Characterization of ictal/non-ictal EEG patterns and Neuronal Networks in Childhood Absence Epilepsy
Childhood absence epilepsy (CAE) is one of the most common pediatric epilepsy syndromes found in children. It is associated with distinct seizure semiology and clear electroencephalographic (EEG) features. In CAE patients, differentiating EEG ictal and non-ictal generalised spikes and waves discharges (GSWDs) is however difficult, since these events have an identical appearance. The differentiation of these two events is very important in a clinical setting as it has a direct effect on diagnosis and management strategies of patients. This study focuses on differentiating ictal and non-ictal discharges at sensor and source level using only surface EEG. Twelve CAE patients having both ictal and non-ictal discharges were selected for this study. For all levels of analysis, frequency ranges of 1-30 Hz containing four important frequency bands (delta, theta, alpha and beta) were used. At sensor level, spectral analysis and functional connectivity (FC) based on imaginary part of coherency, were used to evaluate the spectral changes and channel connectivity at the surface, respectively. At source level, the onset zone for ictal and non-ictal discharges were reconstructed using the eLORETA algorithm, and FC was used again to analyse the neuronal networks. Furthermore, we gave a detailed mathematical background of the EEG, forward and inverse problem, along with the mathematical foundation for the eLORETA algorithm. Additionally, for the first time we prove the correctness of the eLORETA algorithm based on the correct regularization problem. At sensor level, ictal discharges showed significantly higher power compared to non-ictal discharges, followed by FC depicting a desynchronization of channel connections (weaker connectivity) for ictal discharges. At source level, a fascinating observation was that ictal and non-ictal discharges have the same source or onset zone in the brain. However, ictal discharges had a stronger source power compared to non-ictal discharges. FC at source level revealed that the connectivity between certain brain regions and the seeds of interest (source maximum and thalamus) was stronger for ictal discharges, compared to non-ictal discharges. This study clearly shows the significant differences between ictal and non-ictal discharges at sensor and source level using only surface EEG. This study would be a great interest to clinicians, since it could be the potential foundation for future diagnostics research for CAE patients.
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