Cognitive and Neurophysiological Representations of Impossible Space [CoNRIS]

不可能空间的认知和神经生理学表征 [CoNRIS]

• 批准号: 511678193
• 负责人: Professor Dr. Klaus Gramann
• 金额: --
• 依托单位: Fachgebiet Biopsychologie und Neuroergonomie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/511678193?language=en
• 关键词: Cognitive; Neurophysiological; Representations; Impossible; Space

Spatial navigation is one of the most fundamental abilities to survival that mobile species have evolved. The human brain contains a host of neural systems that combine together to form a spatial representation of the environment to enable successful navigation. Whilst research in recent decades has revealed much about these neural systems, the format of the integrated cognitive representation is less well understood. Two dominant theories exist: cognitive map and cognitive graph theory. Cognitive map theory suggests that spatial information is encoded in a global Euclidean reference frame, such that metric relationships between places are interdependent. Cognitive graph theory on the other hand describes spatial knowledge as independent chunks of information, that are linked together by experience (e.g. the post office and the bakery are linked by a left turn and a 100-meter walk). In this project, we aim to investigate: (1) whether humans integrate spatial knowledge into single or multiple representations; (2) if the format of those representations conform to the principles of cognitive map and/or cognitive graph theory; and (3) how different sensory modalities contribute to spatial knowledge by contrasting brain dynamics during full mobile with navigation of identical environments in stationary setups. To achieve these objectives, we will bring together key experimental methods that have previously been used separately to investigate spatial navigation behaviour. First, the recording of brain activity in physically moving participants as compared to stationary protocols to examine the neural systems involved with different aspects of navigation; the use of the impossible space paradigm to present participants with space that would never be possible the real world (enabled by virtual reality); the use of head mounted displays (HMDs) and motion tracking to enable participants to physically move during the navigation experiments. In four experiments using the impossible space paradigm, participants will navigate environments where the metric information derived from vision and movement either corresponds to their spatial location (possible) or does not correspond to their spatial location (impossible; e.g. a triangle trajectory where the turning angles do not sum to 180°). The logic behind the impossible space paradigm is that these spaces should prove difficult for participants to represent on a behavioural and neural level under cognitive map theory, but not under cognitive graph theory. These navigation tasks will be presented either on stationary desktop setups or fully mobile HMD setups to contrast the role of movement and body-based feedback to the brain’s navigation network. In order to study brain activity, we will use state-of-the-art mobile EEG recording and analysis techniques, alongside tracking of eye-movements and physical position in space for a multimodal approach to understanding human navigation.

空间导航是移动物种进化出的最基本的生存能力之一。人脑包含许多神经系统，这些神经系统组合在一起形成环境的空间表示，以实现成功的导航。虽然近几十年来的研究已经揭示了很多关于这些神经系统的信息，但人们对综合认知表征的格式还不太了解。存在两种主导理论：认知图论和认知图论。认知地图理论表明，空间信息被编码在全局欧几里得参考系中，使得地点之间的度量关系是相互依赖的。另一方面，认知图论将空间知识描述为独立的信息块，这些信息块通过经验链接在一起（例如，邮局和面包店通过左转和 100 米步行连接起来）。在这个项目中，我们的目标是研究：（1）人类是否将空间知识整合到单个或多个表示中； (2) 这些表示的格式是否符合认知图和/或认知图论的原理； （3）通过对比完全移动时的大脑动态与固定设置中相同环境的导航，不同的感觉方式如何有助于空间知识。为了实现这些目标，我们将汇集以前单独用于研究空间导航行为的关键实验方法。首先，记录身体移动的参与者的大脑活动与固定协议的比较，以检查涉及导航不同方面的神经系统；使用不可能的空间范式向参与者呈现现实世界中永远不可能的空间（通过虚拟现实实现）；使用头戴式显示器 (HMD) 和运动跟踪，使参与者能够在导航实验期间进行身体移动。在使用不可能空间范式的四个实验中，参与者将导航环境，其中从视觉和运动导出的度量信息要么对应于他们的空间位置（可能），要么不对应于他们的空间位置（不可能；例如，旋转角度之和不等于 180° 的三角形轨迹）。不可能空间范式背后的逻辑是，在认知图论下，这些空间对于参与者来说应该难以在行为和神经层面上表示，但在认知图论下则不然。这些导航任务将在固定桌面设置或完全移动的 HMD 设置上呈现，以对比运动和基于身体的反馈与大脑导航网络的作用。为了研究大脑活动，我们将使用最先进的移动脑电图记录和分析技术，同时跟踪眼球运动和空间物理位置，以多模式方法来理解人类导航。