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的生存的最基本能力之一。人脑包含许多神经元系统，它们结合在一起以形成环境的空间表示以实现成功导航。尽管近几十年来的研究已经揭示了这些神经元系统，但综合认知表示的形式却不太了解。存在两个主要理论：认知图和认知图理论。认知图理论表明，空间信息是在全球欧几里得参考框架中编码的，因此位置之间的度量关系是相互依存的。另一方面，认知图理论将空间知识描述为独立的信息块，这些信息是通过经验链接在一起的（例如，邮局和面包店通过左转弯和100米的步行连接）。在这个项目中，我们旨在调查：（1）人类是否将空间知识纳入单一或多个表示； （2）如果这些表示的格式符合认知图和/或认知图理论的原理； （3）不同的感觉方式如何通过将完整移动期间的大脑动态与固定设置中相同环境的导航进行对比，从而有助于空间知识。为了实现这些目标，我们将汇总以前已将其用于研究空间导航行为的关键实验方法。首先，与固定方案相比，记录了在物理移动的参与者中的大脑活动，以检查与导航不同方面相关的神经元系统；使用不可能的空间范式向参与者展示永远不会成为现实世界的空间（通过虚拟现实启用）；使用头部安装显示器（HMD）和运动跟踪，使参与者在导航实验期间能够身体移动。在使用不可能的空间范式的四个实验中，参与者将导航环境，其中从视觉和移动衍生的度量信息对应于它们的空间位置（可能），或者与其空间位置不符（例如，转弯角度不得超过180°）。不可能的空间范式背后的逻辑是，这些空间应该证明参与者在认知图理论下很难在行为和神经层面上代表这些空间，而不是在认知图理论下。这些导航任务将在固定桌面设置或完全移动的HMD设置上介绍，以将运动和基于身体的反馈与大脑的导航网络的作用进行对比。为了研究大脑活动，我们将使用最新的移动脑电图记录和分析技术，以及对眼动和物理位置的跟踪，用于多模式的方法来理解人类导航。