CRCNS: Deciphering the Dynamical Multi-Scale Structure-Function Relation of Dendritic Spines

CRCNS：破译树突棘的动态多尺度结构-功能关系

• 批准号: 9100682
• 负责人: Mark H Ellisman
• 金额: $ 17.65万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9100682
• 关键词: Accounting; Actins; Address; Affect; Algorithms; Alzheimer' s Disease; Architecture; Biological; Biology; Biophysics; Brain; Brain Diseases; Calcium; Career Choice; Chemical Dynamics; Chemicals; Collaborations; Complex; Computational Science; Computer Simulation; Crowding; Cytoskeleton; Data; Dendritic Spines; Dependency; Devices; Diffusion; Disease; Down Syndrome; Electron Microscope; Electrons; Electrophysiology (science); Electrostatics; Elements; Endoplasmic Reticulum; Engineering; Environment; Equation; Fragile X Syndrome; Generations; Geometry; Germany; Goals; Harvest; Head and neck structure; Homeostasis; In Vitro; International; Ions; Kinetics; Laboratories; Lead; Learning; Macromolecular Complexes; Mathematics; Membrane; Memory; Methods; Microfilaments; Microscopic; Modeling; Modification; Molecular; Morphology; Neck; Neurosciences; Neurotransmitter Receptor; Organelles; Performance; Physics; Positioning Attribute; Process; Property; Recruitment Activity; Research; Research Personnel; Resolution; Rest; Role; STEM field; Scheme; Scientist; Shapes; Signal Transduction; Structure; Surface; Synapses; Synaptic Transmission; Synaptic plasticity; System; Technology; Testing; Tissues; Training; Underrepresented Minority; United States; Vertebral column; biophysical model; brain tissue; coping; design; electrical property; graduate student; in vivo; information processing; insight; mathematical analysis; meetings; microscopic imaging; nanometer; nanoscale; neural information processing; neuroinformatics; neurotransmission; novel; physical science; polymerization; postsynaptic; programs; receptor; reconstruction; research study; simulation; theories; tomography; training opportunity

DESCRIPTION (provided by applicant): Our ability to store and retain new information rests upon the brain's immense plastic capabilities. Experimental evidence suggests that morpho-chemical modifications at the level of single dendritic spines may contribute to learning and memory but we lack both a quantitative and a mechanistic understanding of how spines function. To address this deficit, the proposed project aims to explore how the ultra-structural three-dimensional architecture of dendritic spines shapes their electro-chemical signal transduction and how structural changes alter the transduction and thus affect synaptic efficacy. State-of-the-art 3D electron microscope (EM) reconstructions endowed with precise ionotropic receptor kinetics and accurate biophysical models will be used to construct a nanometer-resolution model for dendritic spines. To simulate the electro-chemical dynamics within such a complex multi-scale environment, advanced numeric schemes such as finite-element discretization and fast multi-level solvers will be employed. By performing detailed experiments in silico, the primary factors that influence ionic current conduction in spines will be identified and then used to systematically derive a low-dimensional spine model amenable to exact mathematical analysis. Both, the full and the reduced model will allow the consortium to study the sub-cellular information-processing capabilities of single spines, and to compare the results with in vivo and in vitro data. The models will enable researchers to develop and test spine-related experimental hypotheses and to interpret data recorded in healthy and disease-modified tissue within a unified framework. Objective 1: Reconstruct Dendritic Spines in 3D at Nanometer Resolution; Objective 2: Establish a Biophysically Realistic Nanometer-Resolution Spine Model; Objective 3: Develop High-Performance Numerical Methods to Simulate the Spine Model; Objective 4: Use Simulations and Theory to Study the Computations of Dendritic Spines. The project aims to relate the multi-scale biological organization of dendritic spines to possible functional consequences at the macroscopic and systems level. In the era of ever-increasing super-computing capabilities, any mechanistic model of synaptic transmission and postsynaptic integration should start with a clear insight into precisely how biophysics orchestrates the signal transduction at the smallest scales. Deciphering the impact of micro-structural features on spine dynamics will be a stepping-stone towards understanding neural signal propagation and synaptic plasticity, and likely reveal novel sub-cellular computational principles. The findings wil deepen our understanding of neural information processing in healthy and disease-modified brains and may lead to new designs for neuromorphic devices. Alterations in spine morphology are seen in various brain diseases [1] including Down's syndrome and fragile X syndrome [2]. Similarly, changes of the intra-spine calcium dynamics and homeostasis have been documented for Alzheimer's disease [3]. Developing new cures and therapies for these diseases will profit from a better understanding of the relation between the dynamical structure and the function of dendritic spines. To reach this goal, in continuation of past NSF-supported projects, we will recruit and train young scientists to meet the interdisciplinary challenges of modern multi-scale and multi-modal data-driven biology, where progess is driven not only by neuroscience, but also engineering, mathematics and physical sciences, computational science and neuroinformatics The planned collaboration between the three laboratories in the US and Germany will generate international training opportunities for graduate students and postdoctoral researchers, and the participation of researchers in programs that encourage underrepresented minorities to pursue career paths in STEM disciplines.

