# Surface-Based Fiber Tracking and Modeling Techniques for Mapping the Superficial White Matter Connectome with Diffusion MRI

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2024 · $541,242

## Abstract

Abstract
The superficial white matter (SWM) lies directly beneath the cortex and contains the short association fibers, or
U-fibers, connecting neighboring gyri. The SWM contains around twice as many fiber connections as the deep
white matter (DWM) and plays a crucial role in brain development, aging, and various brain disorders. Existing
connectome imaging research based on diffusion MRI (dMRI), however, mostly focuses on the connections of
long fiber bundles in the DWM even though tremendous advances have been made in human connectome
imaging with much improved spatial and angular resolution. In this proposed renewal of our R01 project (NIBIB
R01EB022744), we will conduct systematic development of novel computational tools to fill major technical gaps
in current SWM research. Our project will provide fundamentally novel solutions to many of the current
challenges in SWM connectome research by developing surface-based tools for fiber tracking, atlas construction,
and personalized analysis. We will also develop novel personalized dMRI harmonization methods with a
particular focus on accounting for the variable cortical anatomy. These developments will for the first time provide
dedicated tools for modeling SWM connectome with greatly improved robustness and accuracy. There are three
specific aims in our project: 1. Development of novel surface-based fiber tracking and filtering algorithms for the
modeling of superficial white matter connectivity. 2. Development of surface-based U-fiber atlases and
personalized SWM connectivity analysis. 3. Development of personalized diffusion MRI harmonization tools with
improved consistency in cortical anatomy. Rigorous validations of our novel surface-based U-fiber tracking and
modeling methods will be performed on high-resolution MRI of post-mortem brains, in vivo intracranial neural
recordings from surgically implanted electrodes in patients with epilepsy, and their application in multiple large-
scale connectome imaging datasets (n>5000). All software tools and atlases developed in this project will be
publicly shared, which will allow brain imaging researchers to augment their current connectome models with U-
fibers in SWM and more completely map human brain connectomes for the detection of their alterations in
various brain disorders.

## Key facts

- **NIH application ID:** 10835006
- **Project number:** 5R01EB022744-06
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Yonggang Shi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $541,242
- **Award type:** 5
- **Project period:** 2016-09-22 → 2028-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10835006

## Citation

> US National Institutes of Health, RePORTER application 10835006, Surface-Based Fiber Tracking and Modeling Techniques for Mapping the Superficial White Matter Connectome with Diffusion MRI (5R01EB022744-06). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10835006. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*