A toolbox for brain network construction and classification (BrainNetClass)

Zhen Zhou, Xiaobo Chen, Yu Zhang, Dan Hu, Lishan Qiao, Renping Yu, Pew Thian Yap, Gang Pan, Han Zhang, Dinggang Shen

Research output: Contribution to journalArticle

Abstract

Brain functional network has been increasingly used in understanding brain functions and diseases. While many network construction methods have been proposed, the progress in the field still largely relies on static pairwise Pearson's correlation-based functional network and group-level comparisons. We introduce a “Brain Network Construction and Classification (BrainNetClass)” toolbox to promote more advanced brain network construction methods to the filed, including some state-of-the-art methods that were recently developed to capture complex and high-order interactions among brain regions. The toolbox also integrates a well-accepted and rigorous classification framework based on brain connectome features toward individualized disease diagnosis in a hope that the advanced network modeling could boost the subsequent classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with both graphical user-friendly interfaces and a command line mode targeting cognitive neuroscientists and clinicians for promoting reliability, reproducibility, and interpretability of connectome-based, computer-aided diagnosis. It generates abundant classification-related results from network presentations to contributing features that have been largely ignored by most studies to grant users the ability of evaluating the disease diagnostic model and its robustness and generalizability. We demonstrate the effectiveness of the toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) is available at https://github.com/zzstefan/BrainNetClass.

Original languageEnglish
Pages (from-to)2808-2826
Number of pages19
JournalHuman Brain Mapping
Volume41
Issue number10
DOIs
Publication statusPublished - 2020 Jul 1
Externally publishedYes

Keywords

  • brain connectome
  • dynamic functional connectivity
  • functional connectivity
  • machine learning
  • prediction
  • sparse representation
  • toolbox

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Fingerprint Dive into the research topics of 'A toolbox for brain network construction and classification (BrainNetClass)'. Together they form a unique fingerprint.

  • Cite this

    Zhou, Z., Chen, X., Zhang, Y., Hu, D., Qiao, L., Yu, R., Yap, P. T., Pan, G., Zhang, H., & Shen, D. (2020). A toolbox for brain network construction and classification (BrainNetClass). Human Brain Mapping, 41(10), 2808-2826. https://doi.org/10.1002/hbm.24979