Multiscale Dynamics of the Frontotemporal Connectome in Refractory Epilepsy

难治性癫痫额颞叶连接组的多尺度动力学

• 批准号: 10510593
• 负责人: Giridhar Padmanabhan Kalamangalam
• 金额: $ 41.94万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10510593
• 关键词: Address; Affect; Anatomy; Anticonvulsants; Archives; Area; Arousal; BRAIN initiative; Base of the Brain; Behavior; Brain; Brain Diseases; Brain region; Characteristics; Chronic; Circadian Rhythms; Clinical; Consent; Data; Dependence; Diagnostic; Dimensions; Electrodes; Electroencephalography; Epilepsy; Excision; Exhibits; Frequencies; Frontal Lobe Epilepsy; Functional Magnetic Resonance Imaging; Future; Goals; Gold; Graph; Hospitalization; Hour; Human; Image; Implant; Inpatients; Intractable Epilepsy; Knowledge; Length; Location; Magnetic Resonance Imaging; Maps; Methods; Mission; Modality; Modeling; Monitor; Mosaicism; National Institute of Neurological Disorders and Stroke; Nature; Neurosciences; Operative Surgical Procedures; Outcome; Partial Epilepsies; Pathway interactions; Patients; Pattern; Periodicity; Predisposition; Public Health; Recurrence; Reporting; Research; Research Proposals; Rest; Risk; Runaway; Sampling; Scalp structure; Scientific Inquiry; Seizures; Signal Transduction; Sleep; Spatial Distribution; Temporal Lobe; Temporal Lobe Epilepsy; Therapeutic; Time; Translational Research; United States National Institutes of Health; Variant; Vision; Wakefulness; Withdrawal; Work; analytical tool; base; brain magnetic resonance imaging; brain volume; chronic neurologic disease; circadian; connectome; data streams; frontal lobe; improved; indexing; individual patient; innovation; insight; nervous system disorder; network architecture; neurophysiology; neuroregulation; novel; spatiotemporal; surgery outcome; vigilance

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.

抽象的 癫痫神经科学的一个基本知识差距涉及癫痫发作的不同倾向。 例如，24小时昼夜节律周期，目前尚不清楚为什么一些额叶癫痫患者可能只会癫痫发作。 了解睡眠时癫痫网络的动态变化对于昼夜节律时间尺度至关重要。 改善目前所有治疗均失败的大部分癫痫患者的治疗前景。 癫痫的网络架构基于结构 MRI 或静息态 (rs) fMRI 这些模式。 揭示固定时间尺度的单个实验时间点，并且不解决时空动态 慢性颅内记录中癫痫发作周期性的报告并未对癫痫发作网络进行采样。 整个癫痫网络，仅记录癫痫发作的发生，而不记录其致病网络的改变。 长期目标是了解癫痫的网络动态，以推进治疗。 脑内立体脑电图（SEEG）信号，旨在建立动态的神经生理学信号 我们的中心假设是基于 SEEG 的额颞叶脑区连接组。 癫痫网络的拓扑结构具有特定的昼夜节律依赖性，并且这种依赖性可以 可以在更长的时间范围内进行调节，包括通过抗惊厥药物进行调节。 了解癫痫网络的网络路径、带宽和昼夜节律状态依赖性将 激发新的癫痫神经调节方法（针对特定频段的大脑区域和 他们的 24 小时周期）。这种洞察力也可能推动新的网络消融手术方法。 追求两个具体目标：（i）确定基于 SEEG 的额颞叶皮层连接组学 昼夜节律警惕状态；以及 (ii) 确定癫痫网络动态的红外特征； 处理我们临床机构患者的连续多天 SEEG 记录， 我们将同时追求这些目标，我们将根据患者的警惕状态并使用分析来组织数据。 在之前的工作中部署的工具中，我们将描述癫痫样额颞叶皮层网络及其 我们将根据 24 小时和红外线周期确定多个时间尺度的相互作用。 网络漏洞锁定于昼夜节律周期，并通过与发作发作的比较来验证我们的结果 我们的建议是创新的，如致癫痫指数的区域和空间分布。 因为我们将超越基于成像的连接组学的静态性质，添加时间维度 通过帮助解决科学问题，我们的贡献将是巨大的。 癫痫神经科学中的谜团，同时提出了难治性癫痫的潜在新疗法。 一般来说，我们的工作将为“构建大脑图谱”、“观察大脑的活动”和“促进人类发展”提​​供信息。 NIH BRAIN 计划的神经科学优先领域。