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Probabilistic Motor Sequence Yields Greater Offline and Less Online Learning than Fixed Sequence

机译:概率运动序列比固定序列产生更多的离线学习和更少的在线学习

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It is well acknowledged that motor sequences can be learned quickly through online learning. Subsequently, the initial acquisition of a motor sequence is boosted or consolidated by offline learning. However, little is known whether offline learning can drive the fast learning of motor sequences (i.e., initial sequence learning in the first training session). To examine offline learning in the fast learning stage, we asked four groups of young adults to perform the serial reaction time (SRT) task with either a fixed or probabilistic sequence and with or without preliminary knowledge (PK) of the presence of a sequence. The sequence and PK were manipulated to emphasize either procedural (probabilistic sequence; no preliminary knowledge (NPK)) or declarative (fixed sequence; with PK) memory that were found to either facilitate or inhibit offline learning. In the SRT task, there were six learning blocks with a 2 min break between each consecutive block. Throughout the session, stimuli followed the same fixed or probabilistic pattern except in Block 5, in which stimuli appeared in a random order. We found that PK facilitated the learning of a fixed sequence, but not a probabilistic sequence. In addition to overall learning measured by the mean reaction time (RT), we examined the progressive changes in RT within and between blocks (i.e., online and offline learning, respectively). It was found that the two groups who performed the fixed sequence, regardless of PK, showed greater online learning than the other two groups who performed the probabilistic sequence. The groups who performed the probabilistic sequence, regardless of PK, did not display online learning, as indicated by a decline in performance within the learning blocks. However, they did demonstrate remarkably greater offline improvement in RT, which suggests that they are learning the probabilistic sequence offline. These results suggest that in the SRT task, the fast acquisition of a motor sequence is driven by concurrent online and offline learning. In addition, as the acquisition of a probabilistic sequence requires greater procedural memory compared to the acquisition of a fixed sequence, our results suggest that offline learning is more likely to take place in a procedural sequence learning task.
机译:众所周知,可以通过在线学习快速学习运动序列。随后,通过离线学习来增强或巩固运动序列的初始获取。然而,人们几乎不了解离线学习是否能够推动运动序列的快速学习(即,在第一训练中的初始序列学习)。为了检查快速学习阶段的离线学习,我们要求四组年轻人以固定或概率序列以及是否有序列的初步知识(PK)来执行串行反应时间(SRT)任务。操纵序列和PK以强调被发现有助于或抑制离线学习的程序性(概率性序列;无初步知识(NPK))或声明性(固定性序列;具有PK)记忆。在SRT任务中,有六个学习块,每个连续块之间有2分钟的间隔。在整个会话过程中,刺激遵循相同的固定或概率模式,但第5块中的刺激以随机顺序出现。我们发现PK有助于学习固定序列,而不是概率序列。除了以平均反应时间(RT)衡量的整体学习之外,我们还研究了区块内和区块间RT的逐步变化(即分别为在线和离线学习)。发现执行固定序列的两组,无论PK如何,都比执行概率序列的其他两组表现出更大的在线学习能力。不论PK如何,执行概率序列的组均未显示在线学习,这由学习范围内的表现下降所表明。但是,他们的确证明了RT的离线改善显着,这表明他们正在离线学习概率序列。这些结果表明,在SRT任务中,电机序列的快速获取是由并发的在线和离线学习驱动的。此外,由于与固定序列的获取相比,概率序列的获取需要更大的过程内存,因此我们的结果表明,离线学习更有可能在过程序列学习任务中进行。

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