Department of Neurology, Zucker School of Medicine at Hofstra-Northwell, Great Neck, New York, U.S.A.
J Clin Neurophysiol. 2024 Mar 1;41(3):207-213. doi: 10.1097/WNP.0000000000001045.
Among the many fears associated with seizures, patients with epilepsy are greatly frustrated and distressed over seizure's apparent unpredictable occurrence. However, increasing evidence have emerged over the years to support that seizure occurrence is not a random phenomenon as previously presumed; it has a cyclic rhythm that oscillates over multiple timescales. The pattern in rises and falls of seizure rate that varies over 24 hours, weeks, months, and years has become a target for the development of innovative devices that intend to detect, predict, and forecast seizures. This article will review the different tools and devices available or that have been previously studied for seizure detection, prediction, and forecasting, as well as the associated challenges and limitations with the utilization of these devices. Although there is strong evidence for rhythmicity in seizure occurrence, very little is known about the mechanism behind this oscillation. This article concludes with early insights into the regulations that may potentially drive this cyclical variability and future directions.
在与癫痫相关的诸多恐惧中，癫痫患者对癫痫发作明显不可预测的发生感到非常沮丧和痛苦。然而，多年来越来越多的证据表明，癫痫发作的发生并非如先前假设的那样是一种随机现象；它具有在多个时间尺度上振荡的周期性节律。癫痫发作率在 24 小时、数周、数月和数年内的上升和下降模式已成为开发旨在检测、预测和预报癫痫发作的创新设备的目标。本文将回顾用于癫痫检测、预测和预报的不同工具和设备，以及使用这些设备所面临的挑战和限制。尽管有大量证据表明癫痫发作存在节律性，但对于这种振荡背后的机制知之甚少。本文最后提出了一些早期的见解，探讨可能驱动这种周期性变化的调节机制以及未来的研究方向。
