, JavaScript, Git, GitHub, and Amazon Web Services. I have worked both as a Frontend and Backend Engineer and therefore have experience writing and integrating APIs in my code. I can understand APIs using documentation and examples. My current side project topics include an AI model to detect cardiovascular diseases from medical images, an AI model to detect some Skin disorders from medical images, and an AI model to help in the detection and assessment of various brain-related disorders with the help of some types of medical images.

Because the human brain is one of the most complex yet compact creations of the world, how it functions and its study has always intrigued me and made me more and more curious. Given an opportunity to contribute to this project, I would consider myself fortunate and take it as a learning opportunity, and would be very happy to help in making the current PyNeuroML viewer more interactive and accessible. I believe participating in this project would further lead to my academic and professional development. Please contact me in case you need any more information about my background or work experience. Thank you for considering my application.

Link to my LinkedIn profile: Mugdha’s LinkedIn.

Thanks and Regards
Mugdha Behere.

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Hello @Mugdha ! Great to have you here. Please do start with the docs and let us know if you have any queries at all. There are a number of good issues in the pyNeuroML repository that you can look at if you want to tinker with the code etc.

@here: please do start working on your proposals if you haven’t already. Please note that we’ll be able to provide feedback for proposals sent to us until the end of Wednesday only. (This is becausee Friday and Monday are both holidays here in the UK, so we won’t be working from Friday all the way until Tuesday morning when your submissions are due)

Sir, I have just sent you a rough draft of my proposal. Please let me know your feedback about it so that I can improve it before the final submission.

Thanks and Regards,
Mugdha Behere.

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Sure, I’ll do that today.

Everyone @here, thanks for all your work on this. I just need to point out that we don’t know how many slots we’ll get from Google yet, so we don’t know how many projects we’ll be able to accept. Please do submit your applications, though, and we’ll try to accept as many as we can manage.

Hello! My name is Giannis Daras and I am a final year student Information and Electronic Engineering at the International Hellenic University, Greece. I am very enthusiastic about the project and have already gone through the documentation and I am currently working on some issues. I have just sent a rough draft of my proposal and I would very much appreciate your feedback to gain a deeper understanding of the requirements for a polished final submission.

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