A naturalistic visual task for studying distance estimation in the mouse

项目总结 视觉通过提供关于环境的感官信息来促进在世界上的导航， 例如到相关对象的距离。视觉感知的一个关键特征是积极探索 通过眼睛、头部和身体的平移而形成的视觉场景。视觉皮质已被提出 将这些自行生成的运动信号与视觉输入相结合，以计算有关对象的信息 环境。虽然最近的研究表明，小鼠V1中的很大一部分神经元 对运动信息进行编码，而不是简单地充当视觉特征检测器，V1功能的模型 在很大程度上忽视了运动传出和感觉传入的贡献。我们的目标是澄清 通过研究运动视差的深度知觉研究主动视觉的神经机制 将观察者自身运动和视网膜图像位移相结合的基本视觉计算 计算到环境中对象的距离。 我们将首先使一个行为学上的、自由移动的沙鼠/大鼠距离估计任务适应于小鼠，以便 确定老鼠在跳过缺口时用来测量深度的视觉线索的类型。到时候我们会的 操纵视觉皮质的活动及其从大脑区域传递运动相关信息 信号，以测试它们在从运动视差进行距离估计方面的具体作用。这个 在此R21应用中提出的实验为未来在神经方面的研究提供了基础 电路级，以确定视觉和运动信号如何集成以进行以下计算 距离估计，特别是在自然环境中。

PROJECT SUMMARY Vision facilitates navigation through the world by providing sensory information about the environment, such as the distance to relevant objects. A key feature of visual perception is the active exploration of the visual scene through translation of the eyes, head, and body. Visual cortex has been proposed to combine these self-generated motor signals with visual input to compute information about objects in the environment. While recent studies have shown that a significant fraction of neurons in mouse V1 encode movement information and do not simply act as visual feature detectors, models of V1 function have largely ignored motor efference and sensory reafferent contributions. We aim to elucidate the neural mechanisms underlying active vision by investigating depth perception from motion parallax - a fundamental visual computation that combines observer self-motion and retinal image displacement to calculate the distance to objects in the environment. We will first adapt an ethological, freely-moving gerbil/rat distance estimation task to mice in order to determine the types of visual cues mice use to gauge depth when jumping across a gap. We will then manipulate the activity of visual cortex and its inputs from brain regions conveying movement-related signals, in order to test their roles specifically in distance estimation from motion parallax. The experiments proposed in this R21 application provide the foundation for future studies at the neural circuit level, to determine how visual and movement signals are integrated for computations such as distance estimation, particularly in a natural context.