Training in Methods of Computational Neuroscience (MCN)

计算神经科学 (MCN) 方法培训

• 批准号: 10451501
• 负责人: Linda E Hyman
• 金额: $ 21.36万
• 依托单位: MARINE BIOLOGICAL LABORATORY
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-22 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10451501
• 关键词: Address; Anatomy; Behavior; Behavioral; Biological; Biological Process; Biological Sciences; Brain; Brain Diseases; Collaborations; Computational Technique; Computer Models; Computers; Computing Methodologies; Data; Data Set; Diagnosis; Dimensions; Disease; Environment; Epilepsy; Event; Explosion; Faculty; Fostering; Foundations; Generations; Goals; Human; Image; Individual; Instruction; International; Laboratories; Lead; Learning; Mathematics; Measurement; Mental Depression; Mental Health; Mental disorders; Mentors; Mentorship; Methods; Modeling; Nervous system structure; Neurobiology; Neurons; Optics; Parkinson Disease; Participant; Pathology; Population; Problem Sets; Psychiatry; Request for Proposals; Research Project Grants; Schizophrenia; Scientist; Series; Statistical Data Interpretation; Students; Supervision; System; Talents; Techniques; Training; Update; Vocabulary; Wood material; Work; addiction; base; brain cell; career; cell type; computational neuroscience; computerized tools; density; design; diverse data; experimental study; faculty mentor; innovation; interdisciplinary collaboration; laboratory curriculum; large datasets; lectures; mathematical sciences; neural circuit; neuromechanism; neurophysiology; novel; optogenetics; relating to nervous system; skills; student training; teaching assistant; theories; tool; training opportunity; web site

ABSTRACT The Methods in Computational Neuroscience (MCN) course at the Marine Biological Laboratory in Woods Hole, MA provides a unique training opportunity to equip students with cutting edge skills and conceptual foundations of computational methods to understanding the biological function and neural mechanisms of brain cells, circuits, and behavior. MCN is an intense lecture and computer laboratory course targeted to a talented mix of students with complementary expertise in biological and mathematical sciences. MCN students interact one-on-one with internationally renowned scientists and carry out hands-on, project-based training with a wide variety of computational techniques and approaches. The goals of the MCN course are to train students 1) in the concepts and methods of computational approaches to understanding brain function 2) in the mathematical foundations and techniques for the analysis of neural data 3) to use computational tools to solve fundamental questions in neurobiology, 4) to use computational methods to diagnose and treat human brain disorders and 5) to foster interdisciplinary collaborations that lead to long term interactions and mentorship. The course provides in-depth instruction on how to use computational approaches to solve fundamental problems in neurobiology using experimental techniques applied across a wide range of biological scales from molecules to behavior. This is accomplished through hands-on training in the mathematical foundations and techniques for the model-based, statistical and theoretical analysis of neural data in the context of mechanistic descriptions of neurons, networks, and brain systems. The MCN course continually updates its computational topics that are relevant to new experimental advances, such anatomical connectivity at microstructural and brain-wide scales, high density measurements using electrical and optical recording, and causal perturbations of neural circuits using optogenetics. These new topics include state-space trajectory analysis, deep networks, compressed sensing, advanced statistical inference, manifold learning, dimensionality reduction, analysis of large data sets including brain wide imaging and large scale cell-type specific connectivity. An additional innovation is an increased emphasis on computational approaches to understanding and addressing brain disorders, including the emerging field of computational psychiatry. Central to the course is an environment of intense interactions with a group of dedicated faculty, many of whom devote weeks or even the entire month to work with students. In the last half of the course students devote concentrated effort to novel cutting edge research projects mentored by a team of faculty and teaching assistants. The course fosters a collegial, international environment that advances student careers by providing students with networking opportunities that lead to long-term interactions, mentorship, and collaborations.

抽象的 伍兹海洋生物实验室的计算神经科学（MCN）课程的方法 马萨诸塞州霍尔（Hole，MA）提供了一个独特的培训机会，可以为学生提供最先进的技能和概念 理解大脑的生物学功能和神经机制的计算方法的基础 细胞，电路和行为。 MCN是针对才华横溢的激烈的讲座和计算机实验室课程 具有生物学和数学科学方面的补充专业知识的学生的混合。 MCN学生互动 与国际知名的科学家一对一，并进行基于项目的动手培训 各种计算技术和方法。 MCN课程的目标是培训学生1） 在理解大脑功能的计算方法的概念和方法中2） 用于分析神经数据的数学基础和技术3）使用计算工具 解决神经生物学中的基本问题，4）使用计算方法诊断和 治疗人脑疾病，5）培养导致长期的跨学科合作 互动和指导。该课程提供了有关如何使用计算的深入指令 使用在A中应用的实验技术解决神经生物学基本问题的方法 从分子到行为的广泛生物量表。这是通过动手培训完成的 基于模型的数学基础和技术，神经的统计和理论分析 在神经元，网络和大脑系统机械描述的背景下进行数据。 MCN课程 不断更新与新实验进步相关的计算主题 微观结构和大脑尺度上的连通性，使用电气和光学的高密度测量 记录和使用光遗传学对神经回路的因果扰动。这些新主题包括州空间 轨迹分析，深网，压缩感应，高级统计推断，多种多样学习， 降低维度的分析，包括大脑宽成像和大型细胞类型在内的大数据集的分析 特定连通性。额外的创新是对计算方法的越来越重视 理解和解决脑疾病，包括计算精神病学的新兴领域。 该课程的核心是与一群敬业的教师进行激烈互动的环境，许多 他们专注于几周甚至整个月与学生一起工作。在课程的下半部学生 奉献精力为由教师和教学团队指导的新型尖端研究项目 助手。该课程促进了一个联合国际环境，该环境通过 为学生提供带来长期互动，指导和 协作。