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Related Experiment Video

Updated: Sep 14, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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A new gradient-based method for analyzing brain white matter fiber geometry.

Jiaolong Qin1, Weihong Dong2, Huangjing Ni3

  • 1Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science & Engineering, Nanjing University of Science and Technology, Nanjing, China.

Journal of Neuroscience Methods
|July 20, 2025
PubMed
Summary
This summary is machine-generated.

A new Large-scale Gradient Feature (LsGF) metric offers robust white matter (WM) geometry analysis, revealing distinct patterns in brain morphology and gender differences. Consistent tractography methods are essential for reliable results.

Keywords:
Gender differenceGeometry analysisGradient featureTractographyWhite matter

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Brain Anatomy

Background:

  • Accurate analysis of white matter (WM) fiber geometry is vital for understanding brain organization and function.
  • Current methods for analyzing WM fiber geometry have limitations.

Purpose of the Study:

  • Introduce a novel Large-scale Gradient Feature (LsGF) metric for quantifying white matter fiber geometry.
  • Evaluate the stability and application of the LsGF metric in analyzing brain morphology and gender disparities.

Main Methods:

  • Developed the Large-scale Gradient Feature (LsGF) metric to measure the rate of change in tangent direction along fiber streamlines.
  • Assessed LsGF map stability using intra-class correlation coefficients (ICC) concerning streamline count and tractography algorithms.
  • Applied LsGF to investigate gender differences in white matter morphology and compared its sensitivity with fiber length maps.

Main Results:

  • LsGF demonstrated high robustness to variations in streamline count (99% ICCs > 0.8).
  • LsGF showed significant dependency on the tractography algorithm used (less than 60% ICCs > 0.6).
  • Analysis revealed distinct geometric patterns in various brain regions, including the thalamus, internal capsule, and cerebellum, associated with gender dimorphism.

Conclusions:

  • The LsGF metric provides voxel-wise quantitative streamline analysis across the entire brain.
  • LsGF complements fiber length metrics in characterizing both microstructural complexity and macroscale architecture.
  • Consistent tractography methods are crucial for obtaining reliable LsGF-based results in white matter analysis.