Elkholy, M. (2023). Effect of interictal epileptiform discharges on EEG coherence and phase lag in patients with focal epilepsy. test, 4(2), 7-18. doi: 10.21608/ejmr.2023.198481.1361
Mostafa Mahmoud Elkholy. "Effect of interictal epileptiform discharges on EEG coherence and phase lag in patients with focal epilepsy". test, 4, 2, 2023, 7-18. doi: 10.21608/ejmr.2023.198481.1361
Elkholy, M. (2023). 'Effect of interictal epileptiform discharges on EEG coherence and phase lag in patients with focal epilepsy', test, 4(2), pp. 7-18. doi: 10.21608/ejmr.2023.198481.1361
Elkholy, M. Effect of interictal epileptiform discharges on EEG coherence and phase lag in patients with focal epilepsy. test, 2023; 4(2): 7-18. doi: 10.21608/ejmr.2023.198481.1361

Effect of interictal epileptiform discharges on EEG coherence and phase lag in patients with focal epilepsy

Egyptian Journal of Medical Research
Volume 4, Issue 2, April 2023, Pages 7-18    PDF (385.13 K)
Document Type: Original Article
DOI: 10.21608/ejmr.2023.198481.1361
Author
Mostafa Mahmoud Elkholy*
Department of Clinical Neurophysiology (Neuro-Diagnostic and Research Center), Faculty of Medicine, Beni-Suef University, Egypt
Abstract
Background and Aim: Epilepsy is a network disease, and its pathological networks could be related to the interictal epileptiform discharges (IEDs). The aim is to explore the effect of IEDs on EEG functional connectivity metrics (coherence and phase lag degree) in patients with focal epilepsy. Methods: The study included 14 patients with focal epilepsy and 14 matched healthy controls. EEGs of the patients were segmented into two-second epochs: a. epochs containing IEDs, b. resting epochs with no IEDs. The selected epochs were analyzed using Fast Fourier Transform to yield four frequency bands: Delta, Theta, Alpha and Beta. Coherence and phase lag degree were computed between the EEG electrodes and were assessed at the intra-hemispheric (frontal-parietal and frontal-temporal) and inter-hemispheric (frontal, temporal and parietal) levels. The frequency of IEDs was calculated from a sixty-minute EEG recording session. Results: Patients had significant IED-related connectivity disruption in the form of higher phase lag degree at both intra-hemispheric and inter-hemispheric levels of the following frequencies: delta (P=0.022) and theta (P=0.041) at the left frontal-parietal, beta at the left frontal-temporal (P=0.009), theta at the inter-hemispheric frontal (P=0.003), delta (P=0.006), and beta (P=0.041) frequency bands at the inter-hemispheric temporal level. The frequency of IEDs correlated with phase lag degree of theta (P=0.004, r= 0.720) frequency over the right frontal-parietal level. Conclusions: Patients with focal epilepsy showed dynamic IED-related changes in EEG functional connectivity mainly demonstrated by increase of phase lag degree of delta and theta frequency over the frontal and temporal regions.
Keywords
Functional connectivity; Electroencephalography; Phase lag; Focal epilepsy; Epileptic networks
References
  1. Bernhardt BC, Bonilha L, Gross DW. Network analysis for a network disorder: the emerging role of graph theory in the study of epilepsy. Epilepsy Behav. 2015;50:162-70.
  2. Carboni M, De Stefano P, Vorderwülbecke BJ, Tourbier S, Mullier E, Rubega M, et al. Abnormal directed connectivity of resting state networks in focal epilepsy. Neuroimage  Clin. 2020;27:102336.
  3. Choi H-S, Chung YG, Choi SA, Ahn S, Kim H, Yoon S, et al. Electroencephalographic resting-state functional connectivity of benign epilepsy with centrotemporal spikes. J Clin Neurol. 2019;15(2):211.
  4. Adebimpe A, Aarabi A, Bourel-Ponchel E, Mahmoudzadeh M, Wallois F. EEG resting state functional connectivity analysis in children with benign epilepsy with centrotemporal spikes. Front Neurosci. 2016;10:143.
  5. Kaiser DA, Sterman MB. Automatic artifact detection, overlapping windows, and state transitions. J Neurother. 2001;4(3):85-92.
  6. Otnes RK, Enochson L. Digital Time Series Analysis John Wiley and Sons. New York. 1972.
  7. Oppenheim AV, Schafer RW. From frequency to quefrency: A history of the cepstrum. IEEE Signal Process Mag. 2004;21(5):95-106.
  8. Kaminski MJ, Blinowska KJ. A new method of the description of the information flow in the brain structures. Biol Cybern. 1991;65(3):203-10.
  9. Iannotti GR, Grouiller F, Centeno M, Carmichael DW, Abela E, Wiest R, et al. Epileptic networks are strongly connected with and without the effects of interictal discharges. Epilepsia. 2016;57(7):1086-96.
  10. Adebimpe A, Aarabi A, Bourel-Ponchel E, Mahmoudzadeh M, Wallois F. Functional brain dysfunction in patients with benign childhood epilepsy as revealed by graph theory. PLoS One. 2015;10(10):e0139228.
  11. Li R, Ji G-J, Yu Y, Yu Y, Ding M-P, Tang Y-L, et al. Epileptic discharge related functional connectivity within and between networks in benign epilepsy with centrotemporal spikes. Int J Neural Syst. 2017;27(07):1750018.
  12. Bettus G, Ranjeva J-P, Wendling F, Bénar CG, Confort-Gouny S, Régis J, et al. Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations. PloS one. 2011;6(5):e20071.
  13. Hu DK, Mower A, Shrey DW, Lopour BA. Effect of interictal epileptiform discharges on EEG-based functional connectivity networks. Clin Neurophysiol. 2020;131(5):1087-98.
  14. van Diessen E, Zweiphenning WJEM, Jansen FE, Stam CJ, Braun KPJ, Otte WM. Brain network organization in focal epilepsy: a systematic review and meta-analysis. PLoS One. 2014;9(12):e114606.
Statistics
Article View: 361
PDF Download: 272