Multiscale Dynamics of the Frontotemporal Connectome in Refractory Epilepsy

摘要 癫痫神经科学中的一个基本知识缺口涉及癫痫发作的不同倾向 24小时昼夜节律。例如，不知道为什么一些额叶癫痫患者可能只会发作 在睡觉的时候。了解癫痫网络在昼夜节律时间尺度上的动力学对于 改善大部分所有治疗失败的癫痫患者的治疗前景。当前 癫痫的网络结构是基于结构磁共振成像或静息状态功能磁共振成像。这些模式 揭示固定时间尺度上的单个实验时间点，而不涉及时空动态 癫痫发作网络的性质。慢性颅内记录中癫痫发作周期性的报告没有抽样 完整的癫痫网络，仅记录癫痫发作的发生，而不是其引起的网络改变。我们的 长期目标是了解癫痫的网络动力学，以推进治疗。我们的目标是，使用 脑内立体脑电(SEEG)信号，是建立动态的神经生理学 基于SEEG的昼夜节律中额-颞脑区域的连接体。我们的中心假设 癫痫网络的拓扑结构具有特定的昼夜依赖性，而这种依赖性可以 在更长的时间尺度上进行调节，包括通过抗惊厥药物。我们这个项目的理由是 有关癫痫网络的网络路径、带宽和昼夜状态依赖性的知识将 激发治疗癫痫的新的神经调节方法(针对特定频段和 它们的24小时周期)。这种洞察力也可能推动以网络为灵感的新的消融手术方法。我们会 追求两个具体目标：(I)确定基于SEEG的额颞叶皮质横跨 昼夜节律警戒状态；以及(Ii)确定癫痫网络动力学的亚昼夜特征 额颞叶皮质。在我们的临床机构使用来自患者的连续多天SEEG记录， 我们将同时追求这些目标。我们将根据患者的警觉状态组织数据，并使用分析 在之前的工作中部署的工具，我们将描述癫痫状额颞叶皮质网络，以及它们 在多个时间尺度上的相互作用，并参照24小时和亚周期。我们将确定密钥 网络漏洞锁定到昼夜节律，并通过与发作发作的比较来验证我们的结果 以及致痫指数等指标的空间分布情况。我们的建议是创新的， 因为我们将超越基于成像的连接学的静态本质，增加时间的维度 对大脑网络体系结构的描述。我们的贡献将是重大的，通过帮助解决科学 癫痫神经科学中的谜题，同时建议难治性癫痫的潜在新治疗方法。更多 一般说来，我们的工作将为“建立大脑图谱”、“观察大脑的活动”和“推动人类进步”提供信息 神经科学是美国国立卫生研究院大脑计划的优先领域。

ABSTRACT A fundamental knowledge gap in epilepsy neuroscience concerns the varying propensity for seizures over the 24h circadian cycle. For example, it is not known why some patients with frontal lobe epilepsy may only seize while asleep. Understanding the dynamics of epilepsy networks on circadian time scales is essential for improving therapeutic prospects of the substantial fraction of epilepsy patients who fail all treatments. Current network architectures of epilepsy are based on structural MRI or resting state (rs) fMRI. These modalities reveal single experimental time points at fixed time scales and do not address the spatiotemporally dynamic nature of seizure networks. Reports of seizure periodicity in chronic intracranial recordings do not sample the whole epileptic network and only document seizure occurrence, not their causative network alterations. Our long-term goal is to understand network dynamics in epilepsy to advance therapies. Our objective here, using the intracerebral stereo-electroencephalographic (SEEG) signal, is to build a dynamic neurophysiological SEEG-based connectome of the frontotemporal brain regions over the circadian cycle. Our central hypothesis is that the topology of epileptic networks has specific circadian dependence, and that such dependence can be modulated on longer time scales, including by anticonvulsant drugs. Our rationale for this project is that knowledge of the network pathways, bandwidths and circadian state-dependence of epileptic networks will inspire new neuromodulatory approaches to epilepsy (targeting brain regions in specific frequency bands and their 24h cycles). Such insight may also drive new network-inspired ablative surgical approaches. We will pursue two specific aims: (i) determine the SEEG-based connectomics of frontotemporal cortex across circadian vigilance states; and (ii) Identify the infradian characteristics of epilepsy network dynamics in frontotemporal cortex. Working with continuous multi-day SEEG recordings from patients at our clinical facility, we will pursue these aims in parallel. We will organize the data by patient vigilance state, and using analytic tools deployed in prior work, we will describe epileptiform frontotemporal cortical networks, and their interaction at multiple time scales and with reference to the 24h and infradian cycles. We will identify key network vulnerabilities locked to the circadian cycle and validate our results with comparisons with ictal onset areas and the spatial distribution of metrics such as epileptogenicity index. Our proposal is innovative, because we will move beyond the static nature of imaging-based connectomics to add the dimension of time to descriptions of brain network architecture. Our contribution will be significant, by helping solve a scientific riddle in epilepsy neuroscience while suggesting potential new treatments for refractory epilepsy. More generally, our work will inform the ‘building brain maps’, ‘observing the brain in action’, and ‘advancing human neuroscience’ priority areas of the NIH BRAIN initiative.