描述(由申请者提供)：我们存储和保留新信息的能力取决于大脑巨大的可塑性。实验证据表明，在单个树突棘突水平上的形态化学修饰可能有助于学习和记忆，但我们缺乏对棘突如何发挥作用的定量和机械理解。为了解决这一缺陷，拟议的项目旨在探索树突棘的超结构三维结构如何塑造其电化学信号转导，以及结构变化如何改变转导从而影响突触效率。最先进的三维电子显微镜(EM)重建被赋予了精确的电离性受体动力学和精确的生物物理模型，将被用来构建树突棘的纳米分辨率模型。为了模拟这种复杂的多尺度环境中的电化学动力学，将采用有限元离散和快速多层求解等先进的数值格式。通过在硅胶中进行详细的实验，将确定影响脊离子电流传导的主要因素。 然后用来系统地推导出符合精确数学分析的低维脊椎模型。完整的和简化的模型都将允许该联盟研究单个脊椎的亚细胞信息处理能力，并将结果与体内和体外数据进行比较。这些模型将使研究人员能够开发和测试与脊柱相关的实验假说，并在统一的框架内解释记录在健康和疾病修改的组织中的数据。目标1：以纳米分辨率重建树突棘；目标2：建立生物物理上逼真的纳米分辨率脊柱模型；目标3：开发高性能的数值方法来模拟脊柱模型；目标4：使用模拟和理论来研究树突棘的计算。 该项目旨在将树突棘的多尺度生物组织与宏观和系统层面上可能产生的功能后果联系起来。在超级计算能力不断增强的时代，任何突触传输和突触后整合的机械模型都应该从清楚地了解生物物理学是如何协调信号开始的 在最小的尺度上进行转导。破译微结构特征对脊柱动力学的影响将是了解神经信号传播和突触可塑性的踏脚石，并可能揭示新的亚细胞计算原理。这些发现将加深我们对健康和疾病修饰的大脑中神经信息处理的理解，并可能导致神经形态设备的新设计。 脊椎形态的改变见于各种脑部疾病，包括唐氏综合症和脆性X综合征[2]。同样，脊椎内钙动力学和稳态的变化已被记录为阿尔茨海默病[3]。更好地了解树突棘的动态结构和功能之间的关系，将有助于开发这些疾病的新疗法和疗法。为了实现这一目标，在过去NSF支持的项目的延续下，我们将招募和培训年轻科学家，以应对现代多尺度和多模式数据驱动生物学的跨学科挑战，在现代数据驱动生物学中，进步不仅由神经科学推动，也由工程、数学和物理科学、计算科学和神经信息学推动。美国和德国的三个实验室计划中的合作将为研究生和博士后研究人员创造国际培训机会，以及研究人员参与鼓励未被充分代表的少数族裔在STEM学科中追求职业道路的计划。