Berkeley Course on Mining and Modeling of Neuroscience Data

伯克利神经科学数据挖掘和建模课程

• 批准号: 9036886
• 负责人: Friedrich T SOMMER
• 金额: $ 10.43万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-22 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9036886
• 关键词: Address; Algorithms; Animals; BRAIN initiative; Behavior; Brain; Brain Diseases; Complex; Computing Methodologies; Data; Data Analyses; Data Set; Educational process of instructing; Effectiveness; Engineering; Goals; Hour; Human; Individual; Injury; Institutes; Investigation; Knowledge; Learning; Mathematics; Measurement; Measures; Methodology; Methods; Mining; Modeling; Neurons; Neurosciences; Participant; Physics; Recruitment Activity; Research; Research Institute; Research Personnel; Science; Stimulus; Students; Teaching Method; Techniques; Technology; Time; Training; Video Recording; computer science; design; experience; improved; interest; lectures; mathematical sciences; nervous system disorder; neurophysiology; novel; public health relevance; relating to nervous system; repository; research study; response; statistics; theories; therapy development; training project

 DESCRIPTION (provided by applicant): This proposal is to administer and further develop a successfully established two-week summer training course titled "Mining and Modeling of Neuroscience Data" which is held at UC Berkeley. The course teaches methods for analyzing neurophysiology data, that is, measurements of the neural activity over time, co-registered with behavior or stimuli. With the Obama BRAIN initiative in full swing, rich neurophysiology data will become available at a high rate. The course has the goal to help build a workforce for leveraging these data and is designed to fill in a significant gap in training opportunities in the intersection between neuroscience and computational methods (computer science, mathematics, statistics, physics, engineering). Specifically, attendees of the course will be individuals either with a quantitative background and interest in neuroscience or with a background in neuroscience who wish to learn cutting edge approaches for the analysis of neuroscience data. To recruit students from Computer Science and Mathematics the project is partnered with the Simons Institute of the Theory of Computing and the Mathematical Sciences Research Institute. The training provided by this course will help increase the pool of researches who can apply existing and develop novel methodology for analyzing and modeling large, complex neurophysiology data sets. Increasing this type of quantitative knowledge in neuroscience will be essential to enhancing the understanding of the brain and developing approaches to treat disorders of the brain.

 描述（由申请人提供）：该提案是管理和进一步开发一个成功建立的为期两周的暑期培训课程，题为“神经科学数据的挖掘和建模”，在加州大学伯克利分校举行。该课程教授分析神经生理学数据的方法，即随着时间的推移测量神经活动，与行为或刺激共同记录。随着奥巴马的大脑计划全面展开，丰富的神经生理学数据将以高速度可用。该课程的目标是帮助建立一支利用这些数据的劳动力队伍，旨在填补 神经科学和计算方法（计算机科学，数学，统计学，物理学，工程学）之间的交叉。具体来说，课程的参加者将是具有定量背景和对神经科学感兴趣的人，或者具有神经科学背景的人，他们希望学习神经科学数据分析的前沿方法。为了招收计算机科学和数学专业的学生，该项目与西蒙斯计算理论研究所和数学科学研究所合作。本课程提供的培训将有助于增加能够应用现有和开发新方法来分析和建模大型复杂神经生理学数据集的研究人员。在神经科学中增加这种类型的定量知识对于增强对大脑的理解和开发治疗大脑疾病的方法至关重要。