Evolution of seizure precursors in refactory epilepsy

描述(由申请人提供)：这项建议的目标是开发和验证一种实用的方法来预测人类颞叶和颞外癫痫的癫痫发作。我们实验室的最新数据表明，人类部分癫痫发作与其在颅内脑电(IEEG)开始前几分钟至几小时内电活动增强有关。发作前积聚的三种最有希望的措施是积累能量、亚临床癫痫样爆发(Chirps)和高频癫痫样振荡。除了在癫痫发作前增加外，这些参数在其他时间起伏不定，表明大脑兴奋性的反复变化重复发生，只在关键时刻进行到癫痫发作。通过在连续、长期、多通道的颅内脑电(IEEG)数据中跟踪上述三项指标，我们计划开发一个实用的模型，说明癫痫网络中癫痫发作是如何产生的，并将前瞻性地验证该模型识别癫痫发作概率增加时期的能力(我们对癫痫发作预测的定义)。我们实验室根据上述定量特征开发的算法目前正在第一代癫痫响应性脑刺激设备上运行，正在进行的临床试验中将其植入约200名患者，取得了令人鼓舞的结果。这些设备刺激大脑，以响应单通道中上述定量措施的积累。这些设备的最佳性能将需要了解这些措施是如何在整个癫痫网络中发展和传播的，以及这一过程背后的机制。在上述发展的推动下，本建议的具体目标是：(1)仔细收集、标记和存档具有药物耐药性的颞叶和颞外癫痫成人和儿童代表性人群的iEEG研究数字数据库；(2)研究上述3种量化措施在所有颅内电极接触中的发生和持续时间，并前瞻性地确定它们与连续、未浸泡的患者数据集中癫痫发作的关系；(3)基于这些发现建立一个实用的癫痫发作产生模型，并前瞻性地验证其预测癫痫发作的能力。实现这些目标将对癫痫产生的潜在机制产生重要的洞察力，并将对提高第一代反应性癫痫装置的性能至关重要。我们的实验室将在这个项目中领导一个成熟的合作者团队，负责收集、处理和解释数据，拥有宾夕法尼亚大学、梅奥诊所和佐治亚理工学院的电气工程、神经科学、临床癫痫、神经病理学和统计学方面的专业知识。

DESCRIPTION (provided by applicant): The goal of this proposal is to develop and validate a practical method to predict epileptic seizures in human temporal and extratemporal epilepsy. Recent data from our laboratory suggest that human partial seizures are associated with a build-up of electrical activity minutes to hours prior to their onset on intracranial EEG (IEEG). The three most promising measures of this pre-ictal build-up are accumulating energy, subclinical seizure-like bursts (chirps), and high frequency epileptiform oscillations. In addition to increasing before seizures, these parameters wax and wane at other times, suggesting that recurrent changes in brain excitability occur repetitively and only proceed to seizures at critical times. By tracking the above three measures in continuous, long-term, multi-channel intracranial EEG (IEEG) data we plan to develop a practical model of how seizures are generated in the epileptic network and will prospectively validate the model's ability to identify periods of increased probability of seizure onset (our definition of "seizure prediction"). Algorithms developed in our laboratory based upon the quantitative features above are currently operating in first generation responsive brain stimulation devices for epilepsy being implanted in about 200 patients in an ongoing clinical trial, with encouraging results. These devices stimulate the brain in response to build-ups of the above quantitative measures in single channels. Optimal performance of these devices will require understanding how these measures develop and spread in the entire epileptic network, and the mechanisms underlying this process. Motivated by the above developments, the specific aims of this proposal are: (1) To meticulously collect, mark and archive a digital database of IEEG studies from a representative population of adults and children with medically resistant temporal and extra-temporal epilepsy, (2) to study the occurrence and duration of the above 3 quantitative measures in all intracranial electrode contacts and prospectively determine their relationship to electrographic seizure onset in continuous, undipped patient data sets; (3) to develop a practical model of seizure generation based upon these findings and prospectively validate its ability to predict seizures. Accomplishing these aims will yield important insight into the mechanisms underlying seizure generation and will be critical to improving the performance of 1st generation reactive epilepsy devices. Our lab will lead an established team of collaborators in this project for data collection, processing and interpretation, with expertise in electrical engineering, neuroscience, clinical epilepsy, neuropathology and statistics at The University of Pennsylvania, The Mayo Clinic and The Georgia Institute of Technology.