Collins Anne Gabrielle Eva, Frank Michael Joshua
Department of Cognitive, Linguistic and Psychological Sciences, Brown Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America.
Department of Psychology, University of California, Berkeley, Berkeley, California, United States of America.
PLoS Comput Biol. 2016 Mar 11;12(3):e1004785. doi: 10.1371/journal.pcbi.1004785. eCollection 2016 Mar.
Study of human executive function focuses on our ability to represent cognitive rules independently of stimulus or response modality. However, recent findings suggest that executive functions cannot be modularized separately from perceptual and motor systems, and that they instead scaffold on top of motor action selection. Here we investigate whether patterns of motor demands influence how participants choose to implement abstract rule structures. In a learning task that requires integrating two stimulus dimensions for determining appropriate responses, subjects typically structure the problem hierarchically, using one dimension to cue the task-set and the other to cue the response given the task-set. However, the choice of which dimension to use at each level can be arbitrary. We hypothesized that the specific structure subjects adopt would be constrained by the motor patterns afforded within each rule. Across four independent data-sets, we show that subjects create rule structures that afford motor clustering, preferring structures in which adjacent motor actions are valid within each task-set. In a fifth data-set using instructed rules, this bias was strong enough to counteract the well-known task switch-cost when instructions were incongruent with motor clustering. Computational simulations confirm that observed biases can be explained by leveraging overlap in cortical motor representations to improve outcome prediction and hence infer the structure to be learned. These results highlight the importance of sensorimotor constraints in abstract rule formation and shed light on why humans have strong biases to invent structure even when it does not exist.
对人类执行功能的研究聚焦于我们独立于刺激或反应方式来表征认知规则的能力。然而，最近的研究结果表明，执行功能不能与感知和运动系统分开进行模块化，相反，它们是建立在运动动作选择之上的。在这里，我们研究运动需求模式是否会影响参与者选择实施抽象规则结构的方式。在一项需要整合两个刺激维度以确定适当反应的学习任务中，受试者通常会分层构建问题，使用一个维度来提示任务集，另一个维度来提示给定任务集时的反应。然而，在每个层面上使用哪个维度的选择可能是任意的。我们假设受试者采用的具体结构将受到每个规则中所提供的运动模式的限制。在四个独立的数据集中，我们表明受试者创建了能够实现运动聚类的规则结构，更喜欢在每个任务集中相邻运动动作有效的结构。在使用指令性规则的第五个数据集中，当指令与运动聚类不一致时，这种偏差强大到足以抵消众所周知的任务切换成本。计算模拟证实，观察到的偏差可以通过利用皮质运动表征中的重叠来改善结果预测，从而推断出要学习的结构来解释。这些结果凸显了感觉运动约束在抽象规则形成中的重要性，并揭示了为什么即使不存在结构，人类也有强烈的倾向去创造结构。
