Undergraduate and Graduate Training in Computational Neuroscience and Data Analysis

项目摘要 这项名为“计算神经科学和数据分析培训”的培训计划的目标是 帮助本科生和博士前学生获得他们需要的知识，技能和态度， 在科学生涯中蓬勃发展，为神经科学的研究带来了定量方法， 行为这个新项目源于之前的计算神经科学培训项目， 布兰迪斯大学在NIDA支持10年后最近到期。鉴于越来越 机器学习在数据分析和解决数据丰富的科学问题中的重要性， 最近布兰迪斯在该领域的招聘，我们的新计划将包括更多的参与，从计算机科学 拥有该领域专业知识的教师。此外，考虑到最近引进的应用数学专业， 布兰迪斯和相关的新教师在该领域，我们已经增加了一倍的培训实验室的数量， 研究神经科学数学模型的学生。该计划要求提供资金 支持6名本科生，4名NRSA合格的研究生和2名非NRSA合格的研究生 学生每年。我们将针对两组潜在的学员：1）具有较强优先级的个人 具有定量方法经验，希望在神经科学领域工作。2)有背景的人 在心理学、神经科学和生物学领域， 解决神经科学中重要问题的方法。我们将继续优先开展外联活动 旨在确保来自代表性不足的人群的受训者被纳入我们的计划。学生将 我有两个互补的导师，所以他们参加实验室与定量和实验 接近神经科学。26名培训教师拥有从人类研究到 认知到细胞和分子神经科学，所以研究问题种类繁多，在众多 学员可获得不同层次的分析。培训教师的选择是基于证明 致力于使用理论和计算方法以及跨学科合作， 了解健康和疾病中的神经系统。学生将学习统计学、数据 分析，计算神经科学，获得建立神经元，突触模型的技能， 网络，并在各种独立的研究项目中使用这些。除了课程作业和 实验室研究，学生和学员将从事大量的其他活动，设计 提高他们的口语技能，写作技能，以及与其他科学家合作的能力。所有学生 学员将接受负责任的科学行为的培训，并将与高级管理人员进行互动。 其他机构的科学家。

Project Summary The goal of this training program entitled “Training in Computational Neuroscience and Data Analysis” is to help undergraduate and predoctoral students gain the knowledge, skills, and attitudes they need to flourish in a scientific career that brings quantitative approaches to the study of neuroscience and behavior. This new program arises from a prior training program in Computational Neuroscience at Brandeis University that expired recently after 10 years of NIDA support. Given the increasing importance of machine learning in data analysis and solving of data-rich scientific problems, coupled with recent Brandeis hires in the field, our new program will include more participation from computer science faculty with expertise in the field. Also, given the recent introduction of an applied mathematics major at Brandeis and associated new faculty in the field, we have doubled the number of training labs with students working on mathematical modeling in neuroscience. The proposed program requests funding to support 6 undergraduates, 4 NRSA eligible graduate students, and 2 non-NRSA eligible graduate students each year. We will target two cohorts of prospective trainees: 1) Individuals with strong prior experience with quantitative methods who wish to work in neuroscience. 2) Individuals with backgrounds in psychology, neuroscience and biology who wish to learn to employ quantitative and computational methods to tackle important problems in neuroscience. We will continue prioritizing outreach activities aimed at ensuring trainees from underrepresented populations are included in our program. Students will have two complementary mentors so they participate in labs with both quantitative and experimental approaches to neuroscience. The 26 training faculty have research expertise ranging from human cognition to cellular and molecular neuroscience, so a wide variety of research problems, at numerous levels of analysis are available to trainees. The training faculty were chosen based on demonstrated commitment to the use of theoretical and computational methods and interdisciplinary collaboration to understand the nervous system in health and disease. Students will take courses in statistics, data analysis, computational neuroscience, obtain skills in building models of neurons, synapses, and networks, and employ these in a variety of independent research projects. In addition to course work and laboratory research, students and trainees will be engaged in a large number of other activities designed to enhance their speaking skills, writing skills, and ability to collaborate with other scientists. All students and trainees will receive training in the responsible conduct of science and will interact with senior scientists at other institutions.