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解剖协变网络。

Networks of anatomical covariance.

机构信息

McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Canada.

出版信息

Neuroimage. 2013 Oct 15;80:489-504. doi: 10.1016/j.neuroimage.2013.05.054. Epub 2013 May 25.

Abstract

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.

摘要

功能成像或弥散加权成像技术广泛用于了解系统水平的大脑连接及其与正常神经发育、认知或大脑疾病的关系。也可以从解剖 MRI 得出的形态测量指标的协方差中提取有关大脑连接的信息。这些协方差模式可能源于对正常发育和衰老的遗传影响、相互营养增强以及与经验相关的可塑性。本综述描述了基本的方法策略、观察到的协方差的生物学基础以及在正常大脑和大脑疾病中的应用,最后对该技术的未来前景进行了综述。

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