Biophysical Modeling of Neural Integration

神经整合的生物物理建模

• 批准号: 6782183
• 负责人: SUSAN L WEARNE
• 金额: $ 36.85万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6782183
• 关键词: biophysics; cell biology; cell cell interaction; cell membrane; cell morphology; cell population study; computational neuroscience; confocal scanning microscopy; dendrites; eye movements; goldfish; model design /development; morphometry; neural plasticity; neuroanatomy; neuroimaging; neurons; neurophysiology; physical model; short term memory; single cell analysis; space perception; synapses

DESCRIPTION (provided by applicant): Neurons of the velocity storage neural integrator store a 'short-term memory' of head velocity that provides a central representation of head and body orientation in space, allowing animals to navigate with respect to an inertial reference frame. Much effort has been focused on modeling vestibular integrators at the systems level and by recurrent feedback networks, however the biophysical mechanisms that subserve neural integration remain unknown. Individual integrator neurons exhibit a corresponding variability in integrator storage capacity and dendritic branching structure, but to date no studies have attempted to relate these. This is primarily due to technical difficulties in obtaining the requisite structure/function to begin biophysical modeling in mammals, and lack of computational and analytic techniques to perform precise geometric modeling. A multidisciplinary approach combining mathematical, experimental and imaging expertise will address these inadequacies in the well-developed goldfish model, in which integrator neurons are easily identified, and finite in number for realistic modeling and structure-function experiments. Our central hypothesis, that spatially-extended single cell properties including dendritic topology and its interaction with active membrane and synaptic properties are essential elements of neural integration, will be tested by (1) characterizing the diversity in integrator neurons and its role in oculomotor behavior and plasticity; (2) parametrising 3-D dendritic branching structure with novel imaging, image analysis and geometric techniques; (3) verifying the relationships determined between function in Aim 1 and morphology in Aim 2 by compartment modeling of high-resolution morphologic data, and evaluation of circuit models containing reduced versions of biophysically realistic neuron models. Development of new mathematical techniques for relating neural dynamics to local and global properties of dendritic structures is a unique feature of this project. In the long term, we want to understand the contributions of cellular properties and interactions between realistic neurons to the persistent neural activity that underlies vestibular neural integrators specifically, and fundamental mechanisms of short-term or working memory in multiple areas of neuroscience. A mechanistic understanding of neural integration will yield basic information leading to rational strategies for prevention, treatment and reversal of balance and equilibrium dysfunction, and for understanding the structural determinants of disorders and loss of short-term memory.

描述（由申请人提供）：速度存储神经积分器的神经元存储头部速度的“短期记忆”，提供头部和身体在空间中的方向的中心表征，使动物能够在惯性参照系中导航。很多研究都集中在系统水平和循环反馈网络的前庭整合器建模上，然而，支持神经整合的生物物理机制仍然未知。单个积分器神经元在积分器存储容量和树突分支结构上表现出相应的变异性，但迄今为止还没有研究试图将这些联系起来。这主要是由于在获得哺乳动物生物物理建模所需的结构/功能方面的技术困难，以及缺乏执行精确几何建模的计算和分析技术。结合数学，实验和成像专业知识的多学科方法将解决发达的金鱼模型中的这些不足之处，其中积分器神经元很容易识别，并且用于现实建模和结构-功能实验的数量有限。我们的中心假设是，空间扩展的单细胞特性，包括树突拓扑结构及其与活性膜和突触特性的相互作用是神经整合的基本要素，将通过(1)表征整合神经元的多样性及其在动眼行为和可塑性中的作用来验证；(2)利用新的成像、图像分析和几何技术对三维树突分支结构进行参数化；(3)通过高分辨率形态学数据的隔室建模，验证Aim 1功能与Aim 2形态之间的关系，并评估包含生物物理真实神经元模型的简化版本的电路模型。将神经动力学与树突结构的局部和全局特性联系起来的新数学技术的发展是这个项目的独特之处。从长远来看，我们希望了解细胞特性和现实神经元之间的相互作用对持续神经活动的贡献，特别是前庭神经整合器，以及神经科学多个领域短期或工作记忆的基本机制。对神经整合的机制理解将产生基本信息，从而导致预防、治疗和逆转平衡和平衡功能障碍的合理策略，以及理解障碍和短期记忆丧失的结构性决定因素。