Local White Matter Architecture Defines Functional Brain Dynamics

被引:1
|
作者
Choe, Yo Joong [1 ]
Balakrishnan, Sivaraman [2 ]
Singh, Aarti [3 ]
Vettel, Jean M. [4 ]
Verstynen, Timothy [5 ,6 ]
机构
[1] Kakao, Seongnam Si, South Korea
[2] Carnegie Mellon Univ, Dept Stat & Data Sci, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, Machine Learning Dept, Pittsburgh, PA 15213 USA
[4] US Army Res Lab, Aberdeen Proving Ground, MD USA
[5] Carnegie Mellon Univ, Dept Psychol, Pittsburgh, PA 15213 USA
[6] Carnegie Mellon Univ, CNBC, Pittsburgh, PA 15213 USA
关键词
local connectome; structure-function relationship; high-dimensional statistics; canonical correlation analysis; PRINCIPAL COMPONENTS; LARGEST EIGENVALUE; SELECTION;
D O I
10.1109/SMC.2018.00110
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Large bundles of myelinated axons, called white matter, anatomically connect disparate brain regions together and compose the structural core of the human connectome. We recently proposed a method of measuring the local integrity along the length of each white matter fascicle, termed the local connectome [1]. If communication efficiency is fundamentally constrained by the integrity along the entire length of a white matter bundle [2], then variability in the functional dynamics of brain networks should be associated with variability in the local connectome. We test this prediction using two statistical approaches that are capable of handling the high dimensionality of data. First, by performing statistical inference on distance-based correlations, we show that similarity in the local connectome between individuals is significantly correlated with similarity in their patterns of functional connectivity. Second, by employing variable selection using sparse canonical correlation analysis and cross-validation, we show that segments of the local connectome are predictive of certain patterns of functional brain dynamics. These results are consistent with the hypothesis that structural variability along axon bundles constrains communication between disparate brain regions.
引用
收藏
页码:595 / 602
页数:8
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