Gadelkarim Johnson J, Ajilore Olusola, Schonfeld Dan, Zhan Liang, Thompson Paul M, Feusner Jamie D, Kumar Anand, Altshuler Lori L, Leow Alex D
Electrical and Computer Engineering department, University of Illinois at Chicago, Chicago, Illinois; Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois.
Hum Brain Mapp. 2014 May;35(5):2253-64. doi: 10.1002/hbm.22324. Epub 2013 Jun 25.
In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling.
在本文中,我们提出了与路径长度相关的社区估计(PLACE),这是一个用于研究节点级社区结构的综合框架。与著名的Q模块度指标不同,PLACE使用一种新的指标Ψ(PL),该指标衡量社区间路径长度与社区内路径长度之间的差异。我们比较了使用这两种指标生成的人类健康脑网络中的社区结构,并认为Ψ(PL)可能具有理论优势。PLACE包括以下内容:(1)使用自上而下的层次二叉树提取社区结构,其中每个分叉处的一个分支表示在该级别形成一个社区的节点集合,(2)构建和评估平均组社区结构,以及(3)检测组间社区的节点级变化。我们应用PLACE并研究了从25名处于双相情感障碍I型缓解期的受试者与25名性别和年龄匹配的健康对照样本中获得的脑结构网络。结果显示,在默认模式网络的后部区域存在社区结构差异,双相情感障碍组表现出左右解耦。