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Stereo-Electro-Encephalo-Graphy SEEG With Robotic Assistance in the Presurgical Evaluation of Medical Refractory Epilepsy: A Technical Note
Published on: June 13, 2016
Sleep-related epilepsy through the lens of stereo-EEG: Clinical and research update
Lino Nobili1, Steve Alex Gibbs2, Gaia Burlando3
1Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Children's Sciences, University of Genoa, Largo Paolo Daneo 3, 16132 Genoa, Italy; Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, Full Member of the ERN EpiCARE, Via Gerolamo Gaslini 5, 16147 Genoa, Italy.
Abstract:
The complex interactions between sleep and epilepsy have drawn increasing attention, and stereo-electroencephalography (SEEG) has become a pivotal tool for investigating their underlying pathophysiological mechanisms. This review highlights key contributions from SEEG studies over the past two decades, with a focus on Sleep-Related Hypermotor Epilepsy (SHE). Considered a disorder of frontal lobe origin, SHE is now recognized as a network-based epilepsy with a broader involvement of cortical regions. Sleep instability in Non-Rapid Eye Movement (NREM) sleep, indexed by the cyclic alternating pattern (CAP), and increased bistability, emerge as critical facilitators of epileptiform discharges. In contrast, rapid eye movement (REM) sleep, particularly its phasic substate, exerts a strong suppressive effect on epileptic activity. SEEG has been instrumental in characterizing these mechanisms and identifying novel biomarkers, including cross-frequency coupling and network-level measures of cortical instability. These findings have implications not only for diagnosis and surgical targeting but also for the development of neuromodulatory and state-based therapeutic approaches. Looking forward, the integration of SEEG with advanced computational tools offers new avenues for real-time brain-state mapping and seizure risk stratification. By bridging clinical neurophysiology with systems neuroscience, SEEG provides a unique platform for advancing the understanding of epilepsy within the dynamic context of sleep.
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