Neuroimaging of dynamic navigational codes

动态导航代码的神经影像

• 批准号: 9166218
• 负责人: RUSSELL A EPSTEIN
• 金额: $ 20.13万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9166218
• 关键词: Accelerometer; Alzheimer' s Disease; Animal Model; Animals; Architecture; Behavior; Brain; Brain region; Cities; Code; Cognition; Cognitive; Complex; Cues; Data Set; Diagnosis; Disease; Electrophysiology (science); Environment; Episodic memory; Foundations; Functional Magnetic Resonance Imaging; Future; Health; Hippocampus (Brain); Human; Image Analysis; Imagination; Individual; Investigation; Knowledge; Learning; Literature; Location; Locomotion; Maps; Measurement; Medial; Mediating; Memory; Methods; Modeling; Movement; Neurocognitive; Neurodegenerative Disorders; Organism; Parietal Lobe; Participant; Performance; Physiological; Physiology; Positioning Attribute; Problem Solving; Psyche structure; Robotics; Rodent; Route; Sensory; Signal Transduction; Stimulus; Stroke; Structure; System; Temporal Lobe; Testing; Time; Training; Vision; Work; base; blood oxygen level dependent; cognitive function; cognitive process; hemodynamics; innovation; meetings; movie; neuroimaging; neuromechanism; nonhuman primate; novel; reconstruction; rehabilitation strategy; relating to nervous system; response; tool; virtual; virtual reality; way finding

Project Summary: Spatial navigation is a challenge that must be met by all mobile organisms. Although much is known about the neural mechanisms that underlie spatial navigation in animals, the neurocognitive basis of spatial navigation in humans is much less clear. This is partly because of technical limitations: the best tool currently available for noninvasive measurement of brain activity is functional magnetic resonance imaging (fMRI), but traditional fMRI analysis methods are not well-suited for identifying representations elicited in dynamic, naturalistic situations such as unconstrained navigational episodes. The current project will attempt to overcome this limitation by using a recent technical innovation in fMRI analysis—voxel-wise encoding modeling—to identify the neural representations that mediate active navigation. Specifically, we will model the fMRI response during navigation within a virtual-reality city in terms of the spatial variables that are known to have known cellular coordinates correlates in rodents and non-human primates, and we will then evaluate the model by testing whether it predicts fMRI response in a held-out dataset not used to train the model. Additionally, we will explore whether the representations thus revealed suffice to solve the problem of simultaneous localization and mapping (SLAM); that is, whether they allow one to keep track of one's position during exploration of a novel environment while simultaneously learning its layout. Aim 1 is to build the voxel-wise encoding model and to use it to identify the neural representations within specific brain regions that mediate dynamic navigation. Aim 2 is to examine generalization across environments by testing whether a model trained in one virtual environment suffices to solve the problem of SLAM in another. If successful, we anticipate that this project will have a major and sustained impact on the field by achieving a quantitative description of how spatial information is encoded in multiple regions of the human brain during dynamic real-time navigation. This will allow us to test specific hypotheses about spatial representations developed from the animal literature, and potentially allow this literature to be leveraged to better understand multiple cognitive functions that rely on the same underlying neural architecture, including spatial cognition, episodic memory, and imagination. Moreover, this project will provide the essential technical foundation for future tests of novel hypotheses about the physiological basis of navigation.

项目概要： 空间导航是所有移动的生物体必须面对的挑战。虽然很多 已知动物空间导航的神经机制， 人类空间导航的神经认知基础还不太清楚。这部分是因为 技术限制：目前可用于无创测量大脑的最佳工具 活动是功能磁共振成像（fMRI），但传统的fMRI分析方法 不太适合识别在动态的、自然的情况下引出的表征 例如不受约束的导航片段。目前的项目将试图克服这一点 使用fMRI分析中的最新技术创新-逐体素编码的限制 建模-以识别介导主动导航的神经表征。我们特别 将模拟功能磁共振成像响应期间导航在一个虚拟现实的城市方面， 已知具有已知细胞坐标的空间变量在啮齿动物中相关， 然后我们将通过测试该模型是否预测功能磁共振成像来评估该模型 不用于训练模型的保留数据集中的响应。此外，我们还将探讨 这样揭示的表示足以解决同时定位的问题， 地图（SLAM）;也就是说，它们是否允许一个人在 探索一个新的环境，同时学习它的布局。目标1：建立 体素编码模型，并使用它来识别特定的神经表征 调节动态导航的大脑区域。目的2是检查泛化跨越 通过测试在一个虚拟环境中训练的模型是否足以解决 另一个是SLAM的问题。如果成功，我们预计该项目将有一个重大的 对实地的影响和持续影响， 信息在动态实时期间被编码在人脑的多个区域中 导航这将使我们能够测试有关空间表征的特定假设 从动物文献中，并可能允许利用这些文献，以更好地 理解依赖于相同的底层神经结构的多种认知功能， 包括空间认知、情景记忆和想象力。此外，该项目将 为未来测试有关的新假设提供必要的技术基础。 航海的生理基础