NeuroWorkflow

A Python library for building and executing neural simulation workflows.

Features

• Node-based workflow system for neural simulations
• Type-safe connections between workflow components
• Pre-built nodes for common neural simulation tasks
• Extensible architecture for custom nodes
• Parameter optimization support for tuning simulation parameters

Current status

• The src folder contains the core functionality and sample nodes
• In the examples folder:
  • sonata_simulation.py - Basic simulation example
  • neuron_optimization.py - Example of parameter optimization (not yet completed, but running with some bugs)
  • epilepsy_rs.py - Example of epileptic resting state using the virtual brain TVB
• In the notebooks folder:
  • 01_Basic_Simulation.ipynb - Interactive example of basic simulation
  • epilepsy_rs.ipynb - Interactive example of epileptic resting state using the virtual brain TVB
  • SNNbuilder_example1.ipynb - Interactive example of Spiking Neural Network building using SNNbuilder custom nodes

Conference Presentations

This work has been presented at several conferences and workshops, receiving valuable feedback that has contributed to its ongoing development:

2025

• Winter Workshop

  • "Towards a Generic and Open Software for Building Digital Brains"
  • 📄 Poster

• Unified Theory Workshop (May 30, 2025)

  • "NeuroWorkflow: A python-based Graph Framework for Modular Brain Modeling Workflows"
  • 📄 Poster

• NEST Conference 2025 (June 17, 2025)

  • "A Graph-Based, In-Memory Workflow Library for Brain/MINDS 2.0"
  • 📄 Presentation Slides

• CNS 2025 (Computational Neuroscience Society)

  • "A Graph-Based, In-Memory Workflow Library for Brain/MINDS 2.0 – The Japan Digital Brain Project"
  • 📄 Poster

• OIST Hackathon (September 28, 2025)

  • "Building BrainModeling Workflows: A proof-of-concept framework"
  • 📄 Hackathon Material

• INCF/EBrains Summit

  • "NeuroWorkflow: A Node-Based Framework for Scalable Computational Neuroscience with AI-Ready Infrastructure"
  • 📄 Abstract

License

This project is licensed under the MIT License - see the LICENSE file for details.