Biophysical Modeling of Neural Integration

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示，允许动物相对于惯性参考系进行导航。许多努力都集中在系统水平上和通过循环反馈网络对前庭整合器进行建模，但是促进神经整合的生物物理机制仍然未知。单个积分神经元在积分存储容量和树突分支结构方面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/功能方面存在技术困难，并且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成熟金鱼模型中的这些不足之处，在该模型中，积分神经元很容易识别，但在实际建模和结构功能实验中数量有限。我们的中心假设是，空间延伸的单细胞特性（包括树突拓扑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，将通过以下方式进行测试：（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； （2）利用新颖的成像、图像分析和几何技术参数化3D树突分支结构； (3) 通过高分辨率形态数据的区室建模验证目标 1 中的功能和目标 2 中的形态之间确定的关系，并评估包含生物物理现实神经元模型的简化版本的电路模型。开发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是该项目的独特之处。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前庭神经整合器的持续神经活动的贡献，以及神经科学多个领域中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，从而制定预防、治疗和逆转平衡和平衡功能障碍的合理策略，并理解疾病和短期记忆丧失的结构决定因素。

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.