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

• 批准号: 10746671
• 负责人: Brent D. Doiron
• 金额: $ 21.52万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 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/10746671
• 关键词: Appointment; Behavior; Behavioral; Biology; Brain; Chicago; Code; Communities; Competence; Complement; Data; Data Set; Differential Equation; 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 program; 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

Training in Theory and Computation for Next Generation Neuroscientists 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 se- ries 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 behav- ioral 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 pro- gramming, 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 equa- tions, 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.

对下一代神经科学家的理论和计算培训 项目摘要 要了解大脑的功能和功能障碍，必须面对其复杂性。过去 二十年的神经科学利用了电子，遗传学和 显微镜以收集令人困惑的神经元数据，尤其是与领域的状态相比 在上个世纪初。这些数据集比以往任何时候都需要复杂的分析技术来公开 大脑动力学和计算的显着方面。同等重要的是建立一个连贯的理论 大脑功能。理论既可以在概念保护伞下组织这些数据集，并建议 下一个要执行的实验。这些现实需要对更多的神经科学研究人员进行培训 在各种计算和数学技术中。这个项目概述了雄心勃勃的毕业生 芝加哥大学计算神经科学（TPCN）的本科培训计划。 芝加哥大学TPCN有31个培训教师在10个部门分发。培训教师 由6位计算神经科学（干lab）的教职员工组成，9个培训教师的实验室是 第一个实验和15个培训教师，其实验室既计算又实验。 TPCN的研究生级别提供了计算神经科学博士学位课程和完整的博士学位 神经生物学计划。在本科生，芝加哥大学拥有一位非常受欢迎的专业 神经科学和学生可以轻微计算神经科学。 TPCN设置在一个高度合作范围内， 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，旨在促进有关跨学科研究 大脑功能的神经元机制，现在包括87位在16个部门任命的教师。 格罗斯曼中心于2020年成立，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。在接下来的五年中，格罗斯曼中心将增长 容纳5个计算神经科学教师，以完成我们已经存在的理论社区 神经科学家。在此资助期间，TPCN将（1）加强计算中的课程。 毕业生和本科水平的神经科学； （2）创建一个本科研究计划 计算神经科学； （3）通过利用本科生来增强我们的少数族裔招募 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。研究生参加 涵盖统计和建模方法的计算神经科学课程的指示课程。到 确保他们在核心神经科学原则方面的能力，他们还在蜂窝，系统和行为上学习课程 Ioral神经科学。他们的培训将在相关的定量学科中补​​充课程，例如 计算机科学，工程，数学或统计数据。所有研究生都会有丰富的经验 在至少一个实验实验室中，他们参加了大学内的期刊俱乐部和SEMIAR 芝加哥神经科学社区。受支持的大学生参加数学课程，计算机专业 语法，统计和神经科学；他们还接受了神经科学或心理学的额外课程，两个 计算神经科学课程；他们完成了一个研究项目。此外，他们完成了 TPCN夏季计划。夏季计划中的本科学员通过新兵训练营 计算神经科学，包括MATLAB中的教程，统计方法，差异等级的基本原理 神经编码的思想；然后，他们在仔细的指导下完成了一个研究项目。所有学员 将接受负责任的研究培训。在5年的资金中，TPCN支持20个NRSA 研究生，10名非NRSA研究生，30名本科学年和30个夏季研究员。