Neurotechnologies for Analysis of Network Dynamics

用于网络动力学分析的神经技术

• 批准号: 8742713
• 负责人: MICHAEL J BERRY
• 金额: $ 16.15万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8742713
• 关键词: Admission activity; Alzheimer' s Disease; Animals; Behavioral; Biological Neural Networks; Biology; Brain; Brain Diseases; Brain imaging; Chemistry; Cognitive; Complex; Coupled; Data; Data Set; Decision Making; Depressive disorder; Development; Discipline; Engineering; Exercise; Family; Functional Magnetic Resonance Imaging; Generations; Goals; Hippocampus (Brain); Human; Individual; Information Sciences; Intervention; Laboratories; Learning; Mammals; Mathematics; Measurement; Memory; Methodology; Methods; Modeling; Molecular; Motor; Neurons; Neurosciences; Optics; Parkinson Disease; Pathway Analysis; Physics; Physiology; Population; Process; Psychological reinforcement; Recruitment Activity; Research Personnel; Resolution; Rodent; Sensory; Sensory Process; Site; Speed; Students; Synapses; Synaptic plasticity; Technology; Training; Vertebrates; awake; base; brain cell; clinically relevant; computer science; design; experience; extracellular; human subject; information processing; insight; lectures; neural circuit; neurotechnology; new technology; optogenetics; public health relevance; relating to nervous system; skills; theories; tool

DESCRIPTION (provided by applicant): The goal of the proposed course, entitled "Neurotechnologies for Analysis of Network Dynamics" (NAND), is to introduce students with training in physics, mathematics, computer science, and engineering to the theory and practice of modern neuroscience, with special emphasis on modern methods for the analysis of network dynamics in mammalian cortical circuits responsible for behavioral decision making. Recent progress in developing methods for electrical and optical recording from 10s to 100s of neurons simultaneously with cellular resolution is revolutionizing our ability to define neural activity sttes that correspond to periods of memory storage and decision-making in awake, behaving vertebrate animals, including mammals. The goal of this new course is to give students with advanced training in quantitative disciplines outside of neuroscience the theoretical background and practical experience needed to understand and contribute to the ongoing revolution in the analysis of neural network dynamics in anatomically defined neural circuits being used to make decisions based on sensory input, implement those decisions by generation of motor commands, and store information in both short-term and long-tem memory for use in subsequent decision-making. A four-week course is planned. The lectures will introduce the students to: i) the basics of cellular and synaptic physiology; ii) an array of cellular and molecular tools to facilitate network analysis; iii) technology for large scale multi-site recordin; iv) the analysis of large data sets produced by multi-channel recording; v) methods for obtaining multi-site recordings, both electrical and optical, from both animal and human brains; vi) models of information processing in cortical circuits, particularly during reinforcement learning. The laboratory component will provide experience in the recording and analysis of extra- and intracellular recordings, generation and recording of synaptic plasticity in the hippocampus, and multi-site optical and electrical recordings from awake behaving rodents. Students will use optogenetic methods for circuit analysis and learn to make fMRI measurements of activity in human subjects during an information processing task. The capstone of the laboratory is a one-week period devoted to student designed Independent Projects.

描述(申请人提供)：拟开设的课程名为“用于分析网络动力学的神经技术”(NAND)，旨在向受过物理、数学、计算机科学和工程学培训的学生介绍现代神经科学的理论和实践，特别强调用于分析负责行为决策的哺乳动物大脑皮层回路中的网络动力学的现代方法。在开发同时具有细胞分辨率的从10s到100s的神经元的电学和光学记录方法方面的最新进展，正在彻底改变我们定义神经活动STT的能力，这些STT对应于清醒、行为的脊椎动物，包括哺乳动物的记忆存储和决策阶段。这门新课程的目标是为在神经科学以外的定量学科中接受高级培训的学生提供所需的理论背景和实践经验，以了解并促进正在进行的神经网络动力学分析革命，在解剖学定义的神经回路中，被用来根据感觉输入做出决定，通过产生运动命令来实施这些决定，并将信息存储在短期和长期记忆中，以供后续决策使用。计划了一个为期四周的课程。讲座将向学生介绍：i)细胞和突触生理学的基础；ii)一系列促进网络分析的细胞和分子工具；iii)大规模多站点记录的技术；iv)多通道记录产生的大数据集的分析；v)从动物和人类大脑获得多站点记录的方法；vi)大脑皮层回路的信息处理模型，特别是在强化学习期间。实验室部分将在记录和分析细胞外和细胞内记录、海马区突触可塑性的产生和记录以及清醒行为啮齿动物的多点光学和电学记录方面提供经验。学生将使用光遗传学方法进行电路分析，并学习在信息处理任务中对受试者的活动进行fMRI测量。实验室的顶峰是为期一周的学生设计的独立项目。