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Revealing Developmental Regionalization of Infant Cerebral Cortex Based on Multiple Cortical Properties

机译:基于多种皮质特性揭示婴幼儿脑皮层的发育区划

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The human brain develops dynamically and regionally heteroge-neously during the first two postnatal years. Cortical developmental regionalization, i.e., the landscape of cortical heterogeneity in development, reflects the organization of underlying microstructures, which are closely related to the functional principles of the cortex. Therefore, prospecting early cortical developmental regionalization can provide neurobiologically meaningful units for precise region localization, which will advance our understanding on brain development in this critical period. However, due to the absence of dedicated computational tools and large-scale datasets, our knowledge on early cortical developmental regionalization still remains intact. To fill both the methodological and knowledge gaps, we propose to explore the cortical developmental regionalization using a novel method based on nonnegative matrix factorization (NMF), due to its ability in analyzing complex high-dimensional data by representing data using several bases in a data-driven way. Specifically, a novel multi-view NMF (MV-NMF) method is proposed, in which multiple distinct and complementary cortical properties (i.e., multiple views) are jointly considered to provide comprehensive observation of cortical regionalization process. To ensure the sparsity of the discovered regions, an orthogonal constraint defined in Stiefel manifold is imposed in our MV-NMF method. Meanwhile, a graph-induced constraint is also included to improve the compactness of the discovered regions. Capitalizing on an unprecedentedly large dataset with 1,560 longitudinal MRI scans from 887 infants, we delineate the first neurobiologically meaningful representation of early cortical regionalization, providing a valuable reference for brain development studies.
机译:在前两年后,人类大脑在前两年内动态地发展和区域异质。皮质发展区域化,即皮质异质性的景观,反映了潜在的微观结构的组织,与皮质的功能原则密切相关。因此,勘探早期皮质发展区域化可以为精确地区本土化提供神经生物学上有意义的单位,这将推进我们对本次重点期间大脑发展的理解。但是,由于缺乏专用的计算工具和大规模数据集,我们对早期皮质发展区域化的知识仍然完好无损。为了填补方法论和知识差距,我们建议利用基于非负矩阵分解(NMF)的新方法来探讨皮质发展区域化,因为它通过在数据中使用多个基础来分析复杂的高维数据的能力 - 驱动方式。具体地,提出了一种新的多视图NMF(MV-NMF)方法,其中共同认为多个不同和互补的皮质特性(即,多个视图),以提供对皮质区域化过程的综合观察。为了确保发现区域的稀疏性,以我们的MV-NMF方法施加在Stiefel歧管中定义的正交约束。同时,还包括图形诱导的约束以改善发现区域的紧凑性。通过887婴儿的1,560次纵向MRI扫描在一个前所未有的大型数据集中,我们描绘了早期皮质区域化的第一个神经生物学上有意义的代表,为脑发展研究提供了有价值的参考。

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