Resting-brain functional connectivity predicted by analytic measures of network communication
Resting-brain functional connectivity predicted by analytic measures of network communication
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DOI：
10.1073/pnas.1315529111
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发表时间：
2014-01-14
影响因子：
11.1
通讯作者：
Sporns, Olaf
中科院分区：
文献类型：
--
作者：
Goni, Joaquin;van den Heuvel, Martijn P.;Sporns, Olaf
[6]通过对人脑进行非侵入性成像测量，结构和功能连接之间的复杂关系提出了许多尚未解决的挑战和开放性问题。在这里，我们将网络通信的分析措施应用于人脑的结构连接，并探索这些措施在三个独立获取的数据集上预测静息状态功能连接的能力。我们专注于布局的最短路径在整个网络和两个通信措施搜索信息和路径的传递性，这占这些路径是如何嵌入在网络的其余部分。搜索信息是一个现有的信息需要访问或跟踪最短路径的措施，我们引入路径传递性来衡量本地绕道沿着最短路径的密度。我们发现，搜索信息和路径传递性预测连接和未连接的节点对之间的功能连接的强度。他们这样做的水平，匹配或显着超过路径长度的措施，欧几里德距离，以及神经动力学的计算模型。这种能力表明，由于大脑网络中神经元之间的相互作用而产生的动态耦合，在很大程度上受到邻近最短通信路径的更广泛的网络环境的影响。
6 The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures-search information and path transitivity-which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.