使用手动和动眼肌激活版本的连续反应时间任务的内隐序列学习的日间和夜间巩固:反应时间和预期测量。

Psychological Research Pub Date : 2022-04-01 Epub Date: 2021-06-11 DOI:10.1007/s00426-021-01534-1
Eli Vakil, Moran Hayout, Matan Maler, Simone Schwizer Ashkenazi
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引用次数: 3

摘要

本研究通过两个实验探讨了基于两个因变量——反应时间(RT)和正确预期的内隐序列学习的巩固,以阐明睡眠的作用,以及人工成分在巩固过程中是否必要。实验1 (n = 37)使用手动激活的系列反应时间任务(O-SRT)的眼部变体来探索成人的表现,实验2 (n = 37)使用眼部激活(OA)版本的任务。每个实验由白天和夜间组组成,进行两次O-SRT,其间有12小时的离线时间(白天组为早上/晚上,夜间组为晚上/第二天早上)。夜间离线只有在需要手动响应和正确的预期(即准确性)而不是RT(即速度)被测量时才有优势。我们将这一发现与MA O-SRT所需的双重学习过程联系起来,该过程导致一夜之间序列特异性学习增加。当使用OA O-SRT时,两组在RT离线和正确预期后显示出相似的比率。我们将这一发现解释为反映了稳定性,这证实了我们的假设。正如预期的那样,当引入另一个序列时,所有组都表现出性能下降,从而反映了序列特定的学习。本研究使用了一种强大的程序,可以通过几种方式测量内隐序列学习:通过评估两种不同的测量(RT,正确的预期),并通过隔离任务的不同方面(即,有/没有手动学习组件,多/少一般技能学习),这已知会影响学习和巩固。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Day versus night consolidation of implicit sequence learning using manual and oculomotor activation versions of the serial reaction time task: reaction time and anticipation measures.

This study presents two experiments that explored consolidation of implicit sequence learning based on two dependent variables-reaction time (RT) and correct anticipations to clarify the role of sleep, and whether the manual component is necessary for consolidation processes. Experiment 1 (n = 37) explored the performance of adults using an ocular variant of the serial reaction time task (O-SRT) with manual activation (MA), and Experiment 2 (n = 37) used the ocular activation (OA) version of the task. Each experiment consisted of a Day and a Night group that performed two sessions of the O-SRT with an intervening 12-h offline period (morning/evening in Day group, evening/following morning in Night group). Night offline had an advantage only when manual response was required and when correct anticipations (i.e., accuracy) but not RT (i.e., speed) were measured. We associated this finding with the dual-learning processes required in the MA O-SRT that led to increased sequence specific learning overnight. When using the OA O-SRT, both groups demonstrated similar rates after offline in RT and correct anticipations. We interpreted this finding to reflect stabilization, which confirmed our hypothesis. As expected, all the groups demonstrated reduced performance when another sequence was introduced, thus reflecting sequence-specific learning. This study used a powerful procedure that allows measurement of implicit sequence learning in several ways: by evaluating two different measures (RT, correct anticipations) and by isolating different aspects of the task (i.e., with/without the manual learning component, more/less general skill learning), which are known to affect learning and consolidation.

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