High-throughput Physiological Micro-connectivity Mapping in Vivo

体内高通量生理微连接图谱

• 批准号: 10387260
• 负责人: Hillel Adesnik
• 金额: $ 8.39万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10387260
• 关键词: Anatomy; Animals; Architecture; BRAIN initiative; Behavior; Brain; Brain Diseases; Cells; Chronic; Cognition; Data; Disease; Electrophysiology (science); Experimental Designs; Image; Individual; Learning; Maps; Measurement; Neurons; Optical reporter; Optics; Physiological; Resolution; Statistical Algorithm; Statistical Models; Synapses; System; Technology; Time; brain circuitry; connectome; course development; in vivo; neural circuit; neural model; new technology; novel strategies; optogenetics; presynaptic neurons; relating to nervous system

PROJECT SUMMARY Mapping the synaptic connectivity of brain circuits is essential for obtaining a mechanistic understanding of the neural basis of behavior, learning, and cognition. While anatomical approaches can reveal the physical architecture of neural circuits, only a functional approach can reveal the strength and dynamics of each synapse in a network. These parameters are crucial for building any type of quantitative and explanatory model for how neural circuits compute, encode, and store information. This proposal brings together three teams with complementary expertise in holographic optogenetics and electrophysiology (Adesnik), high resolution volumetric imaging (Ji) and statistical modeling and real-time experimental design (Paninski), to develop two new technologies that will be able reveal much of the physiological connectome of single neurons in the brain. The first approach combines high resolution multiphoton photo-stimulation in vivo with single cell intracellular electrophysiology in the intact brain, and statistical algorithms that permit high-throughput mapping of the targeted neuron's presynaptic connectome. The second approach employs the same photo-stimulation system, but leverages optical reporters of activity in individual synapses to achieve the all-optical measurement of synaptic connectivity in a cortical network chronically over time. These two new technologies will allow neuroscientists to obtain the quantitative data on the physiological micro-connectivity of cortical networks across large fractions of the cortex. The first approach provides unparalleled measurements of synaptic strength and dynamics of each identified synaptic connections. The second approach permits the repeated assessment of the micro-connectivity of the same neurons in the same animal over many days, finally opening up the opportunity to map the reorganization of brain circuitry over the course of development, learning, or the progression of brain disease.

项目摘要 映射脑电路的突触连通性对于获得对机械的理解至关重要 行为，学习和认知的神经基础。虽然解剖方法可以揭示物理 神经回路的结构，只有一种功能性方法才能揭示每种突触的强度和动力学 在网络中。这些参数对于建立任何类型的定量和解释模型至关重要 神经回路计算，编码和存储信息。该提议将三支团队汇集在一起 全息光遗传学和电生理学（ADESNIK）的补充专业知识，高分辨率 体积成像（JI）和统计建模和实时实验设计（Paninski），以开发两个 将能够揭示大脑中单个神经元的许多生理连接组的新技术。 第一种方法结合了高分辨率在体内与单细胞内的多光子光刺激 完整大脑中的电生理学和允许高通量映射的统计算法 靶向神经元的突触前连接组。第二种方法采用相同的照片刺激系统， 但是利用单个突触中活动的光学记者，以实现全光测量 随着时间的流逝，皮质网络中的突触连通性。这两种新技术将允许 神经科学家获得有关跨皮质网络生理微连接性的定量数据 皮质的大部分。第一种方法提供了无与伦比的突触强度和 每个已识别的突触连接的动力学。第二种方法允许重复评估 许多天，同一动物中同一神经元的微连接性，最终开放 在开发，学习过程中或 大脑疾病的进展。