Predoctoral Training in Quantitative Neuroscience

7.项目摘要/摘要 这项提案将为加州理工学院的定量神经科学博士前培训创建一个项目。田野 在大量新技术的推动下，神经科学的研究目前正在经历爆炸性的增长 观察和操控大脑。为了有效地应用这些方法并解释由此产生的大量数据， 现代神经科学家需要成熟的数学和计算方法，而不是传统的 神经科学培训项目不能提供。与此同时，我们看到 对大脑组织不同层次的理解，从指定神经的分子 连接到人脑中大型回路的动态功能。因此，迫切需要培训 年轻的神经学家具有跨越多个层次的综合视角-从分子到行为再到 计算--传统上是在不同的程序中教授。加州理工大学处于一个理想的位置， 回答这些要求。这是一所几乎完全致力于科学研究的机构，按惯例排名 是世界上为数不多的顶尖大学之一。加州理工大学以其严格的物理训练而闻名， 数学和工程学，但它在生物学研究和 尤其是神经科学。较小的规模支持了一种环境，在这种环境中，科学合作 纪律是毫不费力的。本提案利用这些体制优势来创造一个新的环境 接受量化神经科学方面的培训。该计划的重点是一年级和二年级的博士生。 战略开始于从广泛的本科生专业中高度选择性地招聘候选人， 从生物化学到心理学再到计算机科学。一年级学生被介绍给教职员工 在三个轮换中进行研究，每个轮换3个月，然后他们选择一位主要导师来监督他们的 博士研究。学员还将完成为期两年的严格课程，以确保在 以下六个领域：(1)分子和细胞神经科学；(2)系统和计算神经科学； (3)人类神经科学和大脑疾病；(4)神经科学的工具和技术；(5)应用 数学和统计；(6)科学规划和数据分析。学员获得写作经验 通过有指导的奖学金申请程序。他们还在论坛上做了大量的口头陈述。 在校园内外。在第二年年底的候选人考试后，受训人员专注于博士研究， 目标是撰写一本或多本主要出版物，并在6年级或更早的时候毕业。每个实习生的 通过节目的轨迹伴随着个性化的建议，调整课程表，确保 广泛的能力，同时也挑战学生在一个特殊的专业领域。总而言之， 拟议的定量神经科学计划及时回应了对新的 在这一快速发展的学科中进行研究生培训。

7. Project Summary/Abstract This proposal will create a program for Predoctoral Training in Quantitative Neurosciences at Caltech. The field of neuroscience is currently experiencing explosive growth, driven by a plethora of new technologies for observing and manipulating the brain. To apply these methods fruitfully and interpret the resulting flood of data, modern neuroscientists need a sophistication in mathematical and computational approaches that traditional neuroscience training programs cannot provide. At the same time we are seeing a convergence of understanding at different levels of brain organization, ranging from the molecules that specify neural connections to the dynamic function of large circuits in the human brain. Thus, there is an urgent need to train young neuroscientists with an integrated perspective that spans many levels – from molecules to behavior to computation – which have traditionally been taught in separate programs. Caltech is in an ideal position to answer these demands. It is an institution almost entirely dedicated to scientific research, routinely ranked among the top few universities in the world. Caltech is well known for its rigorous training in physics, mathematics, and engineering, but it also has a distinguished history in biological research, and in the neurosciences in particular. The small size supports a climate in which scientific collaboration across disciplines is effortless. The present proposal exploits these institutional strengths to create a new environment for training in quantitative neuroscience. The program is focused on PhD students in years 1 and 2. The strategy begins with highly selective recruiting of candidates from a broad range of undergraduate majors, ranging from biochemistry to psychology to computer science. First-year students get introduced to faculty research during three rotations of 3 months each, after which they choose a primary mentor to supervise their PhD research. Trainees also complete a rigorous 2-year course curriculum that ensures core competency in the following six areas: (i) molecular and cellular neuroscience; (ii) systems and computational neuroscience; (iii) human neuroscience and brain disorders; (iv) tools and technology for neuroscience; (v) applied mathematics and statistics; (vi) scientific programming and data analysis. Trainees get writing experience through a mentored process of fellowship applications. They also give numerous oral presentations in forums on and off campus. After a candidacy examination at the end of year 2, trainees focus on PhD research, with the aim of authoring one or more major publications, and graduating by year 6 or earlier. Each trainee's trajectory through the program is accompanied by individualized advising, adjusting coursework to ensure broad competency while also challenging the student in a domain of special expertise. In summary, the proposed program in quantitative neurosciences responds in a timely manner to an urgent demand for a new type of graduate training in this rapidly evolving discipline.