Evidence map›Paper›PMID 26977400›Full record

ArticleNeuroImage. Clinical2016

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

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 2 pooled it
4.5field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed, 2 syntheses or guidelines pooled it, 111 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Tingting XuDepartment of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA. Electronic address: xuxxx591@umn.edu.
Kathryn R CullenDepartment of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA. Electronic address: rega0026@umn.edu.
Bryon MuellerDepartment of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA. Electronic address: muell093@umn.edu.
Mindy W SchreinerDepartment of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA. Electronic address: westl110@umn.edu.
Kelvin O LimDepartment of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA. Electronic address: kolim@umn.edu.
S Charles SchulzDepartment of Psychiatry, University of Minnesota, 2450 Riverside Avenue South, Minneapolis, MN 55454, USA. Electronic address: scs@umn.edu.
Keshab K ParhiDepartment of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA. Electronic address: parhi@umn.edu.
University of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Magnetic Resonance ImagingRestAdultArea Under CurveBorderline Personality DisorderBrainBrain MappingFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedNerve NetNeural PathwaysOxygenPsychiatric Status Rating ScalesOxygenBorderline personality disorder (BPD)Functional brain connectivityFunctional magnetic resonance imaging (fMRI)Graph theoryNetwork analysisResting-state

Identifiers

PMID26977400
PMCPMC4782004
OpenAlexW2281380552

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.