Innovations In Clinical Neuroscience

Current Trends in Epilepsy 2015

A peer-reviewed, evidence-based journal for clinicians in the field of neuroscience

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conjunction with colleagues at Rush University Medical Center have identified the waveform during video EEG monitoring of 129 patients evaluated for epilepsy at institutions in Florida and Illinois. Dubbed the "texting rhythm," the waveform is induced by active text messaging and produces a reproducible, stimulus-evoked, generalized frontocentral monomorphic burst of 5-6 Hz theta. The waveform was not observed during voice calls or during non-texting activities involving cognition, speech/language or movement in one arm of the study. According to the authors, the waveform may reflect the neural coding observed during non-auditory communication, and its significance should be assessed in further studies. In a third study, (abstract 3.092) researchers from Johns Hopkins University use data acquired in real time to train a machine learning algorithm for seizure detection. Few technologies can reliably warn patients of an impending seizure due to wide variations in seizure onset patterns and the locations where seizures originate and spread in the brain. Modern seizure detection technologies rely on machine learning algorithms to sort EEG features into seizure or non-seizure events, but the clinical data needed to build reliable, patient-specific algorithms can be hard to come by. The researchers circumvent this challenge by constantly retraining the machine learning algorithm with the patient's own brain patterns. Using intracranial recordings from patients with focal epilepsy who were undergoing presurgical evaluation, they describe an algorithm capable of detecting previously unnoticed seizures between 0 to 4 seconds after onset, even when those seizures had novel ictal signatures. The ability of the algorithm to adapt to changing brain activity often allows for the detection of seizure onset before clinical symptoms appear. A fourth study (abstract 2.084) describes a carbon nanotube-based strategy for enhancing the power of the Responsive Neurostimulation System (RNS), the only FDA-approved intracerebral neuromodulation therapy to date for patients with drug-resistant focal epilepsy. The electrodes used in the RNS act locally, activating neurons within 4 mm of the electrode's surface. Carbon nanotubes could potentially expand this area of influence by enhancing the conductivity of the brain near the electrode. The authors performed cytotoxicity testing on human brain cells to confirm the safety of functionalized carbon nanotubes. Computational and experimental modeling experiments demonstrated that the nanotubes indeed expand the area of activation. SLEEP DISTURBANCE IN EPILEPSY: CAUSES AND CONSEQUENCES Researchers are only beginning to understand the implications of disrupted sleep in people with epilepsy. Recent findings suggest that seizure-interrupted sleep could impede memory formation, impair cognitive performance and influence a myriad of other aspects of daily life. Four studies presented at the American Epilepsy Society's (AES) 69th Annual Meeting unveil previously unappreciated links between sleep disturbances and seizure control, and help clarify the causes and consequences of these issues in people with epilepsy. In the first study, (abstract 3.019|A.01) researchers at Children's National Medical Center report that disruptions in the body's 24-hour clock, or circadian rhythm, might contribute to certain types of epilepsy. The authors performed a genetic analysis of brain tissue from children who underwent surgery to treat epilepsy. Healthy and seizure-associated brain tissues were removed solely for therapeutic purposes and were donated to researchers with permission from parents or guardians. The analysis revealed that a gene responsible for controlling sleep/wake cycles—dubbed Circadian Locomotor Output Cycles Kaput (CLOCK)—is found in lower levels in seizure-associated tissue than healthy brain tissue, prompting researchers to explore how abnormally low levels of the gene might influence seizure control in mice. A second study (abstract 2.333) reveals that patients who experience seizures at night tend to have worse memory than patients with other types of epilepsy. Scientists from Brigham and Women's Hospital (BWH) explored how disrupted sleep affects memory and cognitive performance in patients with epilepsy. A third study (abstract 2.229|B.08) found that sleep disturbances are extremely common in children with Dravet syndrome, a genetic form of epilepsy that manifests in infancy with drug-resistant seizures, developmental delays and behavioral issues. Researchers from the University of Melbourne obtained completed questionnaires about nighttime seizures and the use of sleep medications from 50 families of children with Dravet syndrome. In a fourth study, (abstract 3.242) researchers from Creighton University describe the physiological events that unfold during the onset and progression of epilepsy. The authors studied a mouse model of temporal lobe epilepsy and sleep disorders, expanding on their past findings that suggest mice with epilepsy undergo changes to their sleep-wake cycles, or diurnal rhythmicity, and express higher than normal levels of the wakefulness- promoting protein, orexin. In the current study, the authors returned to the mouse model to determine if increases in sleep disruptions and orexin levels coincide with the development of epilepsy. Find out more at aesnet.org. Highlights from the American Epilepsy Society 2015 69th Annual Meeting American Epilepsy Society 2016 70th Annual Meeting December 2–6, 2016 George R. Brown Convention Center, Houston, Texas 10 Current Trends in Epilepsy Management [December 2015]

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