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Cone Integration in the visual cortex

视皮层中的视锥细胞整合

基本信息

批准号：
10405082
负责人：
Nicholas J Priebe
金额：
$ 36.8万
依托单位：
UNIVERSITY OF TEXAS AT AUSTIN
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10405082
关键词：
Afferent Neurons Amblyopia Anisotropy Architecture Area Cells Cerebral cortex Color Communication Cone Data Discrimination Disease Dyslexia Electrodes Electrophysiology (science)Experimental Designs Future Genetic Goals Hot Spot Image Individual Interneurons Joints Knock-in Knockout Mice Label Link Literature Location Measurement Measures Methods Modeling Mosaicism Motion Mus Neurons Neurosciences Research Opsin Organism Output Pathology Pathway interactions Pattern Photoreceptors Plant Roots Population Process Property Public Health Research Research Personnel Resolution Retina Rod Route Sampling Schizophrenia Shapes Stimulus Strabismus Stream Structure Testing Time V1 neuron Vision Visual Visual Cortex Visual system structure area striata autism spectrum disorder base cell type color processing extrastriate visual cortex flexibility follow-up foot in vivo novel optogenetics parallel processing presynaptic programs receptive field segregation simulation spatiotemporal tool visual neuroscience visual processing visual stimulus

项目摘要

Abstract A problem at the core neuroscience research is to understand how sensory neurons are wired to detect features that aid in the organism's navigation. Vision begins with the photoreceptor mosaic, followed immediately by exquisite retinal circuitry that detects basic changes in contrast and color, at every location of an image. Beyond the retina, successive stages of visual cortex gradually integrate parallel streams of information to create tuning of increasing complexity. Visual neuroscience has been especially useful for understanding the computations performed by the cortex, partly because the early parallel pathways initiated in the retina can be stimulated in a highly controlled manner with standard visual displays. However, the field still lacks detailed mechanistic models of cortical function that are constrained by experimental data, a necessary hurdle to ultimately bridge studies of visual cortex to cortical-based pathologies. For this reason, the mouse's visual system is an important model for understanding cortical circuits; genetic tools in the mouse allow researchers unparalleled flexibility to manipulate and label specific cell-types that are known to make independent contributions to cortical function. In addition to genetic tools, the use of colored stimuli with the mouse may be especially fruitful for understanding general strategies of cortical computation. This study uses a combination of visual stimuli and knock-out mice to target subpopulations of the retina, with the overall goal of understanding how the integration of retinal populations contributes to multiple stages of processing within the visual cortex. An early goal of the proposal is to generate the first characterization of the spatio-temporal tuning in primary visual cortex (V1), as a function of the distribution of cone inputs from the retina. This characterization is necessary to leverage future studies of parallel processing streams in the mouse visual cortex, such as ours. It will also test the hypothesis that color is encoded independently of the spatial and dynamic patterns of a visual scene. In the next aim, we will measure fundamental principles of cortical wiring by testing the hypothesis that V1 color tuning is shaped by systematic pooling of its feedforward inputs. The alternative hypothesis is that the cortex builds hierarchies of tuning by “random” circuits. These measurements are made possible by coarse anisotropy in the photoreceptor mosaic of mice. In the final aim, we will investigate how different visual cortical areas communicate via parallel channels. To begin, we will determine if higher visual areas are dedicated to processing specific bands of color, space, and time. This will be followed by measurements of how interneurons contribute to the cortico-cortical integration of pathways, using spatially structured optogenetics. The experimental design of the proposal relies on genetic tools, imaging, electrophysiology, optogenetics, and the functional architecture of color tuning in the mouse's visual system.

摘要神经科学研究的一个核心问题是了解感觉神经元是如何连接到检测帮助生物体导航的特征。视觉开始于感光细胞镶嵌，立即通过精致的视网膜电路，检测对比度和颜色的基本变化，在每一个位置，一个形象在视网膜之外，视觉皮层的连续阶段逐渐整合平行的信息流。信息来创建日益复杂的调优。视觉神经科学对于理解皮层执行的计算，部分原因是早期的平行通路始于可以用标准视觉显示器以高度受控的方式刺激视网膜。然而，该领域仍然缺乏受实验数据约束的皮质功能的详细机制模型，这是最终将视觉皮层研究与基于皮层的病理学联系起来的障碍。因此，老鼠的视觉系统是理解皮层回路的重要模型;老鼠的遗传工具允许研究人员无与伦比的灵活性来操纵和标记特定的细胞类型，对皮质功能的独立贡献。除了遗传工具，使用彩色刺激与 mouse可能在理解皮层计算的一般策略方面特别有成效。本研究采用视觉刺激和基因敲除小鼠的组合，以靶向视网膜亚群，总体目标是了解视网膜群体的整合如何有助于内部处理的多个阶段视觉皮层该提案的一个早期目标是产生时空的第一个特征，初级视皮层（V1）的调谐，作为来自视网膜的视锥输入分布的函数。这表征是必要的，以利用未来的研究并行处理流在小鼠视觉皮质，比如我们的。它还将测试颜色编码独立于空间和视觉的假设。视觉场景的动态模式。在下一个目标中，我们将测量皮层布线的基本原理，通过测试V1颜色调谐是由其前馈输入的系统汇集形成的假设。的另一种假设是，大脑皮层通过"随机"回路建立起调谐的层次结构。这些测量是由小鼠感光细胞镶嵌体的粗糙各向异性造成的。在最终目标中，我们将研究不同的视觉皮层区域如何通过平行通道进行交流。开始，我们将确定高级视觉区域专用于处理颜色、空间和时间的特定带。随后将通过测量中间神经元如何促进皮质-皮质整合通路，使用空间结构光遗传学该提案的实验设计依赖于遗传工具，成像，电生理学、光遗传学和小鼠视觉系统中颜色调节的功能结构。