Multiscale analysis and modeling of spatiotemporal dynamics in human epilepsy

项目简介/摘要全球有近5000万人患有癫痫。据估计，这些人中有30%的人，尽管进行了最大的医疗管理，但癫痫发作仍然控制不佳。此外，通过药物治疗癫痫通常会导致严重的副作用，有时会使人衰弱。为了推进癫痫的治疗管理，我们必须了解支持这种疾病的生理机制。解开这些机制尤其困难。像许多神经过程一样，癫痫发作涉及跨越多个数量级的空间尺度，从单个神经元到整个神经系统。此外，典型的临床记录只能对癫痫发作的巨大机制提供有限的看法。在这个项目中，一个由临床医生、统计学家和数学家组成的跨学科研究小组将研究支持癫痫的动力学机制，并在此过程中提出治疗该病的新疗法。这项研究将集中在癫痫发作的三个基本方面——如何开始，如何在大脑中扩散，以及如何结束——通过人类癫痫患者的电压记录来观察。这些记录将跨越多个空间尺度，包括单个神经元、小神经群和大大脑区域产生的活动。为了描述这些数据的特征，将应用复杂的分析技术，将跨空间尺度的活动联系起来。此外，神经活动的计算模型将被开发和约束使用多尺度数据。然后，这些模型将被应用于提示癫痫发作期间支持多尺度相互作用的机制，并提出治疗癫痫的新疗法。这项研究的完成将是朝着更深入、更全面地了解癫痫生理学，以及探索和测试癫痫控制创新方法的系统迈出的重要一步。

DESCRIPTION (provided by applicant): PROJECT SUMMARY / ABSTRACT Across the world, nearly 50 million people suffer from epilepsy. For an estimated 30% of these individuals, seizures remain poorly controlled despite maximal medical management. Moreover, treatment of epilepsy through medication often results in significant - sometimes debilitating - side effects. To advance the therapeutic management of epilepsy, we must understand the physiological mechanisms which support this disease. Unraveling these mechanisms is especially difficult. Like many neural processes, the seizure involves spatial scales spanning many orders of magnitude, from the individual neuron to the entire nervous system. Moreover, typical clinical recordings provide only a limited view of the vast mechanisms underlying the seizure. In this project, an interdisciplinary research group consisting of clinicians, statisticians, and mathematicians will study the dynamical mechanisms that support epilepsy and, in doing so, suggest novel therapies to treat the disease. The research will focus on three fundamental aspects of the seizure - how it begins, how it spreads over the brain, and how it ends - observed in voltage recordings from human patients with epilepsy. These recordings will span multiple spatial scales and include activity generated by individual neurons, small neural populations, and large brain regions. To characterize these data, sophisticated analysis techniques will be applied that link the activity across spatial scales. In addition, computational models of the neural activity will be developed and constrained using the multiscale data. These models will then be applied to suggest the mechanisms that support multiscale interactions during seizure and to propose novel therapies to treat epilepsy. Completion of the proposed research will represent a significant step forward toward a deeper and more complete understanding of epileptic physiology, and toward a system for exploring and testing innovative methods for seizure control.