Training in Theory and Computation for Next Generation Neuroscientists

下一代神经科学家的理论和计算培训

基本信息

批准号：
10879209
负责人：
Brent D. Doiron
金额：
$ 24.72万
依托单位：
UNIVERSITY OF CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-15 至 2028-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10879209
关键词：
Appointment Behavior Biology Brain Chicago Code Communities Competence Complement Computers Data Data Set Discipline Doctor of Philosophy Dryness Educational Status Electronics Engineering Ensure Environment Exposure to Faculty Fostering Funding Genetic Human Interdisciplinary Study Journals Laboratories Mathematics Microscopy Minor Minority Recruitment Modeling National Research Service Awards Neurobiology Neurons Neurosciences Neurosciences Research Psychology Research Research Personnel Research Project Grants Schools Series Statistical Methods Students System Teacher Professional Development Techniques Training Training Programs Universities Work brain dysfunction computational neuroscience computer science experience experimental study graduate student laboratory experiment neural neuromechanism next generation programs responsible research conduct statistics summer program theories undergraduate research experience undergraduate student

项目摘要

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.

项目概要要了解大脑的功能和功能障碍，有必要面对它的复杂性。过去的事二十年来，神经科学领域利用了电子学、遗传学和显微镜收集大量令人眼花缭乱的神经元数据，特别是与现场状态相比在上世纪之交。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突出方面。同样重要的是建立一个连贯的理论大脑功能。理论既可以在概念框架下组织这些数据集，也可以提出建议接下来要进行的一系列实验。这些现实需要培训更多的神经科学研究人员各种计算和数学技术。该项目概述了一位雄心勃勃的毕业生和芝加哥大学计算神经科学（TPCN）本科生培训项目。芝加哥大学 TPCN 拥有 31 名培训教师，分布在 10 个院系。培训师资队伍由 6 名计算神经科学教师（干实验室）和 9 名培训教师组成，其实验室为主要是实验性的，还有 15 名培训教师，他们的实验室既是计算实验室又是实验实验室。在 TPCN 研究生阶段提供计算神经科学博士课程和补充性博士课程神经生物学计划。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 建立在一个高度学院化、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脑功能的神经机制，目前由 16 个系的 87 名教职人员组成。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，具有明确的专注于计算和理论神经科学。未来五年格罗斯曼中心将不断发展容纳 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) 加强计算方面的课程设置研究生和本科生的神经科学；（二）设立本科生科研项目计算神经科学；（三）发挥本科生优势，加大少数民族招收力度神经科学研究计划。 TPCN 学员在垂直整合的跨学科研究团队中工作。研究生学习一系列涵盖统计和建模方法的计算神经科学定向课程。到确保他们掌握核心神经科学原理的能力，他们还学习细胞、系统和行为神经科学课程。他们的培训将辅以相关定量学科的课程，例如计算机科学、工程、数学或统计学。所有研究生都将拥有丰富的经验他们至少在一个实验实验室工作，并且参加大学内的期刊俱乐部和研讨会芝加哥神经科学界。支持的本科生学习数学、计算机编程、统计学和神经科学课程；他们额外修读一门神经科学或心理学课程，以及两门课程计算神经科学课程；他们完成了一个研究项目。此外，他们还完成 TPCN 暑期项目。暑期项目的本科生学员将参加有关主题的训练营计算神经科学，包括 Matlab 教程、统计方法、微分方程基础知识和神经编码思想；然后他们在认真的指导下完成一个研究项目。所有练习生将接受负责任的研究行为的培训。在 5 年的资助中，TPCN 支持了 20 个 NRSA 研究生、10 名非 NRSA 研究生、30 名本科生和 30 名暑期研究员。