We conducted an exploratory study in virtual reality to examine if people can discover causal relations in a realistic sensorimotor context and how such learning is represented at different processing levels (conscious-cognitive vs. sensorimotor). Additionally, we explored the relation between human causal learning and state-of-the-art causal discovery algorithms. The task consisted of placing a glass on a surface, that breaks if the contact force exeeded its breakability threshold, determined by weight and color. Ecological validity was enhanced by haptic rendering simulating weight and contact forces. Participants were asked to repeatedly transport and place glasses of varying weights and colors on a surface without breaking them. For success, participants had to discover the underlying causal structure. The trials were conducted over three sessions, reflecting naive, exploratory, consolidated and causally aware behavior, with questionnaires assessing conscious causal understanding of the task's causal structure. Sensorimotor representations were inferred by applying causal-discovery algorithms (PC, FCI, FGES) to the recorded trial-by-trial variables, and conditional mutual information was used to quantify the strength of causal influence on the sensorimotor level. Results show that (i) participants identified the weight-breakability link (76% correct after experiment) and the color-breakability link (43%) but struggle to infer causal direction. (ii) Sensorimotor analysis revealed a robust weight-force coupling increasing across sessions, whereas for color-force it was weak and noisy, yet mutual information indicated an attempted learning. (iii) Discovery algorithms recovered the causal structure across sessions. Together, these findings indicate that humans can, partially, perceive the causal structure of the task, with partially dissociated conscious and sensorimotor representations.

翻译：我们在虚拟现实中开展了一项探索性研究，旨在检验人们能否在现实的感觉运动情境中发现因果关系，以及这种学习在不同处理层面（意识认知层面与感觉运动层面）如何表征。此外，我们探讨了人类因果学习与前沿因果发现算法之间的关系。任务要求参与者将玻璃杯放置于一个表面上，若接触力超过由其重量和颜色决定的破裂阈值，玻璃杯便会破碎。通过模拟重量和接触力的触觉渲染，增强了实验的生态效度。参与者被要求反复搬运并放置不同重量和颜色的玻璃杯到表面上，且不能使其破碎。要成功完成任务，参与者必须发现潜在的因果结构。实验分三个阶段进行，分别反映了初始、探索、巩固及因果意识行为阶段，并通过问卷评估参与者对任务因果结构的意识层面因果理解。我们通过对记录的逐次试验变量应用因果发现算法（PC、FCI、FGES）来推断感觉运动表征，并使用条件互信息来量化感觉运动层面因果影响的强度。结果表明：（i）参与者识别出了重量与破裂性之间的联系（实验后正确率为76%）以及颜色与破裂性之间的联系（43%），但在推断因果方向上存在困难。（ii）感觉运动分析揭示出重量与作用力之间存在稳健的耦合关系，且随实验阶段推进而增强；而颜色与作用力之间的耦合则微弱且充满噪声，但互信息表明存在尝试学习的迹象。（iii）因果发现算法在不同实验阶段均能复原因果结构。综上所述，这些发现表明人类能够部分地感知任务的因果结构，且其意识表征与感觉运动表征存在部分分离。