ACTION Software

Introduction

The Augmentation and Computation Toolbox for braIn netwOrk aNalysis (ACTION) is an open-source software package that is designed for fast facilitation and easy customization of functional MRI based brain connectivity network/graph analysis. [GitHub][Manual]

The ACTION software consists of four major components:

  • FMRI Data Augmentation: Designed for fMRI time series augmentation and graph-based data augmentation
  • Brain Network Construction: Designed for brain functional connectivity network construction and visualization
  • Brain Network Feature Extraction: Designed for feature extraction based on brain functional connectivity networks
  • Artificial Intelligence Model Construction: Designed for conventional machine learning model construction, deep learning model construction (with models pre-trained on 3,800+ fMRI scans in a self-supervised learning manner), and federated learning for multi-site fMRI analysis

User Instruction

  • Please register online (see the following) as a new user. Then, you will receive the link to download the software.
  • Please use the institutional email corresponding to your organization.
  • Before your registration, please print & sign “Agreements of ACTION.pdf” (digital signature is not acceptable) and upload the signed agreement in the following form:

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Register for ACTION Software

Accepted file types: pdf, Max. file size: 1 MB.
Full name of the applicant:(Required)
Institutional Email address of the applicant:(Required)

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How to Cite

If you use this toolbox or benchmark in your research, please cite this project:

@misc{action,
  author = {Fang, Yuqi and Zhang, Junhao and Wang, Linmin 
            and Wang, Qianqian and Liu, Mingxia},  
  title = {ACTION-Software-for-Functional-MRI-Analysis},  
  year = {2024},  
  publisher = {GitHub},
  journal = {GitHub Repository},  
  howpublished = {\url{https://github.com/mxliu/ACTION-Software-for-Functional-MRI-Analysis}},  
}

About Us

The ACTION software is developed by the Machine Intelligence in Biomedical Computing Lab at the University of North Carolina at Chapel Hill. If you have any problem with our code or have some suggestions, please feel free to contact us: