Functional Connectivity Analysis: A Promising Approach to Understanding Idiopathic Childhood Epilepsy | ||||
| The Medical Journal of Cairo University | ||||
| Volume 93, Issue 03, March 2025, Page 387-398 PDF (127.21 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjcu.2025.423592 | ||||
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| Author | ||||
| MANAL M. GABER, M.D.*; AYA EWAIS T. ALI, M.Sc.*; AIDA M.S. SALEM, M.D.**; HANAN HOSNY, M.D.* and MARWA A. ELGALY, M.D.* | ||||
| The Department of Clinical Neurophysiology* and Pediatrics Department**, Faculty of Medicine, Beni-Suef University | ||||
| Abstract | ||||
| Background: Epilepsy, a common neurological disorder affecting around 50 million people globally, involves recur-rent seizures and complex brain alterations. This study focuses on childhood epilepsy, where the immature brain is especially prone to seizures due to unique developmental factors. Current diagnostic tools, like EEG and MRI, have limitations in thor-oughly assessing brain connectivity. While some studies have shown altered brain synchrony in epilepsy, they are often in-consistent due to heterogenous methodologies. Aim of Study: To comparethe brain connectivity in untreat-ed children with idiopathic epilepsy to healthy controls, using EEG coherence and phase lag as parameters for a clearer un-derstanding. Patients and Methods: This case-control study, conducted at Beni Suef University Hospital, followed the STROBE guide-lines and involved 60 participants aged 6-14. Group I included 30 newly diagnosed idiopathic childhood epilepsy cases (15 generalized and 15 focal), and Group II consisted of 30 healthy controls. Subjects, recruited retrospectively, underwent demo-graphic, clinical assessments, EEG monitoring, and functional connectivity analysis. EEG data were quantified using FFT, with coherence and phase lag measurements across frequency bands. Statistical analyses were performed using SPSS, with significance set at p<0.05. Ethical approval and informed con-sent were obtained, ensuring participant confidentiality and rights. Results: The study compares EEG coherence and phase lag in three groups generalized, focal, and control across various frequency bands. Demographic data showed no significant dif-ferences in age or sex. In the left hemisphere, the generalized group exhibited significantly lower coherence in the beta band (F3-F7) and higher coherence in the delta (F3-F7) and theta bands (P3-T5) compared to other groups. In the right hemi-sphere, the generalized group showed notably higher theta band coherence at F4-F8. Interhemispheric coherence results re-vealed significantly higher coherence in the generalized group across alpha, beta, and delta bands (F3-F4, P3-P4, T5-T6). Phase lag findings showed lower alpha and beta phase lags in the generalized group, especially in left hemisphere pairs (P3-T5) compared to focal and control groups, indicating distinct brain activity patterns across the epileptic spectrum. Conclusion: Our study identified significant connectivity differences in newly diagnosed, untreated pediatric epilepsy. Generalized epilepsy showed reduced coherence, especially in beta and delta bands, compared to focal epilepsy and controls. Findings regarding the phase lag analysis highlighted that gen-eralized epilepsy disruptedbrain connectivity more, with ab-normal interhemispheric variations observed in alpha and delta bands, emphasizing the need forfiltered frequency analyses. | ||||
| Keywords | ||||
| Epilepsy; Functional connectivity; Generalized Epilepsy; Focal Epilepsy; Coherence; Phase Lag; Idiopathic Childhood Epilepsy; EEG; Phase; Based Connectivity | ||||
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