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。越来越大 复杂的数据集正在收集，但分析和建模数据的工具还没有 available.迫切需要更多受过计算神经科学训练的研究人员。这个项目 支持计算神经科学（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（皮特），以及一个暑期学校， 计算神经科学的本科生，这是提供给学生来自大学和 美国各地的大学。 CMU-Pitt TPCN拥有16名计算神经科学培训教师，22名培训教师， 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 实验性的在研究生阶段，TPCN提供神经计算（PNC）博士课程和联合 CMU统计系（PNC-Stat）和机器学习系（PNC- MLD），所有这些都在我们的神经基础中心的高度学院化，跨学科的环境中进行。 认知（CNBC），这是由CMU和皮特共同经营。CNBC成立于1994年， 对大脑功能的神经机制进行跨学科研究，目前拥有145名教师， 22个部门的任命。在本科阶段， 在夏天，来自全国各地的一批学生补充了这一点。在此次融资过程中， 在此期间，该项目正在加强统计和机器学习在整个培训方案中的作用; (2)通过在开始时创建一个为期两周的说教式“靴子训练营”来修改夏季本科课程， 其中包括20个讲座的计算神经科学概述;（3）创建在线材料， 与靴子训练营相结合，这将不仅服务于我们自己的学生，也为更大的训练世界 在计算神经科学;和（4）提高我们的少数招聘（a）利用靴子 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 运行一个为期一年的“桥梁”计划，以更好地为博士课程的代表性不足的少数民族准备。 TPCN学员在垂直整合的跨学科研究团队中工作。研究生需要一年的时间- 计算神经科学的长期课程，连接建模和现代统计机器学习 接近神经科学。为了确保他们在核心神经科学原理方面的能力，他们还采取了 认知神经科学、神经生理学和系统神经科学课程。然后，他们追求深度， 相关的定量学科，如计算机科学，工程，数学或统计学。研究生 学生在至少一个实验室有丰富的经验，他们参加期刊俱乐部 和匹兹堡神经科学界的研讨会。为期一年的本科生参加课程， 数学，计算机编程，统计学和神经科学;他们需要一个额外的课程， 神经科学或心理学和计算神经科学课程， 研究项目。此外，他们还完成了TPCN夏季计划。大学本科实习生 暑期课程通过靴子营在计算神经科学的主题，包括教程， Matlab，统计方法，微分方程的基本原理，以及神经编码的思想;然后， 在认真指导下完成一个研究项目。所有受训人员将接受负责任地开展 research.在5年的资金，TPCN支持20 NRSA研究生，10非NRSA研究生 学生，30个本科全年研究员，和60个本科暑期研究员。

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.