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默认模式网络组件的功能连接性:相关性、反相关性和因果关系。

Functional connectivity of default mode network components: correlation, anticorrelation, and causality.

作者信息

Uddin Lucina Q, Kelly A M, Biswal Bharat B, Castellanos F Xavier, Milham Michael P

机构信息

The Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience, New York University Child Study Center, New York, New York 10016, USA.

出版信息

Hum Brain Mapp. 2009 Feb;30(2):625-37. doi: 10.1002/hbm.20531.

Abstract

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here, we examined functional differentiation within the DMN, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the DMN are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated.

摘要

默认模式网络(DMN)以腹内侧前额叶皮质(vmPFC)和后扣带回皮质(PCC)为基础,在静息状态下比在执行外部定向认知任务时表现出更高的代谢活性。最近的研究表明,DMN与参与任务执行的各种任务积极网络之间的竞争关系在大脑中以这些网络自发波动之间强烈的负相关(反相关)形式内在地表现出来。大多数神经影像学研究将DMN表征为一个同质网络,因此很少有研究考察DMN各组成部分对这种竞争关系的不同贡献。在这里,我们研究了DMN内的功能分化,重点是理解它与其他网络之间的竞争关系。我们对静息状态数据使用种子相关方法来评估这两个区域及其反相关网络之间功能连接的差异。虽然vmPFC和PCC种子的正相关网络在很大程度上重叠,但每个的反相关网络都显示出显著差异。vmPFC的活动对顶叶视觉空间和时间注意网络的活动有负向预测作用,而PCC的活动对基于前额叶的运动控制回路的活动有负向预测作用。格兰杰因果分析表明,vmPFC和PCC对其反相关网络的影响大于反方向的影响,这表明这两个默认模式节点可能直接调节任务积极网络中的活动。因此,构成DMN的两个主要节点在与其相互作用的特定脑系统方面存在差异,这表明该网络内的异质性比通常认为的更大。

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