Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients

Jui Hong Chien; Deng Shan Shiau; J. Chris Sackellares; Jonathan J. Halford; Kevin M. Kelly; Panos M. Pardalos

doi:10.1007/978-1-4614-2107-8_4

Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients

Jui Hong Chien, Deng Shan Shiau, J. Chris Sackellares, Jonathan J. Halford, Kevin M. Kelly, Panos M. Pardalos

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Electroencephalography (EEG) is a technology for measuring brain neuronal activity and is used to investigate various pathological conditions of the brain. A brain can be viewed as a complex network of neurons. A brain functional network represents quantitative interactions among EEG channels and can be expressed as a graph. Graph theoretical analysis, therefore, can be applied to offer a broader scope to inspect the global functional network characteristics of epileptic brains and can reveal the existence of small-world network structure. In this study, we inspected the interhemispheric power asymmetry (IHPA) of interictal scalp EEG signals recorded from patients with epilepsy and psychogenic nonepileptic events and found significant differences between the two patient groups. Specifically, the degrees of IHPA in the two patient groups differed in signals from the frontal lobe regions in the delta, theta, alpha, and gamma frequency bands.

Original language	English (US)
Title of host publication	Springer Optimization and Its Applications
Publisher	Springer
Pages	57-77
Number of pages	21
DOIs	https://doi.org/10.1007/978-1-4614-2107-8_4
State	Published - 2012
Externally published	Yes

Publication series

Name	Springer Optimization and Its Applications
Volume	65
ISSN (Print)	1931-6828
ISSN (Electronic)	1931-6836

Keywords

Functional Network
Power Asymmetry
Symmetric Pair
Temporal Lobe Epilepsy
Visual Working Memory

ASJC Scopus subject areas

Control and Optimization

Access to Document

10.1007/978-1-4614-2107-8_4

Cite this

Chien, J. H., Shiau, D. S., Sackellares, J. C., Halford, J. J., Kelly, K. M., & Pardalos, P. M. (2012). Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients. In Springer Optimization and Its Applications (pp. 57-77). (Springer Optimization and Its Applications; Vol. 65). Springer. https://doi.org/10.1007/978-1-4614-2107-8_4

Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients. / Chien, Jui Hong; Shiau, Deng Shan; Sackellares, J. Chris et al.
Springer Optimization and Its Applications. Springer, 2012. p. 57-77 (Springer Optimization and Its Applications; Vol. 65).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Chien, JH, Shiau, DS, Sackellares, JC, Halford, JJ, Kelly, KM & Pardalos, PM 2012, Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients. in Springer Optimization and Its Applications. Springer Optimization and Its Applications, vol. 65, Springer, pp. 57-77. https://doi.org/10.1007/978-1-4614-2107-8_4

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Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Nonepileptic Seizure and Complex Partial Seizure Patients

Abstract

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