CRCNS: Neural Populations, High Frequency Oscillations and EEG seizures

CRCNS：神经群体、高频振荡和脑电图癫痫发作

基本信息

批准号：
9047876
负责人：
Catherine A Schevon
金额：
$ 34.49万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-30 至 2018-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9047876
关键词：
Accounting Affect Area Biological Markers Brain Cells Clinical Computer Simulation Coupling Data Data Set Electroencephalogram Electrophysiology (science)Epilepsy Event Excision Failure Fire - disasters Frequencies Goals High Frequency Oscillation Hodgkin Disease Human Individual Interneurons Invaded Investigation Lead Linear Models Literature Measurement Methods Microelectrodes Modeling Modification Monitor N-Methylaspartate Neurons Operative Surgical Procedures Outcome Output Partial Epilepsies Patients Physiology Population Probability Property Pyramidal Cells Recruitment Activity Resected Role Seizures Shapes Signal Transduction Site Slice Source Structural defect Structure Synapses Synaptic Transmission Syndrome Techniques Testing Tissues Translating Validation Visual Work abstracting brain tissue driving force excitatory neuron extracellular improved in vivo insight interdisciplinary approach nervous system disorder network models postsynaptic public health relevance receptor relating to nervous system response restraint simulation stem

Accounting Affect Area Biological Markers Brain Cells Clinical Computer Simulation Coupling Data Data Set Electroencephalogram Electrophysiology (science)Epilepsy Event Excision Failure Fire - disasters Frequencies Goals High Frequency Oscillation Hodgkin Disease Human Individual Interneurons Invaded Investigation Lead Linear Models Literature Measurement Methods Microelectrodes Modeling Modification Monitor N-Methylaspartate Neurons Operative Surgical Procedures Outcome Output Partial Epilepsies Patients Physiology Population Probability Property Pyramidal Cells Recruitment Activity Resected Role Seizures Shapes Signal Transduction Site Slice Source Structural defect Structure Synapses Synaptic Transmission Syndrome Techniques Testing Tissues Translating Validation Visual Work abstracting brain tissue driving force excitatory neuron extracellular improved in vivo insight interdisciplinary approach nervous system disorder network models postsynaptic public health relevance receptor relating to nervous system response restraint simulation stem

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项目摘要

Abstract Epilepsy is a neurological disease affecting 65 million people worldwide. Patients with medically intractable seizures and with a clearly localized focus can often be successfully treated by surgical resection of the epileptic tissue. However, localization accuracy is limited, especially if overt structural abnormalities are absent. High frequency oscillations have been proposed as a key localizing biomarker. Unfortunately, progress in understanding the dynamics of seizure electrophysiology has been impeded by lack of measurement techniques for detailed monitoring of large networks both the temporal and spatial domains. We propose that multiscale network modeling incorporating known pathological mechanisms can provide useful insights into the circumstances under which high frequency oscillations are generated. We propose an interdisciplinary approach coupling modeling with an existing dataset of unique multiscale recordings, ranging from single-cell to large networks of millions of cells, during seizure activity in human cortical networks. Our proposal is focused around several important clinical questions. First, we seek to define precisely how high frequency spectral components in broadband clinical recordings reflect the pathological activity specific to seizing brain areas. Second, we will identify the neuronal mechanisms permitting localized pathological activity to propagate, and how this propagation affects the properties· of broadband clinical recordings. In contrast to the prior literature in this area, our approach explicitly incorporates the network effects of cellular dynamics known to occur during experimental seizures, I.e. paroxysmal depolarization and depolarization block of specific cell populations. In Aim 1 we use scalable and detailed modeling of individual network nodes to relate single-cell activity to the mesoscopic network scale. The focus of this aim is to determine how network interactions generate high frequency oscillations. Independently, in Aim 2 we test the hypothesis that these small, mesoscopic networks are responsible, via propagation of the high frequency components, for the high-gamma oscillation in macroelectrode signals. We accomplish this by generating the macroelectrode signal with a simple linear model that employs single-cell and small network signals as its input. In Aim 3 we relate the observed seizure propagation, due to failure of the inhibitory veto, to network dynamics associated with the paroxysmal depolarization block. For all aims we will validate simulated results with data recorded during experimental seizures in slices of human cortex (single-cell and local network activity), and in vivo microelectrode recordings during human seizures (multi-unit as well as local network activities).

抽象的癫痫病是一种神经系统疾病，影响了全球6500万人。癫痫组织的手术切除术通常可以成功治疗具有医学上棘手的癫痫发作和明显局部焦点的患者。但是，本地化准确性受到限制，尤其是在没有明显的结构异常的情况下。已经提出了高频振荡作为定位生物标志物的关键。不幸的是，缺乏对临时和空间域的大型网络进行详细监测的测量技术的详细监测，因此阻碍了理解癫痫发作电生理学动力学的进展。我们建议，多尺度网络建模纳入已知的病理机制可以为产生高频振荡的情况提供有用的见解。我们在人类皮质网络中的癫痫发作活性期间，建议使用现有的独特多尺度记录的现有数据集进行跨学科方法耦合建模。我们的建议集中在几个重要的临床问题上。首先，我们试图准确地定义宽带临床记录中的高频光谱成分如何反映针对大脑区域的病理活性。其次，我们将确定允许局部病理活性传播的神经元机制，以及这种传播如何影响宽带临床记录的特性。与该领域的先前文献相反，我们的方法明确纳入了在实验性癫痫发作期间已知的细胞动力学的网络效应，即特定细胞群体的阵发性沉积和沉积块。在AIM 1中，我们使用单个网络节点的可扩展和详细的建模将单细胞活动与介观网量表相关联。该目标的重点是确定网络交互如何产生高频振荡。独立地，在AIM 2中，我们检验了以下假设：这些小型的介镜网络通过高频组件传播而导致了大型电极信号中的高γ振荡。我们通过使用简单的线性模型生成大型电信信号来实现这一目标，该模型采用单细胞和小网络信号作为输入。在AIM 3中，我们将观察到的癫痫传播（由于抑制性否决权失败）与与阵发性沉积块相关的网络动力学。对于所有目标，我们将验证模拟结果，并在人类皮质切片（单细胞和局部网络活动）中记录的数据记录，以及人类癫痫发作期间的体内微电极记录（多单元以及本地网络活动）。