BrainX Ecosystem
Research papers

Papers about BrainX.

Core publications describing the BrainX framework and its scientific foundations — spanning differentiable brain simulation, just-in-time compilation for neural dynamics, physical-unit-aware AI computing, and online learning in spiking networks. Together these works define the methods and design principles behind the BrainX ecosystem.

Nature Comm · 2026

Model-agnostic linear-memory online learning in spiking neural networks

BrainTrace Read paper →
Nature Comm · 2025

Integrating physical units into high-performance AI-driven scientific computing

BrainUnit Read paper →
eLife · 2023

BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming

BrainPy Read paper →
ICLR · 2024

A differentiable brain simulator bridging brain simulation and brain-inspired computing

BrainPy Read paper →
ICML · 2024

A Differentiable Approach to Multi-scale Brain Modeling

Differentiable Simulation Read paper →
ICONIP · 2021

A just-in-time compilation approach for neural dynamics simulation

BrainPy Read paper →
How to cite

Citing BrainX.

If your work uses or builds on BrainX, please cite the canonical papers below. For finer attribution to a specific ecosystem package (brainstate, braincell, brainmass, …), see that package's CITATION.cff on GitHub.

  1. eLife · 2023 · Framework paper

    Wang, C., et al. (2023). BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming. eLife, 12, e86365. https://doi.org/10.7554/eLife.86365 

    @article{wang2023brainpy,
  title={BrainPy, a flexible, integrative, efficient, and extensible framework for general-purpose brain dynamics programming},
  author={Wang, Chaoming and Zhang, Tianqiu and Chen, Xiaoyu and He, Sichao and Li, Shangyang and Wu, Si},
  journal={elife},
  volume={12},
  pages={e86365},
  year={2023},
  publisher={eLife Sciences Publications, Ltd}
  doi={10.7554/eLife.86365}
}
  2. ICLR · 2024 · Differentiable simulation

    Wang, C., et al. (2024). A differentiable brain simulator bridging brain simulation and brain-inspired computing. In International Conference on Learning Representations. openreview.net/forum?id=AU2gS9ut61 

    @inproceedings{wang2024differentiable,
  title={A differentiable brain simulator bridging brain simulation and brain-inspired computing},
  author={Wang, Chaoming and Zhang, Tianqiu and He, Sichao and Gu, Hongyaoxing and Li, Shangyang and Wu, Si},
  booktitle={International Conference on Learning Representations},
  volume={2024},
  pages={54834--54864},
  year={2024},
  url={https://openreview.net/forum?id=AU2gS9ut61}
}
  3. Nature Comm · 2025 · BrainUnit

    Wang, C., et al. (2025). Integrating physical units into high-performance AI-driven scientific computing. Nature Communications. https://doi.org/10.1038/s41467-025-58626-4 

    @article{wang2025brainunit,
  title={Integrating physical units into high-performance AI-driven scientific computing},
  author={Wang, Chaoming and He, Sichao and Luo, Shouwei and Huan, Yuxiang and Wu, Si},
  journal={Nature Communications},
  volume={16},
  number={1},
  pages={3609},
  year={2025},
  publisher={Nature Publishing Group UK London}
  doi={10.1038/s41467-025-58626-4}
}
  4. Nature Comm · 2026 · BrainTrace

    Wang, C., et al. (2026). Model-agnostic linear-memory online learning in spiking neural networks. Nature Communications. https://doi.org/10.1038/s41467-026-68453-w 

    @article{wang2026braintrace,
  title={Model-agnostic linear-memory online learning in spiking neural networks},
  author={Wang, Chaoming and Dong, Xingsi and Ji, Zilong and Xiao, Mingqing and Jiang, Jiedong and Liu, Xiao and Huan, Yuxiang and Wu, Si},
  journal={Nature Communications},
  year={2026},
  publisher={Nature Publishing Group UK London}
  doi={10.1038/s41467-026-68453-w}
}