CAREER: Bridging epileptogenic molecular level changes to neuronal network synchrony to reveal basic mechanisms of epilepsy

PI：Netoff，Theoden I.提案编号：0954797 网络中出现的病态行为的病因尤其难以诊断。 原因通常是节点动态的微妙变化，导致种群行为的变化。这些多尺度问题是非常普遍的。癫痫是由基因突变引起的神经元分子水平变化导致病理性神经元活动产生癫痫发作的疾病的一个实例。虽然有许多假设，但对这些突变如何以及为什么会导致癫痫发作知之甚少，这阻碍了我们开发更好的治疗方法。了解网络中的同步性如何受到已知致癫痫突变和具有已知分子效应的抗癫痫药物的影响，将提供一个模型系统，其中可以桥接多个尺度。将使用数值模拟、电生理学实验和计算模拟的协同方法。 神经元的计算模型将用于预测致痫突变和抗癫痫药物如何改变神经元的相位响应曲线（PRC）。PRC是衡量神经元的一个指标？对突触输入的敏感性。从PRC可以推断致癫痫突变和抗癫痫药物引起的变化如何改变神经元网络的同步性。将使用动态钳实验来测试来自建模的预测，在动态钳实验中，运行实时接口的计算机通过膜片钳放大器和电极与神经元连接。动态钳夹实验将用于测量致癫痫突变（通过电敲入引入）和浴用抗癫痫药物对神经元相位响应曲线的影响。然后，将使用动态钳创建混合网络，以模拟两个膜片钳神经元之间的突触连接，其中致癫痫突变和抗癫痫药物对同步性的影响将被直接测量。生理实验将用于提供参数，以运行大规模的模拟，其中同步将被测量。从模拟和电生理学实验的初步数据，电压门控钠通道的致癫痫突变减少同步和抗癫痫药物增加同步。这些发现与癫痫的流行观点相反，癫痫是由超同步性引起的。通过发展我们对这些突变和药物如何实际工作的理解，我们可以开发新的和更好的方法来治疗这种疾病。 这项拟议研究的目标是测试以下假设：致癫痫突变引起的神经元动力学变化增加了网络同步性，而预防癫痫发作的药物对神经元的调节降低了网络同步性。通过证明或反驳这些假设，我们将了解是否应该优化开发新药或深部脑刺激来预防癫痫发作，以减少网络同步。为了验证这一假设，我们提出了以下具体目标：1）使用单细胞建模来识别致痫突变和抗癫痫药物对细胞动力学的影响，2）网络建模来评估致痫突变和抗癫痫药物对网络同步性的影响，以及3）使用真实的神经元和虚拟离子通道的混合实验来表征SCN 1A通道突变引起的细胞动力学变化。 智力优势：本文提出的研究将有助于阐明神经元动力学和网络连接拓扑结构的变化如何导致病理性神经元活动，如癫痫发作。神经元动力学如何受到致癫痫突变和抗癫痫药物的影响将被发现，以帮助开发更好的癫痫发作模型。已知的致癫痫离子通道突变和抗癫痫药物对网络同步性的影响将被用来探测癫痫中神经元群体同步性的作用。有了这些知识，我们将开发更合理的方法来治疗癫痫。 更广泛的影响：获取的电生理数据将被编目到数据库中，任何有兴趣分析数据的科学家都可以使用。为了完成电生理学实验，我们将为动态钳生成许多模块，这些模块将使用RTXI动态钳提供给社区。使用支持CUDA的机器在桌面上运行超级计算机性能的网络模拟所开发的代码将向公众提供。推广计划包括与巴肯博物馆，癫痫基金会，明尼苏达大学？是什么？大脑U？暑期高中课程吗探索工程和物理科学的职业生涯？，它呢？北星星联盟计划。

PI: Netoff, Theoden I.Proposal Number: 0954797 The etiologies of pathological behaviors that emerge in networks are especially difficult to diagnose. The causes are usually subtle changes in the dynamics of the nodes that lead to changes in population behavior. These multi-scale problems are very general. Epilepsy is an example of disease where molecular level changes in neurons caused by genetic mutations lead to pathological neuronal activity generating seizures. While there are many hypotheses, very little is known about how and why these mutations cause seizures, which prevents us from developing better treatments. Understanding how synchrony in networks are affected by known epileptogenic mutations and antiepileptic drugs with known molecular effects will provide a model system in which multiple scales may be bridged. A synergistic approach using numerical simulations electrophysiology experiments and computational simulations will be used. Computational models of neurons will be used to predict how epileptogenic mutations and antiepileptic drugs change the phase response curve (PRC) of a neuron. The PRC is a measure of a neuron?s sensitivity to synaptic inputs. From the PRC it is possible to infer how changes caused by epileptogenic mutations and antiepileptic drugs would alter synchrony in a network of neurons. Predictions from the modeling will be tested using dynamic clamp experiments, where a computer running a real-time interface is interfaced to a neuron through a patch clamp amplifier and electrode. Dynamic clamp experiments will be used to measure the effects of epileptogenic mutations (introduced thorough electrical knock-in) and bath applied antiepileptic drugs on the phase response curve of the neuron. Hybrid networks will then be created using the dynamic clamp to simulate synaptic connections between two patch clamped neurons in which effects of epileptogenic mutations and antiepileptic drugs on synchrony will be measured directly. Physiological experiments will be used to provide parameters to run large scale simulations where synchrony will be measured. Preliminary data is presented from simulations and electrophsiological experiments that epileptogenic mutations in voltage gated sodium channels decrease synchrony and antiepileptic drugs increase synchrony. These findings are in contrast to the popular view of epilepsy that epilepsy is caused by hypersynchrony. By developing our understanding of how these mutations and drugs actually work, we may develop new and better approaches to treating this disease. The goal of this proposed research is to test the hypotheses that changes in the dynamics of neurons caused by epileptogenic mutations increase network synchrony, and that the modulation of neurons by drugs that prevent seizures decrease network synchrony. By proving, or disproving these hypotheses, we will understand if developing new drugs or deep brain stimulation to prevent seizures should be optimized to decrease network synchrony. To test this hypothesis we propose the following specific aims: 1) use single cell modeling to identify effects of epileptogenic mutations and antiepileptic drugs on cell dynamics, 2) network modeling to assess the effect of epileptogenic mutations and antiepileptic drugs on network synchrony, and 3) characterize changes in cell dynamics caused by mutation of SCN1A channel using hybrid experiments with real neurons and virtual ion channels. Intellectual Merit: The research proposed here will help elucidate how changes in neuronal dynamics and topology of network connectivity result in pathological neuronal activity such as seizures. How neuron dynamics are affected by epileptogenic mutations and antiepileptic drugs will be discovered to help develop better models of seizures. Effects of known epileptogenic ion channel mutations and antiepileptic drugs on network synchrony will be used to probe the role of neuronal population synchrony in epilepsy. With this knowledge we will develop more rational approaches to treating epilepsy. Broader impact: Electrophysiolgy data acquired will be cataloged in a database available to any scientist interested in analyzing the data. To complete the electrophysiolgical experiment, we will generate many modules for the dynamicclamp which will be made available to the community using the RTXI dynamic clamp. Code developed to run network simulations using CUDA enabled machines for supercomputer performance on a desktop will be made available to the public. Outreach plan includes collaborations with the Bakken museum, the Epilepsy Foundation, the University of Minnesota?s ?Brain U?, its summer high school program ?Exploring Careers in Engineering and Physical Science?, and it?s North Star Alliance Program.