INTERDISCIPLINARY TRAINING IN COMPUTATIONAL NEUROSCIENCE

项目摘要 要了解大脑的许多紊乱，有必要弄清楚它的复杂性。规模越来越大 复杂的数据集正在被收集，但用于分析和建模数据的工具还没有 可用。迫切需要更多受过计算神经科学培训的研究人员。这个项目 支持两所大学计算神经科学(TPCN)的研究生和本科生培训计划 卡内基梅隆大学(CMU)和匹兹堡大学(匹兹堡)，以及 面向本科生的计算神经科学，可供来自大学和 全美的大学。 CMU-PIT TPCN拥有16名计算神经科学培训教员，22名培训教员 实验室主要是实验性的，以及20名培训教师，他们的实验室既是计算实验室，也是 试验性的。在研究生阶段，TPCN提供神经计算(PNC)和联合 CMU统计系(PNC-Stat)及其机器学习系(PNC-STAT)的博士项目 MLD)，所有这些都设置在我们的神经基础中心高度合作的、跨学科的环境中 认知(CNBC)，由CMU和PIT联合运营。CNBC成立于1994年，旨在促进 对大脑功能的神经机制进行跨学科研究，目前有145名教职员工 22个部门的任命。在本科阶段，相当多的本地学生是 暑假期间，来自全国各地的一群学生补充了这一点。在此续订期间提供资金 期间，该项目在整个培训方案中加强了统计和机器学习的作用； (2)修订暑期本科课程，在开始时设立为期两周的“新兵训练营”， 其中包括20堂课的计算神经科学概述；(3)创建在线材料，在 与新兵训练营相结合，这不仅将服务于我们自己的学生，也将服务于更广阔的培训世界 在计算神经科学方面；和(4)通过(A)利用启动的优势来促进我们的少数族裔的招募 营地和在线材料，以及对目标校园进行宣传访问，以及(B)创建和 开办一个为期一年的“过桥”计划，以更好地为代表不足的少数族裔攻读博士学位做准备。 TPCN的受训人员在垂直整合的跨学科研究团队中工作。研究生要花一年时间- 连接建模和现代统计机器学习的计算神经科学的长期课程 神经科学的方法。为了确保他们在核心神经科学原理方面的能力，他们还 认知神经科学、神经生理学和系统神经科学课程。然后，他们在一种 相关的定量学科，如计算机科学、工程、数学或统计学。毕业生 学生至少有一个实验实验室的丰富经验，他们还参加了期刊俱乐部。 以及匹兹堡大型神经科学界的研讨会。一年制本科生选修 数学、计算机编程、统计学和神经科学；他们在 神经科学或心理学和一门计算神经科学的课程；他们完成了一年的课程 研究项目。此外，他们还完成了TPCN夏季项目。大学本科生培训计划 暑期计划通过计算神经科学主题的新兵训练营，包括 MatLab、统计学方法、微分方程式的基础和神经编码的思想；然后 在仔细的指导下完成一个研究项目。所有受训人员将接受负责任的行为培训 研究。在5年的资助中，TPCN支持20名NRSA研究生，10名非NRSA毕业生 学生，30名本科生一年制研究员，60名本科生暑期研究员。

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.