Bera Krishn, Shukla Anuj, Bapi Raju S
Cognitive Science Lab, Kohli Center on Intelligent Systems, International Institute of Information Technology, Hyderabad, India.
Front Psychol. 2021 Apr 9;12:604323. doi: 10.3389/fpsyg.2021.604323. eCollection 2021.
Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task, × task) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative of sequencing-motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks that involve sequencing-where the sequence of motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task (GST), which required navigating (by executing sequential keypresses) a 5 × 5 grid from start to goal (SG) position while using a particular key-mapping (KM) among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments-Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning.
为了研究顺序按键任务中的典型行为现象和学习本质，人们提出了几种经典的实验范式（例如，序列反应时任务、离散序列生成任务、×任务）。大多数范式的一个特征是，它们代表了排序运动任务，在这些任务中，环境或任务范式从外部提供刺激序列，即反应是由刺激驱动的。以往利用此类经典范式的研究在很大程度上忽略了一类更现实的运动任务中的学习行为，这类任务涉及排序，即运动动作序列是自我生成或内部指定的。在这项工作中，我们使用网格导航任务作为内部引导排序的一个实例，来研究此类范式中的学习本质。参与者执行网格航行任务（GST），该任务要求（通过执行顺序按键）在一个5×5的网格中从起始位置导航到目标（SG）位置，同时在三个光标移动方向和三个键盘按钮之间使用特定的按键映射（KM）。参与者进行了两个行为实验——单SG和混合SG条件。单SG条件要求在单个SG位置上反复执行GST，而混合SG条件则涉及使用相同的KM在以随机、混合方式呈现的两个新SG位置上执行GST。在单SG条件下，我们表明运动学习通过重复执行相同轨迹有助于GST中的序列特定学习。在混合SG条件下，由于参与者利用了先前学到的KM，我们预期会出现从单SG条件的学习迁移。特定于KM的内部模型的获取和迁移有助于在新的SG条件下进行高效的轨迹规划。获取这样一个特定于KM的内部模型相当于GST中与轨迹无关的认知学习。我们通过在混合SG条件下展示与迁移相关的性能提升，表明认知学习对GST中的学习有贡献。总之，我们展示了认知和运动学习过程在内部引导排序中的作用，并进一步支持在研究内部引导技能学习时使用类似GST的网格导航范式。
