Training in Theory and Computation for Next Generation Neuroscientists

项目摘要 要了解大脑的功能和功能障碍，就必须面对它的复杂性。过去 二十年来，神经科学领域利用了电子学、遗传学和 显微镜收集了大量令人眼花缭乱的神经元数据，特别是与该领域的状态相比时， 在上个世纪之交。这些数据集比以往任何时候都更需要复杂的分析技术来揭示 大脑动力学和计算的重要方面。同样重要的是建立一个连贯的理论， 大脑功能理论既可以将这些数据集组织在一个概念性的保护伞下，也可以建议 接下来的一系列实验。这些现实需要培养更多的神经科学研究人员 各种计算和数学技术。这个项目概述了一个雄心勃勃的毕业生， 在芝加哥大学的计算神经科学（TPCN）本科培训计划。 芝加哥大学TPCN有31个培训教师分布在10个部门。培训学院 由6名计算神经科学教师（干实验室），9名培训教师组成，他们的实验室是 主要是实验，和15个培训教师，其实验室都是计算和实验。在 研究生水平TPCN提供了计算神经科学博士课程和补充博士学位 神经生物学的程序。在本科阶段，芝加哥大学有一个非常受欢迎的专业， 神经科学，学生可以辅修计算神经科学。TPCN设置在一个高度学院化的， 我们的神经科学研究所和格罗斯曼定量生物学中心的跨学科环境 和人类行为神经科学研究所成立于2014年，旨在促进跨学科研究， 研究大脑功能的神经机制，目前有87名教员，在16个系任职。 格罗斯曼中心于2020年启动，是神经科学研究所内的一个空间， 专注于计算和理论神经科学。在接下来的五年里，格罗斯曼中心将继续发展壮大。 容纳5名计算神经科学教师，以补充我们现有的理论社区 神经科学家在此资助期间，TPCN将（1）加强计算课程的提供， 神经科学在研究生和本科水平;（2）创建一个本科研究计划， 计算神经科学;（3）利用本科生的优势，加强我们的少数民族招聘 神经科学研究项目 TPCN学员在垂直整合的跨学科研究团队中工作。研究生参加一个在计算神经科学的指导课程，跨越统计和建模方法的系列。到 确保他们在核心神经科学原理方面的能力，他们还参加了细胞，系统和神经网络课程。口腔神经科学他们的培训将辅以有关数量学科的课程，例如 计算机科学、工程学、数学或统计学。所有的研究生都将有丰富的经验 在至少一个实验室，他们参加杂志俱乐部和大学内的研讨会 芝加哥神经科学社区受资助的本科生学习数学、计算机专业、语法，统计学和神经科学;他们需要在神经科学或心理学和两个额外的课程 计算神经科学的课程;他们完成一个研究项目。此外，他们还完成了 TPCN暑期课程。暑期项目的本科学员参加靴子营，主题是 计算神经科学，包括Matlab教程，统计方法，微分方程基础，的概念和神经编码的想法;然后他们在仔细的指导下完成一个研究项目。所有学员 将接受负责任地进行研究的培训。在5年的资助中，TPCN支持20个NRSA 研究生，10名非NRSA研究生，30名本科学年和30名暑期研究员。

Project Summary To understand the function and dysfunction of the brain it is necessary to confront its complexity. Over the past two decades the field of neuroscience has leveraged the tremendous advances in electronics, genetics, and microscopy to collect a bewildering amount of neuronal data, especially when compared to the state of the field at the turn of the last century. More than ever these datasets require sophisticated analysis techniques to expose the salient aspects of brain dynamics and computation. Of equal importance is building a coherent theory of brain function. Theory can both organize these datasets under a conceptual umbrella, as well as suggest the next series of experiments to be performed. These realities require more neuroscience researchers to be trained in a variety of computational and mathematical techniques. This project outlines an ambitious graduate and undergraduate Training Program in Computational Neuroscience (TPCN) at the University of Chicago. The University of Chicago TPCN has 31 training faculty distributed over 10 departments. The training faculty are composed of 6 faculty in computational neuroscience (dry-lab), 9 training faculty whose laboratories are primarily experimental, and 15 training faculty whose laboratories are both computational and experimental. At the graduate level the TPCN offers a PhD program in Computational Neuroscience and a complementary PhD program in Neurobiology. At the undergraduate level the University of Chicago has a highly popular Major in Neuroscience, and students can Minor in Computational Neuroscience. The TPCN is set within a highly collegial, cross-disciplinary environment of our Neuroscience Institute and the Grossman Center for Quantitative Biology and Human Behavior. The Neuroscience Institute was established in 2014 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 87 faculty having appointments in 16 departments. The Grossman Center was launched in 2020 and is a space within the Neuroscience Institute with an explicit focus on computational and theoretical neuroscience. Over the next five years the Grossman Center will grow to house 5 computational neuroscience faculty to complement our already existing community of theoretical neuroscientists. During this funding period the TPCN will (1) strengthen the course offerings in computational neuroscience at both the graduate and undergraduate level; (2) create a undergraduate research program in computational neuroscience; (3) enhance our minority recruitment by taking advantage of the undergraduate neuroscience research program. TPCN trainees work in vertically integrated, cross-disciplinary research teams. Graduate students take a series of directed courses in computational neuroscience that span both statistical and modeling approaches. To ensure their competency in core neuroscience principles they also take courses in cellular, systems, and behavioral neuroscience. Their training will be supplemented with courses in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics. All graduate students will have extended experience in at least one experimental laboratory, and they take part in journal clubs and seminars within the University of Chicago Neuroscience community. Supported undergraduates take courses in mathematics, computer programming, statistics, and neuroscience; they take an additional course in neuroscience or psychology and two courses in Computational Neuroscience; and they complete a 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 school-year and 30 summer fellows.