Representation and integration of diverse visual features in circuits and behavior

项目总结 视觉感知和视觉引导行为依赖于大脑结合有关信息的能力 视觉场景的多个方面。在所有有视力的动物中，包括人类在内，视觉系统使用平行 在不同的视觉路径或群体中表示视觉场景的不同特征的处理策略 神经元。那么，大脑是如何将关于视觉世界的这些不同方面的信息组合成一个 统一的视觉感知，以及动物如何根据由编码的多个视觉线索来指导行为 分开的小路？根据该奖项进行的研究将使用视觉系统来回答这个问题 果蝇作为模型，它允许识别和定位精确的、定义的神经 代表视觉线索的种群。这项工作将：(1)确定视觉特征联合的多样性程度 由视觉投射神经元群体代表，这些神经元将信息从视觉系统传递到其余部分 决定这些视觉投射通路之间的相互作用如何塑造视觉信息 以及(3)确定场景的不同特征如何组合以指导动物行为。这 这项工作将推动国家眼科研究所的核心使命，为理解 视觉功能。这项研究将依赖于神经科学中广泛的现代方法，包括功能 脑活动成像、遗传操作、计算和统计建模以及行为 测量。除了上述研究外，该奖项还将支持获奖者向 在研究密集型大学的独立研究生涯，并进一步支持他们视觉的建立 神经科学实验室。

PROJECT SUMMARY Visual perception and visually-guided behavior relies on the ability of the brain to combine information about multiple aspects of a visual scene. In all sighted animals, including humans, the visual system uses parallel processing strategies to represent different features of a visual scene in different visual pathways or populations of neurons. How, then, does the brain combine information about these different aspects of the visual world into a unified visual percept, and how do animals guide behavior based on multiple visual cues that are encoded by separate pathways? The research performed under this award will answer this question using the visual system of the fruit fly Drosophila as a model, which allows for the identification and targeting of precise, defined neural populations that represent visual cues. This work will: (1) Determine how diverse visual features are jointly represented by populations of visual projection neurons that carry information from the visual system to the rest of the brain, (2) Determine how interactions among these visual projection pathways shape the visual information encoded in them, and (3) Determine how different features of a scene are combined to guide animal behavior. This work will advance the core mission of the National Eye Institute by making contributions to the understanding of visual function. This research will rely on a wide array of modern approaches in neuroscience, including functional imaging of brain activity, genetic manipulations, computational and statistical modeling, and behavioral measurements. In addition to the research described above, this award will support the awardee’s transition to an independent research career at a research-intensive university and further support the establishment of their visual neuroscience laboratory.