Skip to main content

Ecosystem for Brain Simulation.

Project description

Brain Simulation Ecosystem (BrainX)

PyPI version License Documentation Continuous Integration

Header image of Brain Modeling Ecosystem.

Overview

The BrainX ecosystem provides a comprehensive framework for brain simulation and modeling. It provides tools and libraries for researchers to model, simulate, train, and analyze neural systems at different scales.

Core components in this ecosystem includes:

  • BrainPy: Modeling of point neuron-based spiking neural networks (SNNs), comes from Prof. Si Wu's lab at Peking University.

  • BrainUnit: Comprehensive physical units and unit-aware mathematical system for brain dynamics.

  • BrainCell: Intuitive, parallel, and efficient simulation for biologically detailed brain cell modeling. Collaborated with Prof. Songting Li's lab at Shanghai Jiao Tong University.

  • BrainMass: Whole-brain modeling with differentiable neural mass models.

  • BrainState: State-based IR compilation for efficient simulation of brain models on CPUs, GPUs, and TPUs.

  • BrainTaichi: The first-generation framework for customizing event-driven operators based on Taichi Lang syntax.

  • BrainEvent: Enabling event-driven computations in brain dynamics.

  • BrainTrace: Eligibility trace-based online learning for brain dynamics: $O(N)$ complexity for SNNs and $O(N^2)$ for RNN computations.

  • BrainTools: Commonly used tools for brain dynamics programming, for example checkpointing.

  • PINNx: Physics-informed neural networks for scientific machine learning in JAX.

  • More components may be added in the future.

Installation

The ecosystem can be installed with the following command:

pip install BrainX -U

This command installs the core package and pins specific versions of the component projects known to work together, ensuring compatibility based on integration tests.

On CPU platforms, the following command can be used to install the ecosystem with all components:

pip install BrainX[cpu] -U

On GPU platforms, the following command can be used to install the ecosystem with all components:

pip install BrainX[cuda12] -U

pip install BrainX[cuda13] -U

On TPU platforms, the following command can be used to install the ecosystem with all components:

pip install BrainX[tpu] -U

For development, you might want to clone the repository and install it in editable mode:

git clone https://github.com/chaobrain/brainx.git
cd brainx
pip install -e .

Documentation

For detailed documentation, tutorials, and examples, visit our Documentation Portal.

Contributing

We welcome contributions from the community! Please see our Contributing Guidelines for more information on how to get involved.

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for details.

Citation

If you use the BrainX Ecosystem in your research, please cite it appropriately. Refer to the citation guide on our documentation portal.

Support

If you have questions, encounter issues, or need support, please:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

brainx-2026.6.14.tar.gz (8.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

brainx-2026.6.14-py3-none-any.whl (8.9 kB view details)

Uploaded Python 3

File details

Details for the file brainx-2026.6.14.tar.gz.

File metadata

  • Download URL: brainx-2026.6.14.tar.gz
  • Upload date:
  • Size: 8.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for brainx-2026.6.14.tar.gz
Algorithm Hash digest
SHA256 60c6c72c52a5623abd01305f7e777a315598018b36e14857c2f9888677771afd
MD5 68a037e7e95e85934cf6ae359dac1f06
BLAKE2b-256 3477591e66c07221c84ebbdba5564aa74abf35e1617958cb9eea657fa89d6baf

See more details on using hashes here.

File details

Details for the file brainx-2026.6.14-py3-none-any.whl.

File metadata

  • Download URL: brainx-2026.6.14-py3-none-any.whl
  • Upload date:
  • Size: 8.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for brainx-2026.6.14-py3-none-any.whl
Algorithm Hash digest
SHA256 45f26e88760d25440b893205660330194da40493fff0eec35fcd955ebd2afe6e
MD5 3513b0c23f7a5c384ec9fe31966e645b
BLAKE2b-256 ba31137bf6897749a21bb76094f05f61543e66e1644b15a43ab980308a289408

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page