Interdisciplinary Training in Computational Neuroscience

计算神经科学跨学科培训

• 批准号: 7213051
• 负责人: ROBERT E KASS
• 金额: $ 3.88万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-30 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7213051
• 关键词: Interdisciplinary; Training; Computational; Neuroscience

DESCRIPTION (provided by applicant): Neuroscience increasingly requires the integration of sophisticated experimental and quantitative approaches. The development of increasingly sophisticated models and the analysis of massive sources of data routinely push neuroscientists to the limits of their quantitative and analytical abilities. In this way, computational neuroscience has become an element of the mainstream of neuroscience research. However, few training programs have adapted to this increase in the importance of quantitative approaches in neuroscience, leaving many students under prepared to exploit future opportunities in the field. Here we propose training programs involving faculty from more than ten departments at Carnegie Mellon University and the University of Pittsburgh that seek to move computational neuroscience into the mainstream of the field. Specifically, we seek to: 1) expose hundreds of undergraduate students in biomedical fields and hundreds of students in quantitative disciplines to computational neuroscience each year. 2) develop a comprehensive research and education program that provide excellent in depth training in computational neuroscience to 10-15 undergraduates from a variety of disciplines each year 3) develop and extend the training of our graduate students to include substantial additional education in computational neuroscience and 4) expose a group of a dozen talented students primarily from other institutions to training and research in computational neuroscience. This last group of students will consist mostly of students from groups underrepresented in the field of computational neuroscience. The training will be broad and interdisciplinary including biological and psychological approaches on the experimental side and statistical, computational and mathematical on the quantitative side.

描述（由申请人提供）：神经科学越来越多地需要整合复杂的实验和定量方法。越来越复杂的模型的发展以及大量数据来源的分析通常将神经科学家推向其定量和分析能力的限制。这样，计算神经科学已成为神经科学研究主流的元素。但是，很少有培训计划适应神经科学中定量方法的重要性的增加，因此许多学生准备利用该领域的未来机会。在这里，我们提出了涉及卡内基梅隆大学和匹兹堡大学十多个系的教职员工的培训计划，这些培训计划试图将计算神经科学转移到该领域的主流。具体来说，我们寻求：1）每年在生物医学领域中揭露数百名本科生，并在定量学科中揭露计算神经科学的定量学科。 2）制定一项全面的研究和教育计划，该计划每年从各种学科中为10 - 15名本科生提供了极好的深入培训。最后一组学生将主要由来自计算神经科学领域中代表性不足的学生组成。该培训将是广泛的跨学科，包括实验方面的生物学和心理方法以及定量方面的统计，计算和数学。