Cone Integration in the visual cortex

视皮层中的视锥细胞整合

基本信息

批准号：
10159928
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 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10159928
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.

抽象的神经科学研究的核心问题是了解感觉神经元如何连接以检测帮助生物体导航的特征始于感光细胞马赛克，然后是。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，在每个位置在视网膜之外，视觉皮层的连续阶段逐渐整合并行的图像流。信息来创建日益复杂的调整对于视觉神经科学特别有用。了解皮层执行的计算，部分原因是早期的并行路径始于视网膜可以通过标准视觉显示器以高度受控的方式受到刺激，但是该领域仍然存在。缺乏受实验数据限制的详细的皮质功能机械模型，这是必要的最终将视觉皮层研究与基于皮质的病理学联系起来是一个障碍。视觉系统是理解小鼠皮质回路的重要模型；研究人员具有无与伦比的灵活性来操纵和标记已知的特定细胞类型对皮质功能的独立贡献除了遗传工具外，还可以使用彩色刺激。小鼠对于理解皮层计算的一般策略可能特别有效。结合视觉刺激和基因敲除小鼠，以视网膜亚群为目标，总体目标了解视网膜群体的整合如何有助于多个阶段的处理该提案的早期目标是生成时空的第一个特征。初级视觉皮层（V1）的调节，作为来自视网膜的视锥细胞输入分布的函数。表征对于利用鼠标视觉中并行处理流的未来研究是必要的它也将测试颜色独立于空间和空间进行编码的假设。视觉场景的动态模式在下一个目标中，我们将测量皮质布线的基本原理。通过测试 V1 颜色调整是由其前馈输入的系统池化形成的假设。另一种假设是，皮层通过这些测量的“随机”电路构建了调谐层次结构。通过小鼠感光细胞镶嵌的粗各向异性，我们将实现这一目标。研究不同的视觉皮层区域如何通过并行通道进行通信首先，我们将确定是否。更高的视觉区域专门处理特定的颜色、空间和时间带，这将在后面介绍。通过测量中间神经元如何促进皮质-皮质通路的整合，使用空间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颜色调节的功能结构。