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Abstract #1036

Structural Gradients of the Developing Brain Connectome

Juhyun Lee1, Khoi Minh Huynh2,3, Hoyt Patrick Taylor1, Jiarui Mao4, Guoye Lin2,3, Sahar Ahmad2,3, and Pew-Thian Yap2,3
1Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 2Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 3Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, 4Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

Synopsis

Keywords: Normal Development, Data Analysis, Structural gradients, morphological similarity network, early brain development

Motivation: While functional gradients are widely studied, the development of structural gradients—especially during the first five years, a period of major structural changes—remains largely unexplored.

Goal(s): We aim to establish a method to derive structural gradients and track their development over time.

Approach: We calculate the structural connectivity network using tractography and cortical microstructure features, then apply diffusion embedding to analyze network gradients.

Results: The first three principal axes of the structural gradients resemble functional gradients but also reveal unique spatial patterns.

Impact: For the first time at the vertex level, we map the development of neocortical structural gradients during the first five years of life, enabling fine-scale study of the functional-structural connectome relationship.

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Keywords