Centre for Cognitive Science & Institute of Psychology, Technical University of Darmstadt, Darmstadt, Germany.
Frankfurt Institute for Advanced Studies, Goethe University, Frankfurt, Germany.
Nat Commun. 2024 Jul 6;15(1):5677. doi: 10.1038/s41467-024-49722-y.
Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. Here, we provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action.
目标导向的导航需要不断地将不确定的自身运动和地标线索整合到内部的位置和方向感中，同时规划未来的路径，并顺序执行运动动作。在这里，我们提供了一个统一的解释这些过程的方法，使用不确定性下最优反馈控制框架中的概率路径规划的计算模型。该模型产生了多种人类导航策略，这些策略以前被认为是不同的行为，并定量地预测了大量实验中导航的误差和可变性。这进一步解释了如何顺序的自我中心地标观测形成不确定的他心认知地图，如何在路线规划和运动执行期间使用这个内部地图，以及调和了关于导航中线索整合行为的看似矛盾的结果。总之，本工作提供了一个简洁的解释，说明人类目标导向导航行为模式如何从感知、认知和动作中的空间不确定性的连续和动态相互作用中产生。
