Orthogonalized Minimum Spanning Tree and Their Application for Human Brain Mapping - Paper Review

Explore a comprehensive video review of the paper "Topological Filtering of Dynamic Functional Brain Networks Unfolds Informative Chronnectomics: A Novel Data-Driven Thresholding Scheme Based on Orthogonal Minimal Spanning Trees (OMSTs)." Delve into the challenges of thresholding brain connectivity graphs and discover how Orthogonalized Minimum Spanning Trees (OMST) offer a data-driven solution. Learn about the problem formulation, OMST methodology, research methods, and results. Gain insights from a code walkthrough of the original and cleaned implementations. Understand how OMST optimizes between network global efficiency and wiring cost preservation, outperforming other thresholding techniques in distinguishing individual subjects from large EEG and fMRI datasets. Discover the potential of OMST as a standardized tool for neuroimaging and multimodal studies in neuroscience and physics research.

- Introduction :
- Thresholding Problem Formulation:
- Orthogonalized Minimal Spanning Tree:
- Methods:
- Results:
- Code Walkthrough:
- Conclusion :