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。 正在收集越来越大和复杂的数据集，但用于分析和 目前还没有对数据进行建模的方法。更多受过计算神经科学培训的研究人员 迫切需要。该项目支持以下领域的研究生和本科生培训计划 卡内基梅隆大学(CMU)和加州大学计算神经科学(TPCN) 匹兹堡(匹兹堡)，以及为本科生开设的计算神经科学暑期学校，这些学校是 适用于来自全美高校的学生。 CMU-PIT TPCN拥有16名计算神经科学培训教员，22名培训教员 实验室主要是试验性的，20名培训教师的实验室既是 计算的和实验的。在研究生阶段，TPCN提供神经方面的博士课程 计算(PNC)和与CMU统计系(PNC-STAT)和ITS的联合博士项目 机器学习部门(PNC-MLD)，所有这些都设置在高度合作的、跨学科的 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，旨在促进对神经的跨学科研究 大脑功能机制，现在由145名教职员工组成，在22个系任职。 在本科阶段，在暑期补充了大量的本地学生。 来自全国各地的一群学生。在此续签资助期内，该项目 加强统计和机器学习在整个培训方案中的作用； (2)修订暑期本科课程，在大学开设为期两周的教学“新兵训练营” 开始，其中包括20个讲座的计算神经科学概述；(3)创建在线 材料，与新兵训练营一起，不仅将服务于我们自己的学生，而且将服务于 在计算神经科学方面进行更大的培训；以及(4)加强我们的少数群体 通过以下方式进行征聘：(A)利用新兵训练营和在线材料， 对目标校园进行宣传访问，以及(B)创建和实施为期一年的“过桥”方案 以更好地为代表不足的少数族裔准备博士课程。 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 选修一门为期一年的计算神经科学课程，将建模与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课程。 神经科学。然后，他们追求相关量化学科的深度，如计算机 科学、工程、数学或统计学。研究生有丰富的At经验。 至少一个实验实验室，他们参加杂志俱乐部和研讨会 匹兹堡大型神经科学社区。一年制的本科生选修数学课程， 计算机编程、统计学和神经科学；他们还选修了神经科学方面的额外课程 或心理学和一门计算神经科学课程；他们完成了一项为期一年的研究 项目。此外，他们还完成了TPCN夏季项目。暑期本科实习生 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、微分方程式基本原理和神经编码思想； 然后，他们在仔细的指导下完成一个研究项目。所有受训人员都将接受 负责任的研究行为。在5年的资助中，TPCN支持20名NRSA毕业生 学生，10名非NRSA研究生，30名本科生一年制研究员和60名本科生 夏日伙伴。

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.