Classification of borderline personality disorder based on spectral power of resting-state fMRI

Tingting Xu, Kathryn R. Cullen, Alaa Houri, Kelvin O. Lim, S. Charles Schulz, Keshab K. Parhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Borderline personality disorder (BPD) is a serious mental illness that can cause significant suffering and carries a risk of suicide. Assigning an accurate diagnosis is critical to guide treatment. Currently, the diagnosis of BPD is made exclusively through the use of clinical assessment; no objective test is available to assist with its diagnosis. Thus, it is highly desirable to explore quantitative biomarkers to better characterize this illness. In this study, we extract spectral power features from the power spectral density and cross spectral density of resting-state fMRI data, covering 20 brain regions and 5 frequency bands. Machine learning approaches are employed to select the most discriminating features to identify BPD. Following a leave-one-out cross validation procedure, the proposed approach achieves 93.55% accuracy (100% specificity and 90.48% sensitivity) in classifying 21 BPD patients from 10 healthy controls based on the top ranked features. The most discriminating features are selected from the 0.1∼0.15Hz frequency band, and are located at the left medial orbitofrontal cortex, the left thalamus, and the right rostral anterior cingulate cortex. The high classification accuracy indicates the discriminating power of the spectral power features in BPD identification. The proposed machine learning approach may be used as an objective test to assist clinical diagnosis of BPD.

Original languageEnglish (US)
Title of host publication2014 International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5036-5039
Number of pages4
Volume2014
ISBN (Electronic)9781424479290
DOIs
StatePublished - Nov 2 2014
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Publication series

Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period8/26/148/30/14

Keywords

  • borderline personality disorder (BPD)
  • classification
  • feature selection
  • functional magnetic resonance imaging (fMRI)
  • spectral power

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    Xu, T., Cullen, K. R., Houri, A., Lim, K. O., Schulz, S. C., & Parhi, K. K. (2014). Classification of borderline personality disorder based on spectral power of resting-state fMRI. In 2014 International Conference of the IEEE Engineering in Medicine and Biology Society (Vol. 2014, pp. 5036-5039). [6944756] (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6944756