Quantitative interictal networks to localize seizure generators

项目摘要 难治性癫痫患者的手术疗效一般，很大程度上是由于定位错误 癫痫发作发生器目前，癫痫学家通过手动识别癫痫发作来定位癫痫发作发生器 颅内脑电图的起始区还有大量的发作间期EEG数据（发作之间）， 忽视，因为到目前为止，临床医生缺乏严格的方法来解释这些数据。最近的工作博士。 Conrad和她的合著者以及其他人验证了两种定量方法来分析发作间期EEG： 癫痫样放电（IED）和功能连接（FC）。这项工作表明，定量 对简易爆炸装置和FC的分析揭示了有助于识别癫痫发作发生器的区域--这里称为枢纽 （Conrad等人，Brain，2020; Conrad等人，网络神经科学，2020）。该项目将评估 IED和FC中心，以阐明其机制及其在手术计划中的潜在效用。 这一提议的中心假设是癫痫可测量地改变发作间期网络， 用发作间期数据探测癫痫发作发生器该提案的目标是： IED和FC中心之间的时间稳定性和空间对应性（目标1），以确定这些中心是否 定位癫痫发作发生器（目标2），并通过皮层刺激主动探测发作间期网络，以验证 假设的FC集线器（目标3）。这些研究将扩大我们对癫痫网络的理解。如果 成功地定量分析发作间期EEG将增强癫痫发作发生器的定位， 手术结果。 这个拟议的项目还将提供关键的职业发展培训康拉德博士，癫痫 宾夕法尼亚大学讲师。该提案建立在康拉德博士在定量脑电图方面的背景之上 癫痫临床分析康拉德博士将由布赖恩利特，世界知名的专家， 计算性癫痫; Danielle Bassett，网络理论的领先专家; Eric Marsh，网络理论的领先专家 简易爆炸装置定量分析本建议书中的培训计划包括指导完成拟议的 研究，以及严格的教学计划，研讨会，实验室会议，以及直接相关的临床 工作总之，这些经验将提供时间序列统计，机器学习， 受试者登记、皮层刺激和EEG数据采集。本拟议项目和培训计划将 启动康拉德博士的独立研究生涯，专注于使用多模态方法来评估 发作间期的数据，以提高我们对癫痫的认识和治疗。

PROJECT SUMMARY Surgical outcomes for patients with intractable epilepsy are modest, in large part due to mis-localization of seizure generators. Currently, epileptologists localize seizure generators by manually identifying the seizure onset zone on intracranial EEG. There is also abundant interictal EEG data (between seizures) that is largely ignored because, until now, clinicians lacked rigorous approaches to interpret this data. Recent work by Dr. Conrad, her co-authors, and others, validated two quantitative methods to analyze interictal EEG: interictal epileptiform discharges (IEDs) and functional connectivity (FC). This work demonstrates that quantitative analysis of IEDs and FC reveals regions — referred to here as hubs — that help identify seizure generators (Conrad et al., Brain, 2020; Conrad et al., Network Neuroscience, 2020). This proposed project will evaluate IED and FC hubs in order to elucidate their mechanisms and their potential utility in surgical planning. The central hypothesis of this proposal is that epilepsy measurably alters the interictal network, allowing us to probe seizure generators with interictal data. The objectives of the proposal are: to determine the temporal stability and spatial correspondence between IED and FC hubs (Aim 1), to determine if these hubs localize seizure generators (Aim 2), and to actively probe the interictal network with cortical stimulation to verify hypothesized FC hubs (Aim 3). These studies will expand our understanding of epileptic networks. If successful, quantitative analysis of interictal EEG will enhance localization of seizure generators and improve surgical outcomes. This proposed project will also provide critical career development training to Dr. Conrad, an Epilepsy Instructor at University of Pennsylvania. The proposal builds on Dr. Conrad's background in quantitative EEG analysis and clinical epilepsy. Dr. Conrad will be mentored by Brian Litt, a world-renowned expert in computational epilepsy; Danielle Bassett, a leading expert in network theory; and Eric Marsh, a leading expert in quantitative IED analysis. The training plan in this proposal includes mentored completion of the proposed research, as well as a rigorous program of didactics, workshops, lab meetings, and directly relevant clinical work. Together, these experiences will provide essential training in time-series statistics, machine learning, subject enrollment, cortical stimulation, and EEG data acquisition. This proposed project and training plan will launch Dr. Conrad on an independent research career focused on using a multimodal approach to evaluating interictal data in order to improve our understanding and treatment of epilepsy.