The gist of the space: A space centered approach to visual scene perception

描述（由申请人提供）：愿景是我们与世界互动的核心。除了识别面孔和与人交流，我们的日常活动还围绕着两个基本任务：识别我们的环境和在环境中导航。Aude Oliva博士的研究项目将场景感知的行为、计算和认知神经科学研究结合起来。越来越多来自行为、成像和计算研究的证据表明，对复杂现实世界场景的感知与物体识别的认知和神经机制截然不同。然而，到目前为止，这些证据还没有形成一个理解场景处理的综合框架。在这里，PI提议测试一个新的假设，即现实世界的场景分析是在一个由不同大脑区域组成的网络中进行的，每个区域专门代表不同层次的场景信息。由于场景本质上是三维空间，她将展示大脑利用从场景所包含的空间中获得的独特信息，而不是完全基于对象的描述。换句话说，在了解“场景要点”之前，我们先分析“空间要点”。了解大脑对视觉场景表征的本质是一项事业，它将推动为视觉和空间障碍患者制定快速可靠的康复策略，并推动依赖于对视觉空间理解的基于辅助的系统的发展。现实世界的场景识别是一个未解之谜，它将对神经科学、计算视觉、人工智能、机器人和心理学产生影响。

DESCRIPTION (provided by applicant): Vision is central to our interactions with the world. Aside from recognizing faces and communicating with people, our daily activities are also organized around two fundamental tasks: recognizing our environment and navigating through it. The research program of Dr. Aude Oliva constitutes a new integration of behavioral, computational and cognitive neuroscience research on scene perception. A growing body of evidence from behavioral, imaging and computational investigations has shown that the perception of complex real-world scenes engages distinct cognitive and neural mechanisms from those engaged in object recognition. To date, however, this evidence has not resulted in a comprehensive framework for understanding scene processing. Here, the PI proposes to test the novel hypothesis that real-world scene analysis is performed in a network of distinctive brain regions, with each region specialized in representing a different level of scene information. Since scenes are inherently three-dimensional spaces, she will show that the brain capitalizes on information uniquely derived from the space encompassed by a scene, rather than an exclusively object-based description. In other words, before knowing the "gist of a scene," we analyze the "gist of the space." Understanding the nature of the brain's representations of visual scenes is an enterprise that will push the development of fast and reliable rehabilitation strategies for individuals with visual and spatial impairments, and push forward the development of aid-based systems that rely on an understanding of the visual space. Real-world scene recognition is an unsolved mystery that will have implications for neuroscience, computational vision, artificial intelligence, robotics and psychology. PUBLIC HEALTH RELEVANCE: The research program constitutes a new integration of computational and cognitive neuroscience research on scene and space perception, with the aim of unraveling how the understanding of visual environments (where we are, where to navigate) arises in the human brain.