Skip to main content

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:

Download files

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

Source Distribution

brainx-2026.7.9.tar.gz (13.9 kB view details)

Uploaded Source

Built Distribution

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

brainx-2026.7.9-py3-none-any.whl (13.9 kB view details)

Uploaded Python 3

File details

Details for the file brainx-2026.7.9.tar.gz.

File metadata

  • Download URL: brainx-2026.7.9.tar.gz
  • Upload date:
  • Size: 13.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for brainx-2026.7.9.tar.gz
Algorithm Hash digest
SHA256 9360f76d175bdd26d80ac7d699c3df443b2df424b1f17dfa073eb6011b212929
MD5 e08a05320a379700865d257310ee0486
BLAKE2b-256 bf5a79abdaa9e00d7a67f0bed4302fb6f7bd59be8020644c6921534add7881e1

See more details on using hashes here.

File details

Details for the file brainx-2026.7.9-py3-none-any.whl.

File metadata

  • Download URL: brainx-2026.7.9-py3-none-any.whl
  • Upload date:
  • Size: 13.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for brainx-2026.7.9-py3-none-any.whl
Algorithm Hash digest
SHA256 0d6b1f12424a2b22f349fe1dd34a019299de2cdb2795a751004d9ac02995c30a
MD5 bd601a2cef707690eee7f22045e548db
BLAKE2b-256 af190616d1d8617d96122dd647d61de238d3377a9c5f0ee0b1e3c8757b608610

See more details on using hashes here.

Release history Release notifications | RSS feed

2026.8.18

2 files

This release

2026.7.9 This release

2 files

2026.6.29

2 files

2026.6.19

2 files

2026.6.18

2 files

2026.6.14

2 files

2026.6.11

2 files

2026.6.8

2 files

2026.3.12

2 files

2026.1.31

2 files

2026.1.27

2 files

2026.1.22

2 files

2026.1.21

2 files

2026.1.19

2 files

2026.1.18

2 files

2026.1.17

2 files

2026.1.16

2 files

2025.12.27

2 files

2025.12.26

2 files

2025.12.25

2 files

2025.12.2

2 files

2025.10.20

2 files

2025.10.16

2 files

2025.10.13

2 files

2025.10.8

2 files

2025.9.15

2 files

2025.9.13

2 files

2025.8.31

1 file

2025.8.1

1 file

2025.7.31

1 file

2025.7.30

1 file

2025.7.29

1 file

2025.7.22

1 file

2025.7.14

1 file

2025.7.13

1 file

2025.6.14

1 file

2025.6.2

1 file

2025.5.31

1 file

2025.5.22

1 file

2025.5.11

1 file

2025.5.5

1 file

2025.5.4

1 file

Supported by

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