electroencephalography and single-unit recordings

科学抽象 癫痫是一种慢性和衰弱性疾病，导致高达40%的患者出现难治性癫痫发作。一 更好地理解导致反复发作的神经机制可能会改善 诊断标志物和新的神经保护疗法。 我最近的研究表明，睡眠中异常的慢波活动（SWA）模式可能 构成了一个有前途的诊断标记，定位癫痫发作区（SOZ）。在高密度 我对15名局灶性癫痫患者进行了脑电图（hdEEG）研究，发现睡眠SWA增加 在SOZ中最大，并与癫痫发作和发作间期峰频率相关。建筑 大量的研究证实睡眠SWA是突触强度的标志，我的结果表明， 癫痫发作和尖峰在人脑中诱导突触增强。 为了进一步验证睡眠SWA作为SOZ的诊断标志物，我的目标是利用更高的 直接颅内EEG（iEEG）记录的时空分辨率。在目标1中，我将分析 局灶性癫痫患者的连续iEEG记录，以量化SOZ中的睡眠SWA， 癫痫发作传播网络（SPN，在发作节律中二次募集的区域）和周围 （不涉及发作节律的区域）。我假设：1）在SOZ中，SWA将最大限度地增加; 2)在外围，睡眠SWA将具有较低值;以及3）SPN将显示中间模式。 在目标2中，我还将分析单单位（SU）记录，以确定睡眠的神经元贡献者 睡眠期间的SWA及其在癫痫发作区域的变化。我将使用现有的长期 癫痫患者的微电极记录，以量化SU放电率和多单位活动（MUA） 睡眠期间的同步性（突触强度的两个标志）在SOZ，SPN和周边。到 为了阐明睡眠SWA增加与发作放电率之间的关系，我将使用SU 记录以将SPN分成高与低发作放电率的区域（发作核心与发作核心）。 半影）。我假设1）在SOZ中，SU放电率和MUA同步将 2）在外周，SU放电率和MUA同步将显示较低的值;以及 3)SPN将显示中间模式，但在发作半影区总体上具有更多正常值 与发作核心相比。 如果这个项目是成功的，它将为慢性疾病之间的联系提供机械证据。 癫痫网络中的过度兴奋和癫痫发作引起的突触增强， 使用颅内睡眠脑电图敏感地检测到。它还将允许研究人员和临床医生开发 新的诊断工具，定位SOZ，为新的治疗干预措施铺平道路， 睡眠减少癫痫患者发作频率。

Scientific abstract Epilepsy is a chronic and debilitating disease, leading to refractory seizures in up to 40% of patients. A better understanding of the neural mechanisms that cause recurrent seizures could lead to improved diagnostic markers and new neuroprotective therapies. My recent research suggests that abnormal slow-wave activity (SWA) patterns during sleep may constitute a promising diagnostic marker to locate the seizure onset zone (SOZ). In a high-density electroencephalogram (hdEEG) study of fifteen focal epilepsy patients, I found increases in sleep SWA that were maximal in the SOZ and were correlated with seizure and interictal spike frequency. Building on a wealth of studies validating sleep SWA as a marker of synaptic strength, my results suggest that seizures and spikes induce synaptic potentiation in the human brain. To further validate sleep SWA as a diagnostic marker for the SOZ, I aim to make use of the higher spatio-temporal resolution of direct intracranial EEG (iEEG) recordings. In Aim 1, I will analyze continuous iEEG recordings in patients with focal epilepsy to quantify sleep SWA in the SOZ, in the seizure propagation network (SPN, areas secondarily recruited in the ictal rhythm), and in the periphery (areas not involved in the ictal rhythm). I hypothesize that 1) in the SOZ, SWA will increase maximally; 2) in the periphery, sleep SWA will have lower values; and 3) the SPN will show intermediate patterns. In Aim 2, I will also analyze single-unit (SU) recordings to identify the neuronal contributors to sleep SWA during sleep and their alterations across seizure territories. I will use existing long-term microelectrode recordings from epileptic patients to quantify SU firing rates and multi-unit activity (MUA) synchrony during sleep (two markers of synaptic strength) in the SOZ, the SPN, and the periphery. To shed light on the relationship between increased sleep SWA and ictal firing rates, I will use the SU recordings to separate the SPN into areas of high vs. low ictal firing rates (the ictal core vs. ictal penumbra, respectively). I hypothesize that 1) in the SOZ, SU firing rates and MUA synchrony will increase maximally; 2) in the periphery, SU firing rates and MUA synchrony will show lower values; and 3) the SPN will show intermediate patterns, but with more normal values overall in the ictal penumbra compared to the ictal core. If this project is successful, it will provide mechanistic evidence for a link between chronic hyperexcitability in the epileptic network and synaptic potentiation due to seizures, which can be sensitively detected using intracranial sleep EEG. It will also allow researchers and clinicians to develop new diagnostic tools to localize the SOZ, paving the way for new therapeutic interventions targeting sleep to decrease seizure frequency in patients with epilepsy.