Networks of anatomical covariance

被引：319

作者：

Evans, Alan C. ^{[1
]}

机构：

[1] McGill Univ, Montreal Neurol Inst, McConnell Brain Imaging Ctr, Montreal, PQ H3A 2B4, Canada

来源：

NEUROIMAGE | 2013年 / 80卷

关键词：

Connectivity; Cortical thickness; Structural covariance; GRAPH-THEORETICAL ANALYSIS; DIFFUSION-WEIGHTED MRI; CORTICAL SURFACE-AREA; AXON DIAMETER DISTRIBUTION; STRUCTURAL BRAIN NETWORKS; AUTOMATED 3-D EXTRACTION; WHITE-MATTER INTEGRITY; FUNCTIONAL CONNECTIVITY; SMALL-WORLD; CEREBRAL-CORTEX;

D O I：

10.1016/j.neuroimage.2013.05.054

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique. (C) 2013 Elsevier Inc. All rights reserved.

引用

页码：489 / 504

页数：16

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