Identification and classification of hubs in brain networks.
Identification and classification of hubs in brain networks.
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DOI：
10.1371/journal.pone.0001049
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发表时间：
2007-10-17
期刊：
影响因子：
3.7
通讯作者：
Kötter R
中科院分区：
文献类型：
--
作者：
Sporns O;Honey CJ;Kötter R
哺乳动物大脑皮层的大脑区域由一个复杂的纤维束网络连接起来。这些区域间网络已经从节点度、结构基序、路径长度和聚类系数分布等方面进行了分析。枢纽区域在信息流协调中起着重要的作用，本文对枢纽区域的识别和分类进行了研究。我们通过检查猫和猕猴大脑皮层内所有区域的基序指纹和中心性指数来识别中心并表征其网络贡献。Motif指纹捕获了局部连接模式的统计数据，而中心性的测量则识别了位于网络各部分之间的许多最短路径上的区域。在猫和猕猴网络中，我们发现程度、基序参与、中间中心性和接近中心性的组合可以可靠地识别中心区域，其中许多区域以前被功能分类为多感官或多模态。然后，我们将中心分类为省级（集群内）中心或连接器（集群间）中心，并进一步表明，从网络中分离出每种类型的中心对小世界指数产生相反的影响。我们的研究提出了一种基于多个网络属性的大脑网络中假定枢纽区域的识别和分类方法，并绘制了这些区域的结构嵌入与其功能角色之间的潜在联系。
Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles.
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影响因子：
5.3
作者：
Achard, S;Salvador, R;Bullmore, ET
通讯作者：
Bullmore, ET
影响因子：
4.3
作者：
Achard S;Bullmore E
通讯作者：
Bullmore E
影响因子：
3.7
作者：
Hagmann, Patric;Kurant, Maciej;Gigandet, Xavier;Thiran, Patrick;Wedeen, Van J.;Meuli, Reto;Thiran, Jean-Philippe
通讯作者：
Thiran, Jean-Philippe
影响因子：
3.7
作者：
Felleman, Daniel J.;Van Essen, David C.
通讯作者：
Van Essen, David C.
DOI：
10.1098/rstb.1996.0129
发表时间：
1996-10-29
期刊：
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES
影响因子：
--
作者：
GoldmanRakic, PS
通讯作者：
GoldmanRakic, PS