West Virginia University Stroke COBRE

项目总结。 在美国，中风是导致成年人残疾的主要原因，因此迫切需要了解中风的影响 中风对大脑功能和结构重组的影响以及这些神经过程如何塑造行为 恢复，最终目标是使用这些信息来优化中风的结果。的具体目标 西弗吉尼亚大学(WVU)Stroke Cobre包括(1)扩大资助的临界质量 研究人员进行中风恢复研究，(2)加强创新科学核心，支持 并推进基础和翻译中风研究，以及(3)促进正在进行的 独立的、可持续的、多学科的中风研究主题计划。《中国日报》的副刊 提升机构数据科学能力建议开发和操作综合图表 数据科学方法，被称为西弗吉尼亚大学大脑多尺度实验中风中心(WVU Brain Mesh)， 基础和临床前研究将使用提取的数据产生新的和重要的见解 来自对啮齿动物多尺度大脑功能网络和中风的研究。这种方法将允许我们使用 大多数数据科学方法本身并不适合利用的数据，而对现代 数据科学。具体地说，在目标1中，使用网络科学方法(即基于图论)，我们提出 建立一个综合分析平台，该平台(1)将提供从微观数据提取的数据的用户友好计算 和(2)应用基于图论的方法来计算每个 并对相应的脑网络进行拓扑特征评估。在目标2中，我们将使用 多管齐下，包括科学界的参与、教育和有指导的研究 激发人们对数据科学，特别是图表数据科学的兴趣，以增强知识，提供数据- 相关技能，并协助研究人员使用西弗吉尼亚州立大学的大脑网络来生成和测试假设。因此，这一点 附录将扩展西弗吉尼亚大学的数据科学能力，其方式将与 WVU Stroke Cobre，最终提供肯定会增加母公司的协同机会 奖的影响通过培养参与基于数据科学的方法来理解中风的机会- 神经网络的相关变化。我们平台的连续性、可持续性和扩展超越了这两个方面- 补充的年限将通过计划中的脑网络和数据科学的全面整合来实现 西弗吉尼亚大学卒中中心第三阶段啮齿动物行为核心提供服务的探讨 支持将数据科学方法纳入外部资金申请。

PROJECT SUMMARY. Stroke is a leading cause of adult disability in the United States, creating urgency in understanding the impact of stroke on brain functional and structural reorganizations and how these neural processes shape behavioral recovery, with the ultimate goal of using this information to optimize stroke outcomes. The Specific Aims of the West Virginia University (WVU) Stroke CoBRE include (1) expanding the critical mass of funded investigators conducting stroke recovery research, (2) strengthening innovative scientific cores that support and advance basic and translational stroke research, and (3) advancing the ongoing development of an independent, sustainable, multidisciplinary thematic program of stroke research. The Supplement to Enhance Institutional Data Science Capacity proposes to develop and operationalize an integrative graph data science approach, known as the WVU Brain Multiscale Experimental Stroke Hub (WVU Brain MESH), for foundational and preclinical research that will generate novel and important insights using data extracted from studies of multiscale brain functional networks and stroke in rodents. This approach will allow us to use data that most data science methods are not inherently suited to leverage and is far more effective for modern data science. Specifically, in Aim 1, using network science approaches (i.e., graph theory-based), we propose to build an integrative analytic platform that (1) will offer user-friendly computing of data extracted from micro- to macroscale brain networks and (2) applies graph theory-based approaches to compute graphs of each corresponding brain network and to evaluate the topological features of them. In Aim 2, we will use a multipronged approach that includes scientific community engagement, education, and mentored research to spark interest in data science, and specifically graph data science, to enhance knowledge, provide data- relevant skills and assist researchers in using WVU Brain MESH to generate and test hypotheses. Thus, this supplement will expand data science capacity at WVU in a way that aligns with all three Specific Aims of the WVU Stroke CoBRE, ultimately providing synergistic opportunities that are certain to increase the parent award’s impact by fostering opportunity to engage in data science-based approaches to understand stroke- related changes to neural networks. Continuity, sustainability, and expansion of our platform beyond the two- year period of the supplement will be achieved by planned full integration of brain networks and data science approaches into services provided by the Rodent Behavior Core in Phase III of the WVU Stroke CoBRE and by supporting the inclusion of data science approaches in applications for extramural funding.