The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.

The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery.
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DOI:
10.1016/j.neuron.2014.10.015
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发表时间:
2014-10-22
期刊:
影响因子:
16.2
通讯作者:
Adali, Tulay
Adali, Tulay
中科院分区:
医学1区
文献类型:
--
作者:
Calhoun, Vince D.;Miller, Robyn;Pearlson, Godfrey;Adali, Tulay

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近年来,人们对功能性磁共振成像(fMRI)的兴趣迅速增长,超越了简单的扫描长度平均值,并进入了捕捉连接性随时间变化的方法。在这个透视图中,我们使用术语“时间连接”来描述允许耦合的动态视图的度量。在时间连接组中,耦合是指大脑区域之间可能随时间变化的相关或相互通知的活动水平,其空间特性也可能随时间演变。我们主要集中在我们的小组开发的多元方法,并审查了一些方法,重点是矩阵分解,如主成分分析和独立成分分析。我们还讨论了这些方法提供的潜力,以改善表征和理解的大脑功能。有许多方法学方向需要进一步发展,但时间连接组方法已经显示出对健康和患病大脑的研究的巨大希望。
Recent years have witnessed a rapid growth of interest in moving functional magnetic resonance imaging (fMRI) beyond simple scan-length averages and into approaches that capture time-varying properties of connectivity. In this Perspective we use the term “chronnectome” to describe metrics that allow a dynamic view of coupling. In the chronnectome, coupling refers to possibly time-varying levels of correlated or mutually informed activity between brain regions whose spatial properties may also be temporally evolving. We primarily focus on multivariate approaches developed in our group and review a number of approaches with an emphasis on matrix decompositions such as principle component analysis and independent component analysis. We also discuss the potential these approaches offer to improve characterization and understanding of brain function. There are a number of methodological directions that need to be developed further, but chronnectome approaches already show great promise for the study of both the healthy and the diseased brain.
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