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Updated: Aug 23, 2025
Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
Published on: May 23, 2017
Building a tissue-unbiased brain template of fiber orientation distribution and tractography with multimodal
Jinglei Lv1,2, Rui Zeng1,2, Mai Phuong Ho1
1School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales, Australia.
Purpose:
Brain templates provide an essential standard space for statistical analysis of brain structure and function. Despite recent advances, diffusion MRI still lacks a template of fiber orientation distribution (FOD) and tractography that is unbiased for both white and gray matter. Therefore, we aim to build up a set of such templates for better white-matter analysis and joint structural and functional analysis.
Methods:
We have developed a multimodal registration method to leverage the complementary information captured by T1 -weighted, T2 -weighted, and diffusion MRI, so that a coherent transformation is generated to register FODs into a common space and average them into a template. Consequently, the anatomically constrained fiber-tracking method was applied to the FOD template to generate a tractography template. Fiber-centered functional connectivity analysis was then performed as an example of the benefits of such an unbiased template.
Results:
Our FOD template preserves fine structural details in white matter and also, importantly, clear folding patterns in the cortex and good contrast in the subcortex. Quantitatively, our templates show better individual-template agreement at the whole-brain scale and segmentation scale. The tractography template aligns well with the gray matter, which led to fiber-centered functional connectivity showing high cross-group consistency.
Conclusion:
We have proposed a novel methodology for building a tissue-unbiased FOD and anatomically constrained tractography template based on multimodal registration. Our templates provide a standard space and statistical platform for not only white-matter analysis but also joint structural and functional analysis, therefore filling an important gap in multimodal neuroimage analysis.
