Estimating time-varying brain connectivity networks from functional MRI time series
Estimating time-varying brain connectivity networks from functional MRI time series
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DOI：
10.1016/j.neuroimage.2014.07.033
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发表时间：
2014-12-01
期刊：
影响因子：
5.7
通讯作者：
Montana, Giovanni
中科院分区：
文献类型：
--
作者：
Monti, Ricardo Pio;Hellyer, Peter;Montana, Giovanni
神经成像的前沿是对人类大脑功能结构的理解。在大多数应用程序中，假设功能网络是平稳的，从而导致在整个时间过程中估计单个网络。然而，最近的研究结果表明，即使在休息时，大脑区域之间的连接也是高度不稳定的。因此，需要新的脑成像方法，全面考虑功能网络的动态特性。在这项工作中，我们提出了平滑增量图形套索估计（SINGLE）算法，该算法从fMRI数据估计动态脑网络。我们将提出的算法应用于24名健康患者执行选择反应任务的功能性MRI数据，以证明伴随简单但注意力要求高的认知任务的网络结构的动态变化。利用图论的方法，我们发现右下额回和右下顶叶的性质随任务的变化而动态变化。这些区域经常被认为在认知控制中起着重要作用。我们的研究结果表明，这两个区域在认知要求高的任务中对注意力和执行功能起着关键作用，并且可能是调节其他大脑区域之间平衡的基础。(C) 2014年由Elsevier Inc.出版。
At the forefront of neuroimaging is the understanding of the functional architecture of the human brain. Inmost applications functional networks are assumed to be stationary, resulting in a single network estimated for the entire time course. However recent results suggest that the connectivity between brain regions is highly non-stationary even at rest. As a result, there is a need for new brain imaging methodologies that comprehensively account for the dynamic nature of functional networks. In this work we propose the Smooth Incremental Graphical Lasso Estimation ( SINGLE) algorithm which estimates dynamic brain networks from fMRI data. We apply the proposed algorithm to functional MRI data from 24 healthy patients performing a Choice Reaction Task to demonstrate the dynamic changes in network structure that accompany a simple but attentionally demanding cognitive task. Using graph theoretic measures we show that the properties of the Right Inferior Frontal Gyrus and the Right Inferior Parietal lobe dynamically change with the task. These regions are frequently reported as playing an important role in cognitive control. Our results suggest that both these regions play a key role in the attention and executive function during cognitively demanding tasks and may be fundamental in regulating the balance between other brain regions. (C) 2014 Published by Elsevier Inc.