Interdiscplinary Training in Computational Neuroscience

此申请要求更新对本科生和研究生培训计划的支持 在卡内基梅隆大学（CMU）和 匹兹堡大学（皮特），并在计算神经科学暑期学校， 本科生，将向来自学院和大学的学生提供 在整个美国。TPCN将由神经基础中心管理。 认知（CNBC），一个由CMU和皮特联合运营的伞式组织， 成立于1994年，旨在促进对大脑神经机制的跨学科研究。 职能，现在包括107名教师在20个部门的任命。研究 在神经科学领域的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，神经科学家必须利用，理解， 开发新技术，获取和分析更大的数据集， 与神经生物学系统的复杂性直接相关。在这一努力中， 而采用新的计算方法已成为进步的关键。主 TPCN计划的目标是帮助培养新一代跨学科的神经科学家， 较强的量化能力。第二个目标是计算和数据分析的结合 通过加强本科生的培训， 研究生水平。 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（涉及计算机）的深度要求 科学、工程、数学和/或统计学）;他们将在以下方面拥有丰富的经验： 至少一个实验室;他们将参加杂志俱乐部和研讨会内 匹兹堡的大型计算神经科学社区为期一年的本科生将采取 数学，计算机编程，统计学和神经科学课程;他们将参加一个 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，他们还将完成夏季 程序.暑期项目的本科学员将参加一系列关于 计算神经科学的主题，包括Matlab教程，统计方法， 微分方程的基本原理，神经编码的思想，并将完成一项研究 项目所有受训人员都将接受负责任地开展研究的培训。5年来， 资金，TPCN将支持20 NRSA研究生，10非NRSA研究生，30 本科全年研究员，和60名本科暑期研究员。

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.