Neural mechanisms of spatial cognition

空间认知的神经机制

• 批准号: RGPIN-2014-03580
• 负责人: Becker, Suzanna
• 金额: $ 2.19万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644938
• 关键词: Neural; mechanisms; spatial; cognition

The hippocampus is widely believed to be a crucial brain structure for spatial cognition. However, its precise role is still the subject of considerable debate. Our lab has been investigating the role of the hippocampus and related structures in the medial temporal and parietal lobes in spatial memory and mental imagery using a variety of techniques, including computational (neural network) modelling, human memory experiments in virtual reality (VR) environments, neuroimaging using fMRI and EEG, and brain-computer-interfaces. We have developed a computational model that sheds light on the mechanisms underlying spatial memory, mental imagery, and the visual transformation process by which viewer-centred sensory information is transformed into a world-centred representation, commonly known as a "cognitive map". Our recent work has been aimed at testing several predictions of the model. In virtual reality studies where people incidentally learned the layout of a town by playing a virtual taxi game, we found that people were more likely to encode the spatial locations of objects they saw along routes if the objects were at navigationally relevant locations, and also when attention was particularly focused on spatial cues, suggesting that objects may be flexibly treated as landmarks and incorporated into cognitive maps, according to task demands. We also found that people have a strong tendency to form global, hierarchical representations of large-scale spaces. Moreover, recent neuroimaging (fMRI) studies confirm some of the model's predictions regarding the specific neural structures that may be involved in the visual transformation from viewer-centric sensory representations to world-centric cognitive maps. The proposed research will further our understanding of these processes. Our computational models of the hippocampal memory system will be extended to account for how we combine geometric, object and path integration cues, and how we learn temporal sequences. Complementing this theoretical work, empirical methods will be used to test predictions of the model and shed further light on the conditions governing the use of cognitive maps and visuospatial transformations. We will investigate the hippocampal mechanisms involved in the formation of distinctive representations for similar spatial contexts, the link between mental imagery and visuospatial transformations, and the effect of lifestyle factors such as stress, alcohol consumption and exercise on hippocampal-dependent spatial strategies. Finally, we will explore an innovative application of our research on mental imagery, using EEG-based brain-computer interfaces and state-of-the-art machine learning methods to decode a person's internal mental imagery and use it to control a virtual reality display. In the long term, our work could have important implications not only for understanding the basic mechanisms underlying spatial cognition, but for rehabilitating individuals with spatial memory and navigation deficits in ageing, and rehabilitating positive visual imagery deficits in those with mood disorders.

海马体被广泛认为是空间认知的关键大脑结构。然而，它的确切作用仍然是相当大的争论的主题。我们的实验室一直在使用各种技术，包括计算(神经网络)建模、虚拟现实(VR)环境中的人类记忆实验、使用fMRI和EEG的神经成像以及脑机接口，来研究海马体和内侧颞叶和顶叶的相关结构在空间记忆和心理意象中的作用。我们开发了一个计算模型，它揭示了空间记忆、心理意象和视觉转换过程中潜在的机制，通过视觉转换过程，以观众为中心的感觉信息被转换为以世界为中心的表征，即通常所说的“认知地图”。我们最近的工作旨在测试该模型的几个预测。在虚拟现实研究中，人们通过玩虚拟出租车游戏附带地了解了一个城镇的布局，我们发现，如果物体位于与导航相关的位置，并且注意力特别集中在空间线索上，那么人们更有可能编码他们在路线上看到的物体的空间位置，这表明根据任务要求，物体可能被灵活地视为地标，并纳入认知地图。我们还发现，人们有一种强烈的倾向，即形成大规模空间的全局、分层表示。此外，最近的神经成像(FMRI)研究证实了该模型关于特定神经结构的一些预测，这些结构可能涉及从以观众为中心的感觉表征到以世界为中心的认知地图的视觉转换。拟议的研究将进一步加深我们对这些过程的理解。我们对海马体记忆系统的计算模型将被扩展，以解释我们如何结合几何、物体和路径整合线索，以及我们如何学习时间序列。作为这项理论工作的补充，将使用实证方法来测试该模型的预测，并进一步阐明支配认知地图和视觉空间转换的条件。我们将研究参与形成对相似空间背景的不同表征的海马区机制，心理意象和视觉空间转换之间的联系，以及压力、饮酒和锻炼等生活方式因素对海马区依赖的空间策略的影响。最后，我们将探索我们对心理意象的研究的创新应用，使用基于脑电的脑机接口和最先进的机器学习方法来解码一个人的内部心理意象，并用它来控制虚拟现实显示器。从长远来看，我们的工作可能不仅对理解空间认知的基本机制具有重要意义，而且对于恢复老年中空间记忆和导航缺陷的个人，以及恢复情绪障碍患者的积极视觉意象缺陷具有重要意义。