This repository contains the code and example data underlying our recent research on Multiscale Functional Connectivity Patterns of the Aging Brain. Our work leverages harmonized resting-state fMRI (rsfMRI) data from the multi-cohort iSTAGING study to provide new insights into brain aging.
Our research delves into the complex dynamics of brain aging, specifically focusing on how functional connectivity patterns change across different scales. We utilize advanced techniques to analyze harmonized multi-site rsfMRI data, providing a robust framework for understanding age-related alterations in brain networks.
The core contributions of our work, as reflected in the provided code, include:
- Learning Multiscale Functional Connectivity: Methods to extract and analyze functional connectivity patterns at various spatial scales.
- Harmonization of Multi-Site Data: Techniques used to address variability across different imaging sites, crucial for large-scale cohort studies like iSTAGING.
- Brain Age Prediction: Approaches to predict brain age based on functional connectivity, offering insights into accelerated or healthy aging.
Our methodological flowchart illustrates the overall process:
^ Figure: Overview of the Multiscale Brain Aging Pattern analysis workflow.
This repository supports the findings presented in the following papers:
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Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study. Zhou Z, Li H, Srinivasan D, Abdulkadir A, Nasrallah IM, Wen J, Doshi J, Erus G, Mamourian E, Bryan NR, Wolk DA, Beason-Held L, Resnick SM, Satterthwaite TD, Davatzikos C, Shou H, Fan Y; Neuroimage. 2023 Apr 1;269:119911.
- DOI: 10.1016/j.neuroimage.2023.119911
- PMID: 36731813
- PMCID: PMC9992322
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Harmonization of multi-site functional connectivity measures in tangent space improves brain age prediction. Zhou Z, Srinivasan D, Li H, Abdulkadir A, Shou H, Davatzikos C, Fan Y; ISTAGING Consortium. Proc SPIE Int Soc Opt Eng. 2022 Feb-Mar;12036:1203608.
- DOI: 10.1117/12.2611557
- PMID: 36845412
- PMCID: PMC9951555
If you use any part of this code or find our work useful in your research, please cite the relevant papers.
This repository is structured to provide the necessary code and example data for replicating our analyses. Detailed descriptions of key directories/scripts will be added here soon.
./code/: (Example: Placeholder for main analysis scripts)./data_examples/: (Example: Placeholder for small sample data)./utils/: (Example: Placeholder for utility functions)
This code was primarily developed by Dr. Zhen Zhou. While we strive for clarity and functionality, if you encounter any issues or have questions, please open an issue on this GitHub repository. We will do our best to provide support.
This project was developed within the context of the iSTAGING study, a collaborative effort across multiple institutions. We thank all collaborators and participants for their contributions.
This project has been generously supported in part by the National Institutes of Health (NIH) through grants U24NS130411 and R01EB022573. We are grateful for their support in making this research possible.