GSoC 2025 Project #22 HNN Projects :: Develop Python API for multi-network simulations in Human Neocortical Neurosolver (350h)

GSoC
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Mentors: Austin Soplata <austin_soplata@brown.edu>, Dylan S. Daniels <dylan_s_daniels@alumni.brown.edu>, Nicholas Tolley

Skill level: Intermediate

Required Skills: Experience with Python programming, experience with Git version control, experience with Pytest or software testing (optional), experience in neuroscience data analysis (optional)

Time commitment: Full time (350 hours)

Forum for discussion

About: Human Neocortical Neurosolver (HNN) is a software for interpreting the neural origin of macroscale magneto-/electro-encephalography (MEG/EEG) data using biophysically-detailed microcircuit simulations. HNN-core can be run through a user-friendly graphical user interface (GUI) or through a Python API as a library.

Resources:

Aims: The current codebase for HNN-core assumes that only one model Network is being simulated at a time. However, there is strong scientific motivation for simulating multiple distinct cortical networks which interact with each other (such as primary sensory cortex versus an association cortex). HNN-core needs the ability to create multiple distinct networks, create connections both within and between networks, and simulate them all. Subgoals include:

  • Develop the Network API to be able to add long-range connections to other Network objects.
  • Develop the fundamental simulation API to support multiple networks, including Dipole etc. output tied to each individual network.
  • Develop existing or new analysis and plotting functions for analyzing the output of multiple networks, including inter-network communication

Website: https://hnn.brown.edu/

Tech keywords: Python, computational neuroscience, open-source, simulation, neuron

2 Likes
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hi @asoplata ,@ Nicholas Tolley ,@ Dylan S. Daniels
this side dikshant jha ,I am a machine learning enthusiasts and would like to contribute in this project #22 of HNN-CORE ;which demands to develop an api to achieve the following funtionality .I do have a decent idea of hnn-core so ,It would be great if we can discuss regarding this and can you provide me some references of neuroscience data analysis in order to become comfortable with them .

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Hi,

I’m Peicheng Li, an sophemore student majoring in Computer Science & Mathematics at the University of Minnesota. I’m really excited about the opportunity to contribute to the HNN-core project, specifically the development of the Python API for multi-network simulations.

With experience in Python, Git, and computational neuroscience, I’m eager to help expand the HNN-core to support multiple cortical networks and inter-network communication. I’d love to learn more about how the simulation API will be structured and how we can ensure smooth integration between networks.

Looking forward to contributing!
Email: li003347@umn.edu