THALAMOCORTICAL NEURON DYNAMICS AND ABSENCE EPILEPSY

理解失神癫痫需要理解丘脑 震荡。这项研究的长期目标是使用计算机 集成已知的神经元固有属性和细节的模型 突触输入解释生理性和突触的起源 丘脑的病理性慢节奏。固有的细胞动力学和 突触连接以复杂的方式相互作用。个人的典范 大脑区域可以提供一个框架，将新的生理和 药理观察。作为癫痫动物模型的补充， 计算机模型具有广泛探索复杂问题的灵活性 神经元的相互作用可能会提出新的药理学方法。 丘脑的慢振荡，在3赫兹的缺失范围内 癫痫和慢波睡眠在10赫兹范围内出现睡眠纺锤波 涉及T-型钙通道引起的低阈值钙尖峰 (T频道)。乙硫胺，一种用于失神癫痫的抗惊厥药物， 改变此通道的动力学。将使用计算机建模1) 确定被动性质和树枝状离子通道的影响 论神经元的整合性，2)联系神经元 放电模式对离子通道密度和动力学的影响，3) 评价离子通道的生理和药物调节 可能改变丘脑皮质神经元的本征振荡，4) 探索重复的细胞内刺激或重复的皮质 突触输入会影响振荡模式，5)评估 本征属性与网络属性对同步慢速的贡献 简化模型神经元网络中的振荡。

Understanding absence epilepsy will require understanding thalamic oscillations. The long term goal of this research is to use computer models to integrate known details of intrinsic neuronal properties and synaptic inputs to explain the genesis of the physiological and pathological slow rhythms of the thalamus. Intrinsic cell dynamics and synaptic connectivity interact in complex ways. Models of individual brain areas can provide a framework for integrating new physiological and pharmacological observations. A complement to animal models of epilepsy, computer models have the flexibility to extensively explore complex neuronal interactions that may suggest new pharmacological approaches. Slow oscillations in the thalamus, in both the 3 Hz range of absence epilepsy and slow-wave sleep in the 10 Hz range of sleep spindles, appear to involve low-threshold calcium spikes due to the T-type calcium channel (T channel). Ethosuximide, an anticonvulsant used for absence epilepsy, alters the kinetics of this channel. Computer modeling will be used 1) to determine the effects of passive properties and dendritic ion channels on the integrative properties of the neurons, 2) to relate neuronal firing patterns to the density and kinetics of ion channels, 3) to evaluate how physiological and pharmacological modulation of ion channels might alter the intrinsic oscillations of thalamocortical neurons, 4) to explore how repetitive intracellular stimulation or repetitive cortical synaptic input would affect oscillatory patterns, 5) to evaluate the contribution of intrinsic versus network properties in synchronizing slow oscillations in networks of simplified model neurons.