INTERDISCIPLINARY TRAINING IN COMPUTATIONAL NEUROSCIENCE

项目摘要 要了解大脑的许多疾病，就必须解决它的复杂性。 越来越多的大型和复杂的数据集正在收集，但用于分析和 数据的建模还不可用。越来越多接受过计算神经科学培训的研究人员 迫切需要的。该项目支持研究生和本科生的培训计划， 卡内基梅隆大学（CMU）和卡内基梅隆大学（University of Carnegie Mellon）的计算神经科学（TPCN） 匹兹堡（皮特），和计算神经科学的本科生暑期学校，这是 提供给来自美国各地学院和大学的学生。 CMU-Pitt TPCN有16个计算神经科学培训学院，22个培训学院， 实验室主要是实验性的，20个培训教师的实验室都是 计算和实验。在研究生阶段，TPCN提供神经科学博士课程 计算（PNC）和联合博士课程与CMU的统计部门（PNC-Stat）及其 机器学习部门（PNC- MLD），都设置在一个高度学院化，跨学科的 我们的认知神经基础中心（CNBC）的环境，该中心由 CMU和皮特。CNBC成立于1994年，旨在促进神经系统的跨学科研究。 大脑功能的机制，现在包括145名教师在22个部门的任命。 在学士学位课程方面，我们会在暑假期间，吸纳大量本地学生 来自全国各地的一群学生在此更新资助期间，该项目将 加强统计和机器学习在整个培训方案中的作用; (2)修改夏季本科课程，在大学开设为期两周的“靴子营”， 开始，其中包括计算神经科学的20个讲座概述;（3）在线创建 材料，与靴子营，这将不仅服务于我们自己的学生， 计算神经科学培训的更大世界;（4）提高我们的少数民族 （a）利用靴子训练营和网上材料， 对目标校园进行宣传访问，以及（B）创建和运行一个为期一年的“桥梁”计划 为博士课程做好准备。 TPCN学员在垂直整合的跨学科研究团队中工作。研究生 参加为期一年的计算神经科学课程，该课程将建模和现代统计学联系起来 神经科学的机器学习方法。以确保他们在核心神经科学方面的能力 他们还学习认知神经科学、神经生理学和系统学的课程。 神经科学然后，他们在相关的定量学科中追求深度，如计算机 科学、工程、数学或统计学。研究生在at方面有丰富的经验 至少有一个实验室，他们参加杂志俱乐部和研讨会内， 匹兹堡神经科学社区。一年的本科生学习数学课程， 计算机编程、统计学和神经科学;他们还学习神经科学课程 或者心理学和计算神经科学的课程，他们完成了一年的研究 项目此外，他们还完成了TPCN夏季计划。本科生暑期实习生 程序通过靴子训练营在计算神经科学的主题，包括教程， Matlab，统计方法，微分方程基础，神经编码思想; 然后在精心指导下完成研究项目。所有学员将接受以下培训： 负责任地进行研究。在5年的资助，TPCN支持20 NRSA毕业生 学生，10名非NRSA研究生，30名本科一年的研究员，60名本科生 暑期伙伴。

Project Summary To understand the many disorders of the brain it is necessary to grapple with its complexity. Increasingly large and complicated data sets are being collected, but the tools for analyzing and modeling the data are not yet available. More researchers trained in computational neuroscience are desperately needed. This project supports graduate and undergraduate training programs in computational neuroscience (TPCN) at both Carnegie Mellon University (CMU) and the University of Pittsburgh (Pitt), and a summer school in computational neuroscience for undergraduates, which are available to students coming from colleges and universities throughout the United States. The CMU-Pitt TPCN has 16 training faculty in computational neuroscience, 22 training faculty whose laboratories are primarily experimental, and 20 training faculty whose laboratories are both computational and experimental. At the graduate level the TPCN offers a PhD program in Neural Computation (PNC) and joint PhD programs with CMU’s Department of Statistics (PNC-Stat) and its Machine Learning Department (PNC- MLD), all set within a highly collegial, cross-disciplinary environment of our Center for the Neural Basis of Cognition (CNBC), which is operated jointly by CMU and Pitt. The CNBC was established in 1994 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 145 faculty having appointments in 22 departments. At the undergraduate level a substantial pool of local students is supplemented during the summer by a cohort of students from across the country. During this renewal funding period the project is strengthening the role of statistics and machine learning throughout the training programs; (2) revising the summer undergraduate program by creating a didactic two-week “boot camp” at the beginning, which includes a 20-lecture overview of computational neuroscience; (3) creating online materials, in conjunction with the boot camp, that will serve not only our own students but also the greater world of training in computational neuroscience; and (4) enhancing our minority recruitment by (a) taking advantage of the boot camp and online materials, as well as making promotional visits to targeted campuses, and (b) creating and running a one-year “bridge” program to better prepare under-represented minorities for PhD programs. TPCN trainees work in vertically integrated, cross-disciplinary research teams. Graduate students take a year- long course in computational neuroscience that bridges modeling and modern statistical machine learning approaches to neuroscience. To ensure their competency in core neuroscience principles they also take courses in cognitive neuroscience, neurophysiology, and systems neuroscience. They then pursue depth in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics. Graduate students have extended experience in at least one experimental laboratory, and they take part in journal clubs and seminars within the large Pittsburgh neuroscience community. Year-long undergraduates take courses in mathematics, computer programming, statistics, and neuroscience; they take an additional course in neuroscience or psychology and a course in computational neuroscience; and they complete a year-long research project. In addition, they complete the TPCN summer program. Undergraduate trainees in the summer program go through the boot camp on topics in computational neuroscience, including tutorials in Matlab, statistical methods, fundamentals of differential equations, and ideas of neural coding; they then complete a research project under careful guidance. All trainees will receive training in responsible conduct of research. Across 5 years of funding, the TPCN supports 20 NRSA graduate students, 10 non-NRSA graduate students, 30 undergraduate year-long fellows, and 60 undergraduate summer fellows.