electroencephalography and single-unit recordings

科学摘要 癫痫是一种慢性和衰弱的疾病，在高达40%的患者中导致难治性癫痫发作。一个 更好地了解导致反复发作的神经机制可能会带来改善 诊断标记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 是定位癫痫起始区(SOZ)的一种有前景的诊断标志物。在高密度下 对15例局灶性癫痫患者的脑电(HdEEG)研究，发现睡眠SWA增加 在SOZ中最大，与发作和发作间期棘波频率相关。建房 在大量研究证实睡眠SWA是突触强度的标志后，我的结果表明 癫痫发作和棘波在人脑中诱导突触增强。 为了进一步验证睡眠SWA作为SOZ的诊断标记，我打算使用更高的 直接脑电(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 癫痫传播网络(SPN，在发作节律中二次招募的区域)，以及在外周 (未参与发作节律的区域)。我假设：1)在SOZ中，SWA将最大限度地增加； 2)在外周，睡眠声波值较低；3)SPN将呈现中间模式。 在目标2中，我还将分析单个单位(SU)的记录，以确定神经元对睡眠的贡献 睡眠中的SWA及其在癫痫发作区域的变化。我将使用现有的长期 癫痫患者微电极记录以量化SU放电率和多单位活动(MUA) 睡眠时SOZ、SPN和外周的同步(突触强度的两个标志)。至 为了阐明睡眠SWA增加和发作性放电频率之间的关系，我将使用SU 记录将SPN分成高与低发作性放电频率的区域(发作性核心与发作性 分别为半影)。我假设1)在SOZ中，SU射速和MUA同步性将 最大限度地增加；2)在外围，SU放电率和MUA同步性将呈现较低的值；以及 3)SPN表现为中间型，但发作半影区总体正常值较高。 与发作核心相比。 如果这个项目成功，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性和癫痫发作引起的突触增强，这可能是 用颅内睡眠脑电灵敏地检测到。它还将允许研究人员和临床医生开发 本地化SOZ的新诊断工具，为新的靶向治疗干预铺平了道路 睡眠可减少癫痫患者的癫痫发作频率。

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.