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

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...

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Autores principales: Xu, Tingting, Cullen, Kathryn R., Mueller, Bryon, Schreiner, Mindy W., Lim, Kelvin O., Schulz, S. Charles, Parhi, Keshab K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782004/
https://www.ncbi.nlm.nih.gov/pubmed/26977400
http://dx.doi.org/10.1016/j.nicl.2016.02.006
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author Xu, Tingting
Cullen, Kathryn R.
Mueller, Bryon
Schreiner, Mindy W.
Lim, Kelvin O.
Schulz, S. Charles
Parhi, Keshab K.
author_facet Xu, Tingting
Cullen, Kathryn R.
Mueller, Bryon
Schreiner, Mindy W.
Lim, Kelvin O.
Schulz, S. Charles
Parhi, Keshab K.
author_sort Xu, Tingting
collection PubMed
description 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.
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spelling pubmed-47820042016-03-14 Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI Xu, Tingting Cullen, Kathryn R. Mueller, Bryon Schreiner, Mindy W. Lim, Kelvin O. Schulz, S. Charles Parhi, Keshab K. Neuroimage Clin Regular Article 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. Elsevier 2016-02-18 /pmc/articles/PMC4782004/ /pubmed/26977400 http://dx.doi.org/10.1016/j.nicl.2016.02.006 Text en © 2016 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Xu, Tingting
Cullen, Kathryn R.
Mueller, Bryon
Schreiner, Mindy W.
Lim, Kelvin O.
Schulz, S. Charles
Parhi, Keshab K.
Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title_full Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title_fullStr Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title_full_unstemmed Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title_short Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI
title_sort network analysis of functional brain connectivity in borderline personality disorder using resting-state fmri
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782004/
https://www.ncbi.nlm.nih.gov/pubmed/26977400
http://dx.doi.org/10.1016/j.nicl.2016.02.006
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