Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

Tingting Xu, Kathryn R. Cullen, Bryon Mueller, Mindy W. Schreiner, Kelvin O. Lim, S. Charles Schulz, Keshab K. Parhi

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)302-315
Number of pages14
JournalNeuroImage: Clinical
Volume11
DOIs
StatePublished - 2016

Bibliographical note

Funding Information:
This study was partially supported by an investigator-initiated grant awarded to Dr. Schulz from AstraZeneca ( D1443C00097/IRUSQUET0454 ) to conduct a clinical trial in adults with borderline personality disorder. A subset of the patients in the clinical trial also participated in this neuroimaging study. These funds supported recruitment and clinical assessment of the patients. AstraZeneca did not contribute to the study design; the collection, analysis or interpretation of data; the writing of the report; or the decision to submit the article for publication. The neuroimaging costs of the study were supported by internal funds through the University of Minnesota . T. Xu was supported by the Interdisciplinary Doctoral Fellowship and the Doctoral Dissertation Fellowship at the University of Minnesota.

Keywords

  • Borderline personality disorder (BPD)
  • Functional brain connectivity
  • Functional magnetic resonance imaging (fMRI)
  • Graph theory
  • Network analysis
  • Resting-state

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