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Evolution of Graph Theory in Dynamic Functional Connectivity for Lateralization of Temporal Lobe Epilepsy Publisher Pubmed



Fallahi A1 ; Baniasad F2 ; Lotfi N3 ; Mirbagheri M3 ; Mohammadimobarakeh N2 ; Tapak L1 ; Hashemifesharaki SS4 ; Pooyan M5 ; Mehvarihabibabadi J6 ; Nazemzadeh MR7
Authors
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Authors Affiliations
  1. 1. Biomedical Engineering Department, Hamedan University of Technology, Hamedan, Iran
  2. 2. Biomedical Engineering Department, Shahed University, Tehran, Iran
  3. 3. University of Zanjan, Zanjan, Iran
  4. 4. Pars Advanced Medical Research Center, Pars Hospital, Tehran, Iran
  5. 5. Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Isfahan Neuroscience Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  7. 7. Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran, Iran

Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS Published:2019


Abstract

Resting-state functional magnetic resonance imaging (rsfMRI) has described the functional architecture of the human brain in the absence of any task or stimulus. Since the functional connectivity (FC), has non-stationary nature, it is evidenced to be varying over time. Using dynamic functional connectivity, six graph theoretical characteristics were measured and compared between left and right temporal lobe epilepsy (TLE). We also obtain a trend for each characteristic in the time course of experiments. The results demonstrated that the static connectivity analysis failed to fully separate the left and right TLE patients for some characteristics, whereby the dynamic analysis has been shown capable of identifying the laterality. Furthermore, the results suggest that the temporal trend of some graph theoretical characteristics can be exploited as a novel marker for TLE laterality. © 2019 IEEE.