Neural Models of Plasticity: Molecules to Networks

描述(由申请人提供)： 神经系统的主要功能是以导致适应行为的方式处理信息。两种不同的方法，一种是理论的，另一种是经验的，正在被用来探索神经元可塑性在发育、学习、记忆、信息处理和其他复杂的大脑功能中的作用。该理论方法根据已知的和假想的神经功能原理，用数学模型模拟和合成大脑功能。经验方法描述了神经元的复杂生化和生物物理属性，决定其连通性的规则，以及在发育和学习过程中修改其属性和连接的机制。虽然这两种方法传统上是独立使用的，但神经生物学家、心理学家和适应系统理论家越来越认识到，理解大脑的进步依赖于这两种方法的结合。此外，在许多情况下，关于系统的知识已经成熟到不仅有足够的信息量来保证计算方法的程度，而且在对系统的理解方面的进一步进步也需要这样做。 该计划项目的总体目标是使用计算方法来检查多个组织水平上的神经元可塑性，范围从亚细胞神经元隔间内的分子动力学，到神经元内的遗传网络，再到神经网络机制。研究海马神经元和相关结构的可塑性，并确定其对更高水平的处理的贡献，这一共同目标将各个项目联系在一起。这些单独的项目将检查：1)支持可塑性的基因网络的动力学特性；2)突触后钙/钙调蛋白信号通路的量化行为，它在神经元可塑性中发挥重要作用；3)突触可塑性的分子水平的动力学及其作为海马可塑性底物的重要性；以及4)海马体从多模式输入构建高阶认知表征的神经网络机制。此外，各个项目将得到计算核心基金的支持，该基金将作为开发计算模型和项目间信息交流的资源。

DESCRIPTION (provided by applicant): The main function of the nervous system is to process information in ways that lead to adaptive behavior. Two different approaches, one theoretical and the other empirical, are being used to explore the role of neuronal plasticity in development, learning, memory, information processing, and other complex brain functions. The theoretical approach simulates and synthesizing brain function with mathematical models based on known and hypothesized principles of neural function. The empirical approach delineates the complex biochemical and biophysical properties of neurons, the rules that determine their connectivity, and the mechanisms through which their properties and connections are modified during development and learning. Although these two approaches have traditionally been used independently, there is a growing realization among neurobiologists, psychologists, and adaptive systems theorists that progress in understanding the brain is dependent on a combination of both approaches. In addition, in many cases, the knowledge of systems has matured to the point where there is not only a sufficient body of information to warrant a computational approach, but further progress in the understanding of the system requires it. The overall goal of the Program Project is to use computational approaches to examine neuronal plasticity at multiple levels of organization, ranging from molecular dynamics within subcellular neuronal compartments, to genetic networks within neurons, to neural network mechanisms. The individual Projects are linked by the common goal of investigating plasticity in neurons in the hippocampus and related structures and determining its contributions to higher levels of processing. The individual Projects will examine: 1) the dynamical properties of gene networks underlying plasticity; 2) the quantitative behavior of the postsynaptic Ca2+/calmodulin signaling pathway that plays an essential role in neuronal plasticity; 3) dynamics of synaptic plasticity at the molecular level and its importance as a substrate for plasticity in the hippocampus; and 4) the neural network mechanisms by which the hippocampus constructs high-order cognitive representations from multimodal inputs. In addition, the individual Projects will be supported by a Computational Core Facility that will serve as a resource for developing computational models and for the exchange of information among the projects.