A framework for quantifying node-level community structure group differences in brain connectivity networks.
A framework for quantifying node-level community structure group differences in brain connectivity networks.
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DOI：
10.1007/978-3-642-33418-4_25
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Leow, Alex D.
中科院分区：
文献类型：
--
作者：
GadElkarim, Johnson J.;Schonfeld, Dan;Ajilore, Olusola;Zhan, Liang;Zhang, Aifeng F.;Feusner, Jamie D.;Thompson, Paul M.;Simon, Tony J.;Kumar, Anand;Leow, Alex D.
我们提出了一个框架，用于量化群体之间的节点级社区结构，使用来自dti -神经束成像的解剖脑网络。为了构建社区，我们通过最大化两个度量来计算分层二叉树：众所周知的模块化度量(Q)和一个衡量社区间和社区内路径长度差异的新度量。在节点水平上评估了生成树之间群落结构的变化，并开发了一个统计框架来检测两组群落结构之间的局部差异。我们将这一框架应用于42名重度抑郁症患者和47名健康对照者的样本。结果表明，默认模式网络中的几个节点（包括与自我意识相关的双侧楔前叶）在组间表现出显著差异。这些发现与之前的文献报道一致，表明抑郁症患者有更高程度的反刍性自我反省。
We propose a framework for quantifying node-level community structures between groups using anatomical brain networks derived from DTI-tractography. To construct communities, we computed hierarchical binary trees by maximizing two metrics: the well-known modularity metric (Q), and a novel metric that measures the difference between inter-community and intra-community path lengths. Changes in community structures on the nodal level were assessed between generated trees and a statistical framework was developed to detect local differences between two groups of community structures. We applied this framework to a sample of 42 subjects with major depression and 47 healthy controls. Results showed that several nodes (including the bilateral precuneus, which have been linked to self-awareness) within the default mode network exhibited significant differences between groups. These findings are consistent with those reported in previous literature, suggesting a higher degree of ruminative self-reflections in depression.
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DOI：
10.1523/jneurosci.1929-08.2008
发表时间：
2008-09-10
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Bassett DS;Bullmore E;Verchinski BA;Mattay VS;Weinberger DR;Meyer-Lindenberg A
通讯作者：
Meyer-Lindenberg A
影响因子：
3.5
作者：
Meunier D;Lambiotte R;Fornito A;Ersche KD;Bullmore ET
通讯作者：
Bullmore ET
影响因子：
5.7
作者：
Alexander-Bloch, Aaron;Lambiotte, Renaud;Roberts, Ben;Giedd, Jay;Gogtay, Nitin;Bullmore, Edward T.
通讯作者：
Bullmore, Edward T.
影响因子：
5.3
作者：
van den Heuvel, Martijn P.;Mandl, Rene C. W.;Pol, Hilleke E. Hulshoff
通讯作者：
Pol, Hilleke E. Hulshoff
DOI：
10.1103/physreve.84.016111
发表时间：
2011-07
期刊：
Physical review. E, Statistical, nonlinear, and soft matter physics
影响因子：
--
作者：
Steen M;Hayasaka S;Joyce K;Laurienti P
通讯作者：
Laurienti P