Interdisciplinary Training in Computational Neuroscience

描述（由申请人提供）：本申请要求更新卡内基梅隆大学（CMU）和匹兹堡大学（皮特）的计算神经科学（TPCN）本科生和研究生培训计划的支持，以及为本科生开设的计算神经科学暑期学校，这些课程将提供给来自美国各地学院和大学的学生。TPCN将由认知神经基础中心（CNBC）管理，CNBC是CMU和Pitt联合运营的一个伞式组织，成立于1994年，旨在促进对大脑功能神经机制的跨学科研究，该组织目前包括107名教师，在20个部门任职。神经科学研究对于解决神经和心理健康障碍的原因至关重要。如果神经科学领域要继续快速发展，神经科学家必须使用、理解和开发新技术，获取和分析更大的数据集，并更直接地处理神经生物学系统的复杂性。在这一努力中，广泛开发和采用新的计算方法对进步至关重要。TPCN计划的主要目标是帮助培养新一代具有强大定量技能的跨学科神经科学家。第二个目标是通过加强本科生和研究生水平的培训，将计算和数据分析原理纳入神经科学领域。学员将在垂直整合的跨学科研究团队中工作。研究生将参加认知神经科学，神经生理学和系统神经科学的课程;他们将满足他们选择的定量方法的深度要求（涉及计算机科学，工程，数学和/或统计学）;他们将在至少一个实验室中拥有丰富的经验;他们将参加大型匹兹堡计算神经科学社区内的期刊俱乐部和研讨会。为期一年的本科生将参加数学，计算机编程，统计学和神经科学课程;他们将参加神经科学或心理学的额外课程和计算神经科学课程;他们将完成为期一年的研究项目。此外，他们还将完成暑期课程。暑期课程的本科学员将参加一系列关于计算神经科学主题的讲座，包括Matlab教程，统计方法，微分方程基础和神经编码思想，并将完成一个研究项目。所有受训人员都将接受负责任地开展研究的培训。在5年的资金，TPCN将支持20名NRSA研究生，10名非NRSA研究生，30名本科一年的研究员，和60名本科暑期研究员。

DESCRIPTION (provided by applicant): This application requests renewal of support for undergraduate and graduate training programs in computational neuroscience (TPCN) at both Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), and for a summer school in computational neuroscience for undergraduates, which will be available to students coming from colleges and universities throughout the United States. The TPCN will administered by the Center for the Neural Basis of Cognition (CNBC), an umbrella organization operated jointly by CMU and Pitt that was established in 1994 to foster interdisciplinary research on the neural mechanisms of brain function, which now comprises 107 faculty having appointments in 20 departments. Research in neuroscience is crucial for attacking the causes of neurological and mental health disorders. If the field of neuroscience is to continue its rapid advance, neuroscientists must use, understand, and develop new technologies, acquire and analyze ever larger data sets, and grapple more directly with the complexity of neurobiological systems. In this effort, widespread development and adoption of new computational methods has become essential to progress. The primary goal of TPCN programs is to help train a new generation of interdisciplinary neuroscientists with strong quantitative skills. A second goal is the incorporation of computational and data analytic principles into the field of neuroscience through enhanced training at the undergraduate and graduate level. Trainees will work in vertically integrated, cross-disciplinary research teams. Graduate students will take courses in cognitive neuroscience, neurophysiology, and systems neuroscience; they will satisfy a depth requirement in quantitative methodology of their choice (involving computer science, engineering, mathematics, and/or statistics); they will have extended experience in at least one experimental laboratory; and they will take part in journal clubs and seminars within the large Pittsburgh computational neuroscience community. Year-long undergraduates will take courses in mathematics, computer programming, statistics, and neuroscience; they will take an additional course in neuroscience or psychology and a course in computational neuroscience; and they will complete a year-long research project. In addition, they will complete the summer program. Undergraduate trainees in the summer program will sit through a series of lectures on topics in computational neuroscience, including tutorials in Matlab, statistical methods, fundamentals of differential equations, and ideas of neural coding, and will complete a research project. All trainees will receive training in responsible conduct of research. Across 5 years of funding, TPCN will support 20 NRSA graduate students, 10 non-NRSA graduate students, 30 undergraduate year-long fellows, and 60 undergraduate summer fellows.