Xu Tingting, Cullen Kathryn R, Mueller Bryon, Schreiner Mindy W, Lim Kelvin O, Schulz S Charles, Parhi Keshab K
Department of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA.
Department of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA.
Neuroimage Clin. 2016 Feb 18;11:302-315. doi: 10.1016/j.nicl.2016.02.006. eCollection 2016.
Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works.
边缘性人格障碍（BPD）与情感失调、自我意识受损和自伤行为等症状相关。对BPD的神经影像学研究揭示了特定脑区和连接中的结构与功能异常。然而，关于BPD中脑网络的拓扑组织却知之甚少。我们收集了20名BPD患者和10名健康对照的静息态功能磁共振成像（fMRI）数据，并通过将来自82个皮质和皮质下区域的小波滤波fMRI信号进行关联，构建了频率特异性功能脑网络。我们采用基于图论的复杂网络分析来研究脑网络的拓扑特性，并采用基于网络的统计方法来识别患者中的功能失调连接。在0.03 - 0.06Hz频段，与对照组相比，BPD患者表现出显著更大的全局网络拓扑度量，包括最大连通图组件的大小、聚类系数、小世界特性和局部效率，表明功能性脑网络的局部聚集性增加。与对照组相比，患者在网络中的几个枢纽节点处的节点中心性较低，但在几个非枢纽节点处的中心性较高。此外，在0.03 - 0.06Hz频段识别出一个相互连接的子网，该子网在患者中显示出显著更低的连通性。该子网中的连接主要是位于不同脑叶区域之间的长距离连接；并且该子网的平均连通性与增加的全局拓扑度量呈负相关。最后，关键网络度量与几个临床症状评分显示出高度相关性，并基于线性判别分析以高精度将BPD患者与健康对照进行分类。本研究中发现的异常拓扑特性和连通性可能为当前对BPD中功能性脑网络的理解增添新知识。然而，由于样本量较小的限制，本研究结果应视为探索性的，需要在未来的大样本研究中进行验证。
