Cognitive relevance of the community structure of the human brain functional coactivation network
Cognitive relevance of the community structure of the human brain functional coactivation network
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DOI：
10.1073/pnas.1220826110
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发表时间：
2013-07-09
影响因子：
11.1
通讯作者：
Bullmore, Edward T.
中科院分区：
文献类型：
--
作者：
Crossley, Nicolas A.;Mechelli, Andrea;Bullmore, Edward T.
人们对人脑功能网络的复杂拓扑结构越来越感兴趣，通常使用静息状态功能MRI （fMRI）进行测量。在此，我们对使用功能磁共振成像或PET测量任务相关激活的大量原始文献（1985-2010年共1600项研究）进行了荟萃分析。我们估计了每对638个大脑区域在实验任务中激活模式的相似性（Jaccard指数）。利用该连续共激活矩阵构建加权图来表征网络拓扑结构。共激活网络是模块化的，枕叶、中央和默认模式模块主要由特定的认知领域（分别是感知、行动和情绪）共同激活。它还包括一个丰富的中枢节点俱乐部，位于顶叶和前额叶皮层，经常长距离连接，这些节点被各种各样的实验任务共同激活。通过研究未激活节点和未激活节点之间的边的拓扑作用，我们发现这种竞争性相互作用在不同模块中的节点之间或激活的富俱乐部节点和未激活的外围节点之间最为频繁。共激活网络的许多方面与静息状态fMRI数据得出的连通性网络收敛（n = 27，健康志愿者）；虽然连通性网络连接更为简约，但在一些枢纽的解剖位置上存在差异。我们得出结论，人类大脑网络的社区结构与认知功能有关。失活可能在根据认知需求灵活地重新配置网络中发挥作用，改变模块之间以及外围和中心富裕俱乐部之间的整合。
There is growing interest in the complex topology of human brain functional networks, often measured using resting-state functional MRI (fMRI). Here, we used a meta-analysis of the large primary literature that used fMRI or PET to measure task-related activation (> 1,600 studies; 1985-2010). We estimated the similarity (Jaccard index) of the activation patterns across experimental tasks between each pair of 638 brain regions. This continuous coactivation matrix was used to build a weighted graph to characterize network topology. The coactivation network was modular, with occipital, central, and default-mode modules predominantly coactivated by specific cognitive domains (perception, action, and emotion, respectively). It also included a rich club of hub nodes, located in parietal and prefrontal cortex and often connected over long distances, which were coactivated by a diverse range of experimental tasks. Investigating the topological role of edges between a deactivated and an activated node, we found that such competitive interactions were most frequent between nodes in different modules or between an activated rich-club node and a deactivated peripheral node. Many aspects of the coactivation network were convergent with a connectivity network derived from resting state fMRI data (n = 27, healthy volunteers); although the connectivity network was more parsimoniously connected and differed in the anatomical locations of some hubs. We conclude that the community structure of human brain networks is relevant to cognitive function. Deactivations may play a role in flexible reconfiguration of the network according to cognitive demand, varying the integration between modules, and between the periphery and a central rich club.