SenseLab: Integration of Multidisciplinary Sensory Data

摘要 SenseLab由8个可互操作的数据库组成的套件旨在支持我们对模型的研究 大脑组织系统，嗅球，并与 神经科学和神经信息学社区。在过去的5年中，一项计划项目赠款 使我们能够开始从突触和细胞水平移动到微电路水平，在这个R01中 格兰特，我们将直接建立在这项工作的基础上。首先，我们将继续开发我们最常用的 用于树突信号整合分析的数据库--NeuronDB和ModelDB，以及ORDB， 支持嗅觉受体的工作，嗅觉受体是基因组中最大的家族。我们将继续参与 在神经科学数据库门户、神经科学信息框架和国际 神经信息学协调设施。我们将继续演示数据库如何支持 神经科学研究和两个新的研究项目，以开发提供洞察力的计算模型 转换成实验数据。一个项目是加深对我们最近的实验证据的洞察 对广泛分布的细胞柱的跨突触追踪，我们假设这些细胞柱参与了处理 气味地图。我们将分析这些数据，并使用它来首先改进简化的微电路，其中 肾小球细胞柱对来自气味映射的兴奋性输入做出反应，并通过 与距离无关的肾小球柱之间的侧向抑制。通过不断的测试 实验数据，我们将模型扩展到100列，然后扩展到2,000列，以表征全球 气味地图的处理达到了用实验方法不可能达到的程度。这项工作将付诸实施 作为与瑞士蓝脑项目并行的试点项目，以现实为基础的大型 扩展大脑皮层网络。将开发一个新的数据库，微电路数据库，以支持这一和相关的 微电路组织的研究。第二个新项目将扩展我们的计算分析 能量需求在嗅小球的侧向抑制相互作用中，提供更多 彻底了解处理气味图谱的微电路的能量需求。一种新的 数据库项目是应用NeuronDB和ModelDB来分析早期发病机制的影响 神经退行性疾病对树突信号整合的影响。为此，我们正在开发一种 新的数据库，脑药理学(BrainPharm)。所有这些工作都将受益于持续的支持和 由耶鲁医学信息学中心和神经元模拟环境开发 一队。

Abstract The SenseLab suite of 8 interoperable databases is aimed at supporting our research on a model system for brain organization, the olfactory bulb, and at sharing these and related resources with the neuroscience and neuroinformatics communities. During the past 5 years a Program Project grant has enabled us to begin to move from the synaptic and cell levels to the microcircuit level, and in this R01 grant we will build directly on this work. First, we will continue development of our most heavily used databases - NeuronDB and ModelDB - for the analysis of dendritic signal integration, and ORDB, supporting work on olfactory receptors, the largest family in the genome. We will continue to participate in the Neuroscience Database Gateway, the Neuroscience Information Framework, and the International Neuroinformatics Coordinating Facility. We will continue to demonstrate how databases support neuroscience research with two new research projects to develop computational models that give insight into experimental data. One project is to deepen insight into our recent experimental evidence from transsynaptic tracing for widely distributed cell columns, which we hypothesize are involved in processing odor maps. We will analyze this data and use it to refine first a reduced microcircuit in which the glomerular cell columns respond to the excitatory input from the odor maps and process it through distance-independent lateral inhibition between glomerular columns. With continual testing by the experimental data, we will scale up the model to 100 columns, then to 2,000, to characterize the global processing of odor maps to an extent not possible with experimental methods. This work will be carried out as a pilot project in parallel with the Blue Brain Project in Switzerland on realistically-based large- scale cortical networks. A new database, MicrocircuitDB, will be developed to support this and related studies of microcircuit organization. A second new project will extend our computational analysis of energy demands in the olfactory glomerulus to the lateral inhibitory interactions, to provide a more thorough understanding of the energy demands of the microcircuits that process odor maps. A new database project is to apply NeuronDB and ModelDB to analyzing the impact of the early pathogenesis of neurodegenerative disorders on dendritic signal integration. For this purpose we are developing a new database, Brain Pharmacology (BrainPharm). All of this work will benefit from continued support and development by the Yale Center for Medical Informatics, and by the NEURON simulation environment team.