Cognitive and Neural Representations of Reachable Environments

可到达环境的认知和神经表征

• 批准号: 10040687
• 负责人: Talia Konkle
• 金额: $ 29.58万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10040687
• 关键词: Behavior; Behavioral; Brain; Cognitive; Communities; Computer Models; Computers; Coupled; Data Set; Databases; Dimensions; Environment; Functional Magnetic Resonance Imaging; Goals; Hand; Human; Image; Impairment; Individual; Leisures; Maps; Measurement; Measures; Methods; Modeling; Motor; Participant; Process; Research; Semantics; Services; Stimulus; Structure; Testing; Vision; Visual; Visual Perception; Visual system structure; Work; behavior measurement; behavioral study; cognitive system; experience; experimental study; innovation; insight; large-scale database; neuroimaging; novel; operation; relating to nervous system; response; sensory input; success; visual motor; visual process

Project Summary The broad goal of the proposed research is to characterize the way that humans perceive and represent views of reachable environments. “Reachspaces” are an integral part of our world and day-to-day experience, but how these views are processed by the visual cognitive system is unknown. The present work aims to offer fundamental insights into the structure of internal representations of the reachable environments. First, a large database of reachspace images will be constructed. Next, this proposal will leverage a recently developed approach that employs a large-scale behavioral experiment, coupled with a sparse positive embedding model, which will be used to derive the attributes underlying the similarity structure of reachspace views. Finally, brain responses to a selected subset of reachspace views will be measured and modeled with the derived dimensions. These approaches have been tested and used to great advance in domains of object and scene processing; here, we employ them on the novel stimulus domain of reachspaces. This work has the potential to form new bridges between the vision and visuomotor communities by characterizing high-level visual representations of reachable environments and will expand scientific understand of how humans perceive the visual environment.

项目摘要 拟议研究的广泛目标是描述人类感知的方式， 表示可达环境的视图。“Reachspaces”是我们世界不可或缺的一部分 和日常经验，但这些观点是如何被视觉认知系统处理的， 未知目前的工作旨在提供内部结构的基本见解 可达环境的表示。首先，一个大型的reachspace图像数据库 将被建造。接下来，该提案将利用最近开发的方法， 采用了大规模的行为实验，加上稀疏的正嵌入模型， 这将被用于导出可达空间的相似性结构下的属性 意见.最后，将测量大脑对所选择的到达空间视图子集的反应， 使用衍生尺寸建模。这些方法已经过测试， 先进的领域的对象和场景处理;在这里，我们采用他们的小说 可达空间的刺激域。这项工作有可能在这两个国家之间建立新的桥梁。 视觉和视觉社区的特点高层次的视觉表示， 可到达的环境，并将扩大人类如何感知的科学理解， 视觉环境