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Morphological Brain Networks of White Matter: Mapping, Evaluation, Characterization, and Application

白质 神经科学 连接体 前脑 协方差 生物 计算机科学 磁共振成像 功能连接 医学 数学 中枢神经系统 统计 放射科
作者
Junle Li,Suhui Jin,Zhen Li,Xiangli Zeng,Yuping Yang,Zhenzhen Luo,Xiaoyu Xu,Zaixu Cui,Yaou Liu,Jinhui Wang
出处
期刊:Advanced Science [Wiley]
被引量:6
标识
DOI:10.1002/advs.202400061
摘要

Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good-to-excellent test-retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co-expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co-expression, and is associated with serotonergic system-related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease.
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