Neuronal Dynamics of The Basal Ganglia and Related Systems

基底神经节及相关系统的神经元动力学

• 批准号: 0103822
• 负责人: David Terman
• 金额: $ 25.2万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0103822&HistoricalAwards=false
• 关键词: Neuronal; Dynamics; Basal; Ganglia; Related

Terman0103822 The investigator and his colleague develop geometric,dynamical systems tools for analyzing biophysical,conductance-based models for a broad class of neuronal networks.These systems arise in numerous applications including motoractivity, sensory processing and learning. They also developcomputational models for the generation of sleep rhythms,epilepsy and parkinsonian tremor. The investigators alsoconstruct and refine a mathematical and computational model forelectrical activity in the subthalamic nucleus and externalsegment of the globus pallidus. These are two nuclei in thebasal ganglia, a part of the brain involved in motor activity.Dysfunction of the basal ganglia is associated with movementdisorders such as Parkinson's disease and Huntington's disease.The model is used to test hypotheses on the role of the basalganglia in both normal and pathological movement. Numerousexperiments have demonstrated that neurons within the basalganglia display a rich variety of dynamic behavior; moreover,patterns of neuronal activity, both spatial and temporal, aredifferent between a normal and a pathological state. Theinvestigators characterize the possible patterns of neuronalactivity that arise in the model and determine how these patternschange with respect to modulations of network parameters andstructure. A long term goal is to develop a model realisticenough so that it can shed light upon the key parameters andmechanisms responsible for the generation and modulation ofobserved activity patterns. A mathematical theory for the analysis of neuronal dynamicshelps illuminate the role played by various components of a modelin generating a particular population rhythm. These componentsmay correspond to some intrinsic property of individual cells, orto some network property such as the strength and type ofsynaptic coupling or the probability that two cells communicatewith each other. Clarification of the mechanisms underlyingdifferent activity patterns may lead to a classification of allpossible rhythms that can emerge from a given network, and enableus to determine how complicated a model should be in order todisplay some observed behavior. It also helps predicttransitions of the network behavior as parameters in the modelare varied. The investigators develop models for neuronaldynamics, and in particular of electrical activity in thesubthalamic nucleus and external segment of the globus pallidus.These are two nuclei in the basal ganglia, a part of the braininvolved in motor activity. Dysfunction of the basal ganglia isassociated with movement disorders such as Parkinson's diseaseand Huntington's disease. The model is used to test hypotheseson the role of the basal ganglia in both normal and pathologicalmovement. Such models may help illuminate both fundamentalneuroscience questions and clinical issues about how the brainand central nervous system work.

Terman0103822 研究人员和他的同事开发了几何，动力系统工具，用于分析生物物理，基于电导的模型，用于广泛的神经元网络。这些系统出现在许多应用中，包括运动，感觉处理和学习。 他们还为睡眠节律、癫痫和帕金森震颤的产生开发了计算模型。 研究人员还建立并完善了丘脑底核和苍白球外段电活动的数学和计算模型。 这是基底神经节中的两个核团，基底神经节是大脑中参与运动活动的一部分。基底神经节功能障碍与运动障碍有关，如帕金森病和亨廷顿病。该模型用于检验基底神经节在正常和病理运动中的作用的假设。 大量的实验已经证明，基底神经节内的神经元显示出丰富多样的动态行为;此外，神经元活动的模式，空间和时间，是不同的正常和病理状态之间。 研究人员描述了模型中出现的神经元活动的可能模式，并确定这些模式如何随着网络参数和结构的调制而变化。 一个长期的目标是开发一个足够真实的模型，以便它可以阐明负责产生和调节观察到的活动模式的关键参数和机制。 神经元动力学分析的数学理论阐明了模型的各个组成部分在产生特定群体节律中所起的作用。 这些成分可能对应于单个细胞的某些内在属性，或一些网络属性，如突触耦合的强度和类型或两个细胞相互通信的概率。 阐明不同活动模式的机制可能会导致对给定网络中可能出现的所有可能的节律进行分类，并使我们能够确定模型应该有多复杂，以显示一些观察到的行为。 它还有助于预测模型中参数变化时网络行为的转变。 研究人员开发了神经元动力学模型，特别是丘脑底核和苍白球外侧段的电活动模型。这两个核团位于基底神经节，是大脑参与运动活动的一部分。 基底神经节功能障碍与运动障碍有关，如帕金森病和亨廷顿病。 该模型用于测试基底神经节在正常和病理运动中的作用的假设。 这样的模型可能有助于阐明神经科学的基本问题和关于大脑和中枢神经系统如何工作的临床问题。