Fermin Alan, Yoshida Takehiko, Ito Makoto, Yoshimoto Junichiro, Doya Kenji
Neural Computation Unit, Okinawa Institute of Science and Technology, Onna, Japan.
J Mot Behav. 2010 Nov;42(6):371-9. doi: 10.1080/00222895.2010.526467.
In this article, the authors examine whether and how humans use model-free, reflexive strategies and model-based, deliberative strategies in motor sequence learning. They asked subjects to perform the grid-sailing task, which required moving a cursor to different goal positions in a 5 × 5 grid using different key-mapping (KM) rules between 3 finger keys and 3 cursor movement directions. The task was performed under 3 conditions: Condition 1, new KM; Condition 2, new goal position with learned KM; and Condition 3, learned goal position with learned KM; with or without prestart delay time. The performance improvement with prestart delay was significantly larger under Condition 2. This result provides evidence that humans implement a model-based strategy for sequential action selection and learning by using previously learned internal model of state transition by actions.
在本文中，作者研究了人类在运动序列学习中是否以及如何使用无模型的反射性策略和基于模型的审议性策略。他们要求受试者执行网格航行任务，该任务需要使用3个手指键和3个光标移动方向之间的不同键映射（KM）规则，将光标移动到5×5网格中的不同目标位置。该任务在3种条件下进行：条件1，新的KM；条件2，具有已学习KM的新目标位置；条件3，具有已学习KM的已学习目标位置；有或没有预启动延迟时间。在条件2下，预启动延迟带来的性能提升显著更大。这一结果表明，人类通过使用先前学习的动作状态转换内部模型，为顺序动作选择和学习实施了基于模型的策略。